From c40a04a0f735a1263c7048fcfb96538655ca79c7 Mon Sep 17 00:00:00 2001 From: Rudy Osuna Date: Mon, 1 Jun 2026 07:13:41 -0700 Subject: [PATCH 01/16] Quiver Gov Contracts Notebook --- .../research.ipynb | 264 ++++++++++++++++++ 1 file changed, 264 insertions(+) create mode 100644 project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb diff --git a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb new file mode 100644 index 0000000000..e13f468c46 --- /dev/null +++ b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb @@ -0,0 +1,264 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "a1b2c3d4", + "metadata": {}, + "source": [ + "![QuantConnect Logo](https://cdn.quantconnect.com/web/i/icon.png)\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "e5f6a7b8", + "metadata": {}, + "source": [ + "## Quiver Government Contracts Research\n", + "\n", + "This notebook studies whether government contract dollar volume helps explain next open-to-open returns." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c9d0e1f2", + "metadata": {}, + "outputs": [], + "source": [ + "qb = QuantBook()\n", + "# Daily bars will have an end_time that matches the following midnight.\n", + "qb.settings.daily_precise_end_time = False" + ] + }, + { + "cell_type": "markdown", + "id": "a3b4c5d6", + "metadata": {}, + "source": [ + "### Build a Government Contract Universe\n", + "\n", + "Select assets with frequent, sizable US government contracts, then inspect the returned universe history." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e7f8a9b0", + "metadata": {}, + "outputs": [], + "source": [ + "def select_assets(data: List[QuiverGovernmentContractUniverse]) -> List[Symbol]:\n", + " # Group by ticker and keep names with 3+ contracts totalling over $50K.\n", + " contracts_by_symbol: dict[Symbol, list[QuiverGovernmentContractUniverse]] = {}\n", + " for d in data:\n", + " contracts_by_symbol.setdefault(d.symbol, []).append(d)\n", + " return [s for s, ds in contracts_by_symbol.items()\n", + " if len(ds) >= 3 and sum(x.amount or 0 for x in ds) > 50_000]\n", + "\n", + "# Add the Quiver Government Contract universe.\n", + "universe = qb.add_universe(QuiverGovernmentContractUniverse, select_assets)\n", + "# Request recent universe history.\n", + "universe_history = qb.universe_history(universe, qb.time - timedelta(252), qb.time - timedelta(1), flatten=True)\n", + "# Print the returned shape and columns.\n", + "print(f\"Shape: {universe_history.shape}\")\n", + "print(f\"Columns: {list(universe_history.columns)}\")\n", + "universe_history.head()" + ] + }, + { + "cell_type": "markdown", + "id": "c1d2e3f4", + "metadata": {}, + "source": [ + "### Universe Diagnostics\n", + "\n", + "Aggregate the raw per-contract rows to one row per (`time`, `symbol`), then check how many assets pass the filter each day and summarize the factors." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a5b6c7d8", + "metadata": {}, + "outputs": [], + "source": [ + "# Extract time and symbol arrays.\n", + "by_time = universe_history['time'].values if 'time' in universe_history.columns else universe_history.index.get_level_values(0)\n", + "by_symbol = universe_history['symbol'].values if 'symbol' in universe_history.columns else universe_history.index.get_level_values(1)\n", + "# Aggregate the raw per-contract rows into a single row per (time, symbol).\n", + "universe_history = universe_history.groupby([by_time, by_symbol]).agg(totalamount=('amount', 'sum'), contractcount=('amount', 'count'))\n", + "universe_history.index.names = ['time', 'symbol']\n", + "# Calculate and print universe metrics.\n", + "universe_size = universe_history.groupby(level='time').size()\n", + "print(f\"Universe days: {len(universe_size)}\")\n", + "print(f\"Mean basket size per day: {universe_size.mean():.1f}\")\n", + "factors = ['totalamount', 'contractcount']\n", + "for factor in factors:\n", + " print(f'\\n{universe_history[factor].describe()}')\n", + "# Extract unique assets chronologically and calculate the cumulative growth.\n", + "unique_by_date = universe_history.reset_index().sort_values('time').drop_duplicates(subset=['symbol']).set_index('time')\n", + "unique_by_date['cumulative_count'] = range(1, len(unique_by_date) + 1)\n", + "unique_by_date['cumulative_count'].plot(\n", + " title='Cumulative Unique Assets Added to Universe',\n", + " ylabel='Total Unique Assets',\n", + " marker='o'\n", + ");\n" + ] + }, + { + "cell_type": "markdown", + "id": "e9f0a1b2", + "metadata": {}, + "source": [ + "### Daily Universe Prices\n", + "\n", + "Fetch daily price history for every symbol that appears in the universe." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c3d4e5f6", + "metadata": {}, + "outputs": [], + "source": [ + "# Extract unique assets\n", + "symbols = list(universe_history.index.get_level_values(1).unique())\n", + "# Fetch daily historical price metrics using the earliest timestamp available in the index.\n", + "history = qb.history(symbols, universe_history.index[0][0] - timedelta(1), qb.time, Resolution.DAILY)\n", + "history" + ] + }, + { + "cell_type": "markdown", + "id": "a7b8c9d0", + "metadata": {}, + "source": [ + "### Align Contract Volume And Returns\n", + "\n", + "Build a joined table of factors and the future return." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e1f2a3b4", + "metadata": {}, + "outputs": [], + "source": [ + "universe_history.index.names = ['time', 'symbol']\n", + "# Compute the forward open-to-open returns.\n", + "returns = history.open.unstack(0).pct_change().shift(-2).stack().rename('futurereturn')\n", + "returns.index.names = ['time', 'symbol']\n", + "# Join the dataframes and drop rows containing missing values.\n", + "dataset = universe_history[factors].join(returns, how='inner').dropna()\n", + "dataset.head()" + ] + }, + { + "cell_type": "markdown", + "id": "c5d6e7f8", + "metadata": {}, + "source": [ + "### Analyze Relationships Between Factor and Future Returns\n", + "\n", + "Create a grouped bar chart with standard error bars for each factor." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a9b0c1d2", + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.ticker as mticker\n", + "\n", + "for factor in factors:\n", + " stats=dataset.groupby(factor)['futurereturn'].agg(['mean','sem','count']).reset_index()\n", + " stats['sem']=stats['sem'].fillna(0.0)\n", + " plt.figure(figsize=(10,4))\n", + " # Format dollar amount into metric format.\n", + " labels=stats[factor].apply(lambda x:f'{x/1e6:.1f}M' if x>=1e6 else f'{x/1e3:.0f}K') if factor=='totalamount' else stats[factor].astype(str)\n", + " plt.bar(labels,stats['mean'],yerr=stats['sem'],color='teal',alpha=0.8,capsize=5)\n", + " plt.axhline(0,color='black',linewidth=1,alpha=0.4)\n", + " plt.title(f'Mean Future Return by {factor}')\n", + " plt.xlabel(f'{factor}')\n", + " plt.ylabel('Mean Future Return')\n", + " plt.xticks(rotation=45,ha='right')\n", + " # Annotate each bar with the number of observations in the group.\n", + " for idx,row in stats.iterrows():\n", + " y_pos=row['mean']+(row['sem'] if row['mean']>=0 else-row['sem'])\n", + " v_align='bottom' if row['mean']>=0 else 'top'\n", + " plt.text(idx,y_pos,f\"n={int(row['count'])}\",ha='center',va=v_align,fontsize=9)\n", + " plt.tight_layout()\n", + " plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "e3f4a5b6", + "metadata": {}, + "source": [ + "Create a box plot of the contract volume quintiles compared to future returns." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c7d8e9f0", + "metadata": {}, + "outputs": [], + "source": [ + "y = dataset.futurereturn\n", + "for factor in factors:\n", + " # Split factor values into quantile buckets.\n", + " x = dataset[factor]\n", + " bucket_count = min(5, x.nunique())\n", + " buckets = pd.qcut(x, q=bucket_count, duplicates='drop')\n", + " # Summarize each bucket with distribution statistics.\n", + " summary = dataset.assign(bucket=buckets).groupby('bucket', observed=True).agg(\n", + " mean_factor=(factor, 'mean'),\n", + " min_future_return=('futurereturn', 'min'),\n", + " max_future_return=('futurereturn', 'max'),\n", + " mean_future_return=('futurereturn', 'mean'),\n", + " std_future_return=('futurereturn', 'std'),\n", + " observations=('futurereturn', 'size')\n", + " ).reset_index()\n", + " summary['bucket'] = summary['bucket'].astype(str)\n", + " # Display the bucket summary.\n", + " print(f\"Factor: {factor}\")\n", + " display(summary.style.format({\n", + " 'mean_factor': '{:.3f}',\n", + " 'min_future_return': '{:.2%}',\n", + " 'max_future_return': '{:.2%}',\n", + " 'mean_future_return': '{:.2%}',\n", + " 'std_future_return': '{:.2%}'\n", + " }))\n", + " # Plot the return distribution for each bucket.\n", + " groups = [y[buckets == b].values for b in buckets.cat.categories]\n", + " plt.boxplot(groups, labels=[str(b) for b in buckets.cat.categories])\n", + " plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", + " plt.title(f'Future Return by {factor} Bucket')\n", + " plt.xlabel(f'{factor} Bucket')\n", + " plt.ylabel('Future Return')\n", + " plt.xticks(rotation=45)\n", + " plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.8.0" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From fda2a53f7dbe0af49cb3635c4b239b8b97f99396 Mon Sep 17 00:00:00 2001 From: Rudy Osuna Date: Mon, 1 Jun 2026 07:36:53 -0700 Subject: [PATCH 02/16] fix --- .../research.ipynb | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb index e13f468c46..50d783fd34 100644 --- a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb +++ b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb @@ -16,7 +16,7 @@ "source": [ "## Quiver Government Contracts Research\n", "\n", - "This notebook studies whether government contract dollar volume helps explain next open-to-open returns." + "This notebook studies whether government contract dollar volume helps explain next future returns." ] }, { @@ -148,7 +148,7 @@ "outputs": [], "source": [ "universe_history.index.names = ['time', 'symbol']\n", - "# Compute the forward open-to-open returns.\n", + "# Compute the forward future returns.\n", "returns = history.open.unstack(0).pct_change().shift(-2).stack().rename('futurereturn')\n", "returns.index.names = ['time', 'symbol']\n", "# Join the dataframes and drop rows containing missing values.\n", From 898df92879741252438796593f7ce4a7cc27a35a Mon Sep 17 00:00:00 2001 From: Rudy Osuna Date: Mon, 1 Jun 2026 08:48:07 -0700 Subject: [PATCH 03/16] fix; shortened --- .../research.ipynb | 9 ++------- 1 file changed, 2 insertions(+), 7 deletions(-) diff --git a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb index 50d783fd34..5b3a2acb44 100644 --- a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb +++ b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb @@ -95,7 +95,7 @@ "print(f\"Mean basket size per day: {universe_size.mean():.1f}\")\n", "factors = ['totalamount', 'contractcount']\n", "for factor in factors:\n", - " print(f'\\n{universe_history[factor].describe()}')\n", + " print(f'\n{universe_history[factor].describe().map("{:.3f}".format)}')", "# Extract unique assets chronologically and calculate the cumulative growth.\n", "unique_by_date = universe_history.reset_index().sort_values('time').drop_duplicates(subset=['symbol']).set_index('time')\n", "unique_by_date['cumulative_count'] = range(1, len(unique_by_date) + 1)\n", @@ -147,12 +147,7 @@ "metadata": {}, "outputs": [], "source": [ - "universe_history.index.names = ['time', 'symbol']\n", - "# Compute the forward future returns.\n", - "returns = history.open.unstack(0).pct_change().shift(-2).stack().rename('futurereturn')\n", - "returns.index.names = ['time', 'symbol']\n", - "# Join the dataframes and drop rows containing missing values.\n", - "dataset = universe_history[factors].join(returns, how='inner').dropna()\n", + "dataset = universe_history[factors].join(history.open.unstack(0).pct_change().shift(-2).stack().rename('futurereturn').rename_axis(['time', 'symbol']), how='inner').dropna()\n", "dataset.head()" ] }, From 566a8f66de6ccd6365b36e7970ea42eb2d7cc612 Mon Sep 17 00:00:00 2001 From: Rudy Osuna Date: Mon, 1 Jun 2026 08:52:37 -0700 Subject: [PATCH 04/16] Delete project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb --- .../research.ipynb | 259 ------------------ 1 file changed, 259 deletions(-) delete mode 100644 project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb diff --git a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb deleted file mode 100644 index 5b3a2acb44..0000000000 --- a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb +++ /dev/null @@ -1,259 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "a1b2c3d4", - "metadata": {}, - "source": [ - "![QuantConnect Logo](https://cdn.quantconnect.com/web/i/icon.png)\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "e5f6a7b8", - "metadata": {}, - "source": [ - "## Quiver Government Contracts Research\n", - "\n", - "This notebook studies whether government contract dollar volume helps explain next future returns." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c9d0e1f2", - "metadata": {}, - "outputs": [], - "source": [ - "qb = QuantBook()\n", - "# Daily bars will have an end_time that matches the following midnight.\n", - "qb.settings.daily_precise_end_time = False" - ] - }, - { - "cell_type": "markdown", - "id": "a3b4c5d6", - "metadata": {}, - "source": [ - "### Build a Government Contract Universe\n", - "\n", - "Select assets with frequent, sizable US government contracts, then inspect the returned universe history." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "e7f8a9b0", - "metadata": {}, - "outputs": [], - "source": [ - "def select_assets(data: List[QuiverGovernmentContractUniverse]) -> List[Symbol]:\n", - " # Group by ticker and keep names with 3+ contracts totalling over $50K.\n", - " contracts_by_symbol: dict[Symbol, list[QuiverGovernmentContractUniverse]] = {}\n", - " for d in data:\n", - " contracts_by_symbol.setdefault(d.symbol, []).append(d)\n", - " return [s for s, ds in contracts_by_symbol.items()\n", - " if len(ds) >= 3 and sum(x.amount or 0 for x in ds) > 50_000]\n", - "\n", - "# Add the Quiver Government Contract universe.\n", - "universe = qb.add_universe(QuiverGovernmentContractUniverse, select_assets)\n", - "# Request recent universe history.\n", - "universe_history = qb.universe_history(universe, qb.time - timedelta(252), qb.time - timedelta(1), flatten=True)\n", - "# Print the returned shape and columns.\n", - "print(f\"Shape: {universe_history.shape}\")\n", - "print(f\"Columns: {list(universe_history.columns)}\")\n", - "universe_history.head()" - ] - }, - { - "cell_type": "markdown", - "id": "c1d2e3f4", - "metadata": {}, - "source": [ - "### Universe Diagnostics\n", - "\n", - "Aggregate the raw per-contract rows to one row per (`time`, `symbol`), then check how many assets pass the filter each day and summarize the factors." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a5b6c7d8", - "metadata": {}, - "outputs": [], - "source": [ - "# Extract time and symbol arrays.\n", - "by_time = universe_history['time'].values if 'time' in universe_history.columns else universe_history.index.get_level_values(0)\n", - "by_symbol = universe_history['symbol'].values if 'symbol' in universe_history.columns else universe_history.index.get_level_values(1)\n", - "# Aggregate the raw per-contract rows into a single row per (time, symbol).\n", - "universe_history = universe_history.groupby([by_time, by_symbol]).agg(totalamount=('amount', 'sum'), contractcount=('amount', 'count'))\n", - "universe_history.index.names = ['time', 'symbol']\n", - "# Calculate and print universe metrics.\n", - "universe_size = universe_history.groupby(level='time').size()\n", - "print(f\"Universe days: {len(universe_size)}\")\n", - "print(f\"Mean basket size per day: {universe_size.mean():.1f}\")\n", - "factors = ['totalamount', 'contractcount']\n", - "for factor in factors:\n", - " print(f'\n{universe_history[factor].describe().map("{:.3f}".format)}')", - "# Extract unique assets chronologically and calculate the cumulative growth.\n", - "unique_by_date = universe_history.reset_index().sort_values('time').drop_duplicates(subset=['symbol']).set_index('time')\n", - "unique_by_date['cumulative_count'] = range(1, len(unique_by_date) + 1)\n", - "unique_by_date['cumulative_count'].plot(\n", - " title='Cumulative Unique Assets Added to Universe',\n", - " ylabel='Total Unique Assets',\n", - " marker='o'\n", - ");\n" - ] - }, - { - "cell_type": "markdown", - "id": "e9f0a1b2", - "metadata": {}, - "source": [ - "### Daily Universe Prices\n", - "\n", - "Fetch daily price history for every symbol that appears in the universe." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c3d4e5f6", - "metadata": {}, - "outputs": [], - "source": [ - "# Extract unique assets\n", - "symbols = list(universe_history.index.get_level_values(1).unique())\n", - "# Fetch daily historical price metrics using the earliest timestamp available in the index.\n", - "history = qb.history(symbols, universe_history.index[0][0] - timedelta(1), qb.time, Resolution.DAILY)\n", - "history" - ] - }, - { - "cell_type": "markdown", - "id": "a7b8c9d0", - "metadata": {}, - "source": [ - "### Align Contract Volume And Returns\n", - "\n", - "Build a joined table of factors and the future return." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "e1f2a3b4", - "metadata": {}, - "outputs": [], - "source": [ - "dataset = universe_history[factors].join(history.open.unstack(0).pct_change().shift(-2).stack().rename('futurereturn').rename_axis(['time', 'symbol']), how='inner').dropna()\n", - "dataset.head()" - ] - }, - { - "cell_type": "markdown", - "id": "c5d6e7f8", - "metadata": {}, - "source": [ - "### Analyze Relationships Between Factor and Future Returns\n", - "\n", - "Create a grouped bar chart with standard error bars for each factor." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a9b0c1d2", - "metadata": {}, - "outputs": [], - "source": [ - "import matplotlib.ticker as mticker\n", - "\n", - "for factor in factors:\n", - " stats=dataset.groupby(factor)['futurereturn'].agg(['mean','sem','count']).reset_index()\n", - " stats['sem']=stats['sem'].fillna(0.0)\n", - " plt.figure(figsize=(10,4))\n", - " # Format dollar amount into metric format.\n", - " labels=stats[factor].apply(lambda x:f'{x/1e6:.1f}M' if x>=1e6 else f'{x/1e3:.0f}K') if factor=='totalamount' else stats[factor].astype(str)\n", - " plt.bar(labels,stats['mean'],yerr=stats['sem'],color='teal',alpha=0.8,capsize=5)\n", - " plt.axhline(0,color='black',linewidth=1,alpha=0.4)\n", - " plt.title(f'Mean Future Return by {factor}')\n", - " plt.xlabel(f'{factor}')\n", - " plt.ylabel('Mean Future Return')\n", - " plt.xticks(rotation=45,ha='right')\n", - " # Annotate each bar with the number of observations in the group.\n", - " for idx,row in stats.iterrows():\n", - " y_pos=row['mean']+(row['sem'] if row['mean']>=0 else-row['sem'])\n", - " v_align='bottom' if row['mean']>=0 else 'top'\n", - " plt.text(idx,y_pos,f\"n={int(row['count'])}\",ha='center',va=v_align,fontsize=9)\n", - " plt.tight_layout()\n", - " plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "e3f4a5b6", - "metadata": {}, - "source": [ - "Create a box plot of the contract volume quintiles compared to future returns." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c7d8e9f0", - "metadata": {}, - "outputs": [], - "source": [ - "y = dataset.futurereturn\n", - "for factor in factors:\n", - " # Split factor values into quantile buckets.\n", - " x = dataset[factor]\n", - " bucket_count = min(5, x.nunique())\n", - " buckets = pd.qcut(x, q=bucket_count, duplicates='drop')\n", - " # Summarize each bucket with distribution statistics.\n", - " summary = dataset.assign(bucket=buckets).groupby('bucket', observed=True).agg(\n", - " mean_factor=(factor, 'mean'),\n", - " min_future_return=('futurereturn', 'min'),\n", - " max_future_return=('futurereturn', 'max'),\n", - " mean_future_return=('futurereturn', 'mean'),\n", - " std_future_return=('futurereturn', 'std'),\n", - " observations=('futurereturn', 'size')\n", - " ).reset_index()\n", - " summary['bucket'] = summary['bucket'].astype(str)\n", - " # Display the bucket summary.\n", - " print(f\"Factor: {factor}\")\n", - " display(summary.style.format({\n", - " 'mean_factor': '{:.3f}',\n", - " 'min_future_return': '{:.2%}',\n", - " 'max_future_return': '{:.2%}',\n", - " 'mean_future_return': '{:.2%}',\n", - " 'std_future_return': '{:.2%}'\n", - " }))\n", - " # Plot the return distribution for each bucket.\n", - " groups = [y[buckets == b].values for b in buckets.cat.categories]\n", - " plt.boxplot(groups, labels=[str(b) for b in buckets.cat.categories])\n", - " plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", - " plt.title(f'Future Return by {factor} Bucket')\n", - " plt.xlabel(f'{factor} Bucket')\n", - " plt.ylabel('Future Return')\n", - " plt.xticks(rotation=45)\n", - " plt.show()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "name": "python", - "version": "3.8.0" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From 06d6ffe1ba2233f14d7d372d15535b20066a8ac9 Mon Sep 17 00:00:00 2001 From: Rudy Osuna Date: Mon, 1 Jun 2026 08:52:57 -0700 Subject: [PATCH 05/16] fix --- .../research.ipynb | 793 ++++++++++++++++++ 1 file changed, 793 insertions(+) create mode 100644 project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb diff --git a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb new file mode 100644 index 0000000000..335b1c6d96 --- /dev/null +++ b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb @@ -0,0 +1,793 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "a1b2c3d4", + "metadata": {}, + "source": [ + "![QuantConnect Logo](https://cdn.quantconnect.com/web/i/icon.png)\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "e5f6a7b8", + "metadata": {}, + "source": [ + "## Quiver Government Contracts Research\n", + "\n", + "This notebook studies whether government contract dollar volume helps explain next future returns." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "c9d0e1f2", + "metadata": {}, + "outputs": [], + "source": [ + "qb = QuantBook()\n", + "# Daily bars will have an end_time that matches the following midnight.\n", + "qb.settings.daily_precise_end_time = False" + ] + }, + { + "cell_type": "markdown", + "id": "a3b4c5d6", + "metadata": {}, + "source": [ + "### Build a Government Contract Universe\n", + "\n", + "Select assets with frequent, sizable US government contracts, then inspect the returned universe history." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "e7f8a9b0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Shape: (1307, 5)\n", + "Columns: ['agency', 'amount', 'description', 'value', 'time']\n" + ] + }, + { + "data": { + "text/html": [ + "
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agencyamountdescriptionvaluetime
time
2025-09-23A RPTMYV3VC57PDepartment of Health and Human Services291469.05AGILENT 1290 INFINITY III LC WITH 6475 TRIPLE ...291469.05NaT
CDW VHRARJ4RLSV9Department of Transportation191949.00ELASTIC SEARCH SOFTWARE 12-MONTH SUBSCRIPTION191949.00NaT
EW RTKJ7O7ZTI79Department of Veterans Affairs11000.00IMPLANT11000.00NaT
F R735QTJ8XC9XGeneral Services Administration32976.004X2 PICKUP; MID-SIZE; CREW CAB; MIN 4200 LBS GVWR32976.00NaT
MCK R735QTJ8XC9XDepartment of Veterans Affairs11859.00EMERGENCY PURCHASE OF HUMATIN CAPS 250MG11859.00NaT
\n", + "
" + ], + "text/plain": [ + " agency \\\n", + "time \n", + "2025-09-23 A RPTMYV3VC57P Department of Health and Human Services \n", + " CDW VHRARJ4RLSV9 Department of Transportation \n", + " EW RTKJ7O7ZTI79 Department of Veterans Affairs \n", + " F R735QTJ8XC9X General Services Administration \n", + " MCK R735QTJ8XC9X Department of Veterans Affairs \n", + "\n", + " amount \\\n", + "time \n", + "2025-09-23 A RPTMYV3VC57P 291469.05 \n", + " CDW VHRARJ4RLSV9 191949.00 \n", + " EW RTKJ7O7ZTI79 11000.00 \n", + " F R735QTJ8XC9X 32976.00 \n", + " MCK R735QTJ8XC9X 11859.00 \n", + "\n", + " description \\\n", + "time \n", + "2025-09-23 A RPTMYV3VC57P AGILENT 1290 INFINITY III LC WITH 6475 TRIPLE ... \n", + " CDW VHRARJ4RLSV9 ELASTIC SEARCH SOFTWARE 12-MONTH SUBSCRIPTION \n", + " EW RTKJ7O7ZTI79 IMPLANT \n", + " F R735QTJ8XC9X 4X2 PICKUP; MID-SIZE; CREW CAB; MIN 4200 LBS GVWR \n", + " MCK R735QTJ8XC9X EMERGENCY PURCHASE OF HUMATIN CAPS 250MG \n", + "\n", + " value time \n", + "time \n", + "2025-09-23 A RPTMYV3VC57P 291469.05 NaT \n", + " CDW VHRARJ4RLSV9 191949.00 NaT \n", + " EW RTKJ7O7ZTI79 11000.00 NaT \n", + " F R735QTJ8XC9X 32976.00 NaT \n", + " MCK R735QTJ8XC9X 11859.00 NaT " + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def select_assets(data: List[QuiverGovernmentContractUniverse]) -> List[Symbol]:\n", + " # Group by ticker and keep names with 3+ contracts totalling over $50K.\n", + " contracts_by_symbol: dict[Symbol, list[QuiverGovernmentContractUniverse]] = {}\n", + " for d in data:\n", + " contracts_by_symbol.setdefault(d.symbol, []).append(d)\n", + " return [s for s, ds in contracts_by_symbol.items()\n", + " if len(ds) >= 3 and sum(x.amount or 0 for x in ds) > 50_000]\n", + "\n", + "# Add the Quiver Government Contract universe.\n", + "universe = qb.add_universe(QuiverGovernmentContractUniverse, select_assets)\n", + "# Request recent universe history.\n", + "universe_history = qb.universe_history(universe, qb.time - timedelta(252), qb.time - timedelta(1), flatten=True)\n", + "# Print the returned shape and columns.\n", + "print(f\"Shape: {universe_history.shape}\")\n", + "print(f\"Columns: {list(universe_history.columns)}\")\n", + "universe_history.head()" + ] + }, + { + "cell_type": "markdown", + "id": "c1d2e3f4", + "metadata": {}, + "source": [ + "### Universe Diagnostics\n", + "\n", + "Aggregate the raw per-contract rows to one row per (`time`, `symbol`), then check how many assets pass the filter each day and summarize the factors." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a5b6c7d8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Universe days: 12\n", + "Mean basket size per day: 1.0\n", + "\n", + "count 12.000\n", + "mean 8947552.101\n", + "std 22852918.541\n", + "min 188082.490\n", + "25% 258470.500\n", + "50% 441962.365\n", + "75% 2578237.420\n", + "max 79653765.350\n", + "Name: totalamount, dtype: object\n", + "\n", + "count 12.000\n", + "mean 76.417\n", + "std 133.145\n", + "min 3.000\n", + "25% 3.000\n", + "50% 5.000\n", + "75% 62.500\n", + "max 360.000\n", + "Name: contractcount, dtype: object\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Extract time and symbol arrays.\n", + "by_time = universe_history['time'].values if 'time' in universe_history.columns else universe_history.index.get_level_values(0)\n", + "by_symbol = universe_history['symbol'].values if 'symbol' in universe_history.columns else universe_history.index.get_level_values(1)\n", + "# Aggregate the raw per-contract rows into a single row per (time, symbol).\n", + "universe_history = universe_history.groupby([by_time, by_symbol]).agg(totalamount=('amount', 'sum'), contractcount=('amount', 'count'))\n", + "universe_history.index.names = ['time', 'symbol']\n", + "# Calculate and print universe metrics.\n", + "universe_size = universe_history.groupby(level='time').size()\n", + "print(f\"Universe days: {len(universe_size)}\")\n", + "print(f\"Mean basket size per day: {universe_size.mean():.1f}\")\n", + "factors = ['totalamount', 'contractcount']\n", + "for factor in factors:\n", + " print(f'\\n{universe_history[factor].describe().map(\"{:.3f}\".format)}')\n", + "# Extract unique assets chronologically and calculate the cumulative growth.\n", + "unique_by_date = universe_history.reset_index().sort_values('time').drop_duplicates(subset=['symbol']).set_index('time')\n", + "unique_by_date['cumulative_count'] = range(1, len(unique_by_date) + 1)\n", + "unique_by_date['cumulative_count'].plot(\n", + " title='Cumulative Unique Assets Added to Universe',\n", + " ylabel='Total Unique Assets',\n", + " marker='o'\n", + ");\n" + ] + }, + { + "cell_type": "markdown", + "id": "e9f0a1b2", + "metadata": {}, + "source": [ + "### Daily Universe Prices\n", + "\n", + "Fetch daily price history for every symbol that appears in the universe." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "c3d4e5f6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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closehighlowopenvolume
symboltime
TXG X7SGNKRL4WV92025-09-3011.3411.885711.280011.803774314.0
2025-10-0111.6911.745011.230011.392551389.0
2025-10-0212.3912.530011.680011.753070520.0
2025-10-0312.3112.530012.170012.462344431.0
2025-10-0412.7512.965012.360012.382419124.0
.....................
MDLN YYDBHHPS742T2026-05-2337.0038.400036.960037.7233977674.0
2026-05-2736.1437.290035.710037.0013941196.0
2026-05-2835.8537.020035.690036.086687542.0
2026-05-2936.8136.835035.440135.8512480142.0
2026-05-3036.5237.475036.480036.789421813.0
\n", + "

1624 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + " close high low open volume\n", + "symbol time \n", + "TXG X7SGNKRL4WV9 2025-09-30 11.34 11.8857 11.2800 11.80 3774314.0\n", + " 2025-10-01 11.69 11.7450 11.2300 11.39 2551389.0\n", + " 2025-10-02 12.39 12.5300 11.6800 11.75 3070520.0\n", + " 2025-10-03 12.31 12.5300 12.1700 12.46 2344431.0\n", + " 2025-10-04 12.75 12.9650 12.3600 12.38 2419124.0\n", + "... ... ... ... ... ...\n", + "MDLN YYDBHHPS742T 2026-05-23 37.00 38.4000 36.9600 37.72 33977674.0\n", + " 2026-05-27 36.14 37.2900 35.7100 37.00 13941196.0\n", + " 2026-05-28 35.85 37.0200 35.6900 36.08 6687542.0\n", + " 2026-05-29 36.81 36.8350 35.4401 35.85 12480142.0\n", + " 2026-05-30 36.52 37.4750 36.4800 36.78 9421813.0\n", + "\n", + "[1624 rows x 5 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Extract unique assets\n", + "symbols = list(universe_history.index.get_level_values(1).unique())\n", + "# Fetch daily historical price metrics using the earliest timestamp available in the index.\n", + "history = qb.history(symbols, universe_history.index[0][0] - timedelta(1), qb.time, Resolution.DAILY)\n", + "history" + ] + }, + { + "cell_type": "markdown", + "id": "a7b8c9d0", + "metadata": {}, + "source": [ + "### Align Contract Volume And Returns\n", + "\n", + "Build a joined table of factors and the future return." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e1f2a3b4", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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totalamountcontractcountfuturereturn
timesymbol
2025-09-30BAH UROXQFIWOSX118487206.4060.000401
2025-10-04DNOW VR22RBI5MBFP222382.01214-0.003153
2025-10-08SYK R735QTJ8XC9X450063.6640.015616
2025-10-10DNOW VR22RBI5MBFP294421.70299-0.029392
2025-11-15SENEA R735QTJ8XC9X3194596.80120.010146
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" + ], + "text/plain": [ + " totalamount contractcount futurereturn\n", + "time symbol \n", + "2025-09-30 BAH UROXQFIWOSX1 18487206.40 6 0.000401\n", + "2025-10-04 DNOW VR22RBI5MBFP 222382.01 214 -0.003153\n", + "2025-10-08 SYK R735QTJ8XC9X 450063.66 4 0.015616\n", + "2025-10-10 DNOW VR22RBI5MBFP 294421.70 299 -0.029392\n", + "2025-11-15 SENEA R735QTJ8XC9X 3194596.80 12 0.010146" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Join the factor values with future returns and drop rows containing missing values.\n", + "dataset = universe_history[factors].join(history.open.unstack(0).pct_change().shift(-2).stack().rename('futurereturn').rename_axis(['time', 'symbol']), how='inner').dropna()\n", + "dataset.head()" + ] + }, + { + "cell_type": "markdown", + "id": "c5d6e7f8", + "metadata": {}, + "source": [ + "### Analyze Relationships Between Factor and Future Returns\n", + "\n", + "Create a grouped bar chart with standard error bars for each factor." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "a9b0c1d2", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.ticker as mticker\n", + "\n", + "for factor in factors:\n", + " stats=dataset.groupby(factor)['futurereturn'].agg(['mean','sem','count']).reset_index()\n", + " stats['sem']=stats['sem'].fillna(0.0)\n", + " plt.figure(figsize=(10,4))\n", + " # Format dollar amount into metric format.\n", + " labels=stats[factor].apply(lambda x:f'{x/1e6:.1f}M' if x>=1e6 else f'{x/1e3:.0f}K') if factor=='totalamount' else stats[factor].astype(str)\n", + " plt.bar(labels,stats['mean'],yerr=stats['sem'],color='teal',alpha=0.8,capsize=5)\n", + " plt.axhline(0,color='black',linewidth=1,alpha=0.4)\n", + " plt.title(f'Mean Future Return by {factor}')\n", + " plt.xlabel(f'{factor}')\n", + " plt.ylabel('Mean Future Return')\n", + " plt.xticks(rotation=45,ha='right')\n", + " # Annotate each bar with the number of observations in the group.\n", + " for idx,row in stats.iterrows():\n", + " y_pos=row['mean']+(row['sem'] if row['mean']>=0 else-row['sem'])\n", + " v_align='bottom' if row['mean']>=0 else 'top'\n", + " plt.text(idx,y_pos,f\"n={int(row['count'])}\",ha='center',va=v_align,fontsize=9)\n", + " plt.tight_layout()\n", + " plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "e3f4a5b6", + "metadata": {}, + "source": [ + "Create a box plot of the contract volume quintiles compared to future returns." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c7d8e9f0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Factor: totalamount\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
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\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "y = dataset.futurereturn\n", + "for factor in factors:\n", + " # Split factor values into quantile buckets.\n", + " x = dataset[factor]\n", + " bucket_count = min(5, x.nunique())\n", + " buckets = pd.qcut(x, q=bucket_count, duplicates='drop')\n", + " # Summarize each bucket with distribution statistics.\n", + " summary = dataset.assign(bucket=buckets).groupby('bucket', observed=True).agg(\n", + " mean_factor=(factor, 'mean'),\n", + " min_future_return=('futurereturn', 'min'),\n", + " max_future_return=('futurereturn', 'max'),\n", + " mean_future_return=('futurereturn', 'mean'),\n", + " std_future_return=('futurereturn', 'std'),\n", + " observations=('futurereturn', 'size')\n", + " ).reset_index()\n", + " summary['bucket'] = summary['bucket'].astype(str)\n", + " # Display the bucket summary.\n", + " print(f\"Factor: {factor}\")\n", + " display(summary.style.format({\n", + " 'mean_factor': '{:.3f}',\n", + " 'min_future_return': '{:.2%}',\n", + " 'max_future_return': '{:.2%}',\n", + " 'mean_future_return': '{:.2%}',\n", + " 'std_future_return': '{:.2%}'\n", + " }))\n", + " # Plot the return distribution for each bucket.\n", + " groups = [y[buckets == b].values for b in buckets.cat.categories]\n", + " plt.boxplot(groups, labels=[str(b) for b in buckets.cat.categories])\n", + " plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", + " plt.title(f'Future Return by {factor} Bucket')\n", + " plt.xlabel(f'{factor} Bucket')\n", + " plt.ylabel('Future Return')\n", + " plt.xticks(rotation=45)\n", + " plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Foundation-Py-Default", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.14" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 6a0170dcdf53266e3339c6f9cc7a2aba5f1b5b77 Mon Sep 17 00:00:00 2001 From: Rudy Osuna Date: Mon, 1 Jun 2026 09:24:01 -0700 Subject: [PATCH 06/16] fix --- .../research.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb index 335b1c6d96..7317b304c6 100644 --- a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb +++ b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb @@ -16,7 +16,7 @@ "source": [ "## Quiver Government Contracts Research\n", "\n", - "This notebook studies whether government contract dollar volume helps explain next future returns." + "This notebook studies whether government contract dollar volume helps explain future returns." ] }, { From a45e886879659dd735583732654b7e235ce6e25d Mon Sep 17 00:00:00 2001 From: Rudy Osuna Date: Mon, 1 Jun 2026 14:41:37 -0700 Subject: [PATCH 07/16] Delete project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb --- .../research.ipynb | 793 ------------------ 1 file changed, 793 deletions(-) delete mode 100644 project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb diff --git a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb deleted file mode 100644 index 7317b304c6..0000000000 --- a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb +++ /dev/null @@ -1,793 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "a1b2c3d4", - "metadata": {}, - "source": [ - "![QuantConnect Logo](https://cdn.quantconnect.com/web/i/icon.png)\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "e5f6a7b8", - "metadata": {}, - "source": [ - "## Quiver Government Contracts Research\n", - "\n", - "This notebook studies whether government contract dollar volume helps explain future returns." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "c9d0e1f2", - "metadata": {}, - "outputs": [], - "source": [ - "qb = QuantBook()\n", - "# Daily bars will have an end_time that matches the following midnight.\n", - "qb.settings.daily_precise_end_time = False" - ] - }, - { - "cell_type": "markdown", - "id": "a3b4c5d6", - "metadata": {}, - "source": [ - "### Build a Government Contract Universe\n", - "\n", - "Select assets with frequent, sizable US government contracts, then inspect the returned universe history." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "e7f8a9b0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Shape: (1307, 5)\n", - "Columns: ['agency', 'amount', 'description', 'value', 'time']\n" - ] - }, - { - "data": { - "text/html": [ - "
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agencyamountdescriptionvaluetime
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2025-09-23A RPTMYV3VC57PDepartment of Health and Human Services291469.05AGILENT 1290 INFINITY III LC WITH 6475 TRIPLE ...291469.05NaT
CDW VHRARJ4RLSV9Department of Transportation191949.00ELASTIC SEARCH SOFTWARE 12-MONTH SUBSCRIPTION191949.00NaT
EW RTKJ7O7ZTI79Department of Veterans Affairs11000.00IMPLANT11000.00NaT
F R735QTJ8XC9XGeneral Services Administration32976.004X2 PICKUP; MID-SIZE; CREW CAB; MIN 4200 LBS GVWR32976.00NaT
MCK R735QTJ8XC9XDepartment of Veterans Affairs11859.00EMERGENCY PURCHASE OF HUMATIN CAPS 250MG11859.00NaT
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" - ], - "text/plain": [ - " agency \\\n", - "time \n", - "2025-09-23 A RPTMYV3VC57P Department of Health and Human Services \n", - " CDW VHRARJ4RLSV9 Department of Transportation \n", - " EW RTKJ7O7ZTI79 Department of Veterans Affairs \n", - " F R735QTJ8XC9X General Services Administration \n", - " MCK R735QTJ8XC9X Department of Veterans Affairs \n", - "\n", - " amount \\\n", - "time \n", - "2025-09-23 A RPTMYV3VC57P 291469.05 \n", - " CDW VHRARJ4RLSV9 191949.00 \n", - " EW RTKJ7O7ZTI79 11000.00 \n", - " F R735QTJ8XC9X 32976.00 \n", - " MCK R735QTJ8XC9X 11859.00 \n", - "\n", - " description \\\n", - "time \n", - "2025-09-23 A RPTMYV3VC57P AGILENT 1290 INFINITY III LC WITH 6475 TRIPLE ... \n", - " CDW VHRARJ4RLSV9 ELASTIC SEARCH SOFTWARE 12-MONTH SUBSCRIPTION \n", - " EW RTKJ7O7ZTI79 IMPLANT \n", - " F R735QTJ8XC9X 4X2 PICKUP; MID-SIZE; CREW CAB; MIN 4200 LBS GVWR \n", - " MCK R735QTJ8XC9X EMERGENCY PURCHASE OF HUMATIN CAPS 250MG \n", - "\n", - " value time \n", - "time \n", - "2025-09-23 A RPTMYV3VC57P 291469.05 NaT \n", - " CDW VHRARJ4RLSV9 191949.00 NaT \n", - " EW RTKJ7O7ZTI79 11000.00 NaT \n", - " F R735QTJ8XC9X 32976.00 NaT \n", - " MCK R735QTJ8XC9X 11859.00 NaT " - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def select_assets(data: List[QuiverGovernmentContractUniverse]) -> List[Symbol]:\n", - " # Group by ticker and keep names with 3+ contracts totalling over $50K.\n", - " contracts_by_symbol: dict[Symbol, list[QuiverGovernmentContractUniverse]] = {}\n", - " for d in data:\n", - " contracts_by_symbol.setdefault(d.symbol, []).append(d)\n", - " return [s for s, ds in contracts_by_symbol.items()\n", - " if len(ds) >= 3 and sum(x.amount or 0 for x in ds) > 50_000]\n", - "\n", - "# Add the Quiver Government Contract universe.\n", - "universe = qb.add_universe(QuiverGovernmentContractUniverse, select_assets)\n", - "# Request recent universe history.\n", - "universe_history = qb.universe_history(universe, qb.time - timedelta(252), qb.time - timedelta(1), flatten=True)\n", - "# Print the returned shape and columns.\n", - "print(f\"Shape: {universe_history.shape}\")\n", - "print(f\"Columns: {list(universe_history.columns)}\")\n", - "universe_history.head()" - ] - }, - { - "cell_type": "markdown", - "id": "c1d2e3f4", - "metadata": {}, - "source": [ - "### Universe Diagnostics\n", - "\n", - "Aggregate the raw per-contract rows to one row per (`time`, `symbol`), then check how many assets pass the filter each day and summarize the factors." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "a5b6c7d8", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Universe days: 12\n", - "Mean basket size per day: 1.0\n", - "\n", - "count 12.000\n", - "mean 8947552.101\n", - "std 22852918.541\n", - "min 188082.490\n", - "25% 258470.500\n", - "50% 441962.365\n", - "75% 2578237.420\n", - "max 79653765.350\n", - "Name: totalamount, dtype: object\n", - "\n", - "count 12.000\n", - "mean 76.417\n", - "std 133.145\n", - "min 3.000\n", - "25% 3.000\n", - "50% 5.000\n", - "75% 62.500\n", - "max 360.000\n", - "Name: contractcount, dtype: object\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Extract time and symbol arrays.\n", - "by_time = universe_history['time'].values if 'time' in universe_history.columns else universe_history.index.get_level_values(0)\n", - "by_symbol = universe_history['symbol'].values if 'symbol' in universe_history.columns else universe_history.index.get_level_values(1)\n", - "# Aggregate the raw per-contract rows into a single row per (time, symbol).\n", - "universe_history = universe_history.groupby([by_time, by_symbol]).agg(totalamount=('amount', 'sum'), contractcount=('amount', 'count'))\n", - "universe_history.index.names = ['time', 'symbol']\n", - "# Calculate and print universe metrics.\n", - "universe_size = universe_history.groupby(level='time').size()\n", - "print(f\"Universe days: {len(universe_size)}\")\n", - "print(f\"Mean basket size per day: {universe_size.mean():.1f}\")\n", - "factors = ['totalamount', 'contractcount']\n", - "for factor in factors:\n", - " print(f'\\n{universe_history[factor].describe().map(\"{:.3f}\".format)}')\n", - "# Extract unique assets chronologically and calculate the cumulative growth.\n", - "unique_by_date = universe_history.reset_index().sort_values('time').drop_duplicates(subset=['symbol']).set_index('time')\n", - "unique_by_date['cumulative_count'] = range(1, len(unique_by_date) + 1)\n", - "unique_by_date['cumulative_count'].plot(\n", - " title='Cumulative Unique Assets Added to Universe',\n", - " ylabel='Total Unique Assets',\n", - " marker='o'\n", - ");\n" - ] - }, - { - "cell_type": "markdown", - "id": "e9f0a1b2", - "metadata": {}, - "source": [ - "### Daily Universe Prices\n", - "\n", - "Fetch daily price history for every symbol that appears in the universe." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "c3d4e5f6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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closehighlowopenvolume
symboltime
TXG X7SGNKRL4WV92025-09-3011.3411.885711.280011.803774314.0
2025-10-0111.6911.745011.230011.392551389.0
2025-10-0212.3912.530011.680011.753070520.0
2025-10-0312.3112.530012.170012.462344431.0
2025-10-0412.7512.965012.360012.382419124.0
.....................
MDLN YYDBHHPS742T2026-05-2337.0038.400036.960037.7233977674.0
2026-05-2736.1437.290035.710037.0013941196.0
2026-05-2835.8537.020035.690036.086687542.0
2026-05-2936.8136.835035.440135.8512480142.0
2026-05-3036.5237.475036.480036.789421813.0
\n", - "

1624 rows × 5 columns

\n", - "
" - ], - "text/plain": [ - " close high low open volume\n", - "symbol time \n", - "TXG X7SGNKRL4WV9 2025-09-30 11.34 11.8857 11.2800 11.80 3774314.0\n", - " 2025-10-01 11.69 11.7450 11.2300 11.39 2551389.0\n", - " 2025-10-02 12.39 12.5300 11.6800 11.75 3070520.0\n", - " 2025-10-03 12.31 12.5300 12.1700 12.46 2344431.0\n", - " 2025-10-04 12.75 12.9650 12.3600 12.38 2419124.0\n", - "... ... ... ... ... ...\n", - "MDLN YYDBHHPS742T 2026-05-23 37.00 38.4000 36.9600 37.72 33977674.0\n", - " 2026-05-27 36.14 37.2900 35.7100 37.00 13941196.0\n", - " 2026-05-28 35.85 37.0200 35.6900 36.08 6687542.0\n", - " 2026-05-29 36.81 36.8350 35.4401 35.85 12480142.0\n", - " 2026-05-30 36.52 37.4750 36.4800 36.78 9421813.0\n", - "\n", - "[1624 rows x 5 columns]" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Extract unique assets\n", - "symbols = list(universe_history.index.get_level_values(1).unique())\n", - "# Fetch daily historical price metrics using the earliest timestamp available in the index.\n", - "history = qb.history(symbols, universe_history.index[0][0] - timedelta(1), qb.time, Resolution.DAILY)\n", - "history" - ] - }, - { - "cell_type": "markdown", - "id": "a7b8c9d0", - "metadata": {}, - "source": [ - "### Align Contract Volume And Returns\n", - "\n", - "Build a joined table of factors and the future return." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "e1f2a3b4", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
totalamountcontractcountfuturereturn
timesymbol
2025-09-30BAH UROXQFIWOSX118487206.4060.000401
2025-10-04DNOW VR22RBI5MBFP222382.01214-0.003153
2025-10-08SYK R735QTJ8XC9X450063.6640.015616
2025-10-10DNOW VR22RBI5MBFP294421.70299-0.029392
2025-11-15SENEA R735QTJ8XC9X3194596.80120.010146
\n", - "
" - ], - "text/plain": [ - " totalamount contractcount futurereturn\n", - "time symbol \n", - "2025-09-30 BAH UROXQFIWOSX1 18487206.40 6 0.000401\n", - "2025-10-04 DNOW VR22RBI5MBFP 222382.01 214 -0.003153\n", - "2025-10-08 SYK R735QTJ8XC9X 450063.66 4 0.015616\n", - "2025-10-10 DNOW VR22RBI5MBFP 294421.70 299 -0.029392\n", - "2025-11-15 SENEA R735QTJ8XC9X 3194596.80 12 0.010146" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Join the factor values with future returns and drop rows containing missing values.\n", - "dataset = universe_history[factors].join(history.open.unstack(0).pct_change().shift(-2).stack().rename('futurereturn').rename_axis(['time', 'symbol']), how='inner').dropna()\n", - "dataset.head()" - ] - }, - { - "cell_type": "markdown", - "id": "c5d6e7f8", - "metadata": {}, - "source": [ - "### Analyze Relationships Between Factor and Future Returns\n", - "\n", - "Create a grouped bar chart with standard error bars for each factor." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "a9b0c1d2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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t+/fvD0mSMHbsWFy9erXE920vrg26du2KlJQUjR+hHj16hGXLlsHKygq+vr4AIM+Q//RxU9RnAECJZqkvrc+PiYkJOnfujB07dmgM17958yYiIiLQpk0bWFtbA9DNZ+BplpaWAAq3HRFRecKebiIikg0aNOi5dXx9fTFy5EjMnz8f0dHR6Ny5MypUqIBLly5hy5YtWLp0KXr37o1WrVqhUqVKGDRoED744ANIkoQffvjBIENLO3fujJo1a2LYsGGYOHEiTExMsG7dOtjb2yMhIUGjroeHB1auXIm5c+eibt26qFq1Kjp27KjVNoozceJE7Ny5E4GBgfKtkx48eIC///4bW7duRXx8PKpUqaL1/jVq1Ahdu3bF119/jdDQUNSpUwdz587FlClTEB8fj6CgIFSsWBHXrl3Djz/+iBEjRmDChAny/m7atAkhISFo2bIlrKys8Oabb8LNzQ3e3t6YMmUK7t69i8qVK2Pjxo0v/MPAy8jNzUWnTp3Qp08fxMXFYcWKFWjTpg26d++uUc/e3h5dunTBli1bYGtri27dupVo+8W1wYgRI7B69WoMHjwYp0+fhouLC7Zu3Yrjx49jyZIl8i23VCoVGjVqhE2bNuG1115D5cqV0bhxYzRu3Bjt2rXDokWLkJeXh+rVq+PXX38tUW91aX5+5s6di3379qFNmzYIDg6GqakpVq9ejZycHCxatEiup4vPwNPc3d1hYmKChQsXIi0tDWZmZujYsWOxc0YQERklg8yZTkREBvfkLcOe5elbhhVYs2aN8PDwECqVSlSsWFE0adJETJo0SSQlJcl1jh8/Lry9vYVKpRJOTk5i0qRJ8i2Lnr7llJubW6H3GDRoUJG3cippjE86ffq08PLyEkqlUtSsWVN8/vnnRd7qKCUlRXTr1k1UrFhRANC4fVhJt/GseDIyMsSUKVNE3bp1hVKpFFWqVBGtWrUSixcv1rgtVlGKaychhDh06FCh21b973//E23atBGWlpbC0tJSNGjQQLz//vsiLi5OrpOZmSnefvttYWtrKwBotPeVK1eEn5+fMDMzEw4ODmLq1Kli3759Jf7/K7hl2Kefflpo2dOxFqWgbQ8fPixGjBghKlWqJKysrMSAAQPEnTt3ilxn8+bNAoAYMWLEM7f9pGe1wc2bN8WQIUNElSpVhFKpFE2aNNG43VaBEydOCA8PD6FUKjX27caNG6JHjx7C1tZW2NjYiLfeekskJSUV2v+ijqOX/fwUdxwCEO+//75G2ZkzZ4S/v7+wsrISFhYWokOHDuLEiROF1n3Zz4Cvr2+hW/KtXbtW1K5dW5iYmPD2YURULklCcDYLIiIiKh927NiBoKAgHDlyRON2VURERIbCpJuIiIjKjcDAQJw/fx6XL1/mJF1ERFQm8JpuIiIiMnobN25ETEwMdu/ejaVLlzLhJiKiMoM93URERGT0JEmClZUV+vbti1WrVsHUlP0KRERUNvAbiYiIiIwe+xCIiKis4n26iYiIiIiIiPSESTcRERERERGRnnB4uQ6o1WokJSWhYsWKnLiFiIiIiIjoFSCEQEZGBpycnKBQFN+fzaRbB5KSkuDs7GzoMIiIiIiIiKiUJSYmokaNGsUuZ9KtAxUrVgTwuLGtra0NHA0REZVnKSkpGDduHKKiopCSkoKjR4+iadOmhg6LiIjolZOeng5nZ2c5HywOk24dKBhSbm1tzaSbiIj06uHDhwgMDMTMmTPh5eUFKysrfvcQEREZ0PMuMeZEakRERKXExcUFixYtgre3NypWrAhfX18kJiZqtQ0HBwcEBwfD09NTT1ESERGRLjHpJiIiKkXh4eHYsGEDUlNTYWlpidDQUABAYGAgbG1ti30kJCQYOHIiIiJ6ERxeTkREVIqCg4Ph6uoKABgwYAAWLFgAANi1a5chwyIiIiI9YU83ERFRKXJ0dJSfW1paIiMjw4DREBERkb4x6SYiIioDAgICYGVlVeyDw8uJiIiME4eXExERlQF79uwpcd3s7Gz5eW5uLrKzs6FUKqFQ8Ld0IiKisobfzkREREZGpVJBpVIBALy8vKBSqXDkyBEDR0VERERFkYQQwtBBGLv09HTY2NggLS2N90olIiIiIiJ6BZQ0D2RPNxEREREREZGe8JpuIiIiA4qOjkZsbKzW67m5ucHd3V33AREREZFOMekmIiIqQos1a0rlfeIWL0bmpUtar2dVrx7qT5igh4g0nRoxQu/vQUREVJ4x6SYiIjIg57598TApSev1VE5OeoiGiIiIdI1JNxERkQFZODvDwtnZ0GEQERGRnnAiNSIiIiIiIiI9YdJNREREREREpCdMuomIiIiIiIj0hEk3ERERERERkZ4w6SYiIiIiIiLSEybdRERERERERHrCpJuIiIiIiIhIT5h0ExEREREREekJk24iIiIiIiIiPWHSTURERERERKQnTLqJiIiIiIiI9IRJNxEREREREZGeMOkmIiIiIiIi0hMm3URERERERER6wqSbiIiIiIiISE+YdBMRERERERHpCZNuIiIiIqIyJDk5Gd27d4eTkxMkSUJ0dLShQyKil8Ckm4iIiIioDFEoFOjSpQu2b99u6FCISAeYdBMRERER6YiLiwsWLVoEb29vVKxYEb6+vkhMTNRqGw4ODggODoanp6eeoiSi0sSkm4iIiIhIh8LDw7FhwwakpqbC0tISoaGhAIDAwEDY2toW+0hISDBw5ESkD6aGDoCIiIiIqDwJDg6Gq6srAGDAgAFYsGABAGDXrl2GDIuIDIQ93UREREREOuTo6Cg/t7S0REZGhgGjISJDY9JNRERERFQKAgICYGVlVeyDw8uJyicOLyciIiIiKgV79uwpcd3s7Gz5eW5uLrKzs6FUKqFQsM+MyNgY3ad2+fLlcHFxgbm5Oby8vPDHH388s/6WLVvQoEEDmJubo0mTJvj55581lm/btg2dO3eGnZ0d74NIRERERGWCSqWCSqUCAHh5eUGlUuHIkSMGjoqIXoRRJd2bNm1CSEgIZsyYgTNnzuD111+Hv78/bt26VWT9EydOoH///hg2bBiioqIQFBSEoKAgnD17Vq7z4MEDtGnTBgsXLiyt3SAiIiKicio+Ph5BQUHy66CgIMTHx2u9HSFEoUf79u11FicRlR5JCCEMHURJeXl5oWXLlvjqq68AAGq1Gs7OzhgzZgwmT55cqH7fvn3x4MEDjZkivb294e7ujlWrVmnUjY+Ph6urK6KiouDu7q5VXOnp6bCxsUFaWhqsra213zEiIipzWqxZY+gQyoRTI0YYOgQiIqIyqaR5oNFc052bm4vTp09jypQpcplCoYCfnx8iIyOLXCcyMhIhISEaZf7+/ti+fbs+QyUiIiIikkVHRyM2Nlbr9dzc3LTuDCKissdoku7bt28jPz8fDg4OGuUODg64cOFCkeukpKQUWT8lJeWlYsnJyUFOTo78Oj09/aW2R0RERESlr7RGtMQtXozMS5e0Xs+qXj3UnzBBDxFp4ogWIv0ymqS7LJk/fz5mzZpl6DCIiIiIyAg49+2Lh0lJWq+ncnLSQzREVNqMJumuUqUKTExMcPPmTY3ymzdvwtHRsch1HB0dtapfUlOmTNEYtp6eng5nZ+eX2iYRERERlU8Wzs6w4Lki0SvLaGYvVyqV8PDwwP79++UytVqN/fv3w8fHp8h1fHx8NOoDwL59+4qtX1JmZmawtrbWeBARERERERE9zWh6ugEgJCQEgwYNQosWLeDp6YklS5bgwYMHGDJkCABg4MCBqF69OubPnw8AGDt2LHx9ffHZZ5+hW7du2LhxI06dOoU1T1y/c/fuXSQkJCDp/4f8xMXFAXjcS/6yPeJERERERET0ajOqpLtv375ITU3F9OnTkZKSAnd3d+zdu1eeLC0hIQEKxb+d961atUJERASmTZuGqVOnol69eti+fTsaN24s19m5c6ectANAv379AAAzZszAzJkzS2fHiIiIiIiIqFwyqvt0l1W8TzcRUfnD+3Q/xlmNqTzj5/wxfs6JXkxJ80CjuaabiIiIiIiIyNgw6SYiIiIiIqLnSk5ORvfu3eHk5ARJkhAdHW3okIwCk24iIiIiIiJ6LoVCgS5dumD79u2GDsWoMOkmIiIiIiIq51xcXLBo0SJ4e3ujYsWK8PX1RWJiolbbcHBwQHBwMDw9PfUUZfnEpJuIiIiIiOgVEB4ejg0bNiA1NRWWlpYIDQ0FAAQGBsLW1rbYR0JCgoEjN25GdcswIiIiIiIiejHBwcFwdXUFAAwYMAALFiwAAOzatcuQYZV77OkmIiIiIiJ6BTg6OsrPLS0tkZGRYcBoXh1MuomIiIiIiF5hAQEBsLKyKvbB4eUvh8PLiYiIiIiIXmF79uwpcd3s7Gz5eW5uLrKzs6FUKqFQsD+3OGwZIiIiIiIiKhGVSgWVSgUA8PLygkqlwpEjRwwcVdnGpJuIiIheScnJyejevTucnJwgSRKio6MNHRIRkd7Ex8cjKChIfh0UFIT4+HittyOEKPRo3769zuIsj5h0ExER0StJoVCgS5cu2L59u6FDISKicozXdBMREZHRcXFxQXBwMLZt24bY2Fg0b94c4eHhcHZ2LvE2HBwcEBwcrMcoiYjKtujoaMTGxmq9npubG9zd3XUfUDnFpJuIiIiMUnh4OHbs2IFq1aqhZ8+eCA0NRVhYGAIDA3Hs2LFi14uJiUHNmjVLMVIiopJrsWZNqb1X3OLFyLx0Sev1rOrVQ/0JE/QQkaZTI0bo/T1KA5NuIiIiMkrBwcFwdXUFAAwYMAALFiwAAOzatcuQYRERGQ3nvn3xMClJ6/VUTk56iKb8YtJNRERERsnR0VF+bmlpiYyMDANGQ0RkfCycnWGhxWU59GI4kRoRERGVKwEBAbCysir2kZCQYOgQiYjoFcKebiIiIipX9uzZU+K62dnZ8vPc3FxkZ2dDqVRCoWC/BBER6Qa/UYiIiOiVpVKpoFKpAABeXl5QqVQ4cuSIgaMiIqLyhD3dREREZHTi4+M1XgcFBSEoKEjr7QghdBMQERFRMdjTTURERERERKQn7OkmIiKiciE6OhqxsbFar+fm5gZ3d3fdB0RERIQXSLrz8/MRFhaG/fv349atW1Cr1RrLDxw4oLPgiIiIyPi1WLOmVN4nbvFiZF66pPV6VvXqof6ECXqIqLBTI0aUyvsQEVHZoXXSPXbsWISFhaFbt25o3LgxJEnSR1xEREREWnHu2xcPk5K0Xk/l5KSHaIiIiB7TOuneuHEjNm/ejK5du+ojHiIiIqIXYuHsDAtnZ0OHQUREpEHridSUSiXq1q2rj1iIiIiIiIiIyhWtk+7x48dj6dKlvMUGERERERER0XNoPbz82LFjOHjwIPbs2QM3NzdUqFBBY/m2bdt0FhwRERERERGRMdM66ba1tUWPHj30EQsRERERERFRuaJV0v3o0SN06NABnTt3hqOjo75iIiIiIiIiIioXtLqm29TUFKNGjUJOTo6+4iEiIiIiIiIqN7SeSM3T0xNRUVH6iIWIiIiIiIioXNH6mu7g4GCMHz8eN27cgIeHBywtLTWWN23aVGfBERERERERERkzrZPufv36AQA++OADuUySJAghIEkS8vPzdRcdERERERERkRHTOum+du2aPuIgIiIiIiIiKne0Trpr1aqljziIiIiIiIh0Kjk5GSNHjsSpU6eQnJyMqKgouLu7GzosesVonXR///33z1w+cODAFw6GiIiIiIhIVxQKBbp06YJp06bBy8vL0OHQK0rrpHvs2LEar/Py8pCVlQWlUgkLCwsm3URERERE9NJcXFwQHByMbdu2ITY2Fs2bN0d4eDicnZ1LvA0HBwcEBwfrMUqi59P6lmH37t3TeGRmZiIuLg5t2rTBhg0b9BEjERERERG9gsLDw7FhwwakpqbC0tISoaGhAIDAwEDY2toW+0hISDBw5ET/0rqnuyj16tXDggUL8M477+DChQu62CQREREREb3igoOD4erqCgAYMGAAFixYAADYtWuXIcMi0orWPd3FMTU1RVJSkq42R0RERERErzhHR0f5uaWlJTIyMgwYDdGL0bqne+fOnRqvhRBITk7GV199hdatW+ssMCIiIiIioqIEBATg6NGjxS4/d+4catasWYoRERVP66Q7KChI47UkSbC3t0fHjh3x2Wef6SouIiIiIiKiIu3Zs6fEdbOzs+Xnubm5yM7OhlKphEKhs0G/RM+kddKtVqv1EQcREREREZHOqVQq+XnBbcMOHjyI9u3bGygietVo/fPO7NmzkZWVVaj84cOHmD17tk6CIiIiIiKiV1t8fLzGKNugoCDEx8drvR0hRKEHE24qTVon3bNmzUJmZmah8qysLMyaNUsnQT3L8uXL4eLiAnNzc3h5eeGPP/54Zv0tW7agQYMGMDc3R5MmTfDzzz9rLBdCYPr06ahWrRpUKhX8/Pxw6dIlfe4CERERERERvSK0Hl4uhIAkSYXK//rrL1SuXFknQRVn06ZNCAkJwapVq+Dl5YUlS5bA398fcXFxqFq1aqH6J06cQP/+/TF//nwEBgYiIiICQUFBOHPmDBo3bgwAWLRoEb788kt89913cHV1RWhoKPz9/XHu3DmYm5vrdX+IiIiIiKjkoqOjERsbq/V6bm5ucHd3131ARCVQ4qS7UqVKkCQJkiThtdde00i88/PzkZmZiVGjRuklyAKff/45hg8fjiFDhgAAVq1ahd27d2PdunWYPHlyofpLly5Fly5dMHHiRADAnDlzsG/fPnz11VdYtWoVhBBYsmQJpk2bhv/85z8AgO+//x4ODg7Yvn07+vXrp9f9ISIiIiIqD1qsWVMq7xO3eDEyX2BUqlW9eqg/YYIeIirs1IgRpfI+ZDxKnHQvWbIEQggMHToUs2bNgo2NjbxMqVTCxcUFPj4+egkSeDzT4OnTpzFlyhS5TKFQwM/PD5GRkUWuExkZiZCQEI0yf39/bN++HQBw7do1pKSkwM/PT15uY2MDLy8vREZGMukmIiIiIipDnPv2xcOkJK3XUzk56SEaopIpcdI9aNAgAICrqytat24NU1OtR6a/lNu3byM/Px8ODg4a5Q4ODrhw4UKR66SkpBRZPyUlRV5eUFZcnaLk5OQgJydHfp2eng4AuHPnDnJzc0u4R0REVJY9KmL+klfR7du3X3obbMt/6aI9SXd4bD5mTJ9zZaVKUFaq9ELrllaML9uePC7/Vdb/ZmZkZJSontaZs6+vL65cuYJvv/0WV65cwdKlS1G1alXs2bMHNWvWhJubm9bBGpv58+cXOWnczp07NW5JUJbMO3LE0CGUGR+3a/fS22B7Psa21K2XbU+25b90cWwGW1npIBLjt23btpfeBtvyXy/bnvyc/4ufc93h51y3XrY92Zb/0sWxqU8PHz4sUT2tk+7Dhw8jICAArVu3xpEjRzBv3jxUrVoVf/31F7755hts3bpV62BLokqVKjAxMcHNmzc1ym/evAlHR8ci13F0dHxm/YJ/b968iWrVqmnUedZEC1OmTNEYtp6eng5nZ2d0794dFStW1Gq/SssK/mIm69mz50tvg+35GNtSt162PdmW/9LFsUlUFvFz/i9+zonI0DIyMjBu3Ljn1tM66Z48eTLmzp2LkJAQjQSzY8eO+Oqrr7TdXIkplUp4eHhg//798v361Go19u/fj9GjRxe5jo+PD/bv36/REPv27ZOvPXd1dYWjoyP2798vJ9np6ek4efIk3nvvvWJjMTMzg5mZWaFyOzs7WFtbv9gO6pkpfzGTValS5aW3wfZ8jG2pWy/bnmzLf+ni2CQqi/g5/xc/50RkaEqlskT1tE66//77b0RERBQqr1q1qt7H3IeEhGDQoEFo0aIFPD09sWTJEjx48ECezXzgwIGoXr065s+fDwAYO3YsfH198dlnn6Fbt27YuHEjTp06hTX/P7uiJEkYN24c5s6di3r16sm3DHNycpITeyIiIiIiIqIXpXXSbWtri+TkZLi6umqUR0VFoXr16joLrCh9+/ZFamoqpk+fjpSUFLi7u2Pv3r3yRGgJCQlQKBRy/VatWiEiIgLTpk3D1KlTUa9ePWzfvl2+RzcATJo0CQ8ePMCIESNw//59tGnTBnv37uU9uomIiIiIiOilaZ109+vXDx999BG2bNkCSZKgVqtx/PhxTJgwAQMHDtRHjBpGjx5d7HDyQ4cOFSp766238NZbbxW7PUmSMHv2bMyePVtXIRIREREREREBABTPr6Lpk08+QYMGDeDs7IzMzEw0atQI7dq1Q6tWrfDxxx/rI0YiIiIiIiIio6R1T7dSqcTatWsxffp0/P3338jMzESzZs1Qr149fcRHREREREREZLS0TroLODs7w9nZWX69bds2zJw5EzExMToJjIiIiIiIiMjYaTW8fPXq1ejduzfefvttnDx5EgBw4MABNGvWDO+++y5at26tlyCJiIiIiIiIjFGJk+4FCxZgzJgxiI+Px86dO9GxY0d88sknGDBgAPr27YsbN25g5cqV+oyViIiIiIiIyKiUeHj5t99+i7Vr12LQoEE4evQofH19ceLECVy+fBmWlpb6jJGIiIiIiIjIKJW4pzshIQEdO3YEALRt2xYVKlTArFmzmHATERERERERFaPEPd05OTkwNzeXXyuVSlSuXFkvQZFxy0pMxMOkJK3XUzk5weKJyfmIiIiIiIiMnVazl4eGhsLCwgIAkJubi7lz58LGxkajzueff6676EhnTo0YUWrv1b59exw+fFjr9Xx9fXHo0CHdB0RERERERGQgJU6627Vrh7i4OPl1q1atcPXqVY06kiTpLjIyWkuWLEFsbGyJ69+7dw/r1q1DbGwsJElCVFQU3N3d9RcgERERERFRKSlx0s0eSCopd3d3rZLmmzdvQqFQoEWLFvDy8tJfYEaIQ/WJiIiIiIybVsPLiZ7m4uKC4OBgbNu2DbGxsWjevDnCw8PhrEXC5+DggODgYD1GqXulNVyfQ/WJiIiIiIwbk256aeHh4dixYweqVauGnj17IjQ0FGFhYQgMDMSxY8eKXS8mJgY1a9YsxUiND4fqExEREREZNybd9NKCg4Ph6uoKABgwYAAWLFgAANi1a5chwyoXOFSfiIiIiMi4lfg+3UTFcXR0lJ9bWloiIyPDgNEYLxcXFyxatAje3t6oWLEifH19kZiYqNU2Cobqe3p66ilKIiIiIiLSBpNu0puAgABYWVkV+0hISDB0iGVOeHg4NmzYgNTUVFhaWiI0NBQAEBgYCFtb22IfbEsiIiIiorLphYaXHz16FKtXr8aVK1ewdetWVK9eHT/88ANcXV3Rpk0bXcdIRmrPnj0lrpudnS0/z83NRXZ2NpRKJRSKV+t3IQ7VJyIiIiIqX7TOaP73v//B398fKpUKUVFRyMnJAQCkpaXhk08+0XmA9GpQqVRQqVQAAC8vL6hUKhw5csTAUZU+DtUnIiIiIipftE66586di1WrVmHt2rWoUKGCXN66dWucOXNGp8FR2RcfH4+goCD5dVBQEOLj47XejhCi0KN9+/Y6i9PYcag+EREREZFx0np4eVxcHNq1a1eo3MbGBvfv39dFTET0FA7VJyIiIiIyTlqfhTs6OuLy5cuFyo8dO4batWvrJCgienEcqk9EREREVHZo3dM9fPhwjB07FuvWrYMkSUhKSkJkZCQmTJggz7RMRNp7elh+UFCQxtD9khJC6CYgIiIiIiJ6aVon3ZMnT4ZarUanTp2QlZWFdu3awczMDBMmTMCYMWP0ESMRERERERGRUdIq6c7Pz8fx48fx/vvvY+LEibh8+TIyMzPRqFEjWFlZ6StGIiIiIiIiIqOkVdJtYmKCzp074/z587C1tUWjRo30FRcRERERERGR0dN6IrXGjRvj6tWr+oiFiIiIiIiIqFx5oft0T5gwAbt27UJycjLS09M1HkRERERERET0mNYTqXXt2hUA0L17d0iSJJcLISBJEvLz83UXHREREREREZER0zrpPnjwoD7iICIiIiIiIip3tE66fX199REHERERERERUbmjddJ95MiRZy5v167dCwdDREREREREVJ5onXS3b9++UNmT13bzmm4iIiIiIiKix7SevfzevXsaj1u3bmHv3r1o2bIlfv31V33ESERERERERGSUtO7ptrGxKVT2xhtvQKlUIiQkBKdPn9ZJYERERERERETGTuue7uI4ODggLi5OV5sjIiIiIiIiMnpa93THxMRovBZCIDk5GQsWLIC7u7uu4iIiIiIiIiIyelon3e7u7pAkCUIIjXJvb2+sW7dOZ4ERERERERERGTutk+5r165pvFYoFLC3t4e5ubnOgiIiIiIiIiIqD7S+pvvw4cNwdHRErVq1UKtWLTg7O8Pc3By5ubn4/vvv9REjERERERERkVHSOukeMmQI0tLSCpVnZGRgyJAhOgmKiIiIiIiIqDzQOukWQkCSpELlN27cKPJ2YkRERERERESvqhJf092sWTNIkgRJktCpUyeYmv67an5+Pq5du4YuXbroJUgiIiIiIiIiY1TipDsoKAgAEB0dDX9/f1hZWcnLlEolXFxc0KtXL50HSERERERERGSsSpx0z5gxAwDg4uKCvn37crZyIiIiIiIioufQ+pZhgwYN0kccREREREREROWO1hOpKRQKmJiYFPvQl7t372LAgAGwtraGra0thg0bhszMzGeuk52djffffx92dnawsrJCr169cPPmTY06H3zwATw8PGBmZgZ3d3e9xU9ERERERESvHq17urdt26Yxe3leXh6ioqLw3XffYdasWToN7kkDBgxAcnIy9u3bh7y8PAwZMgQjRoxAREREset8+OGH2L17N7Zs2QIbGxuMHj0aPXv2xPHjxzXqDR06FCdPnkRMTIze4iciIiIiIqJXj9ZJd8GEak/q3bs33NzcsGnTJgwbNkwXcWk4f/489u7diz///BMtWrQAACxbtgxdu3bF4sWL4eTkVGidtLQ0fPPNN4iIiEDHjh0BAN9++y0aNmyI33//Hd7e3gCAL7/8EgCQmprKpJuIiIiIiIh0Suvh5cXx9vbG/v37dbU5DZGRkbC1tZUTbgDw8/ODQqHAyZMni1zn9OnTyMvLg5+fn1zWoEED1KxZE5GRkXqJk4iIiIiIiOhJWvd0F+Xhw4f48ssvUb16dV1srpCUlBRUrVpVo8zU1BSVK1dGSkpKsesolUrY2tpqlDs4OBS7Tknl5OQgJydHfp2env5S2yMiIiIiIqLySeuku1KlShrXdAshkJGRAQsLC4SHh2u1rcmTJ2PhwoXPrHP+/HltQ9S7+fPn6/X6dSIiIiIiIioftE66lyxZovFaoVDA3t4eXl5eqFSpklbbGj9+PAYPHvzMOrVr14ajoyNu3bqlUf7o0SPcvXsXjo6ORa7n6OiI3Nxc3L9/X6O3++bNm8WuU1JTpkxBSEiI/Do9PR3Ozs4vtU0iIiIiIiIqf0qcdK9btw4DBgzQ6X267e3tYW9v/9x6Pj4+uH//Pk6fPg0PDw8AwIEDB6BWq+Hl5VXkOh4eHqhQoQL279+PXr16AQDi4uKQkJAAHx+fl4rbzMwMZmZmL7UNIiIiIiIiKv9KPJHa8OHDkZaWJr92cnJCfHy8PmIqpGHDhujSpQuGDx+OP/74A8ePH8fo0aPRr18/eebyf/75Bw0aNMAff/wBALCxscGwYcMQEhKCgwcP4vTp0xgyZAh8fHzkmcsB4PLly4iOjkZKSgoePnyI6OhoREdHIzc3t1T2jYiIiIiIiMqvEvd0CyE0XmdkZECtVus8oOKsX78eo0ePRqdOnaBQKNCrVy/5dl/A4/uFx8XFISsrSy774osv5Lo5OTnw9/fHihUrNLb73//+F4cPH5ZfN2vWDABw7do1uLi46HeniKjUZCUm4mFSktbrqZycYMHLR4iIiIjoBelk9vLSULlyZURERBS73MXFpdAPA+bm5li+fDmWL19e7HqHDh3SVYhE9AJOjRhRKu/Tvn17jR/YSsrX15d/J4iIiIjohZU46ZYkSWPW8qdfExGVZUuWLEFsbGyJ69+7dw/r1q1DbGwsJElCVFQU3N3d9RcgEREREZVLWg0vf+211+REOzMzE82aNYNCoXlZ+N27d3UbIRGRDri7u2uVNN+8eRMKhQItWrQodsJGIiIiIqLnKXHS/e233+ozDiIinXFxcUFwcDC2bduG2NhYNG/eHOHh4Vrd2s/BwQHBwcF6jJKIiIiIXgUlTrp1easwIiJ9Cw8Px44dO1CtWjX07NkToaGhCAsLQ2BgII4dO1bsejExMahZs2YpRkpERERE5ZnRTKRGRKSN4OBguLq6AgAGDBiABQsWAAB27dplyLCIiIiI6BVT4vt0ExEZE0dHR/m5paUlMjIyDBgNEREREb2qmHQT0SslICAAVlZWxT4SEhIMHSIRERERlSMcXk5Er5Q9e/aUuG52drb8PDc3F9nZ2VAqlYXu2kBEREREVByeORIRFUOlUkGlUgEAvLy8oFKpcOTIEQNHRURERETGROue7vz8fISFhWH//v24desW1Gq1xvIDBw7oLDgiohcRHx+v8TooKAhBQUFab0cIoZuAiIiIiOiVpXXSPXbsWISFhaFbt25o3LgxJEnSR1xERERERERERk/rpHvjxo3YvHkzunbtqo94iIiIiIiIiMoNra/pViqVqFu3rj5iISIiIiIiIipXtE66x48fj6VLl/JaRyIiIiIiIqLn0Hp4+bFjx3Dw4EHs2bMHbm5uqFChgsbybdu26Sw4IiIiIiIiImOmddJta2uLHj166CMWIiIiIiIionJF66T722+/1UccREREREREROWO1td0ExEREREREVHJaN3TDQBbt27F5s2bkZCQgNzcXI1lZ86c0UlgRERERERERMZO657uL7/8EkOGDIGDgwOioqLg6ekJOzs7XL16FQEBAfqIkYiIiIiIiMgoaZ10r1ixAmvWrMGyZcugVCoxadIk7Nu3Dx988AHS0tL0ESMRERERERGRUdI66U5ISECrVq0AACqVChkZGQCAd999Fxs2bNBtdERERERERERGTOuk29HREXfv3gUA1KxZE7///jsA4Nq1axBC6DY6IiIiIiIiIiOmddLdsWNH7Ny5EwAwZMgQfPjhh3jjjTfQt29f3r+biIiIiIiI6Alaz16+Zs0aqNVqAMD7778POzs7nDhxAt27d8fIkSN1HiARERERERGRsdI66VYoFFAo/u0g79evH/r166fToIiIiIiIiIjKA62HlwPA0aNH8c4778DHxwf//PMPAOCHH37AsWPHdBocERERERERkTHTOun+3//+B39/f6hUKkRFRSEnJwcAkJaWhk8++UTnARIREREREREZK62T7rlz52LVqlVYu3YtKlSoIJe3bt0aZ86c0WlwRERERERERMZM66Q7Li4O7dq1K1RuY2OD+/fv6yImIiIiIiIionLhhe7Tffny5ULlx44dQ+3atXUSFBEREREREVF5oHXSPXz4cIwdOxYnT56EJElISkrC+vXrMWHCBLz33nv6iJGIiIiIiIjIKGl9y7DJkydDrVajU6dOyMrKQrt27WBmZoYJEyZgzJgx+oiRiIiIiIiIyChpnXRLkoSPP/4YEydOxOXLl5GZmYlGjRrByspKH/ERERERERERGS2tk+4CSqUSjRo10mUsREREREREROVKiZPuoUOHlqjeunXrXjgYIiIiIiIiovKkxEl3WFgYatWqhWbNmkEIoc+YiIiIiIiIiMqFEifd7733HjZs2IBr165hyJAheOedd1C5cmV9xkZERERERERk1EqcdC9fvhyff/45tm3bhnXr1mHKlCno1q0bhg0bhs6dO0OSJH3GSURERESlKCsxEQ+TkrReT+XkBAtnZz1ERERknLSaSM3MzAz9+/dH//79cf36dYSFhSE4OBiPHj1CbGwsZzAnIiIi0qNTI0aU2nu1b98ehw8f1no9X19fHDp0SPcBEREZqReevVyhUECSJAghkJ+fr8uYiIiIiMjAlixZgtjY2BLXv3fvHtatW4fY2FhIkoSoqCi4u7vrL0AiIiOhVdKdk5MjDy8/duwYAgMD8dVXX6FLly5QKBT6ipGIiIiISpm7u7tWSfPNmzehUCjQokULeHl56S8wIiIjU+KkOzg4GBs3boSzszOGDh2KDRs2oEqVKvqMjYiIiIhKgYuLC4KDg7Ft2zbExsaiefPmCA8Ph7MW12Y7ODggODhYj1ESERmnEifdq1atQs2aNVG7dm0cPny42Gt8tm3bprPgiIiIiKh0hIeHY8eOHahWrRp69uyJ0NBQhIWFITAwEMeOHSt2vZiYGNSsWbMUIyUiMi4lTroHDhzIGcqJiIiIyqng4GC4uroCAAYMGIAFCxYAAHbt2mXIsIiIjF6Jk+6wsDA9hkFEREREhuTo6Cg/t7S0REZGhgGjISIqP4xm9rO7d+9iwIABsLa2hq2tLYYNG4bMzMxnrpOdnY33338fdnZ2sLKyQq9evXDz5k15+V9//YX+/fvD2dkZKpUKDRs2xNKlS/W9K0RERERGIyAgAFZWVsU+EhISDB0iEVGZ9sK3DCttAwYMQHJyMvbt24e8vDwMGTIEI0aMQERERLHrfPjhh9i9eze2bNkCGxsbjB49Gj179sTx48cBAKdPn0bVqlXliUJOnDiBESNGwMTEBKNHjy6tXSMiIiIqs/bs2VPiutnZ2fLz3NxcZGdnQ6lU8i43RPRKM4qk+/z589i7dy/+/PNPtGjRAgCwbNkydO3aFYsXL4aTk1OhddLS0vDNN98gIiICHTt2BAB8++23aNiwIX7//Xd4e3tj6NChGuvUrl0bkZGR2LZtG5NuIiIiIi2pVCr5ecFtww4ePIj27dsbKCIiIsMzip8dIyMjYWtrKyfcAODn5weFQoGTJ08Wuc7p06eRl5cHPz8/uaxBgwaoWbMmIiMji32vtLQ0VK5c+Znx5OTkID09XeNBREREZKzi4+MRFBQkvw4KCkJ8fLzW2xFCFHow4SaiV51RJN0pKSmoWrWqRpmpqSkqV66MlJSUYtdRKpWwtbXVKHdwcCh2nRMnTmDTpk0YMWLEM+OZP38+bGxs5Ic297AkIiIiIiKiV4dBk+7JkydDkqRnPi5cuFAqsZw9exb/+c9/MGPGDHTu3PmZdadMmYK0tDT5kZiYWCoxEhERERERkXEx6DXd48ePx+DBg59Zp3bt2nB0dMStW7c0yh89eoS7d+9q3N7iSY6OjsjNzcX9+/c1ertv3rxZaJ1z586hU6dOGDFiBKZNm/bcuM3MzGBmZvbcekRERERERPRqM2jSbW9vD3t7++fW8/Hxwf3793H69Gl4eHgAAA4cOAC1Wi1P0vE0Dw8PVKhQAfv370evXr0AAHFxcUhISICPj49cLzY2Fh07dsSgQYMwb948HewVERERERER0WNGcU13w4YN0aVLFwwfPhx//PEHjh8/jtGjR6Nfv37yzOX//PMPGjRogD/++AMAYGNjg2HDhiEkJAQHDx7E6dOnMWTIEPj4+MDb2xvA4yHlHTp0QOfOnRESEoKUlBSkpKQgNTXVYPtKRERERERE5YdR3DIMANavX4/Ro0ejU6dOUCgU6NWrF7788kt5eV5eHuLi4pCVlSWXffHFF3LdnJwc+Pv7Y8WKFfLyrVu3IjU1FeHh4QgPD5fLa9Wq9UIzdhIRERERERE9SRJCCEMHYezS09NhY2ODtLQ0WFtbGzocInpFtVizxtAhlBmnnnMXCiIiIqKXVdI80CiGlxMREREREREZIybdRERERERERHrCpJuIiIiIiIhIT5h0ExEREREREekJk24iIiIiIiIiPWHSTURERERERKQnTLqJiIiIiIiI9IRJNxEREREREZGeMOkmIiIiIiIi0hMm3URERERERER6wqSbiIiIiIiISE+YdBMRERERERHpCZNuIiIiIiIiIj1h0k1ERERERESkJ0y6iYiIiIiIiPSESTcRERERERGRnjDpJiIiIiIiItITJt1EREREREREesKkm4iIiIiIiEhPmHQTERERERER6QmTbiIiIiIiIiI9YdJNREREREREpCdMuomIiIiIiIj0hEk3ERERERERkZ4w6SYiIiIiIiLSEybdRERERERERHrCpJuIiIiIiIhIT5h0ExEREREREekJk24iIiIiIiIiPWHSTURERERERKQnTLqJiIiIiIiI9IRJNxEREREREZGeMOkmIiIiIiIi0hMm3URERERERER6wqSbiIiIiIiISE+YdBMRERERERHpCZNuIiIiIiIiIj1h0k1ERERERESkJ0y6iYiIiIiIiPSESTcRERERERGRnjDpJiIiIiIiItITJt1EREREREREesKkm4iIiIiIiEhPmHQTERERERER6QmTbiIiIiIiIiI9MTV0ACV19+5djBkzBj/99BMUCgV69eqFpUuXwsrKqth1srOzMX78eGzcuBE5OTnw9/fHihUr4ODgAAC4c+cOBgwYgJiYGNy5cwdVq1bFf/7zH3zyySewtrYurV0jIjI6WYmJeJiUpPV6KicnWDg76yEiIiIiorJJEkIIQwdREgEBAUhOTsbq1auRl5eHIUOGoGXLloiIiCh2nffeew+7d+9GWFgYbGxsMHr0aCgUChw/fhwAcO/ePWzcuBEtW7aEvb09Ll++jPfffx/Nmzd/5naflp6eDhsbG6SlpTFZJ6JXQvv27XH48GGt1/P19cWhQ4d0HxARERFRKStpHmgUSff58+fRqFEj/Pnnn2jRogUAYO/evejatStu3LgBJyenQuukpaXB3t4eERER6N27NwDgwoULaNiwISIjI+Ht7V3ke3355Zf49NNPkZiYWOL4mHQT0asmOjoasbGxJa5/7949rFu3DomJibh9+zaioqLg7u6uvwCJiIiI9KykeaBRDC+PjIyEra2tnHADgJ+fHxQKBU6ePIkePXoUWuf06dPIy8uDn5+fXNagQQPUrFmz2KQ7KSkJ27Ztg6+v7zPjycnJQU5Ojvw6PT39RXaLiMhoubu7a5U037x5EwqFAi1atICXl5f+AiMiIiIqY4xiIrWUlBRUrVpVo8zU1BSVK1dGSkpKsesolUrY2tpqlDs4OBRap3///rCwsED16tVhbW2Nr7/++pnxzJ8/HzY2NvLDmdcnElE55uLigkWLFsHb2xsVK1aEr6+vVqOBgMd/e4ODg+Hp6amnKImIiIjKJoMm3ZMnT4YkSc98XLhwQe9xfPHFFzhz5gx27NiBK1euICQk5Jn1p0yZgrS0NPmh7cknEZGxCQ8Px4YNG5CamgpLS0uEhoYCAAIDA2Fra1vsIyEhwcCRExERERmWQYeXjx8/HoMHD35mndq1a8PR0RG3bt3SKH/06BHu3r0LR0fHItdzdHREbm4u7t+/r9HbffPmzULrODo6wtHREQ0aNEDlypXRtm1bhIaGolq1akVu28zMDGZmZs/fQSKiciI4OBiurq4AgAEDBmDBggUAgF27dhkyLCIiIqIyz6BJt729Pezt7Z9bz8fHB/fv38fp06fh4eEBADhw4ADUanWx1wZ6eHigQoUK2L9/P3r16gUAiIuLQ0JCAnx8fIp9L7VaDQAa12wTEb3qnvyx0tLSEhkZGQaMhoiIiMh4GMVEag0bNkSXLl0wfPhwrFq1Cnl5eRg9ejT69esnz1z+zz//oFOnTvj+++/h6ekJGxsbDBs2DCEhIahcuTKsra0xZswY+Pj4yJOo/fzzz7h58yZatmwJKysrxMbGYuLEiWjdujVcXFwMuMdERMYhICAAR48eLXb5uXPnULNmzVKMiIiIiKhsMYqkGwDWr1+P0aNHo1OnTlAoFOjVqxe+/PJLeXleXh7i4uKQlZUll33xxRdy3ZycHPj7+2PFihXycpVKhbVr1+LDDz9ETk4OnJ2d0bNnT0yePLlU942IyFjt2bOnxHWzs7Pl57m5ucjOzoZSqYRCYRRzehIRERG9EKNJuitXroyIiIhil7u4uODpW46bm5tj+fLlWL58eZHrdOjQASdOnNBpnEREVDSVSiU/L7g06ODBg2jfvr2BIiIiIiLSP0k8namS1kp6U3QiIiIiIiIqH0qaB3JMHxEREREREZGeGM3w8rKsYLBAenq6gSMhIiIiIiKi0lCQ/z1v8DiTbh0ouHWOs7OzgSMhIiIiIiKi0pSRkQEbG5til/Oabh1Qq9VISkpCxYoVIUmSocMps9LT0+Hs7IzExERe+/6S2Ja6w7bULban7rAtdYdtqVtsT91hW+oO21K32J4lI4RARkYGnJycnnk3FvZ064BCoUCNGjUMHYbRsLa25odXR9iWusO21C22p+6wLXWHbalbbE/dYVvqDttSt9iez/esHu4CnEiNiIiIiIiISE+YdBMRERERERHpCZNuKjVmZmaYMWMGzMzMDB2K0WNb6g7bUrfYnrrDttQdtqVusT11h22pO2xL3WJ76hYnUiMiIiIiIiLSE/Z0ExEREREREekJk24iIiIiIiIiPWHSTURERERERKQnTLqJiIiIiIiI9IRJN720e/fuIT8/39BhlAsXL17Epk2bDB1GucC21K0LFy5g2bJlhg6jXOCxSWVVVlaWoUMgKhLnfSZjx6SbXsq1a9fg5eWFK1euGDoUo5ednY2goCBcv37d0KEYPbal7ggh8OjRIwwdOhRJSUmGDsfo8djUrevXr+P33383dBjlQlxcHN5++23873//M3QoRi81NZWfcR26evUqvv76a6SlpRk6FKN3/fp17N27F9nZ2YYO5ZVjaugAyLj99ddfEELgtddeM3QoRs/c3BympqZwcnIC8DjZkSTJwFEZJ7al7kiSBFNTU0iSBDs7OwCAWq2GQsHfbF8Ej03duXHjBpo0aQJ7e3usWbMGnTp1MnRIRuvhw4cYOXIkjhw5AktLS5iYmCAoKMjQYRmly5cvw8/PDwEBAQgJCUG9evUMHZJRu3nzJry8vGBlZYWHDx9i0KBBsLGxMXRYRikhIQH16tVD/fr1MW/ePPj7+/Me3KWIZ030UjIyMmBqyt9uXlZ+fj6EEMjPz+eXyUtiW+qWWq0GAOTl5cHa2hoAmCS+IB6buhUbGwshBKpXr46ZM2diz549hg7JaKlUKnTp0gWmpqY4d+4c1q1bh59++snQYRmljRs3IiEhAdHR0Vi7di0uXbpk6JCM2sOHD5Gfn4/79+9jx44d+Pbbb5Genm7osIxSVlYWFAoFLl68iDlz5uCXX35Bbm6uocN6ZTBbIq09fPgQZmZmUCgUUKvV8kkkAJiYmBg4OuNy5coVZGdnw83NDampqUhJSZHbkImNdtiWunXp0iWkpKSgbdu2yMrKwu3bt6FSqQCwPbXFY1M/OnXqhNdffx15eXlo2rQp5syZAxMTE3Tu3NnQoRmV/Px8mJiYYPDgwbh8+TLc3Nzw448/YsmSJZAkCYGBgYYO0aiMHDkSP/74IyRJwq+//or8/HwEBwejTp06hg7N6Agh4OLigk8//RS7d+8GAHz77bdQKBQYPHiw/EMwPZ9arUaDBg0wa9Ys3Lp1C1FRUQgJCYEkSfD394dSqTR0iOUee7pJK4mJifDx8cFvv/0G4HHvl4WFBUxMTCBJkpyEA4//WHLii+Ll5uZi9uzZaN68Oc6ePQt7e3tIkgQLCwsAnDREG2xL3VKr1Vi+fDl8fX1x8OBBWFhYID8/X066qeR4bOpHbm4uTE1N8fHHH6NatWrw8fGBk5MTpk+fjl9//dXQ4RmF7OxsCCFgYmICIQQqV66MtLQ0JCYmYteuXXj06BGWLl2KXbt2GTpUo5GXlwc7Ozt069YN//nPf/Dee+9hx44dWL58Oee+0ULB38WCkVYuLi7IyMjA/PnzERAQgDVr1rDHW0sFP/A6OTkhMjISW7duhYeHBz788EP2eJcS9nSTVpydnSGEwKhRoxAWFobExERUrVoVAApd4ylJEjIyMlCxYkVDhFrmKZVKjB07FllZWfD390d4eDiaN2+O69ev4/r167h37x6USiUsLS2RlZWFhIQENGvWTG5v+hfbUrcUCgWmTZuG7OxsdO3aFdu3b0eDBg1w7tw5REVF4fbt2zAzM4OFhQWysrJw48YNNGvWDA0bNjR06GUOj03dSUxMxNWrV+Hr6yv3yjg7OyMhIQEODg6YN28epkyZghkzZgAAe7yf4cKFC5g8eTLc3NwwceJEWFhYQKlU4pNPPoGfnx/69u2L7777Du+88w6+/PJLKBQKdO3a1dBhl0l3795FWloaXF1dUaFCBQCAp6cn/vvf/yI6OhoVK1bEzJkzIUkSe7xL4Nq1a9i/fz/8/Pzg4uIC4PGoluXLlyM0NBSbN29Geno6vvnmGwDA0KFDeZ5ZjOvXr+PChQt4/fXX4ejoCAB499138d1332HRokXYtGkTAgICMH78eABgj7e+CaIX0LZtW9GwYUPx1ltviYoVK4o33nhDtG3bVnTv3l106dJFtGvXTrRt21a888474sGDB4YOt0yLiooSPXv2FJaWlkKSJOHi4iKsra2FmZmZsLS0FJUqVRKWlpbCzs5OXLt2zdDhlmlRUVGiR48ebMsXlJmZKdRqtfz69u3bYtiwYUKSJCFJknB1dRUODg5CpVIJa2tr4ejoKGxsbESVKlXE5cuXDRh52cdj8+Vcv35d2NraCkmSxMSJE8UPP/wgH6tffPGFcHd3FxkZGeLEiROid+/eok2bNmLXrl0GjrpsevDggWjdurWQJEnY2dmJ119/XYSGhopffvlFCCHEe++9Jz799FMhhBAXLlwQvr6+wtPTU+zdu9eQYZdJcXFxwtnZWTRt2lR8/vnnIiEhQTx69EgIIcSQIUPEuHHjhBBCfPnll6J+/fpi4sSJIi4uzpAhl2n//POPsLGxEZIkierVq4ulS5eKX3/9VQghxF9//SUCAwPlv4/Dhg0TzZs3F/Pnzxfp6ekGjLpsio+PF5IkiUqVKommTZuKiIgIERsbK4QQ4scffxSBgYHy39A33nhDNGrUSGzZskXk5uYaMuxyTRKCY9vo2VJTU5GQkIAKFSqgVq1a8gRAnTt3xm+//Ya2bduicePGAABLS0vk5+cjOzsbVlZWGDBgAJo2bWrI8MuUpKQknDlzBrm5uahZsyZatGgBADhz5gyWL1+ODRs2YPXq1ejWrRtu3boFhUKBR48eyT1h1apVM/AelB3x8fHYt28fFAoFqlevji5dugAAYmJi8MUXX2DTpk1sSy2cP38ePXr0wNy5c9G7d2+5PDU1FZ9//jkWLlyIr7/+Gv369cP9+/chSRKEEFAoFKhQoYI8sznx2NSH3bt3Y86cOUhOTkajRo1QqVIlREVF4ZNPPoFSqcT//vc/DBo0CL6+vjhy5AjmzZsHIQS2b98OlUrFa+efsnPnTixcuBCvv/468vPz4eTkhM8++wzjxo3DmTNn8Pvvv+PkyZOoU6cOLl68iLFjx2L16tWoWbOmoUMvU+bNm4fQ0FB4eHggMTERfn5+yMvLw9KlS/Hjjz9i586d+PHHH2Fubo4VK1Zg5syZGDFiBGbMmCH3itO/kpOT8c477yArKwsODg6QJAm3b9+Gs7MzBg8ejLFjx2LAgAGYNm0aAGDAgAFISEjAzp07UalSJQNHX7Zcu3YNHTt2hKWlJZo0aYJLly7BwcEBDRs2xKBBg/DGG29g2rRpGD16NACgVatWyMvLw8GDB2FlZWXg6Mspw+b8VNbFxMSIhg0biiZNmghJksS0adNEdna2vNzf31/UrFlTnDhxwoBRGoeYmBhRu3Zt4enpKapUqSJatGghNm3aJC8/c+aM6N27t6hRo4aIioqSy/Pz8w0QbdkWExMj7OzshLe3t6hTp46wsrISQ4cOFbdu3RJCPP5FvGfPnmxLLUyePFlIkiQqV64stmzZorEsJSVFDBs2TFhYWIjffvtNLmd7FsZjU7cKeg2FEGLLli0iKChItGnTRvz9999i4cKFonv37sLNzU1IkiR69+4t1z1x4oRITEw0RMhl1pPf3UIIsXXrVtGqVSsxcOBAcebMGfH333+L0aNHizfeeENIkiROnDgh94Sx96t448ePFwEBAWLixIkiIiJC9O/fXzRv3lyMGjVKSJIk5syZI9ddu3YtRwU9x/Xr10XXrl1Fnz59xJIlS8SFCxdEjx49xDvvvCNMTU1F9erVRVJSklz/yef0+Ps6JSVFCCHExYsXRaNGjcTQoUNFWFiY2Ldvn/D09BS9e/cWFhYWwsfHR6SmpsrrXr9+3VBhvxKYdFOxLl++LBwcHMRHH30k4uPjxfLly4VCoSh0ItOqVSvh7OwsDh48KHJycgwUbdl2+fJlUaNGDTFp0iRx//59cerUKTFo0CAxdOhQjZOZmJgYERQUJJydncXp06cNGHHZlZGRIXx8fMSYMWOEEEIkJyeLPXv2iMqVK4vOnTuL+Ph4IQTbUltbt24V48aNE3PmzBFKpVLjByEhhMjKyhLDhg0TVlZWHGZaDB6bunXp0iWxYsUKjRPBzZs3i/bt24uAgACRlpYmHj58KLZv3y5atWolvv/+ewNGW7bFxsaKbt26afxoJoQQ27ZtEy1bthR9+/YVFy9eFEI8Hn5+6NAhjXpPXnZChb333nuiVatWYsGCBUIIIfbu3SsWLlwoLC0txdatWw0cXdl26tQpMWLECCHEvz8+Xr16VXTr1k20b99evkzk4sWLYs6cOeKHH34QQmj+IEePnTt3TjRu3Fh8/fXXcllsbKxo1KiRePPNN8Vff/0lhBDit99+E6NHjxZhYWFCCCHy8vIMEu+rhkk3FWvatGkiMDBQoywgIEAcP35cnDhxQv6CFkKIDh06CCsrK3H06NHSDrPMy8nJESEhIaJPnz4aP0p88803ws7OTty+fVuj/t9//y06duwoGjRoILKzs3my85SsrCzRvHlzsXHjRo3yuLg4UaVKFdG9e3e5LDo6mm1ZQocOHRKNGzcWDx8+FMHBwcLc3Fz8+uuvYvz48WLlypVCiMfXePft21c4OjpyroYiPHz4kMemjvz111+iUqVKIiQkRFy8eFGjfbZs2SLatm0rOnXqJBISEoQQgtd0PoNarRaDBg0SNjY2IjAwsFDivWPHDtGiRQvRr18/cfz4cY31SNPVq1fFsmXLxJgxY8TevXvlHkUhhPjggw+Eu7u7WLBggcjIyBBCCHmECxUtOjpaWFhYyD9UCqGZeAcGBoq2bduKDRs2GCpEo1HQlpIkiQ4dOmgsO3/+vHBzcxOdO3cWkZGRBoqQmHRTscaOHSsCAgLE3bt3hRBCzJkzR0iSJFq2bCkcHR2Fv7+/2Ldvn1w/MDBQIxGnxx4+fCg+//xzsXbtWiHEvycy58+fF7Vq1RLJycka5UI87gnj0EhNBe2TkZEhqlevLmbNmiUvKxgt8NdffwlLS0uNZbGxsWzL51Cr1eLGjRvC09NTTl6mTJkiTExMhLW1tTz5ihBC3L17l8P5ivDo0SORmZnJY1MHkpKSRL169cSECRM0yu/fvy8/37p1q/D19RUdOnSQ25BD9IsXHBwsvLy8RI8ePYSfn588OVWB7du3i5YtW4p3331XHDt2zEBRlm0xMTGievXqws/PT7i7uwtra2vx+eefa9QZO3asaN68uZgzZ458vPK4LFp0dLSwtLQs9Dl/0pUrV0RgYKBo3769WL9+fSlGZ1yio6OFSqUS06dPF6dOnRLVq1cXmzdvFkL824tdkHgHBASwg8xAmHRTsZYvXy4sLS1F7969xYABA0SFChXEtm3bRGZmpoiMjBRt27YVkydP5rVeJXDlyhX5eUHymJycLOrWrSv31AjxeJgVFRYfHy9+/vln+fXnn38uatSoIX766Se5rOA4nDt3rvDy8tK4TomK9+SPPW3atJGPwXfffVdUrFhRKJVKsX37dkOFV+bdu3dP4zWPzZf322+/CW9vb/Ho0SPx6NEj8cEHH4jOnTuLtm3bii+++EKut2XLFuHn5yeaN28u/vnnH8MFbAQiIiLEggULxMmTJ4W/v7/o3LmziIqKEp988on8HbRz505Rr1498d///lc8fPjQwBGXLfHx8aJevXpiypQpchKzcOFCUaVKFXHnzh2NumPHjhXe3t5i6tSpHIFRjKSkJGFhYSEGDx4shHg838DkyZPFW2+9Jfz8/MTq1avFjRs3hBCPz5+CgoJEs2bN5ESS/hUVFSUsLCzE1KlThRCP27Zx48Zi1KhRQojH3/FPJt6vv/66aN26NediMgDF86dao1dFVlYW7t27h6ysLABAcHAwFi5ciBYtWiAnJwfDhg1Djx49YGlpCW9vb9SpUwfHjh2DiYmJgSMve+7cuYMLFy7gxIkTAIDatWtDPP6RS55FNy0tDffu3ZPXmT59Ot544w3cuXMHgjcVkJ09exZ169bFpEmT5LIuXbqgdevWWLRoEX799VcAkGeCrVKlCtLT02FhYWGQeMu6pKQk/Pnnn9i1axdycnLkciEErK2t8c8//2Ds2LH47bffcPToUYwbNw49evTAjh07DBh12RQdHY0333wTMTExclnXrl15bL6kxMREmJiYwMTEBH5+frh06RI8PT3h6emJ8ePH48MPPwQA9O7dG0OGDEH16tWRl5dn4KjLtooVK2Lnzp3w9PTExIkTYWlpicDAQHz88cfyd/ibb76JpUuXYurUqTA3NzdwxGVHfn4+tm/fjubNm2PcuHFQKB6fOr/zzjuwsbHBzZs35XoAsGTJEri5uSEyMhK5ubkGi7ssS0pKQsuWLXHq1ClcvnwZPXv2xNGjR1GlShWYm5tj5cqVmDlzJm7duoXatWtj8eLFqF+/Pjw9PQ0depmzdOlSjBkzRr5jQ7Vq1TBp0iSEhYUhMjISkiTB1NQUarUaDRo0wPr166FWq1GjRg1Dh/7qMWjKT2XG2bNnRWBgoGjYsKEICgoq1LM1duxYMXnyZCHEvz1jgwcPFqNGjeIEDE+JiYkRnp6eon79+qJq1arC399fXvZkr2JcXJywt7cXd+/eFXPmzBEqlYo93U+JiooSlpaWolu3bqJOnTriu+++k5cdOHBAdO/eXXh6esrXe+Xm5opJkyYJX19f9jAU4a+//hIuLi6iZcuWolq1asLFxUWsXr1a3Lx5UwghxPz584VSqRQ1atTQmOBr6tSp4vz584YKu0yKjo4WFSpUEBMnTiy07NdffxXdu3cXLVu25LH5Ak6cOCFsbW3F4sWLRdeuXeUeLyEeT/ylUCjEzp075bKC62epeHFxccLLy0t+7efnJywsLIS3tzeHmpbApk2bxNy5czXK0tLSRNWqVQtdI1/gyeu9qbDTp0+Lzp07C0mSREBAgMYIoM8++0y4urpqXOrAc83nKzjHvHLlivD09BTTp08XQvw76VzBvxyhahhMuknExsaKSpUqiffff1+sWrVKtG7dWrz99tsadWbPni0sLS3FkSNHxIkTJ8SMGTNE5cqVNa71JCEuXLggqlSpIiZPniwiIyPFL7/8ImrXri2mTJlSqO7NmzdFs2bNRN++fYVSqWTC/ZSCSUFCQ0NFbm6u8Pb2Fu+++65GnePHj4v33ntPmJqaitdff114e3uLSpUqadyKiR5LTEwUdevWFbNmzRJJSUlCrVaLnj17CnNzczFu3Dhx+/ZtceLECdGnTx+233OcPXtWvn5OiMcnOnfu3NG4FVBkZKQYNWoUj00tqdVqce/ePTFw4EDRrFkz0bRpU41lGRkZolmzZmLZsmUGjNL45Ofni3bt2omEhATx7rvvCicnJ7FixQoRFBQkWrZsKQ4fPmzoEI1GQWLz4MEDUbduXXHkyBF52c8//8wfKJ/jyc6H33//XUyYMEGeH+jJGcltbGzk2eCpaM+a7DAkJEQ4ODgUOekpJ0k0DCbdr7isrCwRFBQkxo4dK5ft2LFD9OjRQ9y8eVOkpaXJ5b179xYKhUK89tprwt3dXURHRxsg4rIrIyND9OnTRwQHB8tl+fn5YsyYMRqzFhc4f/68kCRJqFQqnog/5dKlS0KSJPHxxx/LZVu2bBFmZmbi4MGDGnUzMjJEZGSkmDNnjli1apW4dOlSKUdrHPbu3StfT1wwi/6ff/4pqlSpItzd3eUJvtgL+2y3b98WdevWFc2aNZPLhgwZIjw8PES1atVEmzZt5L+NPDZf3JYtW0S9evWEJEnil19+0VjWsWNHeWJKej61Wi1ycnJE27ZtRfXq1YWzs7P8nbN7927Rt29f3p/3GYpKUNRqtXj48KFo2rSp/IP5Rx99JOzt7TXmaaGiPdmm8fHxGnd2efTokUhOThZeXl4ac2NQyRRM3FcwIeWsWbOYZJcRpoYe3k6GZWZmhjt37qBZs2Zy2dGjRxEVFYXmzZvjtddeg5eXF+bPn48tW7bg8OHDsLOzQ9WqVVG1alUDRl42VaxYEe7u7vJrhUKBNm3a4NChQ8jNzYUkSfL1nXZ2dggODsbo0aPRoEEDA0VcNpmbm2PVqlUYMWIEgMfXG/v4+KBFixbYuXMn2rdvj0ePHsHU1FSeY8Db29vAUZdtCQkJuHbtGqpUqSKXZWZmwsfHB5UqVcKKFSswZMgQODs7GzDKss/Ozg6dO3dGTEwMZs6ciZ9//hl2dnYYOXIk7O3tsWjRIrz55ps4cOAA6taty2NTS+L/573o3bs31Go1Zs+ejWHDhmHOnDmoXbs29uzZg/Pnz6NTp06GDrVMEk/MG1JAkiQolUqMHDkSy5Ytw/Lly+Xvqa5du8LX1xeWlpYGiNY4PN2eBWWPHj3C/fv3kZOTg5kzZ2LZsmU4dOgQ/4Y+Q8Hx+WSb1qpVS6OOiYkJVq1ahfv37+P1118v7RCNXsGcA5UrV0bLli3x888/Y/r06QaOigBAEoIzNr2q1Go1MjMz0adPH1hYWMDPzw83btzAkiVLsGLFCjg6OuKPP/7A9u3bMX36dAQFBRk65DJNrVYjMTFR/gIp+HLZvHkz5s6dqzHZUlZWFiwsLPDw4UOoVCpDhWx0ZsyYgWXLluHSpUuws7Mr8gSTipaSkoJmzZrhjTfewIwZM5CSkoLOnTtj+vTp+Oijj9CgQQO88847mDZtmqFDLZOSk5ORmpqKpk2bAgBCQkIQERGBFi1a4JtvvoGDg4Nct3HjxmjRogXCwsIMFG3Zl5+fX+wknGq1Wj5xPHDgADZv3ozvvvsO9erVgyRJCAsL0/ih+FX34MEDqNVqeTLE4uTl5eHBgwewtbUFUHSC/qq7e/cubt26BRMTE9SqVQtKpbLYug8ePEDr1q1haWmJ06dP4/jx4/Dw8CjFaMu+rKws5OTkQKVSlWhyvr1792L37t344YcfcOjQIY1ODCqsuM9wQfmxY8fQu3dvxMTEsKOsDODs5a+gghk2FQoFrK2tMWvWLDx8+BDHjx/Htm3b8NVXX2Hw4MHo0qULRo4cKc/ETYU9ePAAGRkZSE9Ph0KhkBNutVot/yFUKBRQq9XyOuPHj8dbb72F/Px8JtxPeLItn1bw2+CYMWPg6OiIxYsX84TxOZ5uT0dHR6xcuRKHDh1Cq1at0L17d4waNQofffQRAMDe3h4PHjwwZMhl1j///IMmTZpg5syZ+P333wEAn3/+OcaPH4+hQ4fKJzMFf1sbNGjAtnyGixcvYsmSJUhOTi5yuUKhwKNHjwAAHTt2xKpVq3DlyhXs378fhw4dYsL9hHPnzqFnz57w9fVFw4YNsX79egDQuANGwXFZoUIF2Nrayt9H/Pup6ezZs/Dz80OfPn3QpEkTLFq0SG67pwkh8PDhQ6SmpuLChQv4448/mHA/JTY2Fn379kXr1q3Rv39/7N69u1CdJ8+NACAmJgYJCQk4duwYE+4nXL58GQsXLpRnJU9NTQXw+DNc0IZPfuYLylu0aIFz584x4S4jmHS/Yoo62fHy8sLWrVvx/fffo3LlyrCyspKXVa5cGfXr15d/PefAiH8962SnoJcGACwsLOQTyKlTp2LlypUIDQ3lrdae8LwTx4KTQ1tbW3h7e+Pw4cNym1JhT7dneHg4ACAoKAjnzp3DTz/9hIMHD+Kzzz4DAOTk5MDKykoeFsnPuaZLly4hLS0NaWlpWLlyJU6ePAkAmDhxIgICAuTj08TERP4xqFGjRgDYlk+7fPkyfHx8MHHiRCxbtgy3b98uVEcIAVNTzavfHB0dYW9vj0qVKpVWqGXeuXPn0K5dO7i5uWHChAno168fhgwZgujoaI2EuuC7ZufOnUhNTdX4fqLHzp07h/bt26NTp07YuHEj5s2bh+nTpyMpKUmu82SCKEkSqlSpgokTJ+LIkSPyCBh67Ny5c2jbti1q1aqFsWPHIjU1FRERERp18vPz5WMxPj4eADBp0iR8//33aNy4cWmHXGadPXsWXl5eOHLkCK5du4ZRo0ahT58+8m08FQoF8vPz5c98wd9UhUIBc3NzVK5c2WCx01NK7/JxMrRLly6JypUrC0mSxJQpUzRuz5Cfny8yMzOFl5eXCA0NFffu3RMZGRkiNDRUVKtWTVy9etWAkZc9sbGxws7OTnz44Ydi/fr1IiQkRFSoUKHICdF27NghvL29xdSpU4VSqdS4FROVvC0LJgK5evWqkCRJrF692gDRln3FteeZM2eKrJ+eni4mT54sqlatKq5cuVLK0RqHO3fuiO7du4vVq1eL5s2biwEDBoiYmBghxL+T1gjx+JY206ZNE9WqVeOkaUXIzMwUQ4cOFYMHDxbLly8XkiSJiRMnanwXPWnRokVi9uzZpRylcbhz547o3Lmz+OCDDzTK27dvL8aMGSOE0Jys6qeffhI1atQQH3/8scYxS0KkpqaKdu3aaUwoq1arRZcuXcSJEydEVFSUSExMlJctXbpUfP311waI1Dg8b4LeJ2/xp1arxeLFi4Wfn584efKkAaIt2+7duydatWqlcQec8+fPC1NTU9G8eXMRFhamUX/GjBli6NCh/C4vo5h0vyJKerKzadMmIUmSeO2114SXl5eoVatWsSfrryptT3YK2rRSpUq8LdhTtG3L/Px8kZ6eLsaMGSMuXrxYqrEag5K055Mn3FFRUWLUqFHCycmJPwYV49GjR+LWrVvitddeEzdu3BDbtm0TLVu2FMOHDxetWrUSvXr1EkI8nh3+zTffFI6OjvybWYysrCyxfPlysXHjRiHEv38bi/ouunPnjujbt6/w8vISd+7cMUS4ZVpKSorw9PSUb1dV8LkeMmSIGDBgQJHrhIaG8mS8CLdv3xaffPKJxnfK7NmzhSRJwt3dXdSoUUP4+/uLo0ePijt37oiWLVuKLl26aNzdhf6Vn58v2rZtK98RQwghJkyYIFxcXET16tVFx44dxeTJk+Vl3377rWjXrp3GDxv0WGpqqnB3dxcHDx4UarVaPHjwQDx69Ei0a9dOuLu7i06dOomzZ8/K9RcuXCjq16/Pe8SXUZy9/BWhUCjg4eEBOzs79O3bF1WqVEG/fv0APB7OUzCjcZ8+fVC9enUcOnQIVapUgb+/P1xcXAwYedmTl5eH+/fvo3fv3gD+nfTH1dUVd+/eBaB5rZyHhwfatGmD5cuXo0mTJgaJuazSti0VCgUqVqyITz/9FGZmZgaJuSwrSXs+ObTU3d0dfn5+mDRpElxdXQ0Sc1mnUChgb2+Pli1b4uzZs+jRowfMzMwwaNAg5OTkYPjw4QCAOnXqoGHDhli0aBHvRlAMlUqFQYMGyTNl9+nTB0II9O/fH0IITJ48GXZ2dvKw0xUrViAnJ4fDI4vg4OCA8PBw1KtXD8C/Q3WrV6+O69eva9S9f/8+bG1tMXv2bEOEWubZ2dlh9OjRqFixIgBg48aNmDFjBjZu3Ag/Pz+cPXsWEyZMwG+//YY2bdrgm2++gY2NzTMnrXtVFUzQa2FhgejoaKxYsQI3btzA8uXLNSbo3bFjB7y8vBAUFITBgwejV69ecvsTcOPGDaSmpqJatWqIi4tDSkoKJEmChYUFEhISkJ2djY8++gjvv/8+Nm/ejFmzZgF4fD4/fPhwXoZTRjHpfkU872Tno48+QpUqVZCXl4f69eujdevWBo647NLmZCczMxN16tTBnj17eEuWImjblgXzDTDhLpo27Zmeng5ra2v06tXLEKEajSev1z506BD8/f2xbds25Ofnw9nZGUePHoWbmxtatmyJTz75hHM1PEfB38GCY7Nv374QQuDtt9+GJEkYN24cPv30U8THx2Pjxo1MuJ+h4HOuVqvlW1EKIXDr1i25zvz582FmZoYPPvig0HXy9K8nEz4fHx+cOnUKzZs3BwC0a9cOVatWxalTpyCE4I/nRSi4G8GTE/TOnDkTx48fx+nTp+UJegGgWbNm+OabbzQm6GXC/a/Y2FgEBASgV69e+OKLLxAcHIxBgwbh7NmzqFq1KqZPn46+ffuiX79+SE5OxtatWzFp0iQolUp5skQqm/gX+BVSkpOdxYsXIz4+Hj/88AMsLCw4u2kxSnqyo1QqMW7cOCbcz8ATR91ie+qW+P+J0Tp27Ihr164hODgYP//8M06fPo3o6GhMnDgRFSpUQJMmTUp0Sxx6rGDSObVajX79+kGSJLz77rvYuXMnrly5gj/++IM/rpWQQqHQuJtDwWiW6dOnY+7cuYiKiuLnXAu1atXSuBNJbm4urKys0LRpU54TFeHixYv46aef8Pbbb6NatWoA/p2g19zcHG3btn3mBL30r7/++gutWrWCg4MDNm7ciI8//hizZs1CpUqVsG7dOjg4OGD8+PEIDQ0FANy5cwdCCI1zTB6jZRf/Cr+Cnney8+effzJJLKGSnOyw56tkeOKoW2xP3ShoP1dXVwwZMgQODg7YtWsXXF1d4erqCkmS8PrrrzPhfgEFbSuEQN++fbFmzRpER0fjzJkz7E3UUsFn3dTUFM7Ozli8eDEWLVqEU6dO4fXXXzd0eEZLoVDgk08+QWRkJObMmWPocMqcgrsR3Lt3D3fu3EFISIh8uaJKpcLDhw+hVqtx9uxZdO7cGaampli0aBHOnj2L1atXGzj6suWvv/6Cj48PPvzwQ3z44Ydo164d1qxZg6lTp+Ljjz/G6NGjAQA2NjbyOqmpqWjUqBHy8vJgamrKhLuM4xnXK4onO7rDkx3dYVvqFttTd3x8fPD111+jRYsWaNq0qdy2QUFBhg7NqEmShPz8fEycOBEHDx5EdHQ0v4NeQMGPahUqVMDatWthbW2NY8eOyUOkSXtbtmzB4cOHsXHjRuzbt08eRUSPPXjwAPPnz0f37t3RsmVLjB49Go8ePZLnCVIoFLC0tERISAj69euHTZs2oVKlSkhJScHu3bs5j8gTYmJi4OXlhfHjx2PevHlQq9Vwc3PDjz/+iKlTpwLQTLYvXbqEr7/+Ghs3bsSJEyfkUW1UtjHpfoXxZEc3eLKjO2xL3WJ76k6FChUwePBguU3Zo6Bbbm5uOHPmDO93/JL8/f0RGhqKEydOyPeKpxfTqFEjbN26FUePHkXDhg0NHU6Zwwl6dScnJweTJk3C7Nmz5QlQ586dCy8vL6xcuRLvvfeeXPf+/fv44YcfcPDgQRw+fBhubm4GjJy0IQkhhKGDIMPJz89HWFgYPDw84O7ubuhwjNqpU6fg6emJs2fP8mTnJbEtdYvtSWXdk5dC0Mt58OABLxHTkby8PPYiPsPTx9qmTZvQv39/jB8/XmOC3rS0NDkJp+cTQiA9PR2DBw+GUqnE+vXrYWJiIv+NTE5OhomJCapWrWrgSEkbTLqJJzs6xJMd3WFb6hbbk4iI9KFggl5JkrBx40a8/fbbmDBhAifofUnbtm1D7969cfToUbRu3Zrn60aOSTcREREREb0wIQSEEFAoFNi0aRPeffdd1K5dW56gl6MptZebm4s333wT9vb2WLt2LVQqlaFDopegMHQARERERERkvCRJgiRJ8gS9bdu2RWpqKs6cOcOE+wUplUp06NABP/30E9LS0gwdDr0kJt1ERERERPRSJEmCWq1GSEgIDh48iIMHD3KC3hdUMBB55MiRqFevHrKzsw0cEb0sDi8nIiIiIqKXxgl6dUsIgaysLM7JUg4w6SYiIiIiIp3ghF9EhXF4ORERERER6QQTbqLCmHQTERERERER6QmTbiIiIiIiIiI9YdJNREREREREpCdMuomIiIiIiIj0hEk3ERERERERkZ4w6SYiIiIiIiLSEybdREREhMGDByMoKMjQYRAREZU7TLqJiIjKqPbt22PcuHF6X6c84o8IRERUVjDpJiIiIiIiItITJt1ERERl0ODBg3H48GEsXboUkiRBkiTEx8fj8OHD8PT0hJmZGapVq4bJkyfj0aNHz1wnPz8fw4YNg6urK1QqFerXr4+lS5c+8/337t2LNm3awNbWFnZ2dggMDMSVK1fk5fHx8ZAkCZs3b0bbtm2hUqnQsmVLXLx4EX/++SdatGgBKysrBAQEIDU1VV5PrVZj9uzZqFGjBszMzODu7o69e/fKyw8dOgRJknD//n25LDo6Wt4XAAgLC4OtrS1++eUXNGzYEFZWVujSpQuSk5MBADNnzsR3332HHTt2yO1w6NChl/wfISIiejFMuomIiMqgpUuXwsfHB8OHD0dycjKSk5NRoUIFdO3aFS1btsRff/2FlStX4ptvvsHcuXOLXcfZ2RlqtRo1atTAli1bcO7cOUyfPh1Tp07F5s2bi33/Bw8eICQkBKdOncL+/fuhUCjQo0cPqNVqjXozZszAtGnTcObMGZiamuLtt9/GpEmTsHTpUhw9ehSXL1/G9OnTNfbrs88+w+LFixETEwN/f390794dly5d0qp9srKysHjxYvzwww84cuQIEhISMGHCBADAhAkT0KdPHzkRT05ORqtWrbTaPhERka6YGjoAIiIiKszGxgZKpRIWFhZwdHQEAHz88cdwdnbGV199BUmS0KBBAyQlJeGjjz7C9OnTi1wHAExMTDBr1iz5taurKyIjI7F582b06dOnyPfv1auXxut169bB3t4e586dQ+PGjeXyCRMmwN/fHwAwduxY9O/fH/v370fr1q0BAMOGDUNYWJhcf/Hixfjoo4/Qr18/AMDChQtx8OBBLFmyBMuXLy9x++Tl5WHVqlWoU6cOAGD06NGYPXs2AMDKygoqlQo5OTka7UBERGQI7OkmIiIyEufPn4ePjw8kSZLLWrdujczMTNy4ceOZ6y5fvhweHh6wt7eHlZUV1qxZg4SEhGLrX7p0Cf3790ft2rVhbW0NFxcXACi0TtOmTeXnDg4OAIAmTZpolN26dQsAkJ6ejqSkJDkhf3Ifzp8//8z4n2ZhYSEn3ABQrVo1+X2IiIjKEibdRERE5dzGjRsxYcIEDBs2DL/++iuio6MxZMgQ5ObmFrvOm2++ibt372Lt2rU4efIkTp48CQCF1qlQoYL8vODHgKfLnh6S/iwKxeNTEyGEXJaXl1eo3pPvUfA+T65DRERUVjDpJiIiKqOUSiXy8/Pl1w0bNkRkZKRGcnn8+HFUrFgRNWrUKHKdgjqtWrVCcHAwmjVrhrp162pMiva0O3fuIC4uDtOmTUOnTp3QsGFD3Lt376X3x9raGk5OTjh+/Hih+Bo1agQAsLe3BwB5UjTg8URq2iqqHYiIiAyBSTcREVEZ5eLigpMnTyI+Ph63b99GcHAwEhMTMWbMGFy4cAE7duzAjBkzEBISIvcQP72OWq1GvXr1cOrUKfzyyy+4ePEiQkND8eeffxb7vpUqVYKdnR3WrFmDy5cv48CBAwgJCdHJPk2cOBELFy7Epk2bEBcXh8mTJyM6Ohpjx44FANStWxfOzs6YOXMmLl26hN27d+Ozzz7T+n1cXFwQExODuLg43L59u8jeciIiotLApJuIiKiMmjBhAkxMTNCoUSPY29sjLy8PP//8M/744w+8/vrrGDVqFIYNG4Zp06YVu05CQgJGjhyJnj17om/fvvDy8sKdO3cQHBxc7PsqFAps3LgRp0+fRuPGjfHhhx/i008/1ck+ffDBBwgJCcH48ePRpEkT7N27Fzt37kS9evUAPB42vmHDBly4cAFNmzbFwoUL5dnZtTF8+HDUr18fLVq0gL29faHedSIiotIiCV4ARURERERERKQX7OkmIiIiIiIi0hMm3URERERERER6wqSbiIiIiIiISE+YdBMRERERERHpCZNuIiIiIiIiIj1h0k1ERERERESkJ0y6iYiIiIiIiPSESTcRERERERGRnjDpJiIiIiIiItITJt1EREREREREesKkm4iIiIiIiEhPmHQTERERERER6cn/AVPKorFQdV0aAAAAAElFTkSuQmCC", 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mffKyY8eOZblfKlWqJOmPyfH+7OTJkypduvR9Xc7L1hm3f//9d23evFnTp0/XlClTLO2nTp2y6ufl5SV3d3cdO3bsvl7/7vekatWqmfa5+z1p3ry51XMRERGW56U/fpYyOzT87/wsMVs5gPyCc7oBoABxc3PTu+++q2nTpunJJ5/Msl+XLl2Umpqqf/3rXxmeu3PnjqVISx+tunt0Kjk5We+8807OBs+G9CLi7nOm0y/X9Geurq4ZCk1b15GVLl26aO/evdq4cWOG527evKk7d+5ke113GzdunFJSUvTGG29Ikjp16qRChQpp+vTpGUYHDcOwuryUq6trhkP9pcy3NzU1VYsXL76vjH/H4sWLrS4H9u677+rOnTsZZrXv3r27TCaThg8frtOnT2fruu2PPfaY/P39NW/evAz7Pf29K1u2rAIDA/Xxxx9b9Tl27Jj++9//Zij+syurn7WsZPY7JSnDrPdms1khISH65ptvtH///gzrSV8+/YuCP2do3bq1ihcvrlmzZikxMTHTZevWrasyZcpo0aJFSkpKsjy/fv16nThxQh06dLC0ValSRSdPnlR0dLSl7eeff9bu3buzs9mZyio7AOQ1jHQDQAHTu3fvv+wTHBysQYMGadasWTp8+LBat26tIkWK6NSpU1q1apXmz5+vZ555Ro0aNVKJEiXUu3dvDRs2TCaTSZ9++qlDDhFt3bq1KlasqP79+2vs2LEqVKiQPvroI3l5een8+fNWfevUqaN3331XM2bMUNWqVVWmTBk1b97cpnVkZezYsVq7dq06duyoPn36qE6dOrp165aOHj2qL7/8UmfPnlXp0qVt3r6aNWuqffv2+uCDDzR58mRVqVJFM2bM0IQJE3T27FmFhISoePHiOnPmjP7zn/9o4MCBGjNmjGV7P//8c40aNUr16tWTm5ubnnzySQUEBKhhw4aaMGGCbty4oZIlS2rlypX3/cXA35GcnKwWLVqoS5cuioiI0DvvvKMmTZroqaeesurn5eWltm3batWqVfL09LQq/LJiNpv17rvv6sknn1RgYKD69u2rsmXL6uTJkwoPD7d8QfL666+rXbt2CgoKUv/+/S2XDPPw8NC0adPua7vq1Kmj77//Xm+88YbKlSsnf39/NWjQIMv+7u7uatq0qebMmaOUlBSVL19e//3vfzM9emTmzJn673//q+DgYA0cOFA1atRQZGSkVq1apV27dsnT01OBgYEqVKiQXnvtNcXExMjZ2VnNmzdXmTJl9Oabb+r5559XvXr1LNcK//nnn5WQkKCPP/5YRYoU0Wuvvaa+ffsqODhY3bt3t1wyzM/PTyNHjrRk6devn9544w21adNG/fv319WrV7Vo0SIFBATYNLHcn987SRo2bJjatGmjQoUKqVu3bve1LgBwKAfMmA4AeEDuvmTYvfz5kmHpFi9ebNSpU8dwcXExihcvbjz88MPGuHHjjMuXL1v67N6922jYsKHh4uJilCtXzhg3bpyxcePGTC85FRAQkOE1/nxJIVsz3u3AgQNGgwYNDCcnJ6NixYrGG2+8kellsaKioowOHToYxYsXNyRZXeoou+u4V564uDhjwoQJRtWqVQ0nJyejdOnSRqNGjYy5c+daXRYrM1m9T4ZhGNu2bbO6TJphGMZXX31lNGnSxHB1dTVcXV2N6tWrG4MHDzYiIiIsfeLj440ePXoYnp6ehiSr9/u3334zWrZsaTg7Oxve3t7GxIkTjU2bNmV7/6VfAur111/P8Nyfs2Ym/b3dvn27MXDgQKNEiRKGm5ubERoaanXprrt98cUXhiRj4MCB91z3n+3atcto1aqVUbx4ccPV1dV45JFHjLfeesuqz/fff280btzYcHFxMdzd3Y0nn3zSOH78uFWf9Mt9RUdHZ7otd/+cnDx50mjatKnh4uJiSLJcPiyrdRiGYVy8eNF4+umnDU9PT8PDw8N49tlnjcuXL2f6fp47d87o1auX4eXlZTg7OxuVK1c2Bg8ebCQlJVn6vP/++0blypWNQoUKZdiva9euNRo1amTZ3vr16xsrVqyweo3PP//cqF27tuHs7GyULFnSCA0NNS5evJgh97Jly4zKlSsbTk5ORmBgoLFx48YsLxmWnZ+XO3fuGEOHDjW8vLwMk8nE5cMA5Fkmw2DGCgAAkHd8/fXXCgkJ0Y4dOyyXmgIAILei6AYAAHlKx44ddeLECf36669MtgUAyPU4pxsAAOQJK1eu1JEjR/Ttt99q/vz5FNwAgDyBkW4AAJAnmEwmubm5qWvXrlq0aJEKF2bsAACQ+/G/FQAAyBMYJwAA5EVcpxsAAAAAADuh6AYAAAAAwE44vDwHpKWl6fLlyypevDiTugAAAABAAWAYhuLi4lSuXDmZzVmPZ1N054DLly/L19fX0TEAAAAAAA/YhQsXVKFChSyfp+jOAcWLF5f0x5vt7u7u4DQAAAAAAHuLjY2Vr6+vpR7MCkV3Dkg/pNzd3Z2iGwVSZGSkBg0apP379ysyMlKHDh1SYGCgo2MBAAAAdvdXpxgzkRqAv81sNqtt27Zas2aNo6MAAAAAuQpFN1DA+fn5ac6cOWrYsKGKFy+u4OBgXbhwwaZ1eHt7KywsTPXr17dTSgAAACBvougGoGXLlmnFihWKjo6Wq6urJk+eLEnq2LGjPD09s7ydP3/ewckBAACA3I1zugEoLCxM/v7+kqTQ0FDNnj1bkrRu3TpHxgIAAADyPEa6AcjHx8dy39XVVXFxcQ5MAwAAAOQfFN0AstSuXTu5ublleePwcgAAAODeOLwcQJbWr1+f7b6JiYmW+8nJyUpMTJSTk5PMZr7bAwAAQMHFX8MAcoSLi4tcXFwkSQ0aNJCLi4t27Njh4FQAAACAY5kMwzAcHSKvi42NlYeHh2JiYuTu7u7oOAAAAAAAO8tuHchINwAAAAAAdsI53QAyOHz4sMLDw21eLiAgQIGBgTkfCAAAAMijKLqBXKLu4sWOjmARMXeu4k+dsnk5t2rV9NCYMXZIZLv9Awc6OgIAAABA0Q0gI9+uXXX78mWbl3MpV84OaQAAAIC8i6IbQAbFfH1VzNfX0TEAAACAPI+J1AAAAAAAsBOKbgAAAAAA7ISiGwAAAAAAO6HoBgAAAADATii6AQAAAACwE4puAAAAAADshKIbAAAAAAA7oegGAAAAAMBOKLoBAAAAALATim4AAAAAAOyEohsAAAAAADuh6AYAAAAAwE4ougEAAAAAsBOKbgAAAAAA7ISiGwAAAAAAO6HoBgAAAADATii6AQAAAACwE4puAACAvxAZGamnnnpK5cqVk8lk0uHDhx0dCQCQR1B0AwAA/AWz2ay2bdtqzZo1jo4CAMhjKLoBAEC+5ufnpzlz5qhhw4YqXry4goODdeHCBZvW4e3trbCwMNWvX99OKQEA+RVFNwAAyPeWLVumFStWKDo6Wq6urpo8ebIkqWPHjvL09Mzydv78eQcnBwDkdYUdHQAAAMDewsLC5O/vL0kKDQ3V7NmzJUnr1q1zZCwAQAHASDcAAMj3fHx8LPddXV0VFxfnwDQAgIKEohsAABRY7dq1k5ubW5Y3Di8HAPxdHF4OAAAKrPXr12e7b2JiouV+cnKyEhMT5eTkJLOZMQwAQNby3P8SCxculJ+fn4oWLaoGDRroxx9/vGf/VatWqXr16ipatKgefvhhfffdd1bPr169Wq1bt1apUqW47iYAAMiSi4uLXFxcJEkNGjSQi4uLduzY4eBUAIDcLk8V3Z9//rlGjRqlqVOn6uDBg3r00UfVpk0bXb16NdP+e/bsUffu3dW/f38dOnRIISEhCgkJ0bFjxyx9bt26pSZNmui11157UJsBAAAeoLNnzyokJMTyOCQkRGfPnrV5PYZhZLg1a9Ysx3ICAPInk2EYhqNDZFeDBg1Ur149vf3225KktLQ0+fr6aujQoRo/fnyG/l27dtWtW7esZiZt2LChAgMDtWjRIqu+Z8+elb+/vw4dOqTAwECbcsXGxsrDw0MxMTFyd3e3fcMASXUXL3Z0hHxl/8CBjo4AAACAfCy7dWCeOac7OTlZBw4c0IQJEyxtZrNZLVu21N69ezNdZu/evRo1apRVW5s2bbRmzZq/lSUpKUlJSUmWx7GxsX9rfQAA4ME6fPiwwsPDbV4uICDA5i/nAQAFW54puq9du6bU1FR5e3tbtXt7e+vkyZOZLhMVFZVp/6ioqL+VZdasWZo+ffrfWgcAAAVNbjqiJ2LuXMWfOmXzcm7VqumhMWPskMh2HNEDAHlDnim6c5MJEyZYjaDHxsbK19fXgYkAAIAtfLt21e3Ll21ezqVcOTukAQDkZ3mm6C5durQKFSqkK1euWLVfuXJFPj4+mS7j4+NjU//scnZ2lrOz899aBwAAcJxivr4qxhfmAIAHIM/MXu7k5KQ6depo8+bNlra0tDRt3rxZQUFBmS4TFBRk1V+SNm3alGV/AAAAAAByUp4Z6ZakUaNGqXfv3qpbt67q16+vefPm6datW+rbt68kqVevXipfvrxmzZolSRo+fLiCg4P173//Wx06dNDKlSu1f/9+Lb7rnLIbN27o/Pnzuvy/Q8wiIiIk/TFK/ndHxAEAAAAABVueKrq7du2q6OhoTZkyRVFRUQoMDNSGDRssk6WdP39eZvP/D943atRIy5cv16RJkzRx4kRVq1ZNa9asUa1atSx91q5daynaJalbt26SpKlTp2ratGkPZsMAAAAAAPlSnrpOd27FdbqRE3LTrL75AbP6ArkPn3M5i885AHCs7NaBeeacbgAAAAAA8hqKbgAAAAAA7ISiGwAAAAAKuMjISD311FMqV66cTCaTDh8+7OhI+QZFNwAAAAAUcGazWW3bttWaNWscHSXfoegGAAAAgDzMz89Pc+bMUcOGDVW8eHEFBwfrwoULNq3D29tbYWFhql+/vp1SFlwU3QAAAACQxy1btkwrVqxQdHS0XF1dNXnyZElSx44d5enpmeXt/PnzDk6e/+Wp63QDAAAAADIKCwuTv7+/JCk0NFSzZ8+WJK1bt86RsSBGugEAAAAgz/Px8bHcd3V1VVxcnAPT4G4U3QAAAACQT7Vr105ubm5Z3ji83P44vBwAAAAA8qn169dnu29iYqLlfnJyshITE+Xk5CSzmbHav4N3DwAAAAAgFxcXubi4SJIaNGggFxcX7dixw8Gp8j5GugEAAAAgDzt79qzV45CQEIWEhNi8HsMwciYQrDDSDQAAAACAnTDSDQAAAAD5zOHDhxUeHm7zcgEBAQoMDMz5QAUYRTcAAAAA5IC6ixc7OoJFxNy5ij91yubl3KpV00Njxtghke32Dxzo6Ag5gqIbAAAAAPIZ365ddfvyZZuXcylXzg5pCjaKbgAAAADIZ4r5+qqYr6+jY0BMpAYAAAAAgN1QdAMAAAAAYCcU3QAAAAAA2AlFNwAAAAAAdkLRDQAAAACAnTB7OR64yMhIRUZG2rxc2bJlVbZsWTskAgAAAAD7oOjGA/fee+9p+vTpNi83depUTZs2LecDAQAAAICdUHTjgRs0aJCeeuopq7bbt2+rSZMmkqRdu3bJxcUlw3KMcgMAAADIayi68cBldpj4rVu3LPcDAwPl6ur6oGMBAAAAQI6zuehOTU3V0qVLtXnzZl29elVpaWlWz2/ZsiXHwgEAAAAAkJfZXHQPHz5cS5cuVYcOHVSrVi2ZTCZ75AIAAAAAIM+zueheuXKlvvjiC7Vv394eeQAAAAAAyDdsvk63k5OTqlatao8sAAAAAADkKzYX3aNHj9b8+fNlGIY98gAAAAAAkG/YfHj5rl27tHXrVq1fv14BAQEqUqSI1fOrV6/OsXAAAAAAAORlNhfdnp6eevrpp+2RBQAAAACAfMWmovvOnTt64okn1Lp1a/n4+NgrEwAAAAAA+YJN53QXLlxYL7zwgpKSkuyVBwAAAACAfMPmidTq16+vQ4cO2SMLAAAAAAD5is3ndIeFhWn06NG6ePGi6tSpI1dXV6vnH3nkkRwLBwAAAABAXmZz0d2tWzdJ0rBhwyxtJpNJhmHIZDIpNTU159IBAAAAAJCH2Vx0nzlzxh45AAAosCIjIzVo0CDt379fkZGROnTokAIDAx0dCwAA5ACbi+5KlSrZIwcAAAWW2WxW27ZtNWnSJDVo0MDRcQAAQA6yuej+5JNP7vl8r1697jsMAAB5jZ+fn8LCwrR69WqFh4frscce07Jly+Tr65vtdXh7eyssLMyOKQEAgKPYXHQPHz7c6nFKSooSEhLk5OSkYsWKUXQDAAqcZcuW6euvv1bZsmXVqVMnTZ48WUuXLlXHjh21a9euLJc7cuSIKlas+ACTAgCAB83movv333/P0Hbq1Cm9+OKLGjt2bI6EAgAgLwkLC5O/v78kKTQ0VLNnz5YkrVu3zpGxAABALmDzdbozU61aNc2ePTvDKDgAAAWBj4+P5b6rq6vi4uIcmAYAAOQmOVJ0S1LhwoV1+fLlnFodAAB5Xrt27eTm5pbl7fz5846OCAAA7Mzmw8vXrl1r9dgwDEVGRurtt99W48aNcywYAAB53fr167PdNzEx0XI/OTlZiYmJcnJyktmcY9+PAwAAB7C56A4JCbF6bDKZ5OXlpebNm+vf//53TuUCAKBAcXFxsdxPv2zY1q1b1axZMwclAgAAOcHmr8/T0tKsbqmpqYqKitLy5ctVtmxZe2S0snDhQvn5+alo0aJq0KCBfvzxx3v2X7VqlapXr66iRYvq4Ycf1nfffWf1vGEYmjJlisqWLSsXFxe1bNlSp06dsucmAADykbNnz1p9IR0SEqKzZ8/avB7DMDLcKLgBAMj7bC66X3nlFSUkJGRov337tl555ZUcCZWVzz//XKNGjdLUqVN18OBBPfroo2rTpo2uXr2aaf89e/aoe/fu6t+/vw4dOqSQkBCFhITo2LFjlj5z5szRggULtGjRIu3bt0+urq5q06aN1WF+AAAAAADcD5NhGIYtCxQqVEiRkZEqU6aMVfv169dVpkwZpaam5mjAuzVo0ED16tXT22+/LemPUXdfX18NHTpU48ePz9C/a9euunXrltUlWxo2bKjAwEAtWrRIhmGoXLlyGj16tMaMGSNJiomJkbe3t5YuXapu3bplK1dsbKw8PDwUExMjd3f3HNjSgufWrVtyc3OTJMXHx8vV1dXBiR68uosXOzpCvrJ/4EBHR0ABdvjwYYWHh9u8XEBAgAIDA3M+UC7B51zO4nMOyH34nMtZuf1zLrt1oM3ndBuGIZPJlKH9559/VsmSJW1dXbYlJyfrwIEDmjBhgqXNbDarZcuW2rt3b6bL7N27V6NGjbJqa9OmjdasWSNJOnPmjKKiotSyZUvL8x4eHmrQoIH27t2b7aIbAJA75JY/diLmzlX8fZyq5Fatmh7635fAjpbb/9ABACCvyHbRXaJECZlMJplMJv3jH/+wKrxTU1MVHx+vF154wS4hJenatWtKTU2Vt7e3Vbu3t7dOnjyZ6TJRUVGZ9o+KirI8n96WVZ/MJCUlKSkpyfI4NjZW0h+j/cnJydncItzt1q1blvvXrl3T7du3HZjGMe7Exzs6Qr5y7do1R0eAA+SW36OyTz6pxHv8P5KVoj4+uWYb7PE7lFu2Lb/gcw7Ifficy1m5/XMuLi4uW/2yXXTPmzdPhmGoX79+mj59ujw8PCzPOTk5yc/PT0FBQbYnzYNmzZql6dOnZ2hfu3at1eyzucmrO3Y4OsI9pd25Y7nf5KWXZC5s80EYD9TLTZvm+DrD/nd4PXLG6tWrc3yduf33KK/J179HDz30xy0Ps8fvUK7ZP/kEn3O5nz0+59hHOSdf/z+UT9jjcy4nZXegMNuVTe/evSVJ/v7+aty4sQo/4KKodOnSKlSokK5cuWLVfuXKFfn4+GS6jI+Pzz37p/975coVq5nXr1y5cs9z6iZMmGB12HpsbKx8fX311FNPqXjx4jZt14PyTi7/1i01KUkXP/9ckuT56KMq5Ozs4ET31qlTJ0dHgAPk9t+jvIbfIyD34XMuZ9njc459lHP4fwh/V1xcnEaMGPGX/WyunIODg/Xbb79pyZIl+u233zR//nyVKVNG69evV8WKFRUQEHA/ef+Sk5OT6tSpo82bN1suzZKWlqbNmzdryJAhmS4TFBSkzZs3W70RmzZtsozI+/v7y8fHR5s3b7YU2bGxsdq3b59efPHFLLM4OzvLOZOisFSpUrl2IrXCufxbN1ORIpb7hd3ccn3RXbp0aUdHgAPk9t+jvIbfIyD34XMuZ9njc459lHP4fwh/l5OTU7b62XzJsO3bt+vhhx/Wvn37tHr1asX/79u2n3/+WVOnTrV1dTYZNWqU3n//fX388cc6ceKEXnzxRd26dUt9+/aVJPXq1ctqorXhw4drw4YN+ve//62TJ09q2rRp2r9/v6VIN5lMGjFihGbMmKG1a9fq6NGj6tWrl8qVK2d1zVUAAAAAAO6HzSPd48eP14wZMzRq1CirQ6mbN29uuZSXvXTt2lXR0dGaMmWKoqKiFBgYqA0bNlgmQjt//rzM5v//HqFRo0Zavny5Jk2apIkTJ6patWpas2aNatWqZekzbtw43bp1SwMHDtTNmzfVpEkTbdiwQUWLFrXrtgAAAAAA8j+bi+6jR49q+fLlGdrLlCnzQGaXGzJkSJaHk2/bti1D27PPPqtnn302y/WZTCa98soreuWVV3IqIgAAAAAAku7j8HJPT09FRkZmaD906JDKly+fI6EAAAAAAMgPbC66u3XrppdeeklRUVEymUxKS0vT7t27NWbMGPXq1cseGQEAAAAAyJNsLrpnzpyp6tWry9fXV/Hx8apZs6aaNm2qRo0a6eWXX7ZHRgAAAAAA8iSbz+l2cnLS+++/rylTpujo0aOKj49X7dq1Va1aNXvkAwAAAAAgz7K56E7n6+srX19fy+PVq1dr2rRpOnLkSI4EAwAAAAAgr7Pp8PL33ntPzzzzjHr06KF9+/ZJkrZs2aLatWvrueeeU+PGje0SEgAAAACAvCjbRffs2bM1dOhQnT17VmvXrlXz5s01c+ZMhYaGqmvXrrp48aLeffdde2YFAAAAACBPyfbh5UuWLNH777+v3r17a+fOnQoODtaePXv066+/ytXV1Z4ZAQAAAADIk7JddJ8/f17NmzeXJD3++OMqUqSIpk+fTsENAA6QEhOjlJgYm5cr4uGhIh4edkgEAACAzGS76E5KSlLRokUtj52cnFSyZEm7hAIA3Fv0jh2KXLfO5uXKduyock8+aYdEAAAAyIxNs5dPnjxZxYoVkyQlJydrxowZ8vjTiMkbb7yRc+kAAJnyatpUno8+atWWmpysX15/XZL0j7FjVcjJKcNyjHIDAAA8WNkuups2baqIiAjL40aNGun06dNWfUwmU84lAwBkKbPDxFOTkiz3i/n6qpCz84OOBQA5JuHCBd2+fNnm5VzKlVOxuy5rCwCOlu2ie9u2bXaMAQAAAEfbP3CgoyNYNGvWTNu3b7d5ueDgYP5uBZCr2HR4OQAAAPAgzJs3T+Hh4dnu//vvv+ujjz5SeHi4TCaTDh06pMDAQPsFBIBsougGAABArhMYGGhT0XzlyhWZzWbVrVtXDRo0sF8wALCR2dEBAAAAULD5+flpzpw5atiwoYoXL67g4GBduHDBpnV4e3srLCxM9evXt1NKALg/FN0AAABwuGXLlmnFihWKjo6Wq6urJk+eLEnq2LGjPD09s7ydP3/ewckB4N44vBwAAAAOFxYWJn9/f0lSaGioZs+eLUlat26dI2MBwN92XyPdO3fuVM+ePRUUFKRLly5Jkj799FPt2rUrR8MBAACgYPDx8bHcd3V1VVxcnAPTAEDOsbno/uqrr9SmTRu5uLjo0KFDSvrfdWFjYmI0c+bMHA8IAACAgqtdu3Zyc3PL8sbh5QByO5uL7hkzZmjRokV6//33VaRIEUt748aNdfDgwRwNBwAAgIJt/fr1io+Pz/JWsWJFS9/ExEQlJiZKkpKTk5WYmKi0tDRHRQcASfdRdEdERKhp06YZ2j08PHTz5s2cyAQAAADYzMXFRS4uLpKkBg0ayMXFRTt27HBwKgAFnc0Tqfn4+OjXX3+Vn5+fVfuuXbtUuXLlnMoFAACAAuLs2bNWj0NCQhQSEmLzegzDyJlAAJCDbB7pHjBggIYPH659+/bJZDLp8uXL+uyzzzRmzBi9+OKL9sgIAAAAAECeZPNI9/jx45WWlqYWLVooISFBTZs2lbOzs8aMGaOhQ4faIyMAAAAAAHmSTUV3amqqdu/ercGDB2vs2LH69ddfFR8fr5o1a8rNzc1eGQEAAAAAyJNsKroLFSqk1q1b68SJE/L09FTNmjXtlQsAAAAAgDzP5nO6a9WqpdOnT9sjCwAAAAAA+cp9Xad7zJgxWrdunSIjIxUbG2t1AwAAAAAAf7B5IrX27dtLkp566imZTCZLu2EYMplMSk1Nzbl0AAAAAADkYTYX3Vu3brVHDgAAAAAA8h2bi+7g4GB75AAAAAAAIN+xuejesWPHPZ9v2rTpfYeB/ewfONDREe7p1q1bchs2TJK0q18/ubq6OjgRAAAAAPx9NhfdzZo1y9B297ndnNMNAAAAAMAfbC66f//9d6vHKSkpOnTokCZPnqxXX301x4IBQG7DESMAAACwlc1Ft4eHR4a2Vq1aycnJSaNGjdKBAwdyJBgAAAAAAHmdzdfpzoq3t7ciIiJyanUAAAAAAOR5No90HzlyxOqxYRiKjIzU7NmzFRgYmFO5AAAAAADI82wuugMDA2UymWQYhlV7w4YN9dFHH+VYMAAAAAAA8jqbi+4zZ85YPTabzfLy8lLRokVzLBQAAAAAAPmBzed0b9++XT4+PqpUqZIqVaokX19fFS1aVMnJyfrkk0/skREAAAAAgDzJ5qK7b9++iomJydAeFxenvn375kgoAAAAAADyA5uLbsMwZDKZMrRfvHgx08uJAQAAAABQUGX7nO7atWvLZDLJZDKpRYsWKlz4/xdNTU3VmTNn1LZtW7uEBAAAAAAgL8p20R0SEiJJOnz4sNq0aSM3NzfLc05OTvLz81Pnzp1zPCAAAAAAAHlVtovuqVOnSpL8/PzUtWtXZisHAAAAAOAv2HzJsN69e9sjBwAAAAAA+Y7NRbfZbM50IrV0qampfysQAAAAAAD5hc2zl69evdrq9vnnn2v8+PEqW7asFi9ebI+MkqQbN24oNDRU7u7u8vT0VP/+/RUfH3/PZRITEzV48GCVKlVKbm5u6ty5s65cuWLVZ9iwYapTp46cnZ0VGBhot/wAAAAAgILH5pHu9AnV7vbMM88oICBAn3/+ufr3758TuTIIDQ1VZGSkNm3apJSUFPXt21cDBw7U8uXLs1xm5MiR+vbbb7Vq1Sp5eHhoyJAh6tSpk3bv3m3Vr1+/ftq3b5+OHDlil+wAAAAAgILJ5qI7Kw0bNtTAgQNzanVWTpw4oQ0bNuinn35S3bp1JUlvvfWW2rdvr7lz56pcuXIZlomJidGHH36o5cuXq3nz5pKkJUuWqEaNGvrhhx/UsGFDSdKCBQskSdHR0RTdAAAAAIAcZfPh5Zm5ffu2FixYoPLly+fE6jLYu3evPD09LQW3JLVs2VJms1n79u3LdJkDBw4oJSVFLVu2tLRVr15dFStW1N69e/9WnqSkJMXGxlrdAAAAAAD4M5tHukuUKGE1kZphGIqLi1OxYsW0bNmyHA2XLioqSmXKlLFqK1y4sEqWLKmoqKgsl3FycpKnp6dVu7e3d5bLZNesWbM0ffr0v7UOAAAAAED+Z3PRPW/ePKvHZrNZXl5eatCggUqUKGHTusaPH6/XXnvtnn1OnDhha0S7mzBhgkaNGmV5HBsbK19fXwcmAgAAAADkRtkuuj/66COFhobm6HW6R48erT59+tyzT+XKleXj46OrV69atd+5c0c3btyQj49Ppsv5+PgoOTlZN2/etBrtvnLlSpbLZJezs7OcnZ3/1joAAAAAAPlftovuAQMGqGPHjpbDvMuVK6c9e/bIz8/vvl/cy8tLXl5ef9kvKChIN2/e1IEDB1SnTh1J0pYtW5SWlqYGDRpkukydOnVUpEgRbd68WZ07d5YkRURE6Pz58woKCrrvzAAAAAAAZFe2J1IzDMPqcVxcnNLS0nI8UGZq1Kihtm3basCAAfrxxx+1e/duDRkyRN26dbPMXH7p0iVVr15dP/74oyTJw8ND/fv316hRo7R161YdOHBAffv2VVBQkGXmckn69ddfdfjwYUVFRen27ds6fPiwDh8+rOTk5AeybQAAAACA/CvHLhlmb5999pmGDBmiFi1ayGw2q3PnzpbLfUlSSkqKIiIilJCQYGl78803LX2TkpLUpk0bvfPOO1brff7557V9+3bL49q1a0uSzpw587dG8QHAniIjIxUZGWnVdvv2bcv9w4cPy8XFJcNyZcuWVdmyZe2eDwAAAH/IdtFtMpmsZi3/82N7K1mypJYvX57l835+fhlG44sWLaqFCxdq4cKFWS63bdu2nIoIAA/Me++9d8+rKDRp0iTT9qlTp2ratGl2SgUAAIA/Mxl/rlSzYDab5eHhYSm0b968KXd3d5nN1keo37hxI+dT5nKxsbHy8PBQTEyM3N3dHR0nT7p165bc3NwkSfHx8XJ1dXVwIiB3y2yk+1527typjz/+WKdPn5aTk5OaNm2qefPmqUKFCnZMCQDIaXUXL3Z0hHxj/8CBjo6APC67dWC2R7qXLFmSI8EAAH+frYeJnzx5Uv/6178UHBwsk8mkoUOHqkuXLtqzZ48dUwIAACDbRXdOXioMAJB9fn5+CgsL0+rVqxUeHq7HHntMy5Ytk6+vb7bX0aNHD6vHI0aMUO3atXXnzh0VLpxnpvcAAADIc7I9ezkAwHGWLVumFStWKDo6Wq6urpo8ebIkqWPHjvL09Mzydv78+UzXt337dtWoUYOCGwAAwM74awsA8oCwsDD5+/tLkkJDQzV79mxJ0rp162xe16FDhzR58mStWrUqRzMCAAAgI0a6ASAP8PHxsdx3dXVVXFzcfa3n6NGjateund5++221atUqp+IBAAAgCxTdAJCHtWvXTm5ublne7j68/OjRo2rZsqVmzZqlnj17OjA1AABAwcHh5QCQh61fvz5b/cLDw9WyZUvNmDFDffv2tXMqAAAApLO56E5NTdXSpUu1efNmXb16VWlpaVbPb9myJcfCAQByxty5cxUdHa2RI0dq5MiRlvbjx4+rYsWKDkwGAACQv9lcdA8fPlxLly5Vhw4dVKtWLZlMJnvkAgD8z9mzZ60eh4SEKCQkxKZ1LFmyREuWLMm5UAAAAMgWm4vulStX6osvvlD79u3tkQcAAAAAgHzD5onUnJycVLVqVXtkAQAAAAAgX7G56B49erTmz58vwzDskQcAAAAAgHzD5sPLd+3apa1bt2r9+vUKCAhQkSJFrJ5fvXp1joUDAAAAACAvs7no9vT01NNPP22PLAAAAAAA5Cs2F93MfgsAAAAAQPbYfE43AAAAAADIHptHuiXpyy+/1BdffKHz588rOTnZ6rmDBw/mSDAAAAAAAPI6m0e6FyxYoL59+8rb21uHDh1S/fr1VapUKZ0+fVrt2rWzR0YAAAAAAPIkm4vud955R4sXL9Zbb70lJycnjRs3Tps2bdKwYcMUExNjj4wAAAAAAORJNhfd58+fV6NGjSRJLi4uiouLkyQ999xzWrFiRc6mAwAAAAAgD7O56Pbx8dGNGzckSRUrVtQPP/wgSTpz5owMw8jZdAAAAAAA5GE2F93NmzfX2rVrJUl9+/bVyJEj1apVK3Xt2pXrdwMAAAAAcBebZy9fvHix0tLSJEmDBw9WqVKltGfPHj311FMaNGhQjgcEAAAAACCvsrnoNpvNMpv/f4C8W7du6tatW46GAgAAAAAgP7D58HJJ2rlzp3r27KmgoCBdunRJkvTpp59q165dORoOAAAAAIC8zOai+6uvvlKbNm3k4uKiQ4cOKSkpSZIUExOjmTNn5nhAAAAAAADyKpuL7hkzZmjRokV6//33VaRIEUt748aNdfDgwRwNBwAAAABAXmZz0R0REaGmTZtmaPfw8NDNmzdzIhMAAAAAAPnCfV2n+9dff83QvmvXLlWuXDlHQgEAAAAAkB/YXHQPGDBAw4cP1759+2QymXT58mV99tlnGjNmjF588UV7ZAQAAAAAIE+y+ZJh48ePV1pamlq0aKGEhAQ1bdpUzs7OGjNmjIYOHWqPjAAAAAAA5Ek2F90mk0kvv/yyxo4dq19//VXx8fGqWbOm3Nzc7JEPAAAAAIA8y+aiO52Tk5Nq1qyZk1kAAAAAAMhXsl109+vXL1v9Pvroo/sOAwAAAABAfpLtonvp0qWqVKmSateuLcMw7JkJAAAAAIB8IdtF94svvqgVK1bozJkz6tu3r3r27KmSJUvaMxsAAAAAAHlati8ZtnDhQkVGRmrcuHH65ptv5Ovrqy5dumjjxo2MfAMAAAAAkAmbrtPt7Oys7t27a9OmTTp+/LgCAgIUFhYmPz8/xcfH2ysjAAAAAAB50n3PXm42m2UymWQYhlJTU3MyE/K5yMhIRUZGWrXdvn3bcv/w4cNycXHJsFzZsmVVtmxZu+cDAAAAgJxiU9GdlJSk1atX66OPPtKuXbvUsWNHvf3222rbtq3MZpsGzVGAvffee5o+fXqWzzdp0iTT9qlTp2ratGl2SgUAAAAAOc9kZPOE7LCwMK1cuVK+vr7q16+fQkNDVbp0aXvnyxNiY2Pl4eGhmJgYubu7OzpOrpfZSPe97Ny5Ux9//LFOnz4tJycnNW3aVPPmzVOFChXsmBIAACD3qbt4saMj5Bv7Bw50dATkcdmtA7NddJvNZlWsWFG1a9eWyWTKst/q1attT5vHUXTb1/Lly+Xh4aHg4GCZTCYNHTpUJ0+e1J49exwdDQAA4IGi6M45FN34u7JbB2b78PJevXrds9gGMuPn56ewsDCtXr1a4eHheuyxx7Rs2TL5+vpmex09evSwejxixAjVrl1bd+7cUeHC9z0tAQAAAADYXbYrlqVLl9oxBvKzZcuW6euvv1bZsmXVqVMnTZ48WUuXLlXHjh21a9euLJc7cuSIKlasmKF9+/btqlGjBgU3AAAAgFyPqgV2FxYWJn9/f0lSaGioZs+eLUlat26dzes6dOiQJk+erFWrVuVoRgAAAACwB6Ych935+PhY7ru6uiouLu6+1nP06FG1a9dOb7/9tlq1apVT8QAAAADAbvJM0X3jxg2FhobK3d1dnp6e6t+/v+Lj4++5TGJiogYPHqxSpUrJzc1NnTt31pUrVyzP//zzz+revbt8fX3l4uKiGjVqaP78+fbeFPxPu3bt5ObmluXt/Pnzlr5Hjx5Vy5YtNWvWLPXs2dOBqQEAAAAg+/LM4eWhoaGKjIzUpk2blJKSor59+2rgwIFavnx5lsuMHDlS3377rVatWiUPDw8NGTJEnTp10u7duyVJBw4cUJkyZSwTe+3Zs0cDBw5UoUKFNGTIkAe1aQXW+vXrs9UvPDxcLVu21IwZM9S3b187pwIAAACAnJMniu4TJ05ow4YN+umnn1S3bl1J0ltvvaX27dtr7ty5KleuXIZlYmJi9OGHH2r58uVq3ry5JGnJkiWqUaOGfvjhBzVs2FD9+vWzWqZy5crau3evVq9eTdGdi8ydO1fR0dEaOXKkRo4caWk/fvx4phOtAQAAAEBukScOL9+7d688PT0tBbcktWzZUmazWfv27ct0mQMHDiglJUUtW7a0tFWvXl0VK1bU3r17s3ytmJgYlSxZMufCF3Bnz55VSEiI5XFISIjOnj1r0zqWLFmitLQ0xcfHW90ouAEAAADkdnlipDsqKkplypSxaitcuLBKliypqKioLJdxcnKSp6enVbu3t3eWy+zZs0eff/65vv3223vmSUpKUlJSkuVxbGxsNrYCAAAAAFDQOHSke/z48TKZTPe8nTx58oFkOXbsmP75z39q6tSpat269T37zpo1Sx4eHpabr6/vA8kIAAAAAMhbHDrSPXr0aPXp0+eefSpXriwfHx9dvXrVqv3OnTu6ceOG1eWo7ubj46Pk5GTdvHnTarT7ypUrGZY5fvy4WrRooYEDB2rSpEl/mXvChAkaNWqU5XFsbCyFNwAAAAAgA4cW3V5eXvLy8vrLfkFBQbp586YOHDigOnXqSJK2bNmitLQ0NWjQINNl6tSpoyJFimjz5s3q3LmzJCkiIkLnz59XUFCQpV94eLiaN2+u3r1769VXX81WbmdnZzk7O2erLwAAAACg4MoTE6nVqFFDbdu21YABA/Tjjz9q9+7dGjJkiLp162aZufzSpUuqXr26fvzxR0mSh4eH+vfvr1GjRmnr1q06cOCA+vbtq6CgIDVs2FDSH4eUP/HEE2rdurVGjRqlqKgoRUVFKTo62mHbCgAAAADIP/LERGqS9Nlnn2nIkCFq0aKFzGazOnfurAULFlieT0lJUUREhBISEixtb775pqVvUlKS2rRpo3feecfy/Jdffqno6GgtW7ZMy5Yts7RXqlTJ5hm2AQAAAAD4M5NhGIajQ+R1sbGx8vDwUExMjNzd3R0dBwAAAPlU3cWLHR0h39g/cKCjIyCPy24dmCcOLwcAAAAAIC+i6AYAAAAAwE4ougEAAAAAsBOKbgAAAAAA7ISiGwAAAAAAO6HoBgAAAADATii6AQAAAACwE4puAAAAAADshKIbAAAAAAA7oegGAAAAAMBOKLoBAAAAALATim4AAAAAAOyEohsAAAAAADuh6AYAAAAAwE4ougEAAAAAsBOKbgAAAAAA7ISiGwAAAAAAO6HoBgAAAADATii6AQAAAACwE4puAAAAAADshKIbAAAAAAA7oegGAAAAAMBOKLoBAAAAALATim4AAAAAAOyEohsAAAAAADuh6AYAAAAAwE4ougEAAAAAsBOKbgAAAAAA7ISiGwAAAAAAO6HoBgAAAADATii6AQAAAACwE4puAAAAAADshKIbAAAAAAA7oegGAAAAAMBOKLoBAAAAALATim4AAAAAAOyEohsAAAAAADuh6AYAAAAAwE4ougEAAAAAsBOKbgAAAAAA7ISiGwAAAAAAO6HoBgAAAADATii6AQAAAACwE4puAAAAAADshKIbAAAAAAA7oegGAAAAAMBOKLoBAAAAALATim4AAAAAAOyksKMDZNeNGzc0dOhQffPNNzKbzercubPmz58vNze3LJdJTEzU6NGjtXLlSiUlJalNmzZ655135O3tLUm6fv26QkNDdeTIEV2/fl1lypTRP//5T82cOVPu7u4PatMAAACAPCfhwgXdvnzZ5uVcypVTMV9fOyQCcieTYRiGo0NkR7t27RQZGan33ntPKSkp6tu3r+rVq6fly5dnucyLL76ob7/9VkuXLpWHh4eGDBkis9ms3bt3S5J+//13rVy5UvXq1ZOXl5d+/fVXDR48WI899tg91/tnsbGx8vDwUExMDMU6AAAACoRmzZpp+/btNi8XHBysbdu25Xwg4AHLbh2YJ4ruEydOqGbNmvrpp59Ut25dSdKGDRvUvn17Xbx4UeXKlcuwTExMjLy8vLR8+XI988wzkqSTJ0+qRo0a2rt3rxo2bJjpay1YsECvv/66Lly4kO18FN0AAAAoaA4fPqzw8PBs9//999/10Ucf6cKFC7p27ZoOHTqkwMBA+wUE7Cy7dWCeOLx879698vT0tBTcktSyZUuZzWbt27dPTz/9dIZlDhw4oJSUFLVs2dLSVr16dVWsWDHLovvy5ctavXq1goOD75knKSlJSUlJlsexsbH3s1kAAABAnhUYGGhT0XzlyhWZzWbVrVtXDRo0sF8wIJfJExOpRUVFqUyZMlZthQsXVsmSJRUVFZXlMk5OTvL09LRq9/b2zrBM9+7dVaxYMZUvX17u7u764IMP7pln1qxZ8vDwsNx8OScFAAAA+Zifn5/mzJmjhg0bqnjx4goODrbpyFDpj7/Dw8LCVL9+fTulBHInhxbd48ePl8lkuuft5MmTds/x5ptv6uDBg/r666/122+/adSoUffsP2HCBMXExFhutn7gAAAAAHnNsmXLtGLFCkVHR8vV1VWTJ0+WJHXs2FGenp5Z3s6fP+/g5IBjOfTw8tGjR6tPnz737FO5cmX5+Pjo6tWrVu137tzRjRs35OPjk+lyPj4+Sk5O1s2bN61Gu69cuZJhGR8fH/n4+Kh69eoqWbKkHn/8cU2ePFlly5bNdN3Ozs5ydnb+6w0EAAAA8omwsDD5+/tLkkJDQzV79mxJ0rp16xwZC8j1HFp0e3l5ycvL6y/7BQUF6ebNmzpw4IDq1KkjSdqyZYvS0tKyPB+kTp06KlKkiDZv3qzOnTtLkiIiInT+/HkFBQVl+VppaWmSZHXONgAAAFDQ3T1w5erqqri4OAemAfKOPDGRWo0aNdS2bVsNGDBAixYtUkpKioYMGaJu3bpZZi6/dOmSWrRooU8++UT169eXh4eH+vfvr1GjRqlkyZJyd3fX0KFDFRQUZJlE7bvvvtOVK1dUr149ubm5KTw8XGPHjlXjxo3l5+fnwC0GAAAA8oZ27dpp586dWT5//PhxVaxY8QEmAnKXPFF0S9Jnn32mIUOGqEWLFjKbzercubMWLFhgeT4lJUURERFKSEiwtL355puWvklJSWrTpo3eeecdy/MuLi56//33NXLkSCUlJcnX11edOnXS+PHjH+i2AQAAAHnV+vXrs903MTHRcj85OVmJiYlycnKS2Zwn5ncG7kueKbpLliyp5cuXZ/m8n5+f/nzJ8aJFi2rhwoVauHBhpss88cQT2rNnT47mBAAAAJA5FxcXy/3000S3bt2qZs2aOSgRYH8m48+VKmyW3YuiAwAAAADyh+zWgRzHAQAAAACAneSZw8tzs/SDBWJjYx2cBAAAAADwIKTXf3918DhFdw5Iv1yCr6+vg5MAAAAAAB6kuLg4eXh4ZPk853TngLS0NF2+fFnFixeXyWRydJw8KzY2Vr6+vrpw4QLnxudS7KPcj32Uu7F/cj/2Ue7HPsr92Ee5G/sn5xiGobi4OJUrV+6eM/Az0p0DzGazKlSo4OgY+Ya7uzsfALkc+yj3Yx/lbuyf3I99lPuxj3I/9lHuxv7JGfca4U7HRGoAAAAAANgJRTcAAAAAAHZC0Y1cw9nZWVOnTpWzs7OjoyAL7KPcj32Uu7F/cj/2Ue7HPsr92Ee5G/vnwWMiNQAAAAAA7ISRbgAAAAAA7ISiGwAAAAAAO6HoBgAAAADATii6AQAAAACwE4puAAAAAADshKIbKOAiIyN1/PhxR8fAX0hNTZUkccGJ3CkhIUHJycmOjgHkWbdu3XJ0BCBfMAyDvxVyIYpu2NWNGzd08uRJnTp1ij9Ic6FLly7p4Ycf1qRJk7R//35Hx0EWDh8+rJCQECUkJMhkMjk6Dv7k2LFj6tKli3744QclJSU5Og6Q55w4cUJ16tTRl19+6egoyMJvv/2mOXPm6JVXXtGHH36otLQ0R0fCn6T//3Pnzh3+VsiFKLphN8eOHVPLli3VpUsXPfzww5ozZ45ltA65w6lTpxQTE6OYmBi99dZbOnjwoOU5viXNHX7++Wc1atRIAQEBKlasmKWd/ZM7hIeH6/HHH1eFChXk7+8vZ2dnR0fCn5w5c0ZvvvmmRo8erc8//9zRcZCJTz75RL/88osGDRpE4Z0LHTt2TA0aNND27dt18OBBDR8+XK1atdKmTZv4vyiXCA8PV/fu3dWqVSs9+eST2rFjB4NduQxFN+zi+PHjatasmVq0aKGVK1fq1Vdf1ZQpU3T58mVHR8NdHnnkEbVv315du3bVsWPH9MYbbyg8PFwSRV1ucOTIETVu3FhDhgzR7NmzLe3Jycl8i50L3Lp1S6NGjVL37t21aNEi+fr66uTJkzp8+LDOnz/v6HiQdPToUTVt2lTffvutfvjhB/Xo0UOvv/66o2PhT+rWravhw4dr5MiRCg0N1RdffGF5jv+LHCsmJkbPP/+8+vfvr2+//VZr1qzRvn37tGfPHr3yyitas2aNoyMWeKdOnVKjRo3k5eWl2rVrq3jx4mrWrJlmzpzJ/0W5SGFHB0D+c+3aNb344ovq2bOn5Y+bGjVq6Pvvv9fFixd1/fp1lSpVSr6+vg5OWrClpqYqNTVVJ0+e1DvvvCMvLy/NmjVL8+fPV3h4uMqWLcuIgwNFRUWpTZs2atKkieUokTFjxujUqVP67bffNGjQILVt21bVq1d3dNQCq3DhwkpISNCAAQOUmpqqDh06WE6pCQgIsPyhCsc4d+6cOnXqpB49emjWrFkym8366KOPNHHiRIWEhKhatWqOjoj/KV26tL7//nv99NNPioyMVO/evVWiRAn997//lb+/v8LCwhwdscBKSEhQSkqKOnXqJEm6ffu2fH19FRgYqHPnzunNN99U/fr1Vb58eQcnLbg++eQTNWzYUO+9956l7a233tL06dOVmJiokSNHytvb24EJIVF0ww5MJpPatm2rZ555xtI2Y8YMbdy4UVFRUbp27ZoCAgI0adIkNWnSxIFJCzaz2SwvLy/Vq1dPx44d09NPPy1nZ2f17t1bSUlJGjBggKMjFnhBQUG6cOGCvv76ay1atEgpKSkKDAyUn5+fFixYoGPHjmnKlCmqWLGio6MWSDdv3lRERISuXbumsWPHSpI++OADXb58WVu2bNGkSZPk4eFh9VmIByMtLU0rV65U1apVNXHiRJnNfxzYV69ePRUpUoTzUXMRwzBUtWpVFStWTCkpKVq4cKE8PDzUrl07ubq6at++fY6OWKClpKTo5MmTCg8PV4MGDeTi4qJr166pcOHC+uCDD9SlSxctXLhQM2fOdHTUAuv27duW+3fu3FHhwoU1dOhQOTk5afTo0fLz89MLL7ygtLQ0y2chHjzeeeS4UqVKaciQIZZRhJUrV2rq1KlauXKlNm/erM8++0w3btzQ5s2bHZy0YEs/PLlQoULatm2bJGn16tVKTU2Vr6+vdu7cqR9//NGBCQs2Hx8fLVy4UDVr1lT37t2Vmpqqzz//XHPnztXbb7+tGTNm6KuvvrKcDoAHr0yZMmrRooXWrl2rU6dOaeTIkXrkkUfUtm1bDRs2TC1bttTmzZuVmprKIbIPmNlsVlBQkAIDA+Xh4WFpDwgIUOHChRUZGenAdLibyWRS+fLl5eTkpF9++UWSdPHiRRUrVkyJiYmKiIhwcMKCzdfXV4MHD9bUqVM1btw4LV68WIGBgapRo4Zat26tiRMn6uDBg0pMTORzzkEqVaqkvXv36vLlyypcuLDlXO5BgwZp3LhxGjt2rC5cuEDB7WC8+7CL4sWLW+4HBQVp//796tKli0qWLKmmTZuqTJkyOnDggAMTIv0/x+bNm8vZ2VlhYWH67rvvdODAAc2YMUPbt2/XkiVLlJiY6OCkBVfZsmU1a9YsjRgxQuPHj1epUqUs+61Hjx4qXbq0tm7d6uCUBZfJZNLo0aO1ZMkSffvtt1aT1lSoUEHe3t46fvy4zGYz5+A/IHdP1tm0aVPNmjVLkvV5wSaTSSkpKZbHmzdvVnR09IMLWYCl75+7jzRIb/Pw8NClS5c0fPhwff/999q5c6dGjBihp59+Wl9//bVD8hZEly9f1k8//aR169YpKSlJJpNJQ4YM0QsvvKAvvvhCS5Ys0bBhw7R48WJJ0vXr1xUbGytnZ2c+5x6Q06dPa8eOHZbHzz//vOrUqaPOnTvr+vXrcnJysvztNnDgQJUoUYIr1OQCHF4Ou6tUqZIqVaok6Y//aJOTk+Xm5qZHHnnEwckKtvT/HP39/dW3b195e3tr3bp18vf3l7+/v0wmkx599FEVLVrUwUkLtnLlymn8+PGW/WAymWQYhm7cuCEvLy8FBgY6NmABV7duXa1fv17BwcFavHixKleurICAAEl/HJb5j3/8Q3fu3FGRIkUcnDT/++WXX/TNN9+oR48eKlu2rKQ/im2TySSTyaQ7d+4oKSlJhQoVkru7uyRp4sSJmj17ti5evOjI6AXCsWPHNHToUH3yySfy9fW1HOqaPvrWtGlTdenSRV5eXlq3bp0effRRPfrooypcuLAeeughB6cvGI4cOaJ//vOf8vLy0sWLF+Xk5KSXX35ZXbp00csvv6zBgwcrLS1NJUuWtCxz48YNPfroo0pLS1OhQoUcmL5gOHLkiNq2bav27durevXqKlOmjFxcXDRmzBjNmDFDXbt21RdffGHZR87OznJ1deX/oNzAAB6wyZMnGxUrVjR++eUXR0eBYRjJycnGhx9+aPz888+GYRhGWlqagxMhO6ZMmWJUq1bNOHv2rKOjwDCM7du3G+XKlTPq169v9O/f33juuecMDw8P4+jRo46OViCcOnXKKFmypGEymYwJEyYY0dHRGfqkpqYat2/fNqpUqWLs37/feOWVVwxXV1fjxx9/dEDiguXMmTNG1apVDZPJZFSrVs24cOGCYRh/7JN0GzduNLp27WocPnzYUTELtAsXLhhVq1Y1pk+fbly+fNlIS0szOnXqZDg5ORkjRoyw7LN04eHhxoQJEwx3d3fj2LFjDkpdsJw+fdrw8fExxo4dm+FvtdTUVOM///mPUb9+fcPf39/YuHGjsWXLFmPSpEmGj4+Pce7cOQelRjqTYXACBh6MVatWafv27Vq5cqU2bdqk2rVrOzoS/ofJNfKOlStXauvWrVq1apU2b97M71EuEhERoWXLlumHH35QtWrVFBYWplq1ajk6Vr5369YtDRs2TGlpaapXr56GDBmiMWPGaNy4cSpdunSG/o899pgKFy6sn3/+Wbt371bdunUdkLrgSExM1Kuvvqrw8HANGTJE06dP17lz57Rr1y5VqFBBqamplhHSuLg4q9PT8OBs3LhRU6dO1bp16+Tu7i4nJyft379f7dq1k6+vr5566inLUVcJCQmaNm2aNm7cqI8//pgjrh6QTz/9VGvWrNFXX32llJQUvfHGG/rll1/k7e2tjh07qlGjRoqIiNC0adO0efNmlShRQkWKFNEnn3yixx57zNHxCzwOL8cDU7NmTX355ZfauXOnatSo4eg4uAsFd95Rs2ZNLVu2TDt37rQcxozc4aGHHtK//vUvy/mq/F49GGazWXXq1FGpUqXUtWtXlS5dWt26dZMkq8I7NTVVMTExOn36tOLj43Xo0CE9/PDDjoxeIBQtWlS1atXSww8/rObNm6tKlSp67rnn1KRJE0vhnT7jMgW345w/f15nzpyx+qIqPj5eQUFBKlGihBYvXqx+/fqpYsWKKlasmMaPH69Ro0bJx8fHgakLlkOHDllmKm/durWSk5NVqVIlrV69Wlu3blW/fv00YMAArVixQidPnrR8eZLZl4948BjpxgOVkpLCeSXA35ScnCwnJydHxwByjVu3bsnV1dXy+PPPP1f37t01evRoyySEd+7c0c2bN3XgwAFVqFCBL60cxDAMnTlzRn379tW5c+e0e/dulS9fXklJSTp+/LiqV68uFxcXR8cscKKiolS7dm21atVKU6dOVVRUlFq3bq0pU6bopZdeUvXq1dWzZ09NmjTJ6ugEPDhLly7V119/rW7duumDDz7QsmXL5O3traioKI0fP14XL17UihUr5OXlZZnPArkHRTcAAMgXUlNTLbPFr1y5Uj169NCYMWM0YsQIzZ07V2fPntWyZctUrFgxR0fN127duqW0tDQZhmGZtE6yPpXpt99+U79+/XTu3Dlt3bpV//73v7Vv3z5t2rRJnp6eDkpecGS2j9asWaNhw4YpKSlJd+7cUZ8+ffTvf/9bkvT444+rSZMmlisCwP5u3Lihq1evqlChQqpWrZqOHj2q+vXrq0aNGvL399dXX31l6RsREaEaNWpow4YNat26tQNTIyscXg4AAPKFQoUKyTAMpaWlqVu3bjKZTHruuee0du1a/frrr9q/fz8Ft50dP35cI0eOVHR0tK5cuaI5c+YoNDRUhmFYnXJRpUoVLVmyRP3791eVKlVUrFgxbd26lYL7AfjzPnrttdfUs2dPhYSEqGXLljp+/LiKFi1qucpMUlKS3Nzc5OvrK0mMoj4Ax44dU69evXTnzh1FRERo4sSJmjp1qubPn6/BgwfLMAydPn1alStXliSVLl1aQUFBVjPLI3fhhDMAAJBvpF8izDAMde3aVY8//riio6N16NAhJnyys+PHj6tp06YKCAjQmDFj1K1bN/Xt21eHDx/OtEirUKGCfHx8VKJECf3444+qV6+eA1IXLJnto379+unQoUOSJDc3N9WvX99ScMfFxWnatGk6ePCg2rZtK0kU3HZ2/PhxNWvWTC1atNDKlSs1c+ZMTZ8+XefPn1evXr306quv6siRI5o+fbp27typK1euaN68ebp8+bLKlSvn6PjIAoeXAwCAfCc1NVVjx47VvHnzdPjwYUsRAfu4ceOGunfvrurVq2v+/PmW9ieeeEIPP/ywFixYYDVCmpaWpnfeeUcjRozQTz/9xJUYHoDs7KO7TwE4fPiw3nvvPa1du1bffPMNM2A/ANeuXVPnzp1Vu3ZtzZs3T9IfRxa0a9dOU6dOVbFixeTp6anw8HANHDhQd+7cUcmSJZWQkKD//Oc//B7lYhxeDgAA8qWAgAAdPHiQgvsBSElJ0c2bN/XMM89I+v/zt/39/XXjxg1J1iOkZrNZlSpV0okTJ1StWjWHZC5osrOP7j4FIDAwUC1bttS4cePk7+/vkMwFjclkUtu2bS37SJJmzJih//73v4qKitKNGzdUvXp1LVq0SAcOHNCZM2eUnJysatWqqWzZsg5Mjr/CSDcAAMiXOPf0wTp16pSlgE6/WsnkyZN17tw5ffLJJ5Z+XI/bcbK7j2JjY60mwcODc/fvR/qEkCtXrlTLli119OhRjR49Wh06dND06dMdnBS2YKQbAADkSxTcD1Z6MZeWlma5PKhhGLp69aqlz6xZs+Ts7Kxhw4apcGH+DH3Q2Ee5391fSAUFBWn//v2WQ/uDg4Pl4+OjgwcPOioe7hO/SQA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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.ticker as mticker\n", - "\n", - "for factor in factors:\n", - " stats=dataset.groupby(factor)['futurereturn'].agg(['mean','sem','count']).reset_index()\n", - " stats['sem']=stats['sem'].fillna(0.0)\n", - " plt.figure(figsize=(10,4))\n", - " # Format dollar amount into metric format.\n", - " labels=stats[factor].apply(lambda x:f'{x/1e6:.1f}M' if x>=1e6 else f'{x/1e3:.0f}K') if factor=='totalamount' else stats[factor].astype(str)\n", - " plt.bar(labels,stats['mean'],yerr=stats['sem'],color='teal',alpha=0.8,capsize=5)\n", - " plt.axhline(0,color='black',linewidth=1,alpha=0.4)\n", - " plt.title(f'Mean Future Return by {factor}')\n", - " plt.xlabel(f'{factor}')\n", - " plt.ylabel('Mean Future Return')\n", - " plt.xticks(rotation=45,ha='right')\n", - " # Annotate each bar with the number of observations in the group.\n", - " for idx,row in stats.iterrows():\n", - " y_pos=row['mean']+(row['sem'] if row['mean']>=0 else-row['sem'])\n", - " v_align='bottom' if row['mean']>=0 else 'top'\n", - " plt.text(idx,y_pos,f\"n={int(row['count'])}\",ha='center',va=v_align,fontsize=9)\n", - " plt.tight_layout()\n", - " plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "e3f4a5b6", - "metadata": {}, - "source": [ - "Create a box plot of the contract volume quintiles compared to future returns." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c7d8e9f0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Factor: totalamount\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
 bucketmean_factormin_future_returnmax_future_returnmean_future_returnstd_future_returnobservations
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\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "y = dataset.futurereturn\n", - "for factor in factors:\n", - " # Split factor values into quantile buckets.\n", - " x = dataset[factor]\n", - " bucket_count = min(5, x.nunique())\n", - " buckets = pd.qcut(x, q=bucket_count, duplicates='drop')\n", - " # Summarize each bucket with distribution statistics.\n", - " summary = dataset.assign(bucket=buckets).groupby('bucket', observed=True).agg(\n", - " mean_factor=(factor, 'mean'),\n", - " min_future_return=('futurereturn', 'min'),\n", - " max_future_return=('futurereturn', 'max'),\n", - " mean_future_return=('futurereturn', 'mean'),\n", - " std_future_return=('futurereturn', 'std'),\n", - " observations=('futurereturn', 'size')\n", - " ).reset_index()\n", - " summary['bucket'] = summary['bucket'].astype(str)\n", - " # Display the bucket summary.\n", - " print(f\"Factor: {factor}\")\n", - " display(summary.style.format({\n", - " 'mean_factor': '{:.3f}',\n", - " 'min_future_return': '{:.2%}',\n", - " 'max_future_return': '{:.2%}',\n", - " 'mean_future_return': '{:.2%}',\n", - " 'std_future_return': '{:.2%}'\n", - " }))\n", - " # Plot the return distribution for each bucket.\n", - " groups = [y[buckets == b].values for b in buckets.cat.categories]\n", - " plt.boxplot(groups, labels=[str(b) for b in buckets.cat.categories])\n", - " plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", - " plt.title(f'Future Return by {factor} Bucket')\n", - " plt.xlabel(f'{factor} Bucket')\n", - " plt.ylabel('Future Return')\n", - " plt.xticks(rotation=45)\n", - " plt.show()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Foundation-Py-Default", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.14" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From 792057d028f349abcb146d9dabfe3d78e14041f9 Mon Sep 17 00:00:00 2001 From: Rudy Osuna Date: Mon, 1 Jun 2026 14:42:17 -0700 Subject: [PATCH 08/16] fixed notebook - 120 day universe_history lookback --- .../research.ipynb | 697 ++++++++++++++++++ 1 file changed, 697 insertions(+) create mode 100644 project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb diff --git a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb new file mode 100644 index 0000000000..df4e28d4ef --- /dev/null +++ b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb @@ -0,0 +1,697 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "a1b2c3d4", + "metadata": {}, + "source": [ + "![QuantConnect Logo](https://cdn.quantconnect.com/web/i/icon.png)\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "e5f6a7b8", + "metadata": {}, + "source": [ + "## Quiver Government Contracts Research\n", + "\n", + "This notebook studies whether government contract dollar volume helps explain future returns" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "c9d0e1f2", + "metadata": {}, + "outputs": [], + "source": [ + "qb = QuantBook()\n", + "# Daily bars will have an end_time that matches the following midnight.\n", + "qb.settings.daily_precise_end_time = False" + ] + }, + { + "cell_type": "markdown", + "id": "a3b4c5d6", + "metadata": {}, + "source": [ + "### Build a Government Contract Universe\n", + "\n", + "Select assets with frequent, sizable US government contracts, then inspect the returned universe history." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "e7f8a9b0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Shape: (583, 5)\n", + "Columns: ['agency', 'amount', 'description', 'time', 'value']\n" + ] + }, + { + "data": { + "text/html": [ + "
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agencyamountdescriptiontimevalue
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2026-02-03EW RTKJ7O7ZTI79Department of Veterans Affairs32500.0AORTIC VALVE2026-02-0332500.0
EW RTKJ7O7ZTI79Department of Veterans Affairs34000.0AORTIC VALVE2026-02-0334000.0
EW RTKJ7O7ZTI79Department of Veterans Affairs34000.0AORTIC VLAVE2026-02-0334000.0
EW RTKJ7O7ZTI79Department of Veterans Affairs136000.0CUSTOM SURGICAL IMPLANTS2026-02-03136000.0
EW RTKJ7O7ZTI79Department of Veterans Affairs34000.0SURGICAL IMPLANT2026-02-0334000.0
\n", + "
" + ], + "text/plain": [ + " agency amount \\\n", + "time \n", + "2026-02-03 EW RTKJ7O7ZTI79 Department of Veterans Affairs 32500.0 \n", + " EW RTKJ7O7ZTI79 Department of Veterans Affairs 34000.0 \n", + " EW RTKJ7O7ZTI79 Department of Veterans Affairs 34000.0 \n", + " EW RTKJ7O7ZTI79 Department of Veterans Affairs 136000.0 \n", + " EW RTKJ7O7ZTI79 Department of Veterans Affairs 34000.0 \n", + "\n", + " description time value \n", + "time \n", + "2026-02-03 EW RTKJ7O7ZTI79 AORTIC VALVE 2026-02-03 32500.0 \n", + " EW RTKJ7O7ZTI79 AORTIC VALVE 2026-02-03 34000.0 \n", + " EW RTKJ7O7ZTI79 AORTIC VLAVE 2026-02-03 34000.0 \n", + " EW RTKJ7O7ZTI79 CUSTOM SURGICAL IMPLANTS 2026-02-03 136000.0 \n", + " EW RTKJ7O7ZTI79 SURGICAL IMPLANT 2026-02-03 34000.0 " + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def select_assets(data: List[QuiverGovernmentContractUniverse]) -> List[Symbol]:\n", + " # Group by ticker and keep names with 3+ contracts totalling over $50K.\n", + " contracts_by_symbol: dict[Symbol, list[QuiverGovernmentContractUniverse]] = {}\n", + " for d in data:\n", + " contracts_by_symbol.setdefault(d.symbol, []).append(d)\n", + " return [s for s, ds in contracts_by_symbol.items()\n", + " if len(ds) >= 3 and sum(x.amount or 0 for x in ds) > 50_000]\n", + "\n", + "# Add the Quiver Government Contract universe.\n", + "universe = qb.add_universe(QuiverGovernmentContractUniverse, select_assets)\n", + "# Request universe history of the last 120 days.\n", + "universe_history = qb.universe_history(universe, qb.time - timedelta(120), qb.time - timedelta(1), flatten=True)\n", + "# Print the returned shape and columns.\n", + "print(f\"Shape: {universe_history.shape}\")\n", + "print(f\"Columns: {list(universe_history.columns)}\")\n", + "universe_history.head()" + ] + }, + { + "cell_type": "markdown", + "id": "c1d2e3f4", + "metadata": {}, + "source": [ + "### Universe Diagnostics\n", + "\n", + "Inspects the raw contract amount distribution and visualizes how the daily universe size evolves chronologically." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a5b6c7d8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Universe days: 101\n", + "Mean basket size per day: 2.8\n", + "\n", + "count 5.830000e+02\n", + "mean 1.806813e+05\n", + "std 4.145566e+05\n", + "min 0.000000e+00\n", + "25% 3.645650e+04\n", + "50% 5.254690e+04\n", + "75% 2.288102e+05\n", + "max 9.000000e+06\n", + "Name: amount, dtype: float64\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Count selected assets by day.\n", + "universe_size = universe_history.groupby(level=[0, 1]).count().amount.groupby(level=0).count()\n", + "print(f\"Universe days: {len(universe_size)}\")\n", + "# Store the selected symbol list.\n", + "unique_assets = list(universe_history.index.levels[1].unique())\n", + "print(f\"Mean basket size per day: {universe_size.mean():.1f}\")\n", + "print('')\n", + "print(universe_history.amount.describe())\n", + "universe_size.plot(title='Daily Universe Size', ylabel='Universe Size');" + ] + }, + { + "cell_type": "markdown", + "id": "e9f0a1b2", + "metadata": {}, + "source": [ + "### Daily Universe Prices\n", + "\n", + "Fetch daily price history for every symbol that appears in the universe." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "c3d4e5f6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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closehighlowopenvolume
symboltime
EW RTKJ7O7ZTI792026-02-0382.6582.89081.30581.443778612.0
2026-02-0482.1083.77082.00082.383389435.0
2026-02-0579.7781.97079.64581.486115515.0
2026-02-0678.1080.65077.46579.876984869.0
2026-02-0778.7178.84577.44078.356475687.0
.....................
CAH R735QTJ8XC9X2026-05-23200.68202.410199.730201.981323710.0
2026-05-27200.37201.430199.480200.001679645.0
2026-05-28199.84201.400199.310200.591403589.0
2026-05-29199.85201.790197.635199.541914690.0
2026-05-30196.80201.510196.200201.352693424.0
\n", + "

2505 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + " close high low open volume\n", + "symbol time \n", + "EW RTKJ7O7ZTI79 2026-02-03 82.65 82.890 81.305 81.44 3778612.0\n", + " 2026-02-04 82.10 83.770 82.000 82.38 3389435.0\n", + " 2026-02-05 79.77 81.970 79.645 81.48 6115515.0\n", + " 2026-02-06 78.10 80.650 77.465 79.87 6984869.0\n", + " 2026-02-07 78.71 78.845 77.440 78.35 6475687.0\n", + "... ... ... ... ... ...\n", + "CAH R735QTJ8XC9X 2026-05-23 200.68 202.410 199.730 201.98 1323710.0\n", + " 2026-05-27 200.37 201.430 199.480 200.00 1679645.0\n", + " 2026-05-28 199.84 201.400 199.310 200.59 1403589.0\n", + " 2026-05-29 199.85 201.790 197.635 199.54 1914690.0\n", + " 2026-05-30 196.80 201.510 196.200 201.35 2693424.0\n", + "\n", + "[2505 rows x 5 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Extract unique assets\n", + "symbols = list(universe_history.index.get_level_values(1).unique())\n", + "# Fetch daily historical price metrics using the earliest timestamp available in the index.\n", + "history = qb.history(symbols, universe_history.index[0][0] - timedelta(1), qb.time, Resolution.DAILY)\n", + "history" + ] + }, + { + "cell_type": "markdown", + "id": "a7b8c9d0", + "metadata": {}, + "source": [ + "### Align Contract Volume And Returns\n", + "\n", + "Build a joined table of contract dollar volume and future returns." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "3d56c7cd", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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dollarvolumefuturereturn
timesymbol
2026-02-03EW RTKJ7O7ZTI79270500.000.000491
2026-02-04DNOW VR22RBI5MBFP159.250.020526
EW RTKJ7O7ZTI7934000.00-0.030469
MCK R735QTJ8XC9X500000.000.023437
SYK R735QTJ8XC9X28667.94-0.013924
\n", + "
" + ], + "text/plain": [ + " dollarvolume futurereturn\n", + "time symbol \n", + "2026-02-03 EW RTKJ7O7ZTI79 270500.00 0.000491\n", + "2026-02-04 DNOW VR22RBI5MBFP 159.25 0.020526\n", + " EW RTKJ7O7ZTI79 34000.00 -0.030469\n", + " MCK R735QTJ8XC9X 500000.00 0.023437\n", + " SYK R735QTJ8XC9X 28667.94 -0.013924" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset = (\n", + " universe_history.groupby(level=[0, 1]).agg(dollarvolume=('amount', 'sum')).rename_axis(['time', 'symbol'])\n", + " .join(history.open.unstack('symbol').sort_index().pct_change(2, fill_method=None).shift(-2).stack().rename('futurereturn').rename_axis(['time','symbol']), how='inner')\n", + ")\n", + "dataset.head()" + ] + }, + { + "cell_type": "markdown", + "id": "c5d6e7f8", + "metadata": {}, + "source": [ + "### Analyze Relationships Between Factor and Future Returns\n", + "\n", + "Create a box plot of dollar-volume quantile buckets compared to future returns." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "c7d8e9f0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Factor: dollarvolume\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
 bucketmean_factormin_future_returnmax_future_returnmean_future_returnstd_future_returnobservations
0(-0.001, 20310.492]6348.423-18.21%10.21%-0.20%3.89%52
1(20310.492, 36988.0]33767.580-9.29%13.13%0.11%3.57%51
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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "factor = 'dollarvolume'\n", + "# Split factor values into quantile buckets.\n", + "x = dataset[factor]\n", + "y = dataset['futurereturn']\n", + "buckets = pd.qcut(x, q=5, duplicates='drop')\n", + "# Summarize each bucket with distribution statistics.\n", + "summary = dataset.assign(bucket=buckets).groupby('bucket', observed=True).agg(\n", + " mean_factor=(factor, 'mean'),\n", + " min_future_return=('futurereturn', 'min'),\n", + " max_future_return=('futurereturn', 'max'),\n", + " mean_future_return=('futurereturn', 'mean'),\n", + " std_future_return=('futurereturn', 'std'),\n", + " observations=('futurereturn', 'size')\n", + ").reset_index()\n", + "summary['bucket'] = summary['bucket'].astype(str)\n", + "# Display the bucket summary.\n", + "print(f\"Factor: {factor}\")\n", + "display(summary.style.format({\n", + " 'mean_factor': '{:.3f}',\n", + " 'min_future_return': '{:.2%}',\n", + " 'max_future_return': '{:.2%}',\n", + " 'mean_future_return': '{:.2%}',\n", + " 'std_future_return': '{:.2%}'\n", + "}))\n", + "# Plot the return distribution for each bucket.\n", + "groups = [y[buckets == b].values for b in buckets.cat.categories]\n", + "plt.boxplot(groups, labels=[str(b) for b in buckets.cat.categories])\n", + "plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", + "plt.title(f'Future Return by {factor} Bucket')\n", + "plt.xlabel(f'{factor} Bucket')\n", + "plt.ylabel('Future Return')\n", + "plt.xticks(rotation=45)\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Foundation-Py-Default", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.14" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 74eff9ca15f76ef839163063d7d12bcd8ad95dfb Mon Sep 17 00:00:00 2001 From: Rudy Osuna Date: Tue, 2 Jun 2026 15:00:22 -0700 Subject: [PATCH 09/16] Delete project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb --- .../research.ipynb | 697 ------------------ 1 file changed, 697 deletions(-) delete mode 100644 project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb diff --git a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb deleted file mode 100644 index df4e28d4ef..0000000000 --- a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb +++ /dev/null @@ -1,697 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "a1b2c3d4", - "metadata": {}, - "source": [ - "![QuantConnect Logo](https://cdn.quantconnect.com/web/i/icon.png)\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "e5f6a7b8", - "metadata": {}, - "source": [ - "## Quiver Government Contracts Research\n", - "\n", - "This notebook studies whether government contract dollar volume helps explain future returns" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "c9d0e1f2", - "metadata": {}, - "outputs": [], - "source": [ - "qb = QuantBook()\n", - "# Daily bars will have an end_time that matches the following midnight.\n", - "qb.settings.daily_precise_end_time = False" - ] - }, - { - "cell_type": "markdown", - "id": "a3b4c5d6", - "metadata": {}, - "source": [ - "### Build a Government Contract Universe\n", - "\n", - "Select assets with frequent, sizable US government contracts, then inspect the returned universe history." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "e7f8a9b0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Shape: (583, 5)\n", - "Columns: ['agency', 'amount', 'description', 'time', 'value']\n" - ] - }, - { - "data": { - "text/html": [ - "
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agencyamountdescriptiontimevalue
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2026-02-03EW RTKJ7O7ZTI79Department of Veterans Affairs32500.0AORTIC VALVE2026-02-0332500.0
EW RTKJ7O7ZTI79Department of Veterans Affairs34000.0AORTIC VALVE2026-02-0334000.0
EW RTKJ7O7ZTI79Department of Veterans Affairs34000.0AORTIC VLAVE2026-02-0334000.0
EW RTKJ7O7ZTI79Department of Veterans Affairs136000.0CUSTOM SURGICAL IMPLANTS2026-02-03136000.0
EW RTKJ7O7ZTI79Department of Veterans Affairs34000.0SURGICAL IMPLANT2026-02-0334000.0
\n", - "
" - ], - "text/plain": [ - " agency amount \\\n", - "time \n", - "2026-02-03 EW RTKJ7O7ZTI79 Department of Veterans Affairs 32500.0 \n", - " EW RTKJ7O7ZTI79 Department of Veterans Affairs 34000.0 \n", - " EW RTKJ7O7ZTI79 Department of Veterans Affairs 34000.0 \n", - " EW RTKJ7O7ZTI79 Department of Veterans Affairs 136000.0 \n", - " EW RTKJ7O7ZTI79 Department of Veterans Affairs 34000.0 \n", - "\n", - " description time value \n", - "time \n", - "2026-02-03 EW RTKJ7O7ZTI79 AORTIC VALVE 2026-02-03 32500.0 \n", - " EW RTKJ7O7ZTI79 AORTIC VALVE 2026-02-03 34000.0 \n", - " EW RTKJ7O7ZTI79 AORTIC VLAVE 2026-02-03 34000.0 \n", - " EW RTKJ7O7ZTI79 CUSTOM SURGICAL IMPLANTS 2026-02-03 136000.0 \n", - " EW RTKJ7O7ZTI79 SURGICAL IMPLANT 2026-02-03 34000.0 " - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def select_assets(data: List[QuiverGovernmentContractUniverse]) -> List[Symbol]:\n", - " # Group by ticker and keep names with 3+ contracts totalling over $50K.\n", - " contracts_by_symbol: dict[Symbol, list[QuiverGovernmentContractUniverse]] = {}\n", - " for d in data:\n", - " contracts_by_symbol.setdefault(d.symbol, []).append(d)\n", - " return [s for s, ds in contracts_by_symbol.items()\n", - " if len(ds) >= 3 and sum(x.amount or 0 for x in ds) > 50_000]\n", - "\n", - "# Add the Quiver Government Contract universe.\n", - "universe = qb.add_universe(QuiverGovernmentContractUniverse, select_assets)\n", - "# Request universe history of the last 120 days.\n", - "universe_history = qb.universe_history(universe, qb.time - timedelta(120), qb.time - timedelta(1), flatten=True)\n", - "# Print the returned shape and columns.\n", - "print(f\"Shape: {universe_history.shape}\")\n", - "print(f\"Columns: {list(universe_history.columns)}\")\n", - "universe_history.head()" - ] - }, - { - "cell_type": "markdown", - "id": "c1d2e3f4", - "metadata": {}, - "source": [ - "### Universe Diagnostics\n", - "\n", - "Inspects the raw contract amount distribution and visualizes how the daily universe size evolves chronologically." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "a5b6c7d8", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Universe days: 101\n", - "Mean basket size per day: 2.8\n", - "\n", - "count 5.830000e+02\n", - "mean 1.806813e+05\n", - "std 4.145566e+05\n", - "min 0.000000e+00\n", - "25% 3.645650e+04\n", - "50% 5.254690e+04\n", - "75% 2.288102e+05\n", - "max 9.000000e+06\n", - "Name: amount, dtype: float64\n" - ] - }, - { - "data": { - "image/png": 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H48CBA+o0loiIiKJOzAZBJSUl6NatG1577TW/P3/uuefwyiuv4J///Cc2b96M5ORk5Obmory8XOGWEhERUTSK2W0zhgwZgiFDhvj9mRAC8+fPx9/+9jeMHDkSAPD222+jSZMm+PjjjzFu3Dglm0pRyO5wwmiI2d8BiIgoDDR5Fzhy5AjOnj2LwYMHy8+lp6fjmmuuwaZNm/y+x2q1orCw0OsPadP/rT+Irk+uwa7TBWo3hYiIVKTJIOjs2bMAgCZNmng936RJE/lnvubNm4f09HT5T/PmzSPeTlLHpkMXUWpzYNOhi2o3hYiIVKTJIKg2Zs2ahYKCAvnPiRMn1G4SRUiZzQEAOJVfpnJLiIhITZoMgjIyMgAAeXl5Xs/n5eXJP/NlNpuRlpbm9Ye0qazCFQSdZhBERBTXNBkEtWrVChkZGfj666/l5woLC7F582b069dPxZZRNHAHQZwpSEQUz2J2dlhxcTEOHjwoPz5y5Ah27NiBBg0aoEWLFnjooYcwZ84ctGvXDq1atcLs2bORmZmJW265Rb1GU1QotzETREREMRwE/fzzz7j++uvlx4888ggAYNKkSVi8eDFmzpyJkpISTJ06Ffn5+RgwYAC++OILWCwWtZpMUULKBF0ssaG8wgFLgkHlFhERkRp0QgihdiOiUWFhIdLT01FQUMD6II3pMHs1yiucAIBv/jQIrRulqNwiIiIKl1Du35qsCSKqjtMp5AAIAM4UsC6IiCheMQiiuGK1O70ec5o8EVH8YhBEcUWqB5KwOJqIKH4xCKK4wiCIiIgkDIIorkirRUu4VhARUfxiEERxpZyZICIiqsQgiOKKNBxmMri++qfyy8BVIoiI4hODIIor0nBYi4ZJ0Olcs8UuldhUbhUREamBQRDFFSkTlGYxonGqGQDrgoiI4hWDIIorUk1QosmApumJALhWEBFRvGIQRHFFGg5LTDAgq54rCGJxNBFRfIrZDVSJakMaDrMkGNA03bWZLoMgIqL4xEwQxRXPIChTygQVMAgiIopHDIIorpR7DIdJQdApFkYTEcUlBkEUV8o8CqNZE0REFN8YBFFc8Tccdr7ICqvdEehtRESkQQyCKK6U2ZwAXMNh9ZMSYElw/S+QV2BVs1lERKQCBkEUV+R1ghL00Ol0HnVBHBIjIoo3DIIornjWBAFgXRARURxjEERxpdyjJggAMtMZBBERxSsGQRRX5EyQFARxrSAiorjFIIjiirxtRuVwWNN6rlWjuVYQEVH8YRBEcaXcJxPEmiAiovjFIIjiSplvTZBHECSEUK1dRESkPAZBFFeqDIdVbqJaanOgoKxCtXYREZHyGARRXCmvcC+WCLgyQlekmABwrSAionjDIIjiht3hhM3hHQQBnkNiLI4mIoonDIIobpTbnfJ/S8NhANcKIiKKVwyCKG5I9UAAYDa6v/qZnCFGRBSXGARR3PCcHq/T6eTnM+W1ghgEERHFEwZBFDd89w2TSGsFnSlgTRARUTxhEERxQ54en+AdBHE4jIgoPjEIorjhXijR+2svBUF5heWocDirvI+IiLSJQRDFjeqGwxomm2Ay6OEUrkCIiIjiA4Mgihvl1QyH6fU6eSNVrhVERBQ/GARR3PDdN8wT1woiIoo/DIIobpRV+M8EAe66IE6TJyKKHwyCKG74bp7qKUseDmMQREQULxgEUdwoDyITxCCIiCh+MAiiuBGwJoibqBIRxR0GQRQ3ymyVO8j7GQ5jJoiIKP4wCKK4Ebgw2lUTVGS1o7C8QtF2ERGROhgEUdwIVBOUZDKiflICAGaDiIjiBYMgihvS7DCLn+EwgENiRETxhkEQxY1Aw2EA0DSdxdFERPGEQRDFjZqCIK4VREQUXxgEUdyQa4JM/r/2HA4jIoovDIIobsg1QdVkgrhWEBFRfGEQRHGjpuEw7h9GRBRfGARR3HAPh1VXE+QKgs4WlsPhFIq1i4iI1MEgiOKGvIFqNZmgRqlmGPU6OJwC54o4JEZEpHUMgiguCCFqHA4z6HXISOcMMSKieMEgiOKCzeGENMJV3WKJgGddEDNBRERaxyCI4kJ55eapQPWZIMBdF8RMEBGR9jEIorggDYUZ9TokGKr/2mdywUQiorih2SDI4XBg9uzZaNWqFRITE9GmTRs8/fTTEIKzfuJRoM1TPXHBRCKi+GFUuwGR8uyzz+L111/HkiVL0KlTJ/z888+46667kJ6ejgcffFDt5pHCpExQoHogAMhMZ00QEVG80GwQtHHjRowcORLDhg0DAGRnZ+Pdd9/FTz/9pHLLokupzY4kk/a+BiVWO5LN7n7VNDNMEu2ZIN9+ERFR7Wl2OKx///74+uuvsX//fgDAL7/8gu+//x5Dhgzx+3qr1YrCwkKvP1q382QBuj25Bs99sVftpoTVT0cuoeuTa/Dq1wfk58prWCNIItUEFZRVoMRqj1wja2HdvnPo8r9f4s3vDqvdFCIiTdBsEPTYY49h3Lhx6NChAxISEtCjRw889NBDmDBhgt/Xz5s3D+np6fKf5s2bK9xi5f1yMh8VDoGfj11Wuylhtet0ARxOgR8OXZCfC3Y4LNWSgFSLK9NypiC6skE/Hr4IpwA2HrqodlOIiDRBs0HQe++9h2XLluGdd97Btm3bsGTJErzwwgtYsmSJ39fPmjULBQUF8p8TJ04o3GLlFZXbvf7WCqvdNR3ecyNU93BYzV/5rChdK0jqT7QO1RERxRrNFhf8+c9/lrNBANClSxccO3YM8+bNw6RJk6q83mw2w2w2K91MVRWVV3j9rRW2yiDoTEEZnE4BvV5X45YZnjLrJWLv2aKoCzak9nCDVyKi8NBsJqi0tBR6vXf3DAYDnE5nNe+IP9rNBLkCngqHwIViK4CaN0/1FK1rBUntKSq3ay5wJSJSg2YzQTfffDOeeeYZtGjRAp06dcL27dvx0ksv4e6771a7aVFDupEWW+0QQkCn06ncovCQMkGAK2vSOM3irgkKMhMkvTdaVDicyCt0D8+dKShHqiVBxRYREcU+zQZBr776KmbPno37778f586dQ2ZmJu655x48/vjjajctakgZIIdToNTm0MzUa6tHEHSmoBw9AJRVbpsRzHBYNG6dkVdYLu99BrgCtPZNUtVrEBGRBmjjrudHamoq5s+fj/nz56vdlKhV5DEFvKhcO+vPeGaCpEAm2HWCAM+1gqKnMPpMgXdboilAIyKKVZqtCaKaedYCFVu1U2Ni9RkOA0KtCXIFQVJhdTTwDXoYBBER1R2DoDjmWVxbqKHiaL+ZIFvwNUFNUs3Q67wLq9XmW58UTVkqIqJYxSAojnlmgrQ0Q0yaHQa4g4VQhsOMBj2apLlmiEVLcbQUzGU3TAIQPe0iIoplDILilBACxV41QdocDqtSExTEcBgQfXVBUjt6ZTeofMwgiIiorhgExalSmwMOj3oXbWWC3EHQxRIbyisc7pqgIDJBQPRtpCq1o3d2fQDA2YJyr+tHREShYxAUp3yDHi1lgjxrggBXABFKTRDgXjAxWoadpHZ0b14fBr0OdqfA+aLoqFciIopVDILilG/Qo9VMEOAaSgp1OCya1goqLK+Qr0+z+onIiLJ6JSKiWMUgKE75zgbTUhBks3sPfZ3OLwupMBoAMtMrg6Ao2En+TGU9UL2kBCSbjVEVoBERxTIGQXHKNxNUqKHhMCkTlH1FMgBXxqQ8hA1UAY+1gqKgMFoKdqTATBqqOxMFARoRUSxjEBSnqtYEaSkT5AqCWl3hmk7ulQkyBfeVl7ItUmG1mqRhLyn4aRplM9eIiGIVg6A4peXCaKscBLkyQacLykLaQBUA0hKNSDa5h9PUJGeC6iV6/c2aICKiumEQFKekoKdhsqnysfYyQdkNXUHQyctlKK9wPRdsEKTT6aJmrSDfICirMiOkdnBGRBTrGATFKSnokW6sWgqCpBWjpUzQycvuYCHYmiAgetYKkoIw30yQ2u0iIop1DILilJQJkupMtDIcZnc4Ia0h2KJhEnQ6eC0qGGwmCIieYSfp+FIGSGrX5dIKlNq0E7wSESmNQVCc8pcJEiL2VyD2XCMo1ZyARilm+bHJqIdBrwv6szLT1R92cjgFzhZ6Z4LSLAlINRsr28biaCKi2mIQFKekdYKkWVB2p5DrZmKZ52rRJqNeDhyA0IbCAI9hJxWnop8vssLhFDDodWicapGf55AYEVHdMQiKU9LwV+M0C6TkiBaGxKRMkFGvg0Gvk4M8oA5BkIrZFmkoLCPN4pXFymRxNBFRnTEIilPScFiaxYiUyqEV31WkY5GUCTIZXV9tKVgAgt8yQ5LlUROk1lDhabkeKNHreWaCiIjqjkFQnCqyurI+qZYEpFoSXM9pIBNkc7hmhpnlIMgdPIRSFA0ATdLN0OlcgdXFElv4GhmC0z4LJUrcRdusCSIiqi0GQXHKMxOUajF6PRfLpLomk58gKDEhtK+72WiQC6vVyrj4rhEkkTJD3DqDiKj2GATFISGEHPCkWhKQJmeCYj8IsjlcQZDZ6Mr6eNUEhTgcBqg/7HTKZ40gidrtIiLSAgZBcaiswiGvnZPqlQmK/eEwa8BMUOhBUJbKw07V1wRVFkYXlMPpjP2lDYiI1MAgKA5JGR+DXockk0FTw2HuTJDrq10/KQGWymGwUGuCAI8d29UaDivwPxzWpHJWn5r1SkREsY5BUBySMj4pZiN0Oh1SNJUJchVGS5kgzz3AapMJUnOtoBKrHfmlrmvS1KcwOsGgl9cN4pAYEVHtMAiKAQWl4Q1OCuV6IGPl3wlez8cy30wQ4B5KqktN0OHzJTh4rggHzxXh0PliRYagpKLnVLNRrtvybhuDICKiumAQFOW++O0Muj21Bks2Hg3bZ3oWRbv+1s5wmLsmyB3wZKbXPhMkBVB7zxZh8EvfYvBL3+L3L27Ao+//EobWBibVIflmgSTRsrcZEVGsYhAU5X47VVj5d0HYPrO4mkyQFobDpEyQyeD+ao/snokrm6Tiho5NQv68KzNS0b9NQ9RPSkD9pAT5nG0+cik8DQ7gcmWtzxUe+595kp6/XMqaICKi2jCq3QAKrKyyxkX6OxykYCet8oaepqlMUOViiR5rAvVvewW+fHhgrT4vwaDHO1P6yo/PFpSj77yvcbawXN7TK1Kk6yQFXr60lMEjIlIDM0FRTgp+ysMaBFUzHGbVTibIbIjMV7tRqhlGvQ4Op8D5ImtEjiEp9LlOvhgEERHVjWpBUHk5l/sPRrktcpmgqsNhsX8zlWqCzCGuDh0sg16HjHRXjU6ka3GKrd7Dlr60NIxJRKQGRYMgp9OJp59+GllZWUhJScHhw4cBALNnz8Zbb72lZFNihjwcZgtfEFR1dph2Mgr+aoLCTanVmt3BauBMkBZm9RERqUHRIGjOnDlYvHgxnnvuOZhMJvn5zp07480331SyKTHDXRPkDNtnVh0Oc2cU1NotPVysdikTFPpMsGBlpiszNd1zfzd/pOtWzCCIiKhWFA2C3n77bSxcuBATJkyAweC+SXXr1g179+5VsikxQ8oAhbcmyHc4zPV3hUPIQUSsstm1lAmqaThMO7VcRERqUDQIOnXqFNq2bVvleafTiYoK/kPuT3kEhsOkm2uK2XUTTTEZodN5/yxWWe2Vs8OMkQ+CIr2fWE3DYVqa1UdEpAZFg6COHTviu+++q/L8Bx98gB49eijZlJgRkSnyVmmKvOvmqtfrkGLSxtYZUibLFMEgKCtqMkHugvZYH8YkIlKDousEPf7445g0aRJOnToFp9OJDz/8EPv27cPbb7+NTz/9VMmmxIzIrBNU9eaaajGiyGqP+ayCXBOkQCYo0vuJ+dZu+ZKun8MpUFbhQJKJy34REYVC0UzQyJEj8cknn+Crr75CcnIyHn/8cezZsweffPIJbrjhBiWbEjPKbK6bus3uhCNM+1X5u7lqZZq8XBNkjGBhdOU2FvmlFSixRu58FdawWGJigkFerDHWrxsRkRoU/9Xx2muvxdq1a5U+bMzyLIgur3Ag2Vy3SyaE8LsScapGdpJXIhOUanFtn1FUbseZgjK0bZwa9mM4ncK9TlA111yn0yHFbERBWQWKyivQJM3/HmNEROSfopmgu+++G0uWLKnyfGFhIe6++24lmxIThBBew2DhGBKz2p2ocLgySv6DoNjOKNgqC6MjWRMEuOuCIlUcXWKzQyrzqW44zPUzrhVERFRbigZBixcvxv33348HH3wQTqd7KnZZWZnf4CjeVTiE1xBYOGaISUMsOh2QbPIMghK8fh6rlMgEAe66oDMRKo6WglGjXgdLgNWvtTKMSUSkBsW3zfjss8/w+eefIzc3F5cvX1b68DHFN/MTjrWCPKfH6z02/9ROJijys8MAd11QpGaIeRav63TVb9KqlWFMIiI1KB4EdezYEZs3b0ZFRQX69OmDPXv2KN2EmOEb9IRjOMy9CrH3EItWMgruTFDkCqOByK8VVNMaQRKuFUREVHuKBkHSb7QNGzbEV199hUGDBqFfv35YtWqVks2IGb7DX+EYDvNXFO35ONYzCkplgiK9VlBNawRJuIkqEVHtKTo7zHNBN6PRiDfffBMdO3bE/fffr2QzYoZv5iecmSDfm6tWMgpKrBgNAE3TI7tWUE3T4yVaGcYkIlKDokHQunXr0KBBA6/nHnnkEXTt2hU//PCDkk2JCZGpCfI/zCJnFGJ8HyqbYoXRrpqgM/nlcDqFV31VONS0UKKEQRARUe0pGgQNGjTI7/ODBw/G4MGDlWxKTCj3HQ6LYCZI2kcs1m+mStUENUmzQK8DbA4nLpRY0Tg1vGv0hDocFuuz+oiI1BDxIOiRRx7B008/jeTkZDzyyCMBX/vSSy9FujkxpcpwmK3uO7wXVnNz1UpGQamaoASDHk3SLDhTUI7T+eURCIK893erjlauGxGRGiIeBG3fvl3eIX779u3Vvi7QNOB4FZmaoBqGw2I4o+BwCtgr11WK9HAY4Joh5gqCytC9eb2wfjYLo4mIIi/iQdC6dev8/jfVzHc2WDjXCaouExTLKw9LWSAg8pkgwBUEbT12OSIzxKqbxeeLmSAiotpTfJ0gT8eOHcPu3bu9Vo8mN9+gJ5KF0dKwi83ulGdYxRrPIEiZTJC0YGL41woKtjBaK7P6iIjUoEgQ9O9//7tKvc/UqVPRunVrdOnSBZ07d8aJEyeUaEpMqVoTFM7FEn0Koz0ex+oNVQre9DrAaIj8VzuSawVxOIyIKPIUCYIWLlyI+vXry4+/+OILLFq0CG+//Ta2bNmCevXq4cknn1SiKTHFtxA6krPDDHodkk0Gr9fEGqVmhkkyI7hWUGGQK0Z7Dod5rsNFREQ1U2SK/IEDB9CrVy/58cqVKzFy5EhMmDABADB37lzcddddSjQlpihZGC09V2JzxGxWwarQzDBJZgQzQcXW0DJBdqdAeYUTiSZlAkAiIi1Q5G5RVlaGtLQ0+fHGjRsxcOBA+XHr1q1x9uxZJZoSU6QaIGnoKpKF0Z7PxWomSKmFEiXScNiFYltYro2n6oYtfSWbDJDWaYzV4JWISC2K3C1atmyJrVu3AgAuXLiAXbt2IScnR/752bNnkZ6erkRTYop0Y22QbAIQppoga/UFt7G+f5hUE6RUJigt0SgPIZ4pCF9xtBDCIxMUeDhMp9PJC13G8sw+IiI1KHK3mDRpEqZNm4ann34aY8aMQYcOHXD11VfLP9+4cSM6d+4c9uOeOnUKd9xxBxo2bIjExER06dIFP//8c9iPEynS8Fd9KQiqY7bBanfI2RL/mSBp9eHYvJkqnQnS6XQRGRIrtTngqFzvqKbhMNdrWBxNRFQbitQEzZw5E6Wlpfjwww+RkZGB999/3+vnP/zwA8aPHx/WY16+fBk5OTm4/vrrsXr1ajRq1AgHDhzwKtCOdlLmp0GSFATVbSkBaYhFpwNSTNobDnPXBClXF9O0XiIOnCvGqTAGQdL5N+h1SEyouS+xft2IiNSiSBCk1+vx1FNP4amnnvL7c9+gKByeffZZNG/eHIsWLZKfa9WqVdiPE0m+mSDfvcSCUVhegeMXSwG4h2xSTEa/G37GekZBqS0zPGXJawWFMwhyL5QYzErqafJ1Cy0IulBsxdkAw3iWBAPaNErmau5EpFmKbqCqpFWrViE3NxdjxozBhg0bkJWVhfvvvx9Tpkzx+3qr1Qqr1So/LiwsVKqp1apSExTicFh5hQO/e2EDLhRbvZ6vbogl1hfesyo8HAa4p8mfuhy+IKi6/d2qU5tarpOXSzH4pQ0oryG7OGtIB9wzqE3Qn0tEFEtUXTE6kg4fPozXX38d7dq1w5dffon77rsPDz74IJYsWeL39fPmzUN6err8p3nz5gq3uCo5E5RUuyBo39kiXCi2wqDXISPNgow0C5qmW3BHv5Z+Xx/rhdE2h+v8KBoEVdYEhbMwWs4EmQMXRUtqMxz28fZTrin1CQb5u+H5RwqIfz52OcTWExHFDs1mgpxOJ3r16oW5c+cCAHr06IHffvsN//znPzFp0qQqr581a5bXLveFhYWqB0JyTVCy62YY6nDYvrNFAIBrWjXAO1P61vj61FoOq0QLa4UKmaB64V8wMdjVoiWhDmMKIfDxjtMAgCdHdsJtvap+z7/Zm4e7F/+MMxFYCJKIKFpoNhPUtGlTdOzY0eu5q666CsePH/f7erPZjLS0NK8/apOGKmqbCdpbGQRdmZEa1OtjvcDW5lCjJsg9OyxcKzYHu2+YJNTNb/ecKcLBc8UwGfW4qXOG39e4Z72Ff180IqJooUoQZLPZsG/fPtjtkbvZ5uTkYN++fV7P7d+/Hy1b+h8KikZlPjVBdqdAhSP4GWL78lx1TR2CDoIqMwrW2AyC3Jkg5WaHNUk3Q6dzBayXS8MzjBjsDvKSlBCD11W/uLJAv7uysVxU7UsKgi6V2MKyPhURUTRSNAgqLS3F//zP/yApKQmdOnWSszIPPPAA/v73v4f1WA8//DB+/PFHzJ07FwcPHsQ777yDhQsXYtq0aWE9TiRJNx9pdhgQWjZon5wJCi6rFfs1QZWZIAU2T5WYjQY0SjEDCN8MsUgOhzmdAp9UBkEjumdW+7o0S4K8CGMk9kYjIooGigZBs2bNwi+//IL169fDYrHIzw8ePBgrVqwI67F69+6Njz76CO+++y46d+6Mp59+GvPnz5f3K4t2Qgg54EmzJMhbIwRbF3Sh2IoLxTbodED7JilBvSfWh8OslefLnKBsglPKmoRrraBQM0GhzOrbevwyTuWXIcVsxO86NA742swITP8nIoomihZGf/zxx1ixYgX69u3rtfZIp06dcOjQobAfb/jw4Rg+fHjYP1cJ0nRvAEgyGZCYYECJzRF0Jmh/ZRaoRYMkJPlZGNGftBhfJ8iqQiYIcNUF7TiRH4FMUIizw6w1X7eVO04BAHI7ZcBSw0KMmfUSsT+vmEEQEWmWoneL8+fPo3Hjqr99lpSUcEE2H551GJYEg7w7eLBBkFwU3SS4eiDAfTMtr3CGVHsULeSaIMUzQeHNmIS+TpArWCquIRNU4XDi852ujYpHBhgKk7gzXCyOJiJtUvRu0atXL3z22WfyYynwefPNN9GvXz8lmxL1pGDHZNTDoNfJv7UHW6Qq1QMFWxQNQK4BAWJzSMxdE6RcYTQANE0P70wq93BYeNcJ+v7gBVwqseGKFBP6t2lY4+dmRWBfNCKiaKLocNjcuXMxZMgQ7N69G3a7HQsWLMDu3buxceNGbNiwQcmmRD0pCJL2jpL+DjoTlBdaUTQAGA16JJkMKLU5UFReIc9KixXqZYLCXRNU28LowEHQqsq1gYZ1aQpjEEOGrAkiIq1T9G4xYMAA7NixA3a7HV26dMGaNWvQuHFjbNq0yWtXeXJnfOQgqHI4rDyIIMjpFDiQF9oaQZJYLo5WY3YYEP6MiVTbkxbithk2h7Pa70eZzYEvd7mGwkZ0zwrqczPTmQkiIm1TfMXoNm3a4I033lD6sDFHuplJwY97OKzmWp0Tl0tRanPAZNQju2FSSMdNMRuRBysKY7A4Wr3ZYa6MybkiK6x2R53XKQq1MDrFZIROBwjheq+/guev9+ah1OZAs/qJ6NmiXlCf614NuxxCCNbtEZHmKHq32LZtG3bu3Ck/XrlyJW655Rb85S9/gc1mU7IpUU8a9rLUYjhMKopu2yglqGEPT7G8dYZamaAGySZ5q468AmsNrw5MCBHycJher0OKKfAaTysrh8JGdMsMOpjJSLdApwNsdiculvD/TyLSHkXvFvfccw/2798PwLXB6dixY5GUlIT3338fM2fOVLIpUc89HKav/Dv4IKg2RdGSWB4Oc9cEKVsYrdPp5CGxutYFlVU44HC6tt8INhPkem31162gtALr950DAIwMcigMABIMejRJZV0QEWmXokHQ/v370b17dwDA+++/j0GDBuGdd97B4sWL8d///lfJpkS9Mp/hMLkmKIjZYftC3DPMUyyvFaRWJgjw3GurbsGCFMTodUCyKfhgLlAGb/VvZ1DhEOiQkRryd4LF0USkZYreLYQQcDpdN6qvvvoKQ4cOBQA0b94cFy5cULIpUa/cZ3aYJZRMUC2LooEYzwTZ1akJAtzBQl13XZeCzxSzMaQanEBbnqwKYpuM6nCtICLSMsXXCZozZw6WLl2KDRs2YNiwYQCAI0eOoEmTJko2JepJw2Gh1gRZ7Q4cuVACAOgQwvR4SSzvH2arXGXbrGImqK7BQqhF0ZLqgte8wnJsOnwRAHBz19oHQcwEEZEWKXq3mD9/PrZt24bp06fjr3/9K9q2bQsA+OCDD9C/f38lmxL1yirrWyxyJsh1qWpaLPHguWI4nALpiQlokmYO+bgxXRhtV2edICD8w2HBFkVLpOvmO6vvk19OQwjg6pb10bxBaDMFASAzncNhRKRdik2RdzgcyM/Px7fffov69et7/ez555+HQeFVfqNddYsl1rROkGc9UG2mNMf2cJg6K0YD4VsrSDrvaWHKBElDYcFsk+EPM0FEpGWK/cpsMBhw4403Ij8/v8rPLBYLEhJC+0df63zXCQp277C6zAwDqs8oxAI1M0FNPTImQohaf06oO8hL/GXwjlwowa8nC2DQ6zC0S9NatYc1QUSkZYreLTp37ozDhw8reciY5VsTFOzeYXvrMDMM0EomSL3hsBKbA4VltT93tR8Oq1rLJW2TMaDtFbgiJfShUcCd4bpQbA1qtXIiolii6N1izpw5ePTRR/Hpp5/izJkzKCws9PpDbrXdO2xfLXaP96SJwmgVMkGWBAMaVu61Vpe1gkLdPFWS5hO8CiGw8pdTAFwLJNZWvaQE+bt3toDZICLSFkW3zZCmxI8YMcKrXkVakt/h4G+aEncQVLlYYhB7hxWUVuBsoetG1b6WmaC0GC2MdjqFqusEAa5s0MUSG07nl6FjZugz8wCgsI6F0dK+Y7tOF+Lw+RKYjXrc2Kn2My91Oh0y61lw6HwJTueXIfuK5Fp/FhFRtFE0CFq3bp2Sh4tp0qKIck1QEJkgaX2grHqJIRfWSmJ1OEwKgADlV4yWZNazYOepApyuw1pB4ZoiLxVED76qScif5SuzXqIrCGImiIg0RtEgaNCgQUoeLqb57h1mkWeHVb+B6r6zriHF2tYDAe6bb1mFAxUOJxJUyqqESqoHAtTNBAHhGg6rfWG00ynkeqDaLJDoK1wz34iIoo3id4vvvvsOd9xxB/r3749Tp1w1C0uXLsX333+vdFOiWpWaIFPNhdF1LYoGvG++xTGUDZLqgXQ6IMGgzm7n7mCh9hmTcBRG/3T0Es4WliPVYsR1VzaqdVsknCZPRFqlaBD03//+F7m5uUhMTMS2bdtgtbp23C4oKMDcuXOVbErUK6tmOCxQTVBdp8cDrk0zpYUZY2lITNoyw2TQ12p9pHAIR7Ag1fTUdp2gwnK7vGP8kM4ZMBvrPjQYjgwXEVE0Unx22D//+U+88cYbXusC5eTkYNu2bUo2Jer57h1WU02QEKJOe4Z5isW1gqRMkMmo3vBdWIKgysAzJdRMkNl1zWx2Jz77VVogMfgd4wPhJqpEpFWK3jH27duHgQMHVnk+PT3d7yKK8axKTZBJLz/vbzG+0wXlKCq3w6jXofUVKXU6tpRVKLbGUiaocnp8GDIftSUFC3mF5bA7qq/dCqS2w2GeQVNhuR2NUs3o27phrdrgy3OYry4LQRIRRRtFg6CMjAwcPHiwyvPff/89WrdurWRTol51w2FCeBcBS6Si6DaNUuqcDYnF/cPkNYJUzARdkWyGyaCHUwB5RdaQ3y+EqPU6QQa9DskmdwA4vGtTGPThGRbMqFwNu6zCgfzS2MkOEhHVRNE7xpQpUzBjxgxs3rwZOp0Op0+fxrJly/Doo4/ivvvuU7IpUU+aBZboMzvM9bOqQ2LhKIqWpMXggonWKAiC9HqdHDDUZujIaneiwuHKtISaCXK9xx04hWsoDHBl16QVp1kXRERaougU+cceewxOpxO///3vUVpaioEDB8JsNuPRRx/FAw88oGRToprd4ZTXvZGCoASDHgkGHSocAmUVDtTzec++MAZB4Vor6MSlUpwLkBFJMhnQoZYbvV4uscFk1CPZ7GprNNQEAa4hseOXSrHp0EXoQ+xXYZkr6NTpgBRTbYIgI84WAi0bJqFbs/SQ3x9IVj0LLhRbcTq/DJ2z6v7Zxy+W4nyx+7uRmGDAVU1r912oyan8MmSkWcKWGSMi7VA0CNLpdPjrX/+KP//5zzh48CCKi4vRsWNHpKTUrYZFa8o9hrsSPYY4LAkGVDjsfqfJ13W7DE9SkW1dMkG/nSrAyNd+gMMZuIbkqZGdcGe/7JA++0KxFTe+/C0y0iz4fMa1ANyzw9TMBAHu4uiX1u7HS2v31+ozUsxG6Gtxw05LdF23kd0ywx5MZNZLxC8nC8JSHL312GWMfn1jlef/MrQDpg5sU+fP97T58EWMXfgj7srJxhM3dwrrZxNR7FM0CPrPf/6DP/zhD0hKSkLHjh2VPHRM8QxyPG/qiQkGFJXbq8wQq3A4ceh8MYDoyQS9tu4gHE6B+kkJfutbisorcLm0AjuO5+POfqF99me/nsGlEhsuldhQbLUjxWyMmkzQbb2aY9epwhr3eAtkdM9mtXrf5P7ZSLUYMTHEoDIYDSr3RbschpqgvZX1a4kJBjRKNaPYaselEht2nMiv82dXPZbrl4OD54rD/tlEFPsUDYIefvhh3HvvvRgxYgTuuOMO5ObmwmBQbzZPtPKcHu/5G311+4cduVCCCodAitmIZvUT63x89xT52gVBh84X44tdZwEAK+7ph/Z+slMrd5zCjOU7alVjsnLHKfm/z+SXoV2T1KiYHQYAfVs3xJcPV50BqYSbu2Xi5jpslhqI9J0Ix4xBKbge0iUDL93WHV/uOot7lm6t0yKT1R/LFbT5m0xARKTor81nzpzB8uXLodPpcNttt6Fp06aYNm0aNm6smhqPZ/Jq0SbvG7q8VpDN+x906bfd9k1SwjIMUted5N/49jCEAAZf1dhvAAR4rKkT4j5bxy+WYtvxfPmxFERFSyZIq+r6nfAkfYa0IGRmeuRWpJYCLhuDICLyQ9E7htFoxPDhw7Fs2TKcO3cOL7/8Mo4ePYrrr78ebdqEtxYglsnT4302ArVUs2Cie8+w2u1c7qsuw2FnC8rx320nAQD3XVf9NZWCoLMF5TXWDXn6pHIhQImUPYiWmiCtSgvjxrrygpCVRe3S+krniqzydQwXKZvJTBAR+aPocJinpKQk5Obm4vLlyzh27Bj27NmjVlOijnuhRO8benWrRodjuwxP7nWCQv+t/98/HEGFQ6BPdgNc3bJBta9rkmqGXgdUOAQuFFvRJM0S1OdLQ2H1khKQX1ohZw+szARFVDjXjvJdELJBsglmox5WuxN5BVa0aJhU52O4j+X6DtvCHFwRkTYofscoLS3FsmXLMHToUGRlZWH+/PkYNWoUdu3apXRTola1w2FSTZDP7LBwrhEE1P63/oLSCiz78RgA4N7rAi9+aTTokVEZ+ARbF7T3bCH25xXDZNBjfJ8WAFAlCGImKDIiMRwmBVY6nU5elTrc6xDJw2G1XMGbiLRN0UzQuHHj8OmnnyIpKQm33XYbZs+ejX79QpwaFAfKqxkO85cJKrbacfKy68YR/kxQaEHQfzYfQ4nNgSubpOL6KxvX+PrMeok4XVCO0/ll6Nmifo2vlzYGvb5DI7mvrAlSRjgzQYV+tgbJrJeIwxdKwl4XJBdGVzAIIqKqFA2CDAYD3nvvPc4Kq4HvvmESfzVB0lBYkzQz6iWZwnL82vzWX17hwL+/PwLAVQsUTIF2Zr1E4NjloG58TqfAqsogaES3LDRJc61gLBVWR8vsMK3y3KW+rvztjxapTVqZCSKiQBQNgpYtW6bk4WJWWUU1mSBpE1WP4bD9edLMsPBkgQD3zanE5oDDKYJaaff9rSdxscSGrHqJGN61aVDHyfTYmLMm245fxqn8MiSbDPj9VY1xscQGwF1YzUxQZEVyOAyo/WzBmo9VWRjNTBAR+RHxIOiVV17B1KlTYbFY8MorrwR87YMPPhjp5sQEed+waqbIl/vJBIVrKAzw3pG8uNyO9KTAm3naHU4s/PYQAGDqwNYwGoILRLLqBV8TtOoXVxYot3MGLAmGKoXVnB0WWdIq4la7Eza7s07BphSYpPkMhwHAqTCvFSQXRjMTRER+RDwIevnllzFhwgRYLBa8/PLL1b5Op9MxCKpUXl0myM9w2N4wT48HXENKJqMeNrsTheUVNQZBn+08gxOXytAg2YTbejUP+jjuTFDgIKjC4cRnv54B4N4YVCqsPl1QjlP5ZcwERZhnYFxUXoGGlRuqhkoIIS+46JkJygryuxAKh1OgpDJr6nAK2B3OoAN0IooPEQ+Cjhw54ve/qXrScFeVmiCTwevnQoiIZIIA12/pF4ptNRbCCiHwzw2HAbi2bfDNXgUiBUFnCgL/9v/DwQu4WGJDw2QTcto09Hq/VFjNmqDIMuh1SDYZUGJzoKjcXusgqLRyiBWoWhgNuIIgIURYFv0s9vnu2hgEEZEP/osQhWpcMbry5+eLrLhcWgG9DmjbOLyb0Aa7VtCG/eex50whkkwG3NmvZUjHkG58l0psfjeFlUgF0cO6NvW6iXneOJkJirxwzBCT3mvQ65Dk8f1umu4aGi21OVBQVve6IwAo9Pnusi6IiHwpWhjtcDiwePFifP311zh37hycTu9/lL755hslmxO1qi2M9qkJktYHyr4iuUrWqK6CXTX69fWuWqDb+7QIeXZamsWIFLMRxVY7TheUoU2jqoFceYUDX1buQzayu/e+WJ6F1VLNB2uCIifVYsTZwroVR0vvTTEbvbI9lgQDrkgx4UKxDafyy8Iy09H3u8u6ICLypWgQNGPGDCxevBjDhg1D586dw5Ly1qJq1wkyeWeCIjUUBngEQdbqb3jbjl/G5iOXkGDQ4X+ubRXyMXQ6HTLrWbA/rxin8/0HQV/vOYcSmwPN6idWWUsoy2NaNQujIy8c0+T9rREkyayXiAvFNpzOL0enzPRaH0PiG6wxE0REvhQNgpYvX4733nsPQ4cOVfKwMUdeJ8hUzTpBNu9M0JVNwlcULZFmAwXKBP2zMgt0S/csNE2v3e71TdMT5SDIH2mbjBHdMqsEzZ7TqqWAkUFQ5NRlOxWJv+nxkqbpFvx6siBsxdFVM0HcOoOIvCl6xzCZTGjbtq2Sh4xJNQ2HlVX+RrsvT5oZFsFMUDVB0MFzRVizOw86HXDPoMBbZAQSaGp0QVkF1u87DwAY4TMU5vne0/nl3DtMAXXZWFfinhnmPxMEhG+GmHQsSTkzQUTkQ9E7xp/+9CcsWLAAQgS/a3g8qm4XeXnvsArXDJsDecUAIjUc5vpN3be4VCLNCLuxYxO0bVz742cFWCn4y9/OwuZw4somqejgZwkAz8JqqZiWs8MiJ5yF0Wl+giB5mnwNswWDP5b3d5c1QUTkS9HhsO+//x7r1q3D6tWr0alTJyQkeKfEP/zwQyWbE7XkdYJM1ewib3Pg2MUSWO1OWBL0aN4gfLtuSwL91n86v0weprp3UJs6HSfQb/8rf6kcCvOTBQK8C6ul/dOYCYqctDCsGh1oOCzcmSDf2iXWBBGRL0WDoHr16mHUqFFKHjImBbN3mFQU3b5JalDbWoQqUBD01vdHUOEQ6Nu6AXoEsfFpINXd+M4VlmPjoYsAXPVA/ngWVktrz7AmKHLCMRzmb98wSbiDIM4OI6KaKBoELVq0SMnDxazqgyC9/HN3UXT4h8IAIK3yN/Vin9/680ttePen4wCA+66re32X5xCI0ymgrwzoPvn1DIQAeraoFzDTlVnPVVgtYSYocuThsAAzBmsSOAhyDY3mFZajwuFEQh0XNqw6O4yF0UTkjXeMKFRmq9w7rJrCaJvdiT1nIlcUDVT/W//bm46h1OZAx6ZpGNjuijofp0maBTqdq0/SpqiAe68waZuM6kjZAwlrgiInHJmgwgDDYVckm2Ey6OEUrkCorpgJIqKaKBIE1a9fHw0aNKjyp1WrVsjNzcXatWuVaEbMqHbvMI8p8ztO5AOA34LhcPBXBFtqs2PRD66tT+69rk1Y1nkyGfVonOraguFM5Q7iRy+U4JcT+TDodRjaJfCO9Fk+QRAzQZHjLpaPzHCYXq9DU7lQPhxBENcJIqLAFBkOmz9/vt/n8/PzsXXrVgwfPhwffPABbr75ZiWaE9WEENVum2HxyHKcK7ICUCIT5L6RvLflBC6XVqBFgyQM7ZwRtmNl1ktEXqEVp/PL0LVZPTkLlNP2CjRKDbxHlTSEIjFxb6iI8fedCFWgwmgAyExPxLGLpWGpC2ImiIhqokgQNGnSpIA/7969O+bNm8cgCECFQ8hFvr41QXq9DmajXl4Tp2GyqcYgobZ8hz4qHE688Z0rCzRlYOuwbkSZWS8R24/n41R+OYQQXgsk1vhen0UazQkMgiIl0oXRgOe6UeELguolJSC/tII1QURURVTcMYYPH469e/eq3YyoUObxD7XvcBjgnR2KVBYIcP+mXmyzw+kU+PTX0ziVX4YrUkwYc3WzsB4ry2NW0O4zhTh0vgQmox65nZrU+F7fmiBmgiInLSwrRle/ThAQeN2o0I/laucVlTveMxNERL6i4o5htVphMtV9w0QtkOqBDHodEgxVa248A6PIBkGum5QQQJHVjn+udy2OeFdOq7Bv1pqZ7r7xSTvGD76qcbVDJp4y0l2F1RJOkY8c6TtRXuFERS0DihqHw8I4TV4KuBomu/5tYU0QEfmKijvGW2+9he7du6vdjKjguVq0v8JjzyAoEitFSywJBjmrsuqX09iXV4QUsxF39G0Z9mNJN76Tl8vkeqAR3QLPCpMkGNyF1SaDnpvyRlCK2Z29qc2QmBAi6OGwuhZGO50CxTbXsa5IZSaIiPxTpCbokUce8ft8QUEBtm3bhv379+Pbb7+NaBv+/ve/Y9asWZgxY0a1hdrRoLo1giSez7eP0BpBklSLERdLbHj16wMAgAnXtEB6Ys3ZmVBJN77fThdACNdxr7uyUUjvzyu0MgsUYUaDHkkmA0ptDhSVV6BBcmjZ2/IKJ+yV9W7VZ4LCMxxWbLND2p3nCikTZGcQRETeFAmCtm/f7vf5tLQ03HDDDfjwww/RqlWriB1/y5Yt+Ne//oWuXbtG7BjhUlbNlhkSz5ogpYKgc0VWmAx63D0gMtdICoKkm9ZNnTJCGnKTCqs5PT7yUi3GyiAo9EyQNBSm0wHJJv/Xt2lloXuR1Y7C8gq5Din0Y7naZzLo5YDLxiCIiHwoEgStW7dOicP4VVxcjAkTJuCNN97AnDlzVGtHsMqr2TxVIj3fokESks2RvXyev62PvjoLTdIsAV5de/WTEmBJ0Mu7fNe0QKIvqbCamaDIS7UkIK/QWu3GuoFI6wulmI3VDlsmm43ybK7T+WVIy6htECTVHhnl74XVztlhRORN83eNadOmYdiwYRg8eLDaTanWqfwybDp0EZsOXcSOk/kAqg+CpAxJJIuiJVLdhk4HTLm2dcSO49oDzBXIXJFiRr82DUN6v1RYzUxQ5NVlmrwUmNSU3ZGWPajLkJhn7ZFJDoKYCSIib4ruHaa05cuXY9u2bdiyZUuNr7VarbBarfLjwsLCSDZNdq6oHIOeWyfXSkh8F0qUJFU+H8miaIl0sxrSOQOtG6VE9FhZ9RJx+HwJbu7WNOQNYaUAKtyz1qgqfyuJB6umomhJZr1E7D5TiFN1KI72nIUmZYI4HEZEvjQbBJ04cQIzZszA2rVrYbHUPIwzb948PPnkkwq0zNuJS6WwOwUSDDpkN0wG4Joef2e/bL+vH9u7OS6WWDG6Z3jX6vFnYr+WsNodeOymqyJ+rD9e2xoJBj2mDgw94zSg3RX4XYfGQa0rRHVTl1Wjgw2CpLWCzoQtE+QKjpkJIiJfmg2Ctm7dinPnzqFnz57ycw6HA99++y3+8Y9/wGq1wmBwZw5mzZrlNYutsLAQzZs3j3g7pc1S2zRKwRcPDazx9Tltr0BO27pvXBoMJY81qH0jDGof/IwwT0kmI/49uXeYW0T+pJrrPhxW0/pP4VgrqNAjCGImiIiqo9kg6Pe//z127tzp9dxdd92FDh064P/9v//nFQABgNlshtkcmS0oAqlunzCiaKREJigcawV5BlwmFkYTUTU0GwSlpqaic+fOXs8lJyejYcOGVZ5XU1k1O8YTRSN5OxVrXTJBwQVBddk/rIiZICIKAqfTqKymKfFE0UQKYAprMRzmHqIKPBwmLXlwtrBc3kw4VP4zQQyCiMibZjNB/qxfv17tJlQhrxDN4TCKAUrMDmuUaoZRr4PdKXCuqFxeQLE2x0qzGGGuLIxmJoiIfDETpDIOh1EsqVtNUHCF0Qa9Dhnpdds+g+sEEVEwGASprIzDYRRD6rZYojs7UxN3XVDtiqO5ThARBYNBkMrKOTuMYkiaPBxWi0yQNbjCaMBdFxSOTBC3zSCi6jAIUllNu8YTRZNwZIJqGg4D6r6bvOexWBNERNVhEKQyDodRLJECmFKbA3ZHaEFFcZCF0UDdF0z0nI7PmiAiqg6DIJW5C6N5KSj6eQYwoa4VFFImKL32NUFCCLltnsNhdqeo9ZR7ItIm3nlVxpogiiUJBj0slQF7KENi5RUO2CozR6Fkgs4UhJ4JKrE5IMU6aR7rBAEcEiMibwyCVMaaIIo1UianMITiaClg0umAFFMwQZCrJii/tAIlIWecXO1KMOhgNurlTBDAIIiIvDEIUhlrgijW1KY4WgpMUkxG6PW6II6RIB8n1GyQ57CbTqeD0aCHdEjOECMiTwyCVFZW4frNlMNhFCtqs2p0sKtFe8qq5VpB/vYoY3E0EfnDIEhl5VwxmmJMWi1WjQ6lKFpS2xlihX4CLmmaPIMgIvLEIEhl0nAYa4IoVtRlOCyUTFBt1wqSAy6zO+AycdVoIvKDQZDKyjg7jGKMFFzULhMUShAkDYeFGgRVDbi4ajQR+cMgSGXcQJViTW0yQYVBbp7qqbZbZ/gbemMmiIj8YRCkIqdTyP8oMwiiWOGeIh/Zwmh3TVDdC6NZE0RE/jAIUlG5R2qew2EUK1IVLow+U1AGZwgrPfvbrZ6ZICLyh0GQiqSiaABeC7oRRTOlCqObpJqh1wEVDoELxdYQjuVqV4rfmiAGQUTkxjuvijzrgXS6mheQI4oG7nWCQs8EpYUQBBkNemSkuWaIhVIcXeSn/kgKgmwOFkYTkRuDIBVx3zCKRWm1yQRZQy+MBmpXF+R/nSAOhxFRVQyCVFRmY1E0xZ66rBidYg4+EwTUbiPVQLPDOBxGRJ4YBKnIvXkqLwPFjpQ6FUbXLgiq3XBY1dlhzAQRkSfefVXEHeQpFknBRYnNAUeQs7b81ekEozarRvudHWZgJoiIqmIQpCLuIE+xyDPDUhzkkJi/Op1gZKaHVhMkhECxtepwmDmBQRARVcUgSEUsjKZYZDYa5BqbwiCGxKx2hzwMlVbrwujgMkGlHtmpVL+ZIM4OIyI3BkEq4nAYxapQZoh5viYlxEyQtHXGxRKb/EtDMMcy6HVeGVYpE8SaICLyFNq/SBRWHA6jWJVqScCFYht+OHgB54oCD1WdK3ItdJhsMsCgD209rLREI5JNBpTYHFj1y2k0TjUHfP2ZgvLK9hm91t4yGbhtBhFVxSBIRdw8lWJVWqJrWOuZz/cE/Z70xNCGwgBAp9Mhq34i9ucVY+YHv9b6WMwEEZE/DIJUxJogilVTr22Nhd8egkMENztMBx3G9Wleq2Pdf11b/PuHI3CGcKw7+rbweo6zw4jIHwZBKpKGw1gTRLFmWNemGNa1qSLHuqVHFm7pkVWnz3BnglgYTURuLIxWEYfDiJTBTBAR+cMgSEVyEGTiZSCKJHMCV4wmoqp491VROTNBRIpgJoiI/GEQpCLWBBEpg7PDiMgfBkEqKuPsMCJFmLliNBH5wSBIRWUVrt9KORxGFFnMBBGRPwyCVFTOFaOJFMEVo4nIHwZBKpL3DuNwGFFEMRNERP4wCFIR1wkiUgZnhxGRPwyCVMThMCJlmIzMBBFRVQyCVMTZYUTKMEtBkMMJpzO4PciISPsYBKmkwuGEvfIfY64TRBRZUiYIcAVCREQAgyDVSFkggMNhRJFmNrr/H2NdEBFJGASpRKoHMuh1SDDoVG4NkbZ5/j/GuiAikjAIUonnzDCdjkEQUSTpdDq5LoirRhORhEGQSuQ1gjgURqQIzhAjIl8MglQibZ6aaOIlIFKCVBfEwmgikvAOrBIulEikLHk4rIJBEBG5MAhSSTmDICJFea4VREQEMAhSTZnN9Q8xa4KIlGFiJoiIfDAIUglXiyZSljsTxNlhROTCIEglrAkiUhYzQUTki0GQSrh5KpGyODuMiHwxCFKJvE4Qh8OIFMFMEBH5YhCkEg6HESlLniLPTBARVWIQpBJOkSdSljsTxMJoInLRbBA0b9489O7dG6mpqWjcuDFuueUW7Nu3T+1myco5O4xIUVwniIh8aTYI2rBhA6ZNm4Yff/wRa9euRUVFBW688UaUlJSo3TQA7m0zuE4QkTJYE0REvoxqNyBSvvjiC6/HixcvRuPGjbF161YMHDhQpVa5sSaISFmcHUZEvjSbCfJVUFAAAGjQoIHKLXEpq/xtlBuoEimDmSAi8qXZTJAnp9OJhx56CDk5OejcubPf11itVlitVvlxYWFhRNvEdYKIlMUVo4nIV1ykIaZNm4bffvsNy5cvr/Y18+bNQ3p6uvynefPmEW2TvE4QgyAiRTATRES+NB8ETZ8+HZ9++inWrVuHZs2aVfu6WbNmoaCgQP5z4sSJiLaLQRCRslgTRES+NDscJoTAAw88gI8++gjr169Hq1atAr7ebDbDbDYr1Dr37DAOhxEpg5kgIvKl2SBo2rRpeOedd7By5Uqkpqbi7NmzAID09HQkJiaq3DquE0SkNK4TRES+NDsc9vrrr6OgoADXXXcdmjZtKv9ZsWKF2k0DwCnyREqTt82wszCaiFw0mwkSQqjdhGoJIVgTRKQwk6EyE2RnJoiIXDSbCYpmVrsTUozG4TAiZZgTpEwQgyAicmEQpIJyjw0cLUZeAiIlmAyVs8MYBBFRJd6BVSANhZkMehgNvARESmAmiIh88Q6sAvfmqTz9REphTRAR+eJdWAVlnB5PpDhmgojIF4MgFZRzejyR4qRMEKfIE5GEQZAKymyu30Q5PZ5IOeYEFkYTkTcGQSrgcBiR8tyZIGdUryNGRMphEKQCrhZNpDyzx0SECgeDICJiEKSKcm6eSqQ4k8dyFKwLIiKAQZAq5C0zOBxGpBizx8KkrAsiIoBBkCo4HEakPJ1O51UXRETEIEgFZRwOI1KFlA1iJoiIAAZBqijn7DAiVZiMzAQRkRuDIBXINUHMBBEpipkgIvLEIEgFHA4jUoc7E8TZYUTEIEgV7sJonn4iJZmNXDWaiNx4F1YBa4KI1MGaICLyxCBIBawJIlKHmUEQEXlgEKQC1gQRqYM1QUTkiUGQCsoqXL+FcjiMSFmcHUZEnhgEqaCcK0YTqYI1QUTkiUGQCqThMNYEESmLs8OIyBODIBWUcXYYkSqYCSIiTwyCVMANVInUwZogIvJkVLsB8cbhFPI/wAyCiJQlZYJ2nS7Aql9Oq9waIkrQ6zCkS1PVjs8gSGFSUTTA4TAipSVV/j+3Znce1uzOU7k1RJRqNjIIiidOIXBtuytQXuGQU/NEpIzRPZthf14xisvtajeFiOD+xUQtOiGEULUFUaqwsBDp6ekoKChAWlqa2s0hIiKiIIRy/2YqgoiIiOISgyAiIiKKSwyCiIiIKC4xCCIiIqK4xCCIiIiI4hKDICIiIopLDIKIiIgoLjEIIiIiorjEIIiIiIjiEoMgIiIiiksMgoiIiCguMQgiIiKiuMRd5Ksh7StbWFiockuIiIgoWNJ9O5j94RkEVaOoqAgA0Lx5c5VbQkRERKEqKipCenp6wNfoRDChUhxyOp04ffo0UlNTodPpQnpvYWEhmjdvjhMnTiAtLS1CLVQe+xVbtNqvUGn1PGi1X4Fotc9a7VeownUehBAoKipCZmYm9PrAVT/MBFVDr9ejWbNmdfqMtLQ0TX6h2a/YotV+hUqr50Gr/QpEq33War9CFY7zUFMGSMLCaCIiIopLDIKIiIgoLjEIigCz2YwnnngCZrNZ7aaEFfsVW7Tar1Bp9TxotV+BaLXPWu1XqNQ4DyyMJiIiorjETBARERHFJQZBREREFJcYBBEREVFcYhBEREREcYlBEMnsdrvaTaAQ8HppG6+vdvBaRi8GQSEqLi5GQUEBgOA2Z4sFp0+fRp8+ffD444+r3ZSw0uK1ArR7vULF66sdvJbaVlhYiLy8PACuLamiCYOgEPzv//4vOnfujI8++ggAQt5TLBo9/PDDyM7ORkZGBqZPn652c8JGi9cK0O71ChWvr3bwWmrbnDlz0LZtW/zjH/8AgBr38lIa9w4LwqVLlzBz5kxs374dAPD5558jJycH7dq1gxAiJv+nPX78OPr16weLxYLvv/8effr0UbtJYaHFawVo93qFitdXO3gtta24uBgzZ87ETz/9hOzsbPz888/44YcfkJOTE1XXl0FQNTwvkt1uR9OmTTFq1CgkJiZi4sSJ+PLLL5GdnY2EhASVW1o7RqMRWVlZaNOmDfr06YNt27Zh+fLlyMjIQNeuXTFgwABYLBa1mxkUrV8rQFvXK1S8vtq5vryW2rmW/nheX7PZjBYtWmDgwIFo1aoVpk+fjo8++gg9e/ZEYmJi9ARCgqqwWq2ivLxcflxRUSHy8vLkx5MnTxb9+/cXP/30kxrNqxWn0ymEcPVFsnr1aqHT6cSNN94oWrRoIW6++WbRpUsX0bhxY3HvvffK74lmWrxWQmj3eoWK11c715fXUjvX0p+ysjJRWFgoP3Y6naKgoEB+PHv2bNG3b1/x4YcfqtG8ajEI8vHEE0+I3r17i9zcXPGvf/1LXLx4Uf6Zw+EQQghx8uRJ0bJlS/GXv/xFXL58WQghovpL/corr4jHH39cfiy1tbi4WNx7772iV69e4qeffhKlpaVCCCEWLFggunXrJv7v//5PlfYGS4vXSgjtXq9Q8fpq5/ryWmrnWvrz+OOPi6uuukr0799f/OUvfxGnT5+WfyZd37y8PDFo0CAxadIkcerUKSFEdFxfBkGVKioqxMSJE0Xbtm3FkiVLxPjx40WnTp3EsGHDvF5nt9uFEEI8/fTTokOHDmL16tXyz6LhgnrasWOHyM3NFTqdTnTp0kV8/fXXQgh3H4QQYv/+/WLTpk3C4XDIX9aLFy+K3NxcMX36dK/XRgstXishtHu9QsXrq53ry2upnWtZnenTp4u2bduK999/XzzyyCOiW7duonfv3qKoqEh+jdTXN954Q/Ts2VO8/vrr8s/Uvr4MgiodPnxYdOjQQaxatUp+bs2aNSIxMVG89NJL8nPSl9npdIpu3bqJ//mf/xGHDx8WH3/8sXj11VcVb3cgL774ohgxYoRYsmSJGDp0qJg4caKcsvXshyfp+SuvvFJMnTpV2QYHSYvXSgjtXq9Q8fq6xfr15bV0i/Vr6cvpdIrz58+L7t27i3/961/y8wcOHBANGzYUDz/8sCgpKRFCuPsuhBCjRo0St9xyi9i2bZv44IMPxN/+9jfF2+6JQVClffv2CZ1OJ44dO+b1/Ny5c0W9evW8npei2vfee080atRItGjRQhiNRvHKK68o2uaanDlzRmzYsEEIIcT8+fPFNddcIxYvXiyECBx9f/XVV6J3797ihx9+UKSdodLitRJCu9crVLy+3mL5+vJaeovla+nP2bNnhV6vF9u2bRNCuOuili5dKkwmk3yOhHAHQmvXrhVt27YVDRs2FAkJCeKpp55SvuEeGARV2r17t+jevbt47rnnvJ4vKCgQrVu3Fo888ogQwv0/6tGjR8W9994rdDqduOuuu7zGuKPRiRMnxJgxY8SwYcPE2bNnhRDe0fnu3bvF+vXrxYMPPijq168vHn74YWGz2dRqbkBav1ZCaOt6hYrXVzvXl9dSO9fSn8uXL4trrrlGPPDAA0II7wDw6quvFuPHjxdCuM/H0aNHxdSpU6Pq+sZNEFTTuGNxcbEYO3asGD16tDhy5IgQwn3hnn/+edGiRQtRVlYmv/7hhx8WGRkZqs5kCHYsVerHO++8I/r16yeeeeaZKq959913xQ033CAGDBggfvzxx7C2M9xi8VqFQmvXK1S8vtq5vryW2rmW/litVjFz5kzRt29fsXPnTvk5IVwZvcTERK8ZYk8//bRo1KhRVF3fuAiC8vPzRWFhoRw0eEbpntMa3333XdG1a1fx7LPPer1/4cKFonPnzl6pW8+iLzUE2yfPx6WlpeKee+4RgwYNEr/88osQQshfxuLiYrF//34lmh7QuXPnxOHDh+X/cbRwrYQIvl+ej2PheoXqxIkT4j//+Y+4dOlSlZ/F8vUNtl+ej2P9+h46dEhMmzZNbNmypcrPYvlaBtsvz8exfi39OXLkiJg4caJYsWJFlZ95nodvvvlG9O/fX9x7771er1m9erVo2bKl2Lp1a8TbWhfRtX51mAkh8NBDD2HQoEG46aabcOedd6KoqAh6vR4VFRUAXAtbORwOLFu2DOPGjUP//v3x0Ucf4dNPP5U/58KFC6hXrx6ysrLk51JSUhTvDxB8n4QQWLJkifzY6XQiMTERY8eOhdFoxNy5czFkyBBcc801OH36NJKTk9GuXTtV+iT168EHH0Tv3r0xevRo9OrVCwcPHoRer4fD4ZD7EUvXCgi+X7F2vWrjxIkT6NGjByZOnIiff/5Zfj6Wry8QXL+0dH2FELjvvvvQtm1blJWVoWPHjl4/A2LzWgbbLy1dy+o88cQTuOqqq1BSUoKEhAR5A1jP8+B0OvHqq6/i+uuvx8iRI7Fu3Tr8+9//lj/j2LFjaNCggdd5jEqqhF4K2LRpk+jWrZvo27ev+Oyzz8STTz4pOnToIMaOHev1uoULF4rGjRuLG2+8UdhsNrFnzx5x9913C6PRKO677z4xffp0kZ6eLs9QUHM6X6h9Gjp0qNdiZEK41mro1KmT0Ol0YtSoUeLo0aNKdsGvr7/+WnTq1En069dPrFu3TqxevVoMGDBA3HjjjV6vi6VrJUTo/YqV61VbZ86cESNHjhQtW7YUN910U5W+xtr1lQTbLy1c35UrV4oGDRqInj17ip9//tnrZ57XI9auZaj90sK1rM727dtFTk6OWLlyZbWveeONN0STJk1E7969RUFBgThz5oyYPXu23PepU6eK1NRUMWfOHOFwOFS/voFoMgiy2+1i5syZYvz48V7p1RUrVohWrVrJxWtvv/22aN68uXjrrbeqpDlfeOEFMXXqVJGbmyuvAaGm2vTJdx2KTZs2iQYNGogOHTqI77//XtH2B/Lss8+KWbNmefXrueeeEzfffLM8bLR48eKYuVaSUPsVK9ertlavXi1Gjhwpjh07JnQ6nVi0aJFcP7Bo0SLRrFmzmLq+kmD7pYXrO2XKFJGdnS0HCtu3bxcrVqwQ27dvl1cLXrJkScxdy1D7pYVrWZ1p06aJIUOGCCGE+OGHH8SMGTPE888/LzZv3iyEcM1w69q1q3jzzTernIe3335bzJw5U/zhD3+IqusbiGaCIM8aC7vdLlavXu01PU8I1w2nY8eOXkt7e/63EOr/RuIpXH2SFBcXi6VLl0amsSHw7JcQrgXEPOsCzp07J/r06SMeeugh8dFHH8nP+9YLRNO1EiJ8/ZJEy/UKled58PzvjRs3itGjRwshhJgwYYK46qqrRElJiTxTRlpVVxLN17cu/ZLEwvX1/U7v379fDBw4UEyePFmMGjVKZGdni+7du4sGDRqI66+/Xu5rrP2/Wtt+SWLhWvrje4+x2+3irrvuEnPmzBH/+Mc/REZGhrj99ttF9+7dRUZGhpg/f74QQngVs/t+TqzRRBD05JNPismTJ4unnnpKXLhwocrPpWj1xRdfFDk5OcLpdEbd/5S+wt2naOlvTf1asWKF0Ov1IicnR4wePVo0aNBA3HHHHVGfWg53v6LleoUq0HlYsGCBGDp0qPw4MTFR5OTkiMzMTPHdd98p3dSQhLtfsXB9ffss3ejmzZsnmjZtKm699Vaxbds2ceDAAbFp0ybRqFEjMWXKlCo3yGgT7n7FwrX0x/c8SP0YP3686N27txg/frxYuXKl/PyMGTPEgAEDxJdffimEiN1++4rpIOj48eOiZ8+eokuXLmLatGkiIyND9OrVS7z//vtCCHd0Kv09cuRI8f/+3/8TQkTvBdRin4SouV+Sr776yivb9fPPPwuLxSK++uorpZscFK32K1TBnIennnpKrgFZtWqVSE1NFQaDQTz//PNqNbtGWu1XINX1efny5UIIVzbkueeeqzLjSZoSLdXKRNu/R1rtV6hqOg8//vijSEhIEMnJyWLv3r3y+/bv3y+6d+8uLwqpFTEdBC1evFh0795d5OfnCyFcKckRI0aIAQMGiB07dggh3MFCaWmpaNGihddNZ/fu3co3ugZa7JMQwfXLn5KSEmGxWMTChQuVampItNqvUAU6D9IU2Yceekhcd911YuDAgaJ+/fpi/vz5Ijs7W/zxj3+U3xdttNqvQAL1WVoZ2N+Q+7fffisSExOrDNlHC632K1TVnYecnBx5ev8dd9wh0tPTq9Q3ZWVliXnz5ine5kiK6SnyR48eRUJCApKTkwEAycnJ+NOf/gSz2Yxnn30WAKDXu7r43XffQa/Xo3///ti9ezeuv/56XH311Th79qxq7fdHi30CguuXP8uXL0fPnj0xbNgwpZoaEq32K1SBzsMLL7wAAKhfvz5+++03tG/fHlu2bMGMGTPw6quv4q233sLmzZvVbH61tNqvQAL1+fnnnwcApKamVnnf2rVr0b9/f/Tv31/R9gZLq/0KVTD/Zs2ePRtGoxH/93//hx07dgAANmzYgGbNmmnm3yxJTAdB5eXlMBqNOHfunPzcwIEDMWTIEOzZswdfffWV/PzOnTuRkZGBxx9/HF27dkVmZiby8vKQkZGhRtOrpcU+AaH168CBAzh48CCmT5+OWbNmYfTo0WjatKkaza6RVvsVqkDn4bfffsPmzZtx7733YsOGDVi4cCHatGkDABg+fDheeeUVDBo0SK2mB6TVfgUSynd6//79OHToEKZPn4633noLEydOlNfSiTZa7VeoqjsPQ4cOxa5du/DVV1+hffv2eOutt7Br1y4MHjwYI0aMwNChQ5GTkxP96/6ESu1UVG1Iw0F79uwROp3Oa6aNEELs2LFDXHPNNeLvf/+7/Nzvfvc7odPpxLXXXhuVK1hqsU9ChN6vS5cuib/+9a+iVatWIicnJ+CQkpq02q9QBXMe+vTpU2W1YCFElem10USr/Qok1O/0xYsXxZ///GfRtGlTr6GUaKPVfoUq2PPgOdx19OhRsWLFCjFv3jx5WwytidogaP/+/eKtt94SJ0+erPIzz7UnxowZI3r06CHOnz/v9RrPTd0cDod49913Ay7+pAQt9kmI8PRr+vTp8uNdu3ZFxS7LWu1XqML5vY2molKt9iuQcH+nf/nll6ioldFqv0IVj9/puoq64TC73Y777rsPXbp0wU8//eRV3+J0OgG4luy22Ww4ePAgXnjhBezduxcvv/wyCgoK5M8wm82oX78+AFcNzbhx4zBixAjlOwRt9klqU7j61aBBA/m9HTt2VHX8Xav9ClUkvrc6nU75jvjQar8CidR3umvXrhg4cKCynfGg1X6FKh6/02GjdhTm67HHHhM5OTlVdpn1jEoXLFggkpKS5FT0woULRdu2bUVubq5YuXKlePjhh0XTpk2jZqdaLfZJCPYr1voVKq2eB632KxCt9lmr/QoVz0PtRU0Q5HQ6RV5enujRo4dYtWqVEEKILVu2iBUrVojffvtNlJSUCCGE+OMf/ygaN24sli5d6rVK5SeffCKGDh0q+vXrJ3r16iV+/PFHVfrhSYt9EoL9irV+hUqr50Gr/QpEq33War9CxfNQd1ERBEnR6tatW0WjRo1EYWGhuO+++0RWVpbo2bOnyMzMFOPHjxdCCLFv3z5RUFAgv9d3uW5pDy21abFPQrBfQsRWv0Kl1fOg1X4FotU+a7VfoeJ5CA/VgqD3339frF27Vpw+fVp+bs+ePeLqq68W9957r7j55pvFvn37xIkTJ8Snn34qTCaTWLBggRAiemdfaLFPQrBfsdavUGn1PGi1X4Fotc9a7VeoeB7CT/Eg6O233xaNGzcWffr0EY0aNRI5OTniv//9rxBCiMOHD4shQ4aI+vXryxXqkv/93/8VGRkZSjc3KFrskxDsV6z1K1RaPQ9a7VcgWu2zVvsVKp6HyFFsdpjdbseCBQswb948zJ07F9999x0+/vhjtGnTBm+++SbKysrQqlUrDB48GPn5+SgvLwfgrmzv2LEjkpOTcfDgQaWaXCMt9glgv2KtX6HS6nnQar8C0WqftdqvUPE8RJ5iQVBJSQnOnz+PSZMm4a677oLJZEL//v3RsWNHFBYWoqKiAgBw991345ZbbsGnn36K7du3y1tE/Prrr+jSpQvatm2rVJNrpMU+AexXrPUrVFo9D1rtVyBa7bNW+xUqngcFRDLNtH//fq8petu3b5fHJaXCrGXLlonu3bsLq9Uqv27Tpk3ipptuEqmpqeL+++8Xd9xxh2jUqJFYtmyZEELdRZy02Cch2K9Y61eotHoetNqvQLTaZ632K1Q8D8qKSBC0YsUKkZ2dLa688krRp08f8eabb3r93LMy/fbbbxeTJ08WQghhs9nk5ysqKsRTTz0lpk6dKsaOHSv27t0biaYGTYt9EoL9EiK2+hUqrZ4HrfYrEK32Wav9ChXPgzrCHgStWbNGZGdni9dee0188cUX4pFHHhEJCQli4cKFoqysTAjhikidTqcoKysTXbt2FUuXLq3286IhetVin4Rgv2KtX6HS6nnQar8C0WqftdqvUPE8qCdsQZB00p988klx9dVXe0Wn999/v+jVq5f48MMPvd5z6tQpkZ2dLfbv3y+EcKUBH3744XA1qc602Cch2C9PsdCvUGn1PGi1X4Fotc9a7VeoeB7UF7bCaGmfkd27d6NNmzZISEiQi7bmzJkDi8WClStXeu1p8tVXX6F58+Zo2rQpZsyYgY4dO+LYsWOoqKiAECJcTas1LfYJYL9irV+h0up50Gq/AtFqn7Xar1DxPESB2kZPa9asEQ888IB4+eWXxebNm+XnFy5cKFJTU+VCLimyXbhwoWjfvr1Yt26dEMIVAY8ZM0bUr19fNGzYUHTq1Els2bKlts0JCy32SQj2K9b6FSqtnget9isQrfZZq/0KFc9D9Ak5CDp9+rQYPny4aNy4sZgwYYLo0qWLSE9Ply/ovn37RFZWlpg9e7YQQnhVr2dkZIiXX35ZCCFESUmJGD58uGjWrJlYvnx5GLpSe1rskxDsV6z1K1RaPQ9a7VcgWu2zVvsVKp6H6BVSEFR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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Count selected assets by day.\n", - "universe_size = universe_history.groupby(level=[0, 1]).count().amount.groupby(level=0).count()\n", - "print(f\"Universe days: {len(universe_size)}\")\n", - "# Store the selected symbol list.\n", - "unique_assets = list(universe_history.index.levels[1].unique())\n", - "print(f\"Mean basket size per day: {universe_size.mean():.1f}\")\n", - "print('')\n", - "print(universe_history.amount.describe())\n", - "universe_size.plot(title='Daily Universe Size', ylabel='Universe Size');" - ] - }, - { - "cell_type": "markdown", - "id": "e9f0a1b2", - "metadata": {}, - "source": [ - "### Daily Universe Prices\n", - "\n", - "Fetch daily price history for every symbol that appears in the universe." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "c3d4e5f6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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closehighlowopenvolume
symboltime
EW RTKJ7O7ZTI792026-02-0382.6582.89081.30581.443778612.0
2026-02-0482.1083.77082.00082.383389435.0
2026-02-0579.7781.97079.64581.486115515.0
2026-02-0678.1080.65077.46579.876984869.0
2026-02-0778.7178.84577.44078.356475687.0
.....................
CAH R735QTJ8XC9X2026-05-23200.68202.410199.730201.981323710.0
2026-05-27200.37201.430199.480200.001679645.0
2026-05-28199.84201.400199.310200.591403589.0
2026-05-29199.85201.790197.635199.541914690.0
2026-05-30196.80201.510196.200201.352693424.0
\n", - "

2505 rows × 5 columns

\n", - "
" - ], - "text/plain": [ - " close high low open volume\n", - "symbol time \n", - "EW RTKJ7O7ZTI79 2026-02-03 82.65 82.890 81.305 81.44 3778612.0\n", - " 2026-02-04 82.10 83.770 82.000 82.38 3389435.0\n", - " 2026-02-05 79.77 81.970 79.645 81.48 6115515.0\n", - " 2026-02-06 78.10 80.650 77.465 79.87 6984869.0\n", - " 2026-02-07 78.71 78.845 77.440 78.35 6475687.0\n", - "... ... ... ... ... ...\n", - "CAH R735QTJ8XC9X 2026-05-23 200.68 202.410 199.730 201.98 1323710.0\n", - " 2026-05-27 200.37 201.430 199.480 200.00 1679645.0\n", - " 2026-05-28 199.84 201.400 199.310 200.59 1403589.0\n", - " 2026-05-29 199.85 201.790 197.635 199.54 1914690.0\n", - " 2026-05-30 196.80 201.510 196.200 201.35 2693424.0\n", - "\n", - "[2505 rows x 5 columns]" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Extract unique assets\n", - "symbols = list(universe_history.index.get_level_values(1).unique())\n", - "# Fetch daily historical price metrics using the earliest timestamp available in the index.\n", - "history = qb.history(symbols, universe_history.index[0][0] - timedelta(1), qb.time, Resolution.DAILY)\n", - "history" - ] - }, - { - "cell_type": "markdown", - "id": "a7b8c9d0", - "metadata": {}, - "source": [ - "### Align Contract Volume And Returns\n", - "\n", - "Build a joined table of contract dollar volume and future returns." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "3d56c7cd", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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dollarvolumefuturereturn
timesymbol
2026-02-03EW RTKJ7O7ZTI79270500.000.000491
2026-02-04DNOW VR22RBI5MBFP159.250.020526
EW RTKJ7O7ZTI7934000.00-0.030469
MCK R735QTJ8XC9X500000.000.023437
SYK R735QTJ8XC9X28667.94-0.013924
\n", - "
" - ], - "text/plain": [ - " dollarvolume futurereturn\n", - "time symbol \n", - "2026-02-03 EW RTKJ7O7ZTI79 270500.00 0.000491\n", - "2026-02-04 DNOW VR22RBI5MBFP 159.25 0.020526\n", - " EW RTKJ7O7ZTI79 34000.00 -0.030469\n", - " MCK R735QTJ8XC9X 500000.00 0.023437\n", - " SYK R735QTJ8XC9X 28667.94 -0.013924" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dataset = (\n", - " universe_history.groupby(level=[0, 1]).agg(dollarvolume=('amount', 'sum')).rename_axis(['time', 'symbol'])\n", - " .join(history.open.unstack('symbol').sort_index().pct_change(2, fill_method=None).shift(-2).stack().rename('futurereturn').rename_axis(['time','symbol']), how='inner')\n", - ")\n", - "dataset.head()" - ] - }, - { - "cell_type": "markdown", - "id": "c5d6e7f8", - "metadata": {}, - "source": [ - "### Analyze Relationships Between Factor and Future Returns\n", - "\n", - "Create a box plot of dollar-volume quantile buckets compared to future returns." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "c7d8e9f0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Factor: dollarvolume\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
 bucketmean_factormin_future_returnmax_future_returnmean_future_returnstd_future_returnobservations
0(-0.001, 20310.492]6348.423-18.21%10.21%-0.20%3.89%52
1(20310.492, 36988.0]33767.580-9.29%13.13%0.11%3.57%51
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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "factor = 'dollarvolume'\n", - "# Split factor values into quantile buckets.\n", - "x = dataset[factor]\n", - "y = dataset['futurereturn']\n", - "buckets = pd.qcut(x, q=5, duplicates='drop')\n", - "# Summarize each bucket with distribution statistics.\n", - "summary = dataset.assign(bucket=buckets).groupby('bucket', observed=True).agg(\n", - " mean_factor=(factor, 'mean'),\n", - " min_future_return=('futurereturn', 'min'),\n", - " max_future_return=('futurereturn', 'max'),\n", - " mean_future_return=('futurereturn', 'mean'),\n", - " std_future_return=('futurereturn', 'std'),\n", - " observations=('futurereturn', 'size')\n", - ").reset_index()\n", - "summary['bucket'] = summary['bucket'].astype(str)\n", - "# Display the bucket summary.\n", - "print(f\"Factor: {factor}\")\n", - "display(summary.style.format({\n", - " 'mean_factor': '{:.3f}',\n", - " 'min_future_return': '{:.2%}',\n", - " 'max_future_return': '{:.2%}',\n", - " 'mean_future_return': '{:.2%}',\n", - " 'std_future_return': '{:.2%}'\n", - "}))\n", - "# Plot the return distribution for each bucket.\n", - "groups = [y[buckets == b].values for b in buckets.cat.categories]\n", - "plt.boxplot(groups, labels=[str(b) for b in buckets.cat.categories])\n", - "plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", - "plt.title(f'Future Return by {factor} Bucket')\n", - "plt.xlabel(f'{factor} Bucket')\n", - "plt.ylabel('Future Return')\n", - "plt.xticks(rotation=45)\n", - "plt.show()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Foundation-Py-Default", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.14" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From adeac5d6ac2df124f1653afd6394e8f691885715 Mon Sep 17 00:00:00 2001 From: Rudy Osuna Date: Tue, 2 Jun 2026 15:00:31 -0700 Subject: [PATCH 10/16] fix --- .../research.ipynb | 774 ++++++++++++++++++ 1 file changed, 774 insertions(+) create mode 100644 project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb diff --git a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb new file mode 100644 index 0000000000..58c092fedd --- /dev/null +++ b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb @@ -0,0 +1,774 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "a1b2c3d4", + "metadata": {}, + "source": [ + "![QuantConnect Logo](https://cdn.quantconnect.com/web/i/icon.png)\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "e5f6a7b8", + "metadata": {}, + "source": [ + "## Quiver Government Contracts Research\n", + "\n", + "This notebook studies whether government contract dollar volume helps explain future returns" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "c9d0e1f2", + "metadata": {}, + "outputs": [], + "source": [ + "qb = QuantBook()\n", + "# Daily bars will have an end_time that matches the following midnight.\n", + "qb.settings.daily_precise_end_time = False\n", + "# Anchor the research clock to the start of 2026.\n", + "qb.set_start_date(2026, 1, 1)" + ] + }, + { + "cell_type": "markdown", + "id": "a3b4c5d6", + "metadata": {}, + "source": [ + "### Build a Government Contract Universe\n", + "\n", + "Select assets with frequent, sizable US government contracts, then inspect the returned universe history." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "e7f8a9b0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Shape: (580, 5)\n", + "Columns: ['agency', 'amount', 'description', 'time', 'value']\n" + ] + }, + { + "data": { + "text/html": [ + "
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agencyamountdescriptiontimevalue
timesymbol
2025-10-04DNOW VR22RBI5MBFPGeneral Services Administration138.6678C10M02025-10-04138.66
DNOW VR22RBI5MBFPGeneral Services Administration346.6578C10M02025-10-04346.65
DNOW VR22RBI5MBFPGeneral Services Administration452.85CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...2025-10-04452.85
DNOW VR22RBI5MBFPGeneral Services Administration905.70CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...2025-10-04905.70
DNOW VR22RBI5MBFPGeneral Services Administration374.20CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...2025-10-04374.20
\n", + "
" + ], + "text/plain": [ + " agency amount \\\n", + "time symbol \n", + "2025-10-04 DNOW VR22RBI5MBFP General Services Administration 138.66 \n", + " DNOW VR22RBI5MBFP General Services Administration 346.65 \n", + " DNOW VR22RBI5MBFP General Services Administration 452.85 \n", + " DNOW VR22RBI5MBFP General Services Administration 905.70 \n", + " DNOW VR22RBI5MBFP General Services Administration 374.20 \n", + "\n", + " description \\\n", + "time symbol \n", + "2025-10-04 DNOW VR22RBI5MBFP 78C10M0 \n", + " DNOW VR22RBI5MBFP 78C10M0 \n", + " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", + " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", + " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", + "\n", + " time value \n", + "time symbol \n", + "2025-10-04 DNOW VR22RBI5MBFP 2025-10-04 138.66 \n", + " DNOW VR22RBI5MBFP 2025-10-04 346.65 \n", + " DNOW VR22RBI5MBFP 2025-10-04 452.85 \n", + " DNOW VR22RBI5MBFP 2025-10-04 905.70 \n", + " DNOW VR22RBI5MBFP 2025-10-04 374.20 " + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def select_assets(data: List[QuiverGovernmentContractUniverse]) -> List[Symbol]:\n", + " # Group by ticker and keep names with 3+ contracts totalling over $50K.\n", + " contracts_by_symbol: dict[Symbol, list[QuiverGovernmentContractUniverse]] = {}\n", + " for d in data:\n", + " contracts_by_symbol.setdefault(d.symbol, []).append(d)\n", + " return [s for s, ds in contracts_by_symbol.items()\n", + " if len(ds) >= 3 and sum(x.amount or 0 for x in ds) > 50_000]\n", + "\n", + "# Add the Quiver Government Contract universe.\n", + "universe = qb.add_universe(QuiverGovernmentContractUniverse, select_assets)\n", + "# Request universe history of the last 90 days.\n", + "universe_history = qb.universe_history(universe, qb.time - timedelta(90), qb.time - timedelta(1), flatten=True).rename_axis(['time', 'symbol'])\n", + "# Print the returned shape and columns.\n", + "print(f\"Shape: {universe_history.shape}\")\n", + "print(f\"Columns: {list(universe_history.columns)}\")\n", + "universe_history.head()" + ] + }, + { + "cell_type": "markdown", + "id": "c1d2e3f4", + "metadata": {}, + "source": [ + "### Universe Diagnostics\n", + "\n", + "Inspects the raw contract amount distribution and visualizes how the daily universe size evolves chronologically." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a5b6c7d8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Universe days: 19\n", + "Mean basket size per day: 2.6\n", + "\n", + "count 580.000\n", + "mean 20138.930\n", + "std 105049.143\n", + "min 0.000\n", + "25% 259.200\n", + "50% 618.250\n", + "75% 1741.500\n", + "max 1776510.800\n", + "Name: amount, dtype: object\n" + ] + }, + { + "data": { + "image/png": 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sbr/yyito0aIFBg4cqFNERERENVdQaIUhQKnScRtUNX673GYrPz8fH330ESZPnlzum8tsNsNkMtl9EREReYI8SyH+9K8tmLR4t96h+BQmSQC+/PJLXLt2DZMmTSr3MfPmzUN0dLT2lZCQ4L4AiYiIKnDm2nWkX8nF1uMXYSm06h2Oz2CSBOCDDz7A0KFD0ahRo3IfM2vWLGRmZmpfp06dcmOERERE5cuzFNXYigAZWWado/EdfluTpDp58iQ2bNiAVatWVfg4o9EIo9HopqiIiIiqLs9SMnt0PjMP8XVCdYzGd/j9TNLixYsRGxuL4cOH6x0KERFRjZgtJbu1M0x5OkbiW/w6SbJarVi8eDEmTpyIwEC/n1QjIiIvlVdQkiSdZ5LkNH6dJG3YsAHp6emYPHmy3qEQERHVmN1yG5Mkp/Hr6ZMhQ4ZARPQOg4iIqFbybJbbLmQySXIWv55JIiIi8gWcSXINJklERERezm4mycQWAM7CJImIiMjL2RZuXzDlsZTESZgkEREReTmzzXJbbn4hsswFOkbjO5gkEREReTnbmSSAxdvOwiSJiIjIy9nOJAEs3nYWJklERERezrZwGyg6moRqj0kSERGRlyudJF3gTJJTMEkiIiLycmqfpLphQQDYBsBZmCQRERF5ObVwu2n9cACsSXIWJklEREReTl1uS6wfBoDLbc7CJImIiMjLqctt2kwSC7edgkkSERGRl9Nmkm4omkm6lG1GQaG1om+hKmCSRERE5OXMBUUJUaPoUBgCFFgFuJjN4u3aYpJERETk5dSZpLDgQMRGGgFwh5szMEkiIiLycmqSFBIUgAZRIQBYl+QMTJKIiIi8nFq4HRJkQFxxksQdbrXHJImIiMiLiYjWJ8kYFIC46OKZJCZJtcYkiYiIyIvlF1ohUvT/IUEGbbntApfbao1JEhERkRdTl9oAwBgYgLjoosJtziTVHpMkIiIiL2YuLtpWFCDYEIAGkaxJchYmSURERF5M7ZEUEmiAoihoEK0mSWwBUFtMkoiIiLyY7fZ/ANrutmxzAbLNBbrF5QuYJBEREXkx2+3/ABBuDESkMRAAeyXVFpMkIiIiL6Zu/1eTJAA2S25MkmqDSRIREZEXU5fbjIElv9Lj2HXbKZgkERERebHSy20AEBtVfH5bFpOk2mCSRERE5MVKF24DJTNJbChZO0ySiIiIvFhJklQyk8SjSZyDSRIREZEXy7Ppk6RSjyY5z15JtcIkiYiIyIuZudzmMkySiIiIvFhFy20Xs80otIoucfkCJklERERezNHutvrhwQhQgEKr4HI2l9xqikkSERGRF9P6JNkstwUaAhATWdQGgMXbNcckiYiIyItpHbdtCrcBNpR0BiZJREREXszRchtQssONR5PUHJMkIiIiL+boWBKAvZKcgUkSERGRF6tsJul8Jgu3a8qvk6QzZ87gr3/9K+rXr4/Q0FB07NgRv/zyi95hERERVZm5oGyfJKAkScrg+W01Fqh3AHq5evUq+vXrh5tvvhlr165FTEwMjh8/jrp16+odGhERUZWZy5lJYuF27fltkvTPf/4TCQkJWLx4sXatWbNmOkZERERUfXnlzCTFRbMFQG35bZL09ddfIzk5GWPGjMGWLVsQHx+PRx55BA888IDDx5vNZpjNJeu6JpPJXaESEZGOTl3JxXv/S8H1/EK764GGAEzs2xRt46J0iqyI1nE70HFNUlZeAXLzCxAW7Le/8mvMb0csJSUFCxcuxPTp0/HMM89g9+7deOyxxxAcHIyJEyeWefy8efMwe/ZsHSIlIiI9fbAtFUt/PunwvtRL2VgxpY+bI7KnFm4bSy23RYYEITzYgJz8QpzPzEPzmAg9wvNqfpskWa1W9OjRA3PnzgUAdO3aFQcOHMB//vMfh0nSrFmzMH36dO22yWRCQkKC2+IlIiJ9ZOUVAAAGto5BUvN6AIrqgBb8eBy7Uq/gak4+6oYH6xZfnoMDblUNokKQcikH501MkmrCb5Okhg0bol27dnbXbrzxRnzxxRcOH280GmE0Gt0RGhEReZD8wqKZmgGtY3B//5La1fWHLuDwORM2HL6AMT30+0ezowNuVWqSlGFiG4Ca8NsWAP369cPRo0ftrh07dgxNmzbVKSIiIvJE+cWF0cGlmjUmt28AoChZ0lNegePdbQAbStaW3yZJTz75JHbs2IG5c+fixIkT+Pjjj7Fo0SJMnTpV79CIiMiDWAoFABBsUOyuD2kXBwDYeuwicvML3B4XAFitgnw1SQp0vNwGsA1ATfltktSzZ0+sXr0an3zyCTp06ICXXnoJ8+fPx4QJE/QOjYiIPIiahJSeSbqxYSQS6oXCXGDF1mOX9AgN5uLYgHJmkqKKykR4flvN+G1NEgCMGDECI0aM0DsMIiLyYFqSZLBPQhRFwZB2cfhgWyrWHzyPP3eIc3tsaj0SwOU2V/DbmSQiIqKqUAu3S88kAUBy+6LE6McjGbAUWsvc72pqI8kggwJDgFLm/tji5bYLXG6rESZJREREFVBnkoIMZZOQ7k3ron54MDKvW7Ar9Yq7Qys53Daw7CwSUHI0SUaWGVaruC0uX8EkiYiIqAIVzSQZAhTcemPxLreD590aF1Cy3Fa6kaQqJtIIRQEKrILLOfnuDM0nMEkiIiKqgDqTZHSQJAHAEJtWACLuna2pqJEkAAQZAnBDBIu3a4pJEhERUQXUWqMgg+Nfmf1a3oCwYAPOZeZh/5lMd4ZWciRJOQkcULLkxjYA1cckiYiIqALltQBQhQQZMKhNDABgnZuX3NTCbUc721RaryTOJFUbkyQiIqIKlLQAKP9XprrLbf1B93bfNldwJImqAXsl1RiTJCIiogpUVLitGtQmFoEBCo5nZCPlYra7QivZ3VZOTRJQstzGJKn6mCQRERGVQ0RKkqQKZpKiQ4PQp0V9AO49y00r3C6nBQAANNAaSvKQ2+pikkRERFSOAqtA3bBW0UwSAAzRltzcV5dkruBwW1UcG0rWGJMkIiKicuTbnI1WaZLUrqgVwN70a8hw09JWSZ+kCpbbeDRJjTFJIiIiKoftUSPltQBQNYgKQZeEOgCAHw67Z8mtpCap8t1tmdctdme9UeWYJBEREZVDnUlSFCDQwdlopam73Na5aZeb1gKggpqkqJBArbCbvZKqh0kSERFROcw22/8VpfIkSe2+/fMfl2DKs7g0NqDyjtsAoCgKd7jVEJMkIiKicliqsP3fVouYCLSMjYClULDpSIYrQwNQteU2gA0la4pJEhERUTmqsv2/NLWA2x2tAMxVmEkCSoq3OZNUPUySiIiIylHZkSSOqHVJm49kuLxQuirHkgC257exV1J1MEkiIiIqR3WX2wCgY3w04qJCkJNfiJ//uOyq0ADYLLdVULgNALGsSaoRJklERETlUAu3K9v+bysgQNEKuF194G1V+iQBNjNJTJKqhUkSERFROapyuK0jQ9oVLbltOHwBhVZxelyqvCoccAsAcdE85LYmmCQRERGVoyY1SQCQ1LweokICcSk7H3vTr7oiNAAly23GSuJTd7dlmMwQcV3S5muYJBEREZXDUliUUFQ3SQoyBOCWG4t3ublwya2qhduxkUVJUn6hFVdy8l0Wj69hkkRERFSO/MKiJKS6y20AkKzVJV1w2eyNuYp9koIDA3BDRDAA1iVVB5MkIiKictR0uQ0ABrSOgTEwAOlXcnH0QpazQwNQtY7bKnU2iXVJVcckiYiIqBz56nJbDWaSwoIDcVOrGADAugOuaSypJUmVtAAAShpKsldS1TFJIiIiKoc6kxRUg5kkoOQst/WHXFOXlFdQteU2oKR4mzNJVcckiYiIqBw1bQGguvXGBghQgINnTTh9NdeZocFSaNXaC1RluY2H3FYfkyQiIqJy1KYmCQDqhQejZ2I9AMD6g85dclMbXQJVm0lSeyWxcLvqmCQRERGVQz2WpLI+RBVRz3Jz9pKb7blwVYmvgXZ+G5OkqmKSREREVI78QvVYEqXGzzG4XVFd0q7UK07tUaQdSRIYAEWpPD7WJFUfkyQiIqJy1Ha5DQAS6oWhfaMoWAX48bDzltzyqtgjSaXWJF3NtdjNQlH5mCQRERGVQ51JCjZULREpj3qW2zon1iVVp0cSANQJC9KSvYtZbANQFUySiIiIylHSAqDmy20AkNyhaMntf8cvIje/oNZxAYC5ikeSqBRF0WaTWLxdNUySiIiIylHbFgCqNg0i0aReGMwFVmw9dtEZoZUst1WhkaQqjsXb1cIkiYiIqBzO2N0GFM3iqGe5OasVQHWX2wCgQTSLt6uDSRIREVE5nFG4rRpS3Apgw+ELWvJVG+pMkrGKy20A0CCyuFcSZ5KqhEkSERFROUpaANT+12W3JnVRPzwYprwC7Eq9UuvnK5lJqsZyWzRrkqqDSRIREVE5zE6cSTIEKFrPpHUHa99YMq+gpE9SVam9kjJM3N1WFUySiIiIymEpdE7htmqITV2SiNTquarbJwngTFJ1+W2S9MILL0BRFLuvtm3b6h0WERF5kJIWAM75ddm3xQ0IDzbgvCkPv5/OrNVzactt1YjNtgVAbZM0f+C3SRIAtG/fHufOndO+tm3bpndIRETkQdQkyeikmaSQIAMGtYkFUPuz3Mw1qEmKjSoq3M4vsOJarqVWr+8P/DpJCgwMRFxcnPZ1ww036B0SERF5EG25zUkzSUDJklttu2/nFajLbVWPzRhoQN2wIABccqsKv06Sjh8/jkaNGqF58+aYMGEC0tPTy32s2WyGyWSy+yIiIt/mzBYAqpvbxiLIoOBERjbSLuXU+HlqsrsNKCneZpJUOb9NkpKSkrBkyRJ8//33WLhwIVJTU3HTTTchKyvL4ePnzZuH6Oho7SshIcHNERMRkbs5swWAKiokCK0bRAIAUnVIktTi7QwmSZXy2yRp6NChGDNmDDp16oTk5GSsWbMG165dw6effurw8bNmzUJmZqb2derUKTdHTERE7ubMFgC2nHGGmtZMspqxlRxNwjYAlQnUOwBPUadOHbRu3RonTpxweL/RaITRaHRzVEREpCdntwBQqceD1KbzdXUPuNVem8ttVea1M0l5ec79w83OzsYff/yBhg0bOvV5iYjIe7miJgkAGkTW/gy1mvRJAkqSJJ7fVjmvSpKsViteeuklxMfHIyIiAikpKQCAZ599Fh988EG1nmvGjBnYsmUL0tLSsH37dowaNQoGgwF33XWXK0InIiIvU1BohbW4lZCzZ5LioovPUKtVklT9A27tXpvnt1XKq5KkOXPmYMmSJXj11VcRHBysXe/QoQPef//9aj3X6dOncdddd6FNmzYYO3Ys6tevjx07diAmJsbZYRMRkReyFJY0W3T6TFJU7ZfbtBYAgZxJchWvqklaunQpFi1ahFtuuQUPPfSQdr1z5844cuRItZ5rxYoVzg6PiIh8iLrUBrigcFvdYZZV8+LpmjSTBEoKty/n5CO/wOr0n82XeNXInDlzBi1btixz3Wq1wmJh51AiInIec2Gh9v+BAYpTn1tNVK7k5GsF2NVV0+W2euHB2vJhRhZnkyriVUlSu3bt8L///a/M9c8//xxdu3bVISIiIvJVtkXbiuLcJCk6NEjbup9hqtlsUk0LtxVF0Y4n4ZJbxbxque25557DxIkTcebMGVitVqxatQpHjx7F0qVL8e233+odHhER+RC1JslZ57bZUhQFDaJCkH4lF+dNeUioF1bt58grqNlMElBUl3T66nX2SqqEV80k3XHHHfjmm2+wYcMGhIeH47nnnsPhw4fxzTffYPDgwXqHR0REPkSdSQpyUc1OXC2Lt9XlNmM1C7ftXpszSRXyqpkkALjpppvwww8/6B0GERH5OG25zQUzSUBJQ8maLHmJSEnH7RrOJNX0tf2JV80kTZ48GR9++GGZ6yaTCZMnT9YhIiIi8lXquW2u2v0VV4u6ILPNzrvq1iQBJb2SmCRVzKuSpCVLluCRRx7BY489Bqu15A1y/fp1h8kTERFRTbmq27aq5HiQ6tcFmS02SVINltuc0afJH3hVkgQA3333HdasWYPk5GRcvXpV73CIiMhHqTNJQS5ablN7JV2oQaKiFm0HKECQofo77+K43FYlXpcktWvXDjt37oTFYkGvXr1w+PBhvUMiIiIfZHHbTFINkiSbRpI1aU9g+9oiUsmj/ZdXJUnqG6F+/frYsGEDBg4ciD59+uDrr7/WOTIiIvI16kySK1oAAPY7zKqbqNS0R5L22sWzWHkWK0zXC2r0HP7Aq3a32b6JAgMD8f7776Ndu3Z45JFHdIyKiIh8UUkLAOc2klSpDR3zC6y4lmtB3fDgSr6jhDaTVMNZrpAgA6JDg5B53YLzpjxEhwXV6Hl8nVclSZs2bUK9evXsrk2fPh2dOnXCTz/9pFNURETki1zdAsAYaEC98GBcycnHeVNezZKkGs4kAUUzWZnXLbhgykObuMgaP48v86rltoEDByIwsGxed+utt+L555/XISIiIvJVrm4BANS8X1FegdojqeZJktqniQ0ly+fxM0nTp0/HSy+9hPDwcEyfPr3Cx77xxhtuioqIiHydttzmopkkAGgQZcThc9VPksw1PNzWltaniW0AyuXxSdKvv/4Ki8Wi/X95nH34IBER+Td3zCSVHE1SvV5J6kxSTXokqWqzu85feHyStGnTJof/T0RE5EpqCwCjG5bbqpuo5DlhJolHk1TOq2qSSjt58iQOHTpk132biIjIGbSZJBcut8XV8Pw2s5MKtwHOJFXEK5Kk//73v2XqjaZMmYLmzZujY8eO6NChA06dOqVTdERE5IvcUZMUV8PjQWrbJwmwTdCqfyyKv/CKJGnRokWoW7eudvv777/H4sWLsXTpUuzevRt16tTB7NmzdYyQiIh8jdnFHbeBkiWvjCz9ltsuZZthKeSKjCNekSQdP34cPXr00G5/9dVXuOOOOzBhwgR069YNc+fOxY8//qhjhERE5GssbmkBULTD7FJ2vjZzVRXq2W3GWhRu1w8PRmCAAhHgYhZnkxzxiiTp+vXriIqK0m5v374dAwYM0G43b94c58+f1yM0IiLyUe5YbqsXHqzVPFVnNkldbjPWYiYpIEBBbGRRksa6JMe8Iklq2rQp9uzZAwC4dOkSDh48iH79+mn3nz9/HtHR0XqFR0REPkg7u82FM0mKomjHk1SneLvkWJKazyQBJQ0l2SvJMY9vAQAAEydOxNSpU3Hw4EFs3LgRbdu2Rffu3bX7t2/fjg4dOugYIRER+Rp3LLcBRcXbp69er1avJGcUbquvDbANQHm8IkmaOXMmcnNzsWrVKsTFxeGzzz6zu/+nn37CXXfdpVN0RETki1x9dpuqJseDqDVJtSncBmz7NLEmyRGvSJICAgLw4osv4sUXX3R4f+mkiYiIqLbMbqhJAoAGkcU73KqRJDmjTxJQ8z5N/sIrapKIiIjczW3LbdHVL54uWW6r7UxS8WuzJskhJklEREQO5LuhTxJgs+RVjUTFaYXbrEmqEJMkIiIiB9xxLAlQs+Lpkpok5xRunzflQURq9Vy+iEkSERGRA+6aSYqLrn6i4ow+SbavnZtfiGxzQa2eyxd5ZZKUn5+Po0ePoqCAf6BEROQalsKihMVdy215FitM16v2ey3PSYXbYcGBiAwp2sPFJbeyvCpJys3Nxf3334+wsDC0b98e6enpAIBHH30Ur7zyis7RERGRL3FXC4CQIAOiQ4MAABeq2HVbK9yuZU0SYHvILtsAlOZVSdKsWbPw22+/YfPmzQgJCdGu33rrrVi5cqWOkRERka9xVwsAwDZRqVqSZHZSnyTAtlcSZ5JK86ok6csvv8S///1v9O/fH4qiaNfbt2+PP/74Q8fIiIjI17irBQBQ/YaSZid13Aa4w60iXpUkXbx4EbGxsWWu5+Tk2CVNREREtaUut7ny7DZVnHp+WxVmkgqtou28c0aSpPVpYq+kMrwqSerRowe+++477baaGL3//vvo06ePXmEREZEPUhMRty63VWE2R11qA5yz3Mbz28rnFceSqObOnYuhQ4fi0KFDKCgowIIFC3Do0CFs374dW7Zs0Ts8IiLyEYVWQaHVPbvbgJLltqokKmrRNgAYnVC4zeW28nnVTFL//v2xb98+FBQUoGPHjli/fj1iY2Px888/o3v37nqHR0REPkKtRwLclCRFqolK5TvM1O3/QQYFhoDal5rE1eCAXX/hVTNJANCiRQu89957eodBREQ+TN3ZBri+BQBQvUTFWUeSqNSZpItZZhQUWhHohp/XW3jVSOzduxf79+/Xbn/11VcYOXIknnnmGeTn59fquV955RUoioInnniillESEZG3y7dJkoIMrt8YpCYql7LNdrNYjpR023ZOknRDhBGGAAVWAS5l1+53qa/xqiTpwQcfxLFjxwAAKSkpGDduHMLCwvDZZ59h5syZNX7e3bt3491330WnTp2cFSoREXkxi825be7YPV0/PBhBBgUiRTM6FclzYo8kADAEKIiJKN7hxiU3O16VJB07dgxdunQBAHz22WcYOHAgPv74YyxZsgRffPFFjZ4zOzsbEyZMwHvvvYe6des6MVoiIvJW7jq3TRUQoCA2smpLbs46ksRWdQrH/YlXJUkiAqu16I27YcMGDBs2DACQkJCAS5cu1eg5p06diuHDh+PWW2+t8HFmsxkmk8nui4iIfFPJ9n/39eCLrWKvpJJGks77Fa71aWKSZMerCrd79OiBOXPm4NZbb8WWLVuwcOFCAEBqaioaNGhQ7edbsWIF9u7di927d1f62Hnz5mH27NnVfg0iIvI+7p5JAoDYyKJE5VJ2xctt14tnkkKdOJPUuG4YAOCPjGynPacv8KqZpPnz52Pv3r2YNm0a/v73v6Nly5YAgM8//xx9+/at1nOdOnUKjz/+OJYvX253Dlx5Zs2ahczMTO3r1KlTNfoZiIjI8+W78UgSVWRI0SG3WeaCCh+XXXx/uNF58xzdmxaVm+xMveK05/QFXjOTVFhYiGvXrmHr1q1laodee+01GAzVy6j37NmDjIwMdOvWze41tm7din//+98wm812z2k0GmE0Gmv3QxARkVfQZpLcuB0+ojjpyakkSVLvj3BiktQzsR4A4OiFLFzLzUedsGCnPbc385qZJIPBgCFDhuDatWtl7gsJCUFQUFC1nu+WW27B/v37sW/fPu2rR48emDBhAvbt21ftpIuIiHyHmiS540gSVUmSVFjh47LznJ8kxUQa0SImHCLA7rSrTnteb+c1M0kA0KFDB6SkpKBZs2a1fq7IyEh06NDB7lp4eDjq169f5joREfkXtQWAOw63VanLZ1l5lSy35Tt/uQ0AejWrjz8u5mBnymUMblf9Ol9f5DUzSQAwZ84czJgxA99++y3OnTvH3WZEROQSehRuRxiLVjAqW25zxUwSAPRuXrTktiuNdUkqr5pJUrf833777XbNvUQEiqKgsLDiKcrKbN68uVbfT0REvqGkBYAbk6SQol/J2TrUJAFAr2ZFSdKBM5nIyrNoheT+zKuSpE2bNukdAhER+QE9ZpLCg6uWJGUX1yypSZWzNIwORZN6YUi/kotfTl7FzW1infr83sirkqSBAwfqHQIREfmB/EIddreFVG13W7bZAsD5NUkAkNSsHtKv5GJX6hUmSfCymiQA+N///oe//vWv6Nu3L86cOQMAWLZsGbZt26ZzZERE5Cv0qUmq6nJb0UxSpAuSJHXJbWfKZac/tzfyqiTpiy++QHJyMkJDQ7F3716YzUVdSTMzMzF37lydoyMiIl+hR5+k8ComSa5oJqnq3bw+AOD305m4nl+7Ol9f4FVJ0pw5c/Cf//wH7733nl1fpH79+mHv3r06RkZERL7EokfHbZtmkiJS7uNKkiTn9/NrXDcUjaJDUGAV7E1nvySvSpKOHj2KAQMGlLkeHR3tsMkkERFRTehSuF2cJFml5Hw2R9QWAJFG5+8+UxSFS242vCpJiouLw4kTJ8pc37ZtG5o3b65DRERE5IvMOrQACAs2QO1uU96SW6FVtATKFTNJAJBUvOTGc9y8LEl64IEH8Pjjj2Pnzp1QFAVnz57F8uXLMWPGDDz88MN6h0dERD7CUlC03OXOmSRFURChtgEop+t2Tn7JdWe3AFCpM0m/nrqGvApmtPyBV7UAePrpp2G1WnHLLbcgNzcXAwYMgNFoxIwZM/Doo4/qHR4REfmI/OLmxO4s3AaKltyyzAXlnt+mJk9BBgXGQNfMJDW/IRw3RBhxKduM309nakmTP/KqmSRFUfD3v/8dV65cwYEDB7Bjxw5cvHgRL730kt6hERGRD9GjJgkomR3KKu6FVFqOC3e2qRRFQVJz1iUBXpYkffTRR8jNzUVwcDDatWuHXr16ISIiQu+wiIjIx1gKi5fbdJhJAlDuTFKWi44kKS1JLd7287okr0qSnnzyScTGxuLuu+/GmjVran1WGxERkSN6zSRFar2SKp5Jcn2SVFS8vefkVa0dgj/yqiTp3LlzWLFiBRRFwdixY9GwYUNMnToV27dv1zs0IiLyIWadkiR1x1p2OTNJ7kqSWsVGoE5YEK5bCrH/TKZLX8uTeVWSFBgYiBEjRmD58uXIyMjAm2++ibS0NNx8881o0aKF3uEREZGPyNehBQAARBT3Pirv/LasPNfXJAFAQICCXolFS267/HjJzauSJFthYWFITk7G0KFD0apVK6SlpekdEhER+QiLXoXb6kxSeS0A1JkkF23/t6X1S/Lj4m2vS5Jyc3OxfPlyDBs2DPHx8Zg/fz5GjRqFgwcP6h0aERH5CHUmSa/C7fKaSarX1X5KrqQWb/+SdhWF1vKPSfFlXtUnafz48fj2228RFhaGsWPH4tlnn0WfPn30DouIiHyMWrht1KkFQPlJktpt2/W/vm9sGIXI4r5Nh8+Z0CE+2uWv6Wm8KkkyGAz49NNPkZycDIPBNU20iIiILLrVJJUccuuIO5fbDAEKeiTWxaajF7Ej5bJfJkletdymLrMxQSIiIlfSrZlkVZfbXHRuW2lqXZK/Fm97/EzSW2+9hSlTpiAkJARvvfVWhY997LHH3BQVERH5Mv1aAFQ1SQpySzxqXdKutCuwWgUBAYpbXtdTeHyS9Oabb2LChAkICQnBm2++We7jFEVhkkRERE5R0gLAvUlBZctt2VoLAPfMJHWIj0ZYsAHXci04lpGFtnFRbnldT+HxSVJqaqrD/yciInIVtSbJ7YXb6kxSeS0A8t3TTFIVZAhA96Z18b/jl7Ar9YrfJUleVZNERETkDlpNkptrYKu+3Oa+OQ61qeTOFP+rS/L4mSRbhYWFWLJkCX788UdkZGTAarU/T2bjxo06RUZERL5Et7PbbFoAiAgUxX65L9tNHbdtaU0lU684jMmXeVWS9Pjjj2PJkiUYPnw4OnTo4Fd/UERE5B5Wq6CguHmiu2uS1OTHKkCexYrQYPuZLLVWKdINLQBUnROiERwYgEvZZqRcykGLmAi3vbbevCpJWrFiBT799FMMGzZM71CIiMhH5duceu/umaSwoJKkKNtcYJckWa2CnHz3NZNUGQMN6JpQBztTr2BnyhW/SpK8qiYpODgYLVu21DsMIiLyYXomSQEBSrm9ktSibcC9NUmAbb8k/zrHzauSpKeeegoLFiyAiH+eIUNERK6nHm4LAEEB7v81qW7vL90GQE2aAgMUt++6U/slqXVJ/sKrltu2bduGTZs2Ye3atWjfvj2Cguybaa1atUqnyIiIyFfY9kjSo3lihDEQF2BGVqk2AGrSFG4MdHtNbrcmdRFkUHAuMw+nr15HQr0wt76+XrwqSapTpw5GjRqldxhEROTDSrb/67PYUl5DSfVwW3cvtQFAaLABnRrXwZ6TV7Ej5TKTJE+0ePFivUMgIiIfp9f2f5ValG1bgwSUbP/XI0kCgF7N6mHPyavYmXoFY3ok6BKDu3lVTRIREZGrlSy36TuTVHq5TWsk6cbt/7a0c9z86LBbr5hJqlu3rsP11+joaLRu3RozZszA4MGDdYiMiIh8jd4zSeUvt7m/kaSt7k3rIkAB0q/k4lzmdTSMDtUlDnfyiiRp/vz5Dq9fu3YNe/bswYgRI/D555/jtttuc29gRETkc3RPkkLKaQGgHUni3qNSVJEhQegQH43fT2diV+oV3NElXpc43MkrkqSJEydWeH+XLl0wb948JklERFRrlsKiLe56FW6Xd36bHue2lZbUrB5+P52JHSn+kST5RE3SiBEjcOTIEb3DICIiH5BfWLSLTO/ltuxyapL0Wm4DgF7N1HPc/KOppE8kSWazGcHBwXqHQUREPsBjWgDkO15ui9QzSUqsB0UBUi7m4GKWWbc43MUnkqQPPvgAXbp00TsMIiLyAeYCfXe3lSy3FdpdV2eW9JxJig4LQtu4KAD+scvNK2qSpk+f7vB6ZmYm9u7di2PHjmHr1q3Ves6FCxdi4cKFSEtLAwC0b98ezz33HIYOHVrbcImIyItpNUm6L7dZ7K57wnIbUFSXdPicCbtSL2N4p4a6xuJqXpEk/frrrw6vR0VFYfDgwVi1ahWaNWtWreds3LgxXnnlFbRq1Qoigg8//BB33HEHfv31V7Rv394ZYRMRkRfSfXeb1gLAfiZJXX6L1KlPkiqpWT0s2Z6GnZxJ8gybNm1y+nOW3gn38ssvY+HChdixYweTJCIiP5ZfoHPhdjktALTltmB9f3X3LG4qeeR8Fq7m5KNuuO/WBPtETVJtFRYWYsWKFcjJyUGfPn30DoeIiHSkdwsAtQ9SuS0AdJ5JuiHCiJaxEQCA3Wm+PZvkFTNJrrJ//3706dMHeXl5iIiIwOrVq9GuXTuHjzWbzTCbSyr5TSaTu8IkIiI3Uo8l0btPUo65ACKinTjhCX2SVEnN6uFERjZ2pl7BkPZxeofjMn49k9SmTRvs27cPO3fuxMMPP4yJEyfi0KFDDh87b948REdHa18JCf5xuB8Rkb8xe0hNUoFVtFiAkholT0iSevnJOW5+nSQFBwejZcuW6N69O+bNm4fOnTtjwYIFDh87a9YsZGZmal+nTp1yc7REROQOFp0PuLWtOVJnj6xW0Qq39d7dBgBJxU0lD57NhKnULjxf4tdJUmlWq9VuSc2W0WhEVFSU3RcREfkevXe3BQQoCA8urksqLtbOtRRCikqlPGImKS46BE3rh8EqwJ60q3qH4zL6j7ROZs2ahaFDh6JJkybIysrCxx9/jM2bN2PdunV6h0ZERDrSO0kCimaLcvILtZkktdu2IUBBSJBnzG8kNauHk5dzsTP1Cm5uG6t3OC7ht0lSRkYG7r33Xpw7dw7R0dHo1KkT1q1bh8GDB+sdGhER6UhNkow6JkkRxkBkZJm1JClL2/5v0Aq59ZbUrD4+/eW0T5/j5rdJ0gcffKB3CERE5IFKapL0S0bUbf45pWaSIkOCdIupNLV4e//pTOTmFyBM5/5NruAZc3ZEREQewqxzCwCgpHhbnUkqOZLEoFtMpSXUC0N8nVAUWAV7T17TOxyXYJJERERko6QmSb+EpHTXbU85t600dTbJV5fcmCQRERHZ8IjlNqPj5TZP2NlmK0lLknyzXxKTJCIiIhuesbvNvgWAJ3XbtpXUvKhf0r5T15BnKazk0d6HSRIREZENz9jdVlSgnV3cZdtTk6TE+mGIiTQiv8CK305d0zscp2OSREREZEM7u03XJKloJkldZlNnlDytJklRFJ9ecmOSREREZEOdSdLrWBKgZMaodDPJyBDPSpIA27ok3yveZpJERERkI98TWgAYS+9uK7S77knUuqQ9J69qCaavYJJERERkwxMKtyPLtAAoOkTWE5OkVrERqBcejDyLFfvPZOodjlMxSSIiIrJR0gJA/5mkkhYARTNJkR6YJCmKgp6JdQEAu3ysLolJEhERkQ1P2N2mJknqmW1ZHtpMUpXUrGjJzdfqkpgkERER2fCI5TZ1Jinfs5tJqtTO27+kXUVBoe/UJTFJIiIismEpFAB6N5MsWW4TEY9Pkm5sGIXIkEBkmwtw+FyW3uE4DZMkIiKiYiKi7W7TtQVAceG2pVBgLrDa9EnynANubRkCFPRK9L1WAEySiIiIiuXbLBXpOpMUXDJjlG0uQHbxsluEB/ZJUvXywaaSTJKIiIiK2fb50bNPkiFAQWhQ0azRxSwzpGgF0GOX24CSfkm7067AahWdo3EOJklERETF1HokQN8kCSiZNbpgygMABCjQEidP1L5RFMKCDbiWa8HRC75Rl8QkiYiIqJg6kxQYoCAgQNE1FnXWSE2Swo2BUBR9Y6pIkCEA3Zv6Vr8kJklERETFPGH7v0pNks5nmgF4ZiPJ0no3961+Sfq/C4iIiDyEdm6bByRJ6k628zYzSZ5OLd7elXoFIt5fl6T/u4CIiMhDqDNJem7/VzlabvN0nRpHwxgYgEvZ+fjjYo7e4dSa/u8CIiIiD6HNJHlQknQ+syhJivTg7f8qY6ABXZvUAeAbS276vwuIiIg8hCec26YKLz2TFOz5SRJQco6bLxRv6/8uICIi8hAWD+i2rVJbAFzOybe77emSmhc3lUzx/rok/d8FREREHsKjdreVmjny5EaStrom1EWQQcF5Ux5OXbmudzi1ov+7gIiIyEOYPShJKl2o7anntpUWGmxA58Z1AAA7vLwuSf93ARERkYeweFLhdkjpmaQgnSKpPu0ctxTvrkvS/11ARETkIbQWAB4wk1R6eS3CS2aSgJJz3HalcSaJiIjIJ3hiCwDttpcUbgNA96Z1YQhQcOrKdZy95r11Sfq/C4iIiDyEJ7YA0G57SQsAoCjB69AoCoB3twLQ/11ARETkIUpaAOh/kGzp5pHesrtNleQD57gxSSIiIirmybvbvGm5DQB6JXp/8bb+7wIiIiIP4cl9krzh7DZbPZvVg6IAKZdykJGVp3c4NaL/u4CIiMhDlLQA0H8nWem+SJFeliRFhwbhxjjvrktikkRERFSspAWA/jVJgYYAhASV/Jr2tpkkoKRfEpMkIiIiL6e2ADB6QAsAoKSBpKIAYcH6z25VV+/m3l2X5BnvAiIiIg+gLbd5QE0SUNJAMiI4EIqi/+xWdfUsLt4+eiELV4oP6vUmnvEuICIi8gDq7rYgD5lJUpfYvHGpDQDqRxjRKjYCALA7zftmkzzjXUBEROQBPGl3G1DSG8nbtv/bSvLiJTfPeBfoYN68eejZsyciIyMRGxuLkSNH4ujRo3qHRUREOvLUJMlbZ5IAoFcz7z3HzTPeBTrYsmULpk6dih07duCHH36AxWLBkCFDkJOTo3doRESkE4sHnd0GlMwgedv2f1tJxTvcDp01wZRn0Tma6vHeUa+l77//3u72kiVLEBsbiz179mDAgAE6RUVERHrK97DC7ZKaJO/b2aZqEBWCxPphSLuci1/SruBPbRvoHVKVeca7wANkZmYCAOrVq+fwfrPZDJPJZPdFRES+RVtu85SZJB9YbgOApGbqOW7eVZfkGe8CnVmtVjzxxBPo168fOnTo4PAx8+bNQ3R0tPaVkJDg5iiJiMjVMrLMAICo0CCdIynSIia8+L8ROkdSO95avO3dqamTTJ06FQcOHMC2bdvKfcysWbMwffp07bbJZGKiRETkQ67l5uPk5VwAQPtGUTpHU2RM9wR0iI9GmwaReodSK2rn7f1nMpFjLvCamTG/n0maNm0avv32W2zatAmNGzcu93FGoxFRUVF2X0RE5Dt+P11UdpFYPwx1woJ1jqZIQICC9o2iEeghy3811bhuGOLrhKLQKtibflXvcKrMu0e9FkQE06ZNw+rVq7Fx40Y0a9ZM75CIiEhHv526BgDonFBH1zh8lbrLzZuW3Pw2SZo6dSo++ugjfPzxx4iMjMT58+dx/vx5XL9+Xe/QiIhIB7+dvgYA6NS4jq5x+Cq1LsmbDrv12yRp4cKFyMzMxKBBg9CwYUPta+XKlXqHRkREbiYi2HeqaLmtS0K0ztH4JnWH275T15BnKdQ5mqrxjsopFxARvUMgIiIPcS4zD5eyzTAU1wCR8zWtH4bYSCMyssz4Nf0a+rSor3dIlfLbmSQiIiKVWo/UpkEkQoK8t3GjJ1MUBUnNi48o8ZIlNyZJRETk934r3tnGom3XUlsB7Ez1jnPcmCQREZHfU2eSWI/kWr2Lk6S96Ve17uaejEkSERH5NatVsP9M0UwSd7a5VsvYCNQLD0aexYr9Z67pHU6lmCQREZFfS7mUjWxzAUKDDGgV693Hf3g6RVHQK7FoNmmHF/RLYpJERER+Td363zHe+ztbewNv6pfEdwMREfm137UmkqxHcge1ePuXtCsoKPTsuiQmSURE5Nd4HIl7tY2LQlRIIHLyC3HonEnvcCrEJImIiPyWuaDkF3UXJkluYQhQSloBeHhdEpMkIiLyW0fOZcFSKKgbFoTGdUP1DsdveEu/JCZJRETkt9RDbTsn1IGiKPoG40fUc9x2pV6B1eq5x4QxSSIiIr+1T61HYn8kt2rfKArhwQaY8gpw5HyW3uGUi0kSERH5rd+140i4s82dAg0B6J6otgLw3CU3JklEROSXTHkW/HExGwA7beshSatL8tzibSZJRETklw6czoQI0LhuKG6IMOodjt9Rk6RdqVcg4pl1SUySiIjIL/2mLrVxFkkXnRrXgTEwAJdz8rUZPU/DJImIiPxSSRNJ1iPpITgwAN2a1AXguee4MUkiIiK/pG3/50ySbjz9HDcmSURE5HcyTHk4l5mHAAXoEM+ZJL2o/ZJ2pl72yLokJklEROR31HqkVrGRCDcG6hyN/+rapA6CDQG4YDLj5OVcvcMpg0kSERH5HdYjeYaQIIP2Z+CJS25MkoiIyO+o9Ujsj6Q/9Ry3HR7YVJJJEhER+RUR0WaSuiTU0TUWsj/HzdMwSSIiIr+SdjkXprwCBAcGoE1cpN7h+L3uTevCEKDg9NXrOHPtut7h2GGSREREfuX34qW29o2iEGTgr0G9hRsDtR2GO1M8a8mN7w4iIvIr+9SibdYjeYzezTyzXxKTJCIi8iusR/I8vTz0sFsmSURE5DcshVYcPGsCAHRqzO3/nqJHYj0oCpB6KQcZpjy9w9EwSSIiIr9x9HwWzAVWRIUEIrF+uN7hULHo0CC0axgFwLNmk5gkERGR3/i9uNN2p8Z1EBCg6BwN2SpZcvOc4m0mSURE5DfYadtzeWK/JCZJRETkN9RO29zZ5nnUmaRjF7JxJSdf52iKMEkiIiK/kJtfgGMXsgAAnbmzzePUCw9G6wYRADxnNolJEhER+YUDZ0ywChAXFYIGUSF6h0MOqEtunlKXxCSJiIj8AuuRPJ9WvJ3CmSQiIiK3UeuROrEeyWMlFSdJh8+bkHndonM0TJKIiMhPqEkSO217rtioEDS7IRwiwC9p+s8mMUkiIiKfdznbjFNXik6Y78hO2x4tyYPOcfPbJGnr1q247bbb0KhRIyiKgi+//FLvkIiIyEV+P1PURLJ5TDiiQoJ0joYqktS8KEnawSRJPzk5OejcuTPeeecdvUMhIiIX0w61ZT2Sx+tVvMPtwJlMZJsLdI0lUNdX19HQoUMxdOhQvcMgIiI3KNnZVkfXOKhy8XVC0bhuKE5fvY69J69iQOsY3WLx2yTJU13Nycf/TlzSOwwiIp+yrzhJ6sR6JK/Qq1k9nL56BjtTLzNJ8gZmsxlms1m7bTKZXPI6J6/k4rFPfnXJcxMR+bMgg4Ibi0+aJ8/Wu1l9rNp7RvfibSZJVTRv3jzMnj3b5a8TYTSgT/P6Ln8dIiJ/M7RjHEKCDHqHQVWQ1LweWjeIQId4fWf+FBERXSPwAIqiYPXq1Rg5cmS5j3E0k5SQkIDMzExERfFfJkRERN7AZDIhOjq6Sr+/OZNURUajEUajUe8wiIiIyE38NknKzs7GiRMntNupqanYt28f6tWrhyZNmugYGREREXkCv02SfvnlF9x8883a7enTpwMAJk6ciCVLlugUFREREXkKv02SBg0aBJZjERERUXn8tuM2ERERUUWYJBERERE5wCSJiIiIyAEmSUREREQOMEkiIiIicoBJEhEREZEDTJKIiIiIHGCSREREROSA3zaTrC21EaXJZNI5EiIiIqoq9fd2VRpKM0mqoaysLABAQkKCzpEQERFRdWVlZSE6OrrCxyjCszlqxGq14uzZs4iMjISiKHb3mUwmJCQk4NSpU4iKitIpQs/GMXItjm/lOEbOwXGsHMfItao7viKCrKwsNGrUCAEBFVcdcSaphgICAtC4ceMKHxMVFcW/EJXgGLkWx7dyHCPn4DhWjmPkWtUZ38pmkFQs3CYiIiJygEkSERERkQNMklzAaDTi+eefh9Fo1DsUj8Uxci2Ob+U4Rs7Bcawcx8i1XDm+LNwmIiIicoAzSUREREQOMEkiIiIicoBJEhEREZEDTJKIiIiIHGCSRC5RUFCgdwjk59Sjg4hcjZ93votJUjVlZ2cjMzMTQNUOx/M3Z8+eRa9evfDcc8/pHYpPMplMuHDhAoCio3GorLNnz6JPnz6YMWMG8vPz9Q7Hq/HzrmL8vHMtT/i8Y5JUDS+88AI6dOiA1atXA0CZM9v83ZNPPonExETExcVh2rRpeofjc+bMmYOWLVvi3//+NwBUeuaQP5oxYwaaNm2KmJgYPP/88wgODtY7JK/Fz7uK8fPOtTzl845nt1XBlStXMHPmTPz6668AgDVr1qBfv35o1aoVRMTvPzzS09PRp08fhISEYNu2bejVq5feIfmU7OxszJw5E7t27UJiYiJ++eUX/PTTT+jXrx/ff8UuXbqETp06QUSwefNm9OvXT++QvBY/7yrGzzvX8rTPOyZJ5bD9wygoKEDDhg0xatQohIaG4p577sG6deuQmJiIoKAgnSPVX2BgIOLj49GiRQv06tULe/fuxYoVKxAXF4dOnTqhf//+CAkJ0TtMr2L7/jMajWjSpAkGDBiAZs2aYdq0aVi9ejW6deuG0NBQ/uICcMMNN6Br167Iz89Hv3798Ouvv+KDDz5AdHQ02rdvj1tvvRWxsbF6h+mx+HlXdfy8cz6P/rwTKsNsNkteXp5222KxyIULF7TbkyZNkr59+8quXbv0CE93VqtVRIrGRbV27VpRFEWGDBkiTZo0kdtuu006duwosbGx8tBDD2nfQ5W7fv26mEwm7bbVapXMzEzt9rPPPiu9e/eWVatW6RGeR3D0Hjx8+LAEBgZK7969JSEhQcaOHSuDBg2Sxo0bS3JyshQWFuoVrkfj513F+HnnWp7+ecckqZTnn39eevbsKcnJyfLuu+/K5cuXtfvUD9nTp09L06ZN5ZlnnpGrV6+KiPjNX4q33npLnnvuOe22+nNnZ2fLQw89JD169JBdu3ZJbm6uiIgsWLBAOnfuLP/v//0/XeL1Ns8995zceOON0rdvX3nmmWfk7Nmz2n3q++/ChQsycOBAmThxopw5c0ZE/Of9JyLy+uuvy+TJkx3e9/zzz0uHDh1kx44dkp+fLyIiX3/9tbRu3drufUtF+HlXMX7euZY3fN4xSSpmsVjknnvukZYtW8qHH34od911l7Rv316GDx9u97iCggIREXnppZekbdu2snbtWu0+X/7g2LdvnyQnJ4uiKNKxY0f58ccfRaRkPEREjh07Jj///LMUFhZqb/DLly9LcnKyTJs2ze6xVNa0adOkZcuW8tlnn8n06dOlc+fO0rNnT8nKytIeo47he++9J926dZOFCxdq9/ny+09E5ODBg3LbbbdJeHi4NGjQQD777DMRsX8PXrt2TbZu3SoWi0V7D+bm5soDDzwgw4cPl+vXr+sSu6fh513F+Hnnet7yecckqVhKSoq0bdtWvv76a+3a+vXrJTQ0VN544w3tmvqXwWq1SufOneX++++XlJQU+fLLL+Xtt992e9zu8q9//Utuv/12+fDDD2XYsGFyzz33aNPPtmNiS73epk0bmTJlinsD9iJWq1UuXrwoXbp0kXfffVe7fvz4calfv748+eSTkpOTIyJit2Q0atQoGTlypOzdu1c+//xz+cc//uH22N3pvffek9tvv11Wrlwp9957r/Tv31/MZrOISLlLaer1/v37y6hRo3z6F3t18POuYvy8cx1v+7xjklTs6NGjoiiKnDx50u763LlzpU6dOnbX1ez2008/lZiYGGnSpIkEBgbKW2+95daY3encuXOyZcsWERGZP3++JCUlyZIlS0Sk4ox+w4YN0rNnT/npp5/cEqe3On/+vAQEBMjevXtFpKT+YdmyZRIcHKyNvUjJB8cPP/wgLVu2lPr160tQUJC8+OKL7g/cDdT3l8lkkq1bt4qIyOrVq6Vz584yb948ESk/SRIR+emnn6R37952CYG/4+ddxfh551re9HnHJKnYoUOHpEuXLvLqq6/aXc/MzJTmzZvL9OnTRaTkAyMtLU0eeughURRF7rvvPru1fF936tQpGTNmjAwfPlzOnz8vIva/pA4dOiSbN2+Wxx57TOrWrStPPvmkVh9Cjl29elWSkpLk0UcfFRH7D+Lu3bvLXXfdJSIl45yWliZTpkzxy/efiMilS5dk+vTp0qFDB0lLSxMR+6WQ48ePy5o1a2Tq1KkSFRUljzzyiF1xsr/j513V8fPO+bzp885vkqTKptmzs7Nl3Lhxcuedd0pqaqqIlPwBvfbaa9KkSRO7eoYnn3xS4uLifGbHR1WXIdQx+fjjj6VPnz7y8ssvl3nMJ598IoMHD5b+/fvLjh07nBqnrzKbzTJz5kzp3bu37N+/X7smUvQv+NDQULsdHy+99JLExMT4zPuvOtT36ubNm6V///7y4IMPlnnM+vXrZfTo0TJo0CDZuXOnu0PUHT/vKsbPO3150+edXyRJFy9elAsXLmj/KrL9V4Dtts5PPvlEOnXqJP/85z/tvn/RokXSoUMHuylo2+Iyb1fV8bG9nZubKw8++KAMHDhQfvvtNxER7Q2cnZ0tx44dc0foXqF0LYOj+0RENm7cKH379pWHHnrI7jFr166Vpk2byp49e1wbqI6qOka2t/Pz8+WVV16RNm3ayP/+9z8REW2Zw2w2S3p6uitD9ljXrl0Tk8mkJQL8vLNX1fGxvc3Pu6rztc87nz/XYOrUqejYsSOGDBmC5ORknDhxwq69eWBgIAoLC7F8+XKMHz8effv2xerVq/Htt99qj7l06RLq1KmD+Ph47VpERIRbfw5Xqcr4iAg+/PBD7bbVakVoaCjGjRuHwMBAzJ07F0OHDkVSUhLOnj2L8PBwtGrVSq8fyaM8/vjjGD58OAD7tvpSfA6WOp5vv/02br75Ztxxxx3YtGkT/vvf/2qPPXnyJOrVq4d27dq5N3g3qcoYiQjefPNNu9tBQUEYPnw42rdvj1mzZmHYsGHo378/Dh06hODgYCQkJLj/h9GRiOCJJ57AwIED8ec//xn33nsvsrKyEBAQAIvFAsC/P++qOj78vKs5n/y80y09c4OnnnpKunbtKps3b5alS5dK//79pWPHjlrxp4jIu+++K7GxsTJkyBDJz8+Xw4cPy+TJkyUwMFAefvhhmTZtmkRHR2s7OXxpd0x1xmfYsGF2DeZEivpXtG/fXhRFkVGjRmm1IVRUpzBs2DBp0qSJKIoiH330kYiU/dfVe++9Jw0aNJCePXtKZmamnDt3Tp599lltTKdMmSKRkZEyZ84cKSws9Kn3X3XHqHfv3lqfFNX58+elX79+oiiK/OUvfylTiOwvfv75Z+ncubP07t1bvvvuO5k9e7a0bdtWxo0bZ/e4RYsW+eXnXXXHh5931ePLn3c+mSRZrVbJycmRnj17ygsvvKBdz83Nla5du8qECRPk5MmTsnr1amnUqJF88MEHZaZZX3/9dZkyZYokJydrPTJ8RU3Gp3TPj59//lnq1asnbdu2lW3btrn7R/B4X3zxhdx///2yceNGeeKJJyQuLq5MMec333wjXbt2lffff7/M+C5dulRmzpwpf/nLX3zu/aeq7Rj99ttv0qpVK2nZsqVfvwcLCgpk5syZctddd9kti61cuVKaNWumFRsvXbpUEhIS/O7zribjw8+76vHlzzufTJJEirrExsXFadt+bYvC2rdvL//5z39EpGg92ZYnZK7uUNPxUWVnZ8uyZcvcE6wXsW0qd+jQIRERSU1NlUaNGsnTTz8tIva7sEqPrz8cnVHbMVLl5ubKV1995eJovcP3339vt21aRGTJkiXSrl07uyMfbP9fxH8+72o6Pip+3tkr/Tl16dIln/2884kk6YsvvrCrhFf/4vfp00fuvvtuEbEvGLvjjjvk9ttvLzOd6qucPT7+8sFaVaXHt7SCggJ5++23JSgoSFsO8oYPB2dy9hj583uwKmMpUtQQsV+/fmK1Wv1qvJw9Pv40dlUxe/ZsmTRpkrz44oty6dKlMvf72uedVydJmzZtkjZt2oiiKHadO9U39QcffCBBQUHazgN1S+v69eslJCRETp8+bfd4X8Pxca3yxteRixcvSo8ePWTkyJFuis4zcIycp6pjqf5CuuOOO+T//t//KyL+8XeY4+Na6enp0q1bN+nYsaNMnTpV4uLipEePHtrxQLZj6Et/l702STp06JCMGzdOpk6dKlOmTJEmTZrYHY4nUtR6v3///vKnP/3J7vqxY8ckOjra49Y+nYnj41pVGd/SvvnmG1EURZv2X7dunRw9etQd4eqCY+Q81R3L3NxcadKkiWzYsMHuOXwVx8f1lixZIl26dJFr166JSNHS2e233y79+/eXffv2iYj9ioSv/F322iTp/Pnz8v7778uhQ4fEZDJJfHy8PPXUU3aPsVqtsmbNGjEajfLqq69KRkaGiBTtYOjRo0e568++gOPjWlUZ39Jyc3Nl/PjxkpiYKElJSRIaGurTjQ45Rs5T3bFct26dJCYmSm5urhw8eFAGDRokoaGhcu7cOTdG7T4cH9d74YUXpGfPnnaJ0JYtW+SWW27ROmSLlMwo+crfZa9NkkTs1zn/+9//itFo1DJaW+q2wxtvvFFGjx4tRqNR5syZ4/Nr9Rwf16rq+KqOHz8ugwcPFkVR5G9/+5tfJKEcI+epyliqf19ff/116d27t8yYMUMMBoPcfffdPj+WHB/Xevrpp6VPnz5l2nC8/vrr0qVLF/nhhx9EpOTPwVf+Lnt1kiRivw6alJQkt99+e5ntrSJFnXjfeusteeKJJyr8kPY1HB/Xqur4HjlyRHr27Cnt27eXAwcOuDNE3XGMnKeqY3nzzTeLoihy0003eUznYnfg+DifmvQcPnxYFEWR1atX292/b98+SUpKkldeeUW75kt/lz02Sdq/f79dU0Nbpd/06l+MrVu3SkBAgLatvaCgQFtC8jUcH9dy1vhevHhRRIqOQvC15JNj5DzO/vu8fPlyn2qPwPFxrWPHjskHH3ygbdaxZTu+Y8aMka5du2p/Z1W2h9WKFLVS8JW/yx6XJJnNZrn//vtFURS7Roci9v0WLBaL1gTM1oQJE6R79+6yYcMGSU5Oln/84x8+dSIzx8e1XDG+vnb6PMfIeVwxlo5mTrwVx8e1LBaLPPTQQ2I0GuXBBx+UX375RbvPdvnSbDbL8ePH5eTJkxIaGirPPPOMVsBtsVhkwIAB8txzz7k9fnfwqCTp7bfflvDwcOnbt2+FWeiCBQvEaDTK4sWLy9TMbN++XRRFEUVRJDk5Wa5cueLqsN2G4+NaHN/KcYych2NZMY6P6z399NPSr18/7bBele04LliwQMLCwrSDkBctWiQtW7aU5ORk+eqrr+TJJ5+Uhg0blnkOX+ExSdKRI0ckJCRExo4dq107ceKEXLx4UesGnZOTI+PHj5dGjRrJ0qVL7f4gCwoK5MMPP5SgoCBJSkqSvXv3uv1ncCWOj2txfCvHMXIejmXFOD6uZbVa5cKFC9K1a1dtOXL37t2ycuVKOXDggOTk5IiIyN/+9jeJjY2VZcuW2c0sffPNNzJs2DDp06eP9OjRQ3bs2KHLz+EOHpMk5eXlyQsvvCCNGjWSw4cPy/jx46VNmzbSqlUrGTp0qGzcuFFERHbu3Omwm2pOTo7Mnz+/0oZ13orj41oc38pxjJyHY1kxjo/rqMnknj17JCYmRkwmkzz88MMSHx8v3bp1k0aNGmlb+o8ePWo3vqU7Zzta4vQ1uiVJn332mfzwww92Db/S0tKkdevWoiiKTJ48WdauXSvLly+XW265Rbp27apN53lzi/Oq4vi4Fse3chwj5+FYVozj41qOxvfw4cPSvXt3eeihh+S2226To0ePyqlTp+Tbb7+V4OBgWbBggYhImcNo/Y3bk6SlS5dKbGys9OrVS2JiYqRfv37yxRdfiEhRcdhXX30lL730kl32umvXLvnTn/4kU6dOdXe4bsfxcS2Ob+U4Rs7DsawYx8e1KhrflJQUGTp0qNStW9duZ5pIUePIuLg4PUL2OG5LkiwWi8yfP19uvPFGef/998VsNstPP/0k9957rwwdOlQ7N8xkMklWVlaZ7x84cKDcf//97grX7Tg+rsXxrRzHyHk4lhXj+LhWZeObm5srIkWH/CqKIg888ICIlMzKffrpp9KiRQs5fvy4bj+DpwiAm+Tk5ODixYuYOHEi7rvvPgQHB6Nv375o164dTCYTCgoKAACRkZGIiIiw+97Lly8jKysLLVq0cFe4bsfxcS2Ob+U4Rs7DsawYx8e1Khtfi8UCAJg8eTJGjhyJb7/9Fr/++isCAopSgt9//x0dO3ZEy5Yt9fwxPEKgK5/8+PHjaNmyJRRFQXR0NEaPHo2OHTsiICAAVqsVAQEBSEhIQE5ODoKDg8t8f15eHq5evYp//OMfEBGMHj3aleG6HcfHtTi+leMYOQ/HsmIcH9eqzviGhIQAAOrUqYOZM2di9uzZGDhwIO655x6YTCasW7cO8+fPBwCICBRF0fEn05krpqdWrlwpiYmJ0qZNG+nVq5e8//77dvfbFtrdfffdMmnSJBGxLxBbuXKlPPTQQ1K/fn0ZNGiQ/PHHH64IVRccH9fi+FaOY+Q8HMuKcXxcq6bja9tE2GKxyIsvvihTpkyRcePGyZEjR9w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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Count selected assets by day.\n", + "universe_size = universe_history.groupby(level=['time', 'symbol']).size().groupby(level='time').size()\n", + "print(f\"Universe days: {len(universe_size)}\")\n", + "# Store the selected symbol list.\n", + "unique_assets = list(universe_history.index.levels[1].unique())\n", + "print(f\"Mean basket size per day: {universe_size.mean():.1f}\")\n", + "print('')\n", + "print(universe_history.amount.describe().map('{:0.3f}'.format))\n", + "universe_size.plot(title='Daily Universe Size', ylabel='Universe Size');" + ] + }, + { + "cell_type": "markdown", + "id": "e9f0a1b2", + "metadata": {}, + "source": [ + "### Daily Universe Prices\n", + "\n", + "Fetch daily price history for every symbol that appears in the universe." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "c3d4e5f6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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closehighlowopenvolume
symboltime
DNOW VR22RBI5MBFP2025-10-0415.77015.830015.33015.391016905.0
2025-10-0715.91016.260015.82215.861095631.0
2025-10-0815.51015.920015.28515.811093552.0
2025-10-0915.66015.799915.56015.65778108.0
2025-10-1014.69015.680014.69015.56952082.0
.....................
MDLN YYDBHHPS742T2025-12-2544.28045.010043.55043.954363660.0
2025-12-2744.08545.450043.61044.508118252.0
2025-12-3042.09043.800041.73543.575517778.0
2025-12-3141.82043.250041.62042.054102917.0
2026-01-0142.00043.070041.21041.945587994.0
\n", + "

816 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + " close high low open volume\n", + "symbol time \n", + "DNOW VR22RBI5MBFP 2025-10-04 15.770 15.8300 15.330 15.39 1016905.0\n", + " 2025-10-07 15.910 16.2600 15.822 15.86 1095631.0\n", + " 2025-10-08 15.510 15.9200 15.285 15.81 1093552.0\n", + " 2025-10-09 15.660 15.7999 15.560 15.65 778108.0\n", + " 2025-10-10 14.690 15.6800 14.690 15.56 952082.0\n", + "... ... ... ... ... ...\n", + "MDLN YYDBHHPS742T 2025-12-25 44.280 45.0100 43.550 43.95 4363660.0\n", + " 2025-12-27 44.085 45.4500 43.610 44.50 8118252.0\n", + " 2025-12-30 42.090 43.8000 41.735 43.57 5517778.0\n", + " 2025-12-31 41.820 43.2500 41.620 42.05 4102917.0\n", + " 2026-01-01 42.000 43.0700 41.210 41.94 5587994.0\n", + "\n", + "[816 rows x 5 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Extract unique assets\n", + "symbols = list(universe_history.index.get_level_values(1).unique())\n", + "# Fetch daily historical price metrics using the earliest timestamp available in the index.\n", + "history = qb.history(symbols, universe_history.index[0][0] - timedelta(1), qb.time, Resolution.DAILY)\n", + "history" + ] + }, + { + "cell_type": "markdown", + "id": "a7b8c9d0", + "metadata": {}, + "source": [ + "### Align Contract Volume And Returns\n", + "\n", + "Build a joined table of contract dollar volume and future returns." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "3d56c7cd", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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dollarvolumefuturereturn
timesymbol
2025-10-04DNOW VR22RBI5MBFP222382.010.027290
2025-10-08SYK R735QTJ8XC9X450063.660.024027
2025-10-10DNOW VR22RBI5MBFP294421.70-0.087404
2025-11-15SENEA R735QTJ8XC9X798649.200.031759
2025-11-18SENEA R735QTJ8XC9X798649.200.026921
\n", + "
" + ], + "text/plain": [ + " dollarvolume futurereturn\n", + "time symbol \n", + "2025-10-04 DNOW VR22RBI5MBFP 222382.01 0.027290\n", + "2025-10-08 SYK R735QTJ8XC9X 450063.66 0.024027\n", + "2025-10-10 DNOW VR22RBI5MBFP 294421.70 -0.087404\n", + "2025-11-15 SENEA R735QTJ8XC9X 798649.20 0.031759\n", + "2025-11-18 SENEA R735QTJ8XC9X 798649.20 0.026921" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset = (\n", + " universe_history.groupby(level=[0, 1]).agg(dollarvolume=('amount', 'sum')).rename_axis(['time', 'symbol'])\n", + " .join(history.open.unstack('symbol').sort_index().pct_change(2, fill_method=None).shift(-2).stack().rename('futurereturn').rename_axis(['time','symbol']), how='inner')\n", + ")\n", + "dataset.head()" + ] + }, + { + "cell_type": "markdown", + "id": "c5d6e7f8", + "metadata": {}, + "source": [ + "### Analyze Relationships Between Factor and Future Returns\n", + "\n", + "Drop the 1% outliers on each side of the factor and fit a line of best fit." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "21099a93", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Factor: dollarvolume\n", + "Observations: 46\n", + "Mean future return: 0.84%\n", + "Alpha: 1.09%\n", + "Beta: -0.00%\n", + "R-squared: 1.94%\n" + ] + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "factor = 'dollarvolume'\n", + "# Assign the factor values.\n", + "x = dataset[factor]\n", + "y = dataset['futurereturn']\n", + "# Drop the 1% outliers on each side of the factor.\n", + "lower, upper = x.quantile([0.01, 0.99])\n", + "mask = x.between(lower, upper)\n", + "x, y = x[mask], y[mask]\n", + "# Fit a simple linear model.\n", + "slope, intercept = np.polyfit(x, y, 1)\n", + "r_squared = x.corr(y) ** 2\n", + "# Print the linear model statistics.\n", + "print(f\"Factor: {factor}\")\n", + "print(f\"Observations: {len(x)}\")\n", + "print(f\"Mean future return: {y.mean():.2%}\")\n", + "print(f\"Alpha: {intercept:.2%}\")\n", + "print(f\"Beta: {slope:.2%}\")\n", + "print(f\"R-squared: {r_squared:.2%}\")\n", + "# Plot the factor values against future returns.\n", + "plt.scatter(x, y, alpha=0.6)\n", + "plt.plot(x.sort_values(), intercept + slope * x.sort_values(), color='tab:red', label='Linear fit')\n", + "plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", + "plt.title(f'{factor} vs Future Return')\n", + "plt.xlabel(factor)\n", + "plt.ylabel('Future Return')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "7ac413aa", + "metadata": {}, + "source": [ + "Create a box plot of dollar-volume quantile buckets compared to future returns." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "c7d8e9f0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Factor: dollarvolume\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Split factor values into quantile buckets.\n", + "buckets = pd.qcut(x, q=5, duplicates='drop')\n", + "# Summarize each bucket with distribution statistics.\n", + "summary = dataset.assign(bucket=buckets).groupby('bucket', observed=True).agg(\n", + " mean_factor=(factor, 'mean'),\n", + " min_future_return=('futurereturn', 'min'),\n", + " max_future_return=('futurereturn', 'max'),\n", + " mean_future_return=('futurereturn', 'mean'),\n", + " std_future_return=('futurereturn', 'std'),\n", + " observations=('futurereturn', 'size')\n", + ").reset_index()\n", + "summary['bucket'] = summary['bucket'].astype(str)\n", + "# Display the bucket summary.\n", + "print(f\"Factor: {factor}\")\n", + "display(summary.style.format({\n", + " 'mean_factor': '{:.3f}',\n", + " 'min_future_return': '{:.2%}',\n", + " 'max_future_return': '{:.2%}',\n", + " 'mean_future_return': '{:.2%}',\n", + " 'std_future_return': '{:.2%}'\n", + "}))\n", + "# Plot the return distribution for each bucket.\n", + "groups = [y[buckets == b].values for b in buckets.cat.categories]\n", + "plt.boxplot(groups, labels=[str(b) for b in buckets.cat.categories])\n", + "plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", + "plt.title(f'Future Return by {factor} Bucket')\n", + "plt.xlabel(f'{factor} Bucket')\n", + "plt.ylabel('Future Return')\n", + "plt.xticks(rotation=45)\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Foundation-Py-Default", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.14" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 3f3db7f717aa4198b37eeb7748c79793ea05291d Mon Sep 17 00:00:00 2001 From: Rudy Osuna Date: Tue, 2 Jun 2026 15:37:39 -0700 Subject: [PATCH 11/16] Delete project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb --- .../research.ipynb | 774 ------------------ 1 file changed, 774 deletions(-) delete mode 100644 project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb diff --git a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb deleted file mode 100644 index 58c092fedd..0000000000 --- a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb +++ /dev/null @@ -1,774 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "a1b2c3d4", - "metadata": {}, - "source": [ - "![QuantConnect Logo](https://cdn.quantconnect.com/web/i/icon.png)\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "e5f6a7b8", - "metadata": {}, - "source": [ - "## Quiver Government Contracts Research\n", - "\n", - "This notebook studies whether government contract dollar volume helps explain future returns" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "c9d0e1f2", - "metadata": {}, - "outputs": [], - "source": [ - "qb = QuantBook()\n", - "# Daily bars will have an end_time that matches the following midnight.\n", - "qb.settings.daily_precise_end_time = False\n", - "# Anchor the research clock to the start of 2026.\n", - "qb.set_start_date(2026, 1, 1)" - ] - }, - { - "cell_type": "markdown", - "id": "a3b4c5d6", - "metadata": {}, - "source": [ - "### Build a Government Contract Universe\n", - "\n", - "Select assets with frequent, sizable US government contracts, then inspect the returned universe history." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "e7f8a9b0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Shape: (580, 5)\n", - "Columns: ['agency', 'amount', 'description', 'time', 'value']\n" - ] - }, - { - "data": { - "text/html": [ - "
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agencyamountdescriptiontimevalue
timesymbol
2025-10-04DNOW VR22RBI5MBFPGeneral Services Administration138.6678C10M02025-10-04138.66
DNOW VR22RBI5MBFPGeneral Services Administration346.6578C10M02025-10-04346.65
DNOW VR22RBI5MBFPGeneral Services Administration452.85CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...2025-10-04452.85
DNOW VR22RBI5MBFPGeneral Services Administration905.70CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...2025-10-04905.70
DNOW VR22RBI5MBFPGeneral Services Administration374.20CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...2025-10-04374.20
\n", - "
" - ], - "text/plain": [ - " agency amount \\\n", - "time symbol \n", - "2025-10-04 DNOW VR22RBI5MBFP General Services Administration 138.66 \n", - " DNOW VR22RBI5MBFP General Services Administration 346.65 \n", - " DNOW VR22RBI5MBFP General Services Administration 452.85 \n", - " DNOW VR22RBI5MBFP General Services Administration 905.70 \n", - " DNOW VR22RBI5MBFP General Services Administration 374.20 \n", - "\n", - " description \\\n", - "time symbol \n", - "2025-10-04 DNOW VR22RBI5MBFP 78C10M0 \n", - " DNOW VR22RBI5MBFP 78C10M0 \n", - " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", - " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", - " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", - "\n", - " time value \n", - "time symbol \n", - "2025-10-04 DNOW VR22RBI5MBFP 2025-10-04 138.66 \n", - " DNOW VR22RBI5MBFP 2025-10-04 346.65 \n", - " DNOW VR22RBI5MBFP 2025-10-04 452.85 \n", - " DNOW VR22RBI5MBFP 2025-10-04 905.70 \n", - " DNOW VR22RBI5MBFP 2025-10-04 374.20 " - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def select_assets(data: List[QuiverGovernmentContractUniverse]) -> List[Symbol]:\n", - " # Group by ticker and keep names with 3+ contracts totalling over $50K.\n", - " contracts_by_symbol: dict[Symbol, list[QuiverGovernmentContractUniverse]] = {}\n", - " for d in data:\n", - " contracts_by_symbol.setdefault(d.symbol, []).append(d)\n", - " return [s for s, ds in contracts_by_symbol.items()\n", - " if len(ds) >= 3 and sum(x.amount or 0 for x in ds) > 50_000]\n", - "\n", - "# Add the Quiver Government Contract universe.\n", - "universe = qb.add_universe(QuiverGovernmentContractUniverse, select_assets)\n", - "# Request universe history of the last 90 days.\n", - "universe_history = qb.universe_history(universe, qb.time - timedelta(90), qb.time - timedelta(1), flatten=True).rename_axis(['time', 'symbol'])\n", - "# Print the returned shape and columns.\n", - "print(f\"Shape: {universe_history.shape}\")\n", - "print(f\"Columns: {list(universe_history.columns)}\")\n", - "universe_history.head()" - ] - }, - { - "cell_type": "markdown", - "id": "c1d2e3f4", - "metadata": {}, - "source": [ - "### Universe Diagnostics\n", - "\n", - "Inspects the raw contract amount distribution and visualizes how the daily universe size evolves chronologically." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "a5b6c7d8", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Universe days: 19\n", - "Mean basket size per day: 2.6\n", - "\n", - "count 580.000\n", - "mean 20138.930\n", - "std 105049.143\n", - "min 0.000\n", - "25% 259.200\n", - "50% 618.250\n", - "75% 1741.500\n", - "max 1776510.800\n", - "Name: amount, dtype: object\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Count selected assets by day.\n", - "universe_size = universe_history.groupby(level=['time', 'symbol']).size().groupby(level='time').size()\n", - "print(f\"Universe days: {len(universe_size)}\")\n", - "# Store the selected symbol list.\n", - "unique_assets = list(universe_history.index.levels[1].unique())\n", - "print(f\"Mean basket size per day: {universe_size.mean():.1f}\")\n", - "print('')\n", - "print(universe_history.amount.describe().map('{:0.3f}'.format))\n", - "universe_size.plot(title='Daily Universe Size', ylabel='Universe Size');" - ] - }, - { - "cell_type": "markdown", - "id": "e9f0a1b2", - "metadata": {}, - "source": [ - "### Daily Universe Prices\n", - "\n", - "Fetch daily price history for every symbol that appears in the universe." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "c3d4e5f6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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closehighlowopenvolume
symboltime
DNOW VR22RBI5MBFP2025-10-0415.77015.830015.33015.391016905.0
2025-10-0715.91016.260015.82215.861095631.0
2025-10-0815.51015.920015.28515.811093552.0
2025-10-0915.66015.799915.56015.65778108.0
2025-10-1014.69015.680014.69015.56952082.0
.....................
MDLN YYDBHHPS742T2025-12-2544.28045.010043.55043.954363660.0
2025-12-2744.08545.450043.61044.508118252.0
2025-12-3042.09043.800041.73543.575517778.0
2025-12-3141.82043.250041.62042.054102917.0
2026-01-0142.00043.070041.21041.945587994.0
\n", - "

816 rows × 5 columns

\n", - "
" - ], - "text/plain": [ - " close high low open volume\n", - "symbol time \n", - "DNOW VR22RBI5MBFP 2025-10-04 15.770 15.8300 15.330 15.39 1016905.0\n", - " 2025-10-07 15.910 16.2600 15.822 15.86 1095631.0\n", - " 2025-10-08 15.510 15.9200 15.285 15.81 1093552.0\n", - " 2025-10-09 15.660 15.7999 15.560 15.65 778108.0\n", - " 2025-10-10 14.690 15.6800 14.690 15.56 952082.0\n", - "... ... ... ... ... ...\n", - "MDLN YYDBHHPS742T 2025-12-25 44.280 45.0100 43.550 43.95 4363660.0\n", - " 2025-12-27 44.085 45.4500 43.610 44.50 8118252.0\n", - " 2025-12-30 42.090 43.8000 41.735 43.57 5517778.0\n", - " 2025-12-31 41.820 43.2500 41.620 42.05 4102917.0\n", - " 2026-01-01 42.000 43.0700 41.210 41.94 5587994.0\n", - "\n", - "[816 rows x 5 columns]" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Extract unique assets\n", - "symbols = list(universe_history.index.get_level_values(1).unique())\n", - "# Fetch daily historical price metrics using the earliest timestamp available in the index.\n", - "history = qb.history(symbols, universe_history.index[0][0] - timedelta(1), qb.time, Resolution.DAILY)\n", - "history" - ] - }, - { - "cell_type": "markdown", - "id": "a7b8c9d0", - "metadata": {}, - "source": [ - "### Align Contract Volume And Returns\n", - "\n", - "Build a joined table of contract dollar volume and future returns." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "3d56c7cd", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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dollarvolumefuturereturn
timesymbol
2025-10-04DNOW VR22RBI5MBFP222382.010.027290
2025-10-08SYK R735QTJ8XC9X450063.660.024027
2025-10-10DNOW VR22RBI5MBFP294421.70-0.087404
2025-11-15SENEA R735QTJ8XC9X798649.200.031759
2025-11-18SENEA R735QTJ8XC9X798649.200.026921
\n", - "
" - ], - "text/plain": [ - " dollarvolume futurereturn\n", - "time symbol \n", - "2025-10-04 DNOW VR22RBI5MBFP 222382.01 0.027290\n", - "2025-10-08 SYK R735QTJ8XC9X 450063.66 0.024027\n", - "2025-10-10 DNOW VR22RBI5MBFP 294421.70 -0.087404\n", - "2025-11-15 SENEA R735QTJ8XC9X 798649.20 0.031759\n", - "2025-11-18 SENEA R735QTJ8XC9X 798649.20 0.026921" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dataset = (\n", - " universe_history.groupby(level=[0, 1]).agg(dollarvolume=('amount', 'sum')).rename_axis(['time', 'symbol'])\n", - " .join(history.open.unstack('symbol').sort_index().pct_change(2, fill_method=None).shift(-2).stack().rename('futurereturn').rename_axis(['time','symbol']), how='inner')\n", - ")\n", - "dataset.head()" - ] - }, - { - "cell_type": "markdown", - "id": "c5d6e7f8", - "metadata": {}, - "source": [ - "### Analyze Relationships Between Factor and Future Returns\n", - "\n", - "Drop the 1% outliers on each side of the factor and fit a line of best fit." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "21099a93", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Factor: dollarvolume\n", - "Observations: 46\n", - "Mean future return: 0.84%\n", - "Alpha: 1.09%\n", - "Beta: -0.00%\n", - "R-squared: 1.94%\n" - ] - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "factor = 'dollarvolume'\n", - "# Assign the factor values.\n", - "x = dataset[factor]\n", - "y = dataset['futurereturn']\n", - "# Drop the 1% outliers on each side of the factor.\n", - "lower, upper = x.quantile([0.01, 0.99])\n", - "mask = x.between(lower, upper)\n", - "x, y = x[mask], y[mask]\n", - "# Fit a simple linear model.\n", - "slope, intercept = np.polyfit(x, y, 1)\n", - "r_squared = x.corr(y) ** 2\n", - "# Print the linear model statistics.\n", - "print(f\"Factor: {factor}\")\n", - "print(f\"Observations: {len(x)}\")\n", - "print(f\"Mean future return: {y.mean():.2%}\")\n", - "print(f\"Alpha: {intercept:.2%}\")\n", - "print(f\"Beta: {slope:.2%}\")\n", - "print(f\"R-squared: {r_squared:.2%}\")\n", - "# Plot the factor values against future returns.\n", - "plt.scatter(x, y, alpha=0.6)\n", - "plt.plot(x.sort_values(), intercept + slope * x.sort_values(), color='tab:red', label='Linear fit')\n", - "plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", - "plt.title(f'{factor} vs Future Return')\n", - "plt.xlabel(factor)\n", - "plt.ylabel('Future Return')\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "7ac413aa", - "metadata": {}, - "source": [ - "Create a box plot of dollar-volume quantile buckets compared to future returns." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "c7d8e9f0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Factor: dollarvolume\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
 bucketmean_factormin_future_returnmax_future_returnmean_future_returnstd_future_returnobservations
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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Split factor values into quantile buckets.\n", - "buckets = pd.qcut(x, q=5, duplicates='drop')\n", - "# Summarize each bucket with distribution statistics.\n", - "summary = dataset.assign(bucket=buckets).groupby('bucket', observed=True).agg(\n", - " mean_factor=(factor, 'mean'),\n", - " min_future_return=('futurereturn', 'min'),\n", - " max_future_return=('futurereturn', 'max'),\n", - " mean_future_return=('futurereturn', 'mean'),\n", - " std_future_return=('futurereturn', 'std'),\n", - " observations=('futurereturn', 'size')\n", - ").reset_index()\n", - "summary['bucket'] = summary['bucket'].astype(str)\n", - "# Display the bucket summary.\n", - "print(f\"Factor: {factor}\")\n", - "display(summary.style.format({\n", - " 'mean_factor': '{:.3f}',\n", - " 'min_future_return': '{:.2%}',\n", - " 'max_future_return': '{:.2%}',\n", - " 'mean_future_return': '{:.2%}',\n", - " 'std_future_return': '{:.2%}'\n", - "}))\n", - "# Plot the return distribution for each bucket.\n", - "groups = [y[buckets == b].values for b in buckets.cat.categories]\n", - "plt.boxplot(groups, labels=[str(b) for b in buckets.cat.categories])\n", - "plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", - "plt.title(f'Future Return by {factor} Bucket')\n", - "plt.xlabel(f'{factor} Bucket')\n", - "plt.ylabel('Future Return')\n", - "plt.xticks(rotation=45)\n", - "plt.show()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Foundation-Py-Default", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.14" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From bd3fe4f602a05a0c15e683cefcbfd1dc9e34618c Mon Sep 17 00:00:00 2001 From: Rudy Osuna Date: Tue, 2 Jun 2026 15:38:20 -0700 Subject: [PATCH 12/16] fix --- .../research.ipynb | 767 ++++++++++++++++++ 1 file changed, 767 insertions(+) create mode 100644 project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb diff --git a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb new file mode 100644 index 0000000000..161de77ea6 --- /dev/null +++ b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb @@ -0,0 +1,767 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "a1b2c3d4", + "metadata": {}, + "source": [ + "![QuantConnect Logo](https://cdn.quantconnect.com/web/i/icon.png)\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "e5f6a7b8", + "metadata": {}, + "source": [ + "## Quiver Government Contracts Research\n", + "\n", + "This notebook studies whether government contract dollar volume helps explain future returns" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "c9d0e1f2", + "metadata": {}, + "outputs": [], + "source": [ + "qb = QuantBook()\n", + "# Daily bars will have an end_time that matches the following midnight.\n", + "qb.settings.daily_precise_end_time = False\n", + "# Anchor the research clock to the start of 2026.\n", + "qb.set_start_date(2026, 1, 1)" + ] + }, + { + "cell_type": "markdown", + "id": "a3b4c5d6", + "metadata": {}, + "source": [ + "### Build a Government Contract Universe\n", + "\n", + "Select assets with frequent, sizable US government contracts, then inspect the returned universe history." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "e7f8a9b0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Shape: (580, 4)\n", + "Columns: ['agency', 'amount', 'description', 'value']\n" + ] + }, + { + "data": { + "text/html": [ + "
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agencyamountdescriptionvalue
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2025-10-04DNOW VR22RBI5MBFPGeneral Services Administration138.6678C10M0138.66
DNOW VR22RBI5MBFPGeneral Services Administration346.6578C10M0346.65
DNOW VR22RBI5MBFPGeneral Services Administration452.85CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...452.85
DNOW VR22RBI5MBFPGeneral Services Administration905.70CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...905.70
DNOW VR22RBI5MBFPGeneral Services Administration374.20CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...374.20
\n", + "
" + ], + "text/plain": [ + " agency amount \\\n", + "time symbol \n", + "2025-10-04 DNOW VR22RBI5MBFP General Services Administration 138.66 \n", + " DNOW VR22RBI5MBFP General Services Administration 346.65 \n", + " DNOW VR22RBI5MBFP General Services Administration 452.85 \n", + " DNOW VR22RBI5MBFP General Services Administration 905.70 \n", + " DNOW VR22RBI5MBFP General Services Administration 374.20 \n", + "\n", + " description \\\n", + "time symbol \n", + "2025-10-04 DNOW VR22RBI5MBFP 78C10M0 \n", + " DNOW VR22RBI5MBFP 78C10M0 \n", + " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", + " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", + " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", + "\n", + " value \n", + "time symbol \n", + "2025-10-04 DNOW VR22RBI5MBFP 138.66 \n", + " DNOW VR22RBI5MBFP 346.65 \n", + " DNOW VR22RBI5MBFP 452.85 \n", + " DNOW VR22RBI5MBFP 905.70 \n", + " DNOW VR22RBI5MBFP 374.20 " + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def select_assets(data: List[QuiverGovernmentContractUniverse]) -> List[Symbol]:\n", + " # Group by ticker and keep names with 3+ contracts totalling over $50K.\n", + " contracts_by_symbol: dict[Symbol, list[QuiverGovernmentContractUniverse]] = {}\n", + " for d in data:\n", + " contracts_by_symbol.setdefault(d.symbol, []).append(d)\n", + " return [s for s, ds in contracts_by_symbol.items()\n", + " if len(ds) >= 3 and sum(x.amount or 0 for x in ds) > 50_000]\n", + "\n", + "# Add the Quiver Government Contract universe.\n", + "universe = qb.add_universe(QuiverGovernmentContractUniverse, select_assets)\n", + "# Request universe history of the last 90 days.\n", + "universe_history = qb.universe_history(universe, qb.time - timedelta(90), qb.time - timedelta(1), flatten=True).rename_axis(['time', 'symbol']).drop(columns=['time'])\n", + "# Print the returned shape and columns.\n", + "print(f\"Shape: {universe_history.shape}\")\n", + "print(f\"Columns: {list(universe_history.columns)}\")\n", + "universe_history.head()" + ] + }, + { + "cell_type": "markdown", + "id": "c1d2e3f4", + "metadata": {}, + "source": [ + "### Universe Diagnostics\n", + "\n", + "Inspects the raw contract amount distribution and visualizes how the daily universe size evolves chronologically." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a5b6c7d8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Universe days: 19\n", + "Mean basket size per day: 2.6\n", + "\n", + "count 580.000\n", + "mean 20138.930\n", + "std 105049.143\n", + "min 0.000\n", + "25% 259.200\n", + "50% 618.250\n", + "75% 1741.500\n", + "max 1776510.800\n", + "Name: amount, dtype: object\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Count selected assets by day.\n", + "universe_size = universe_history.reset_index().groupby(['time', 'symbol']).size().groupby('time').size()\n", + "print(f\"Universe days: {len(universe_size)}\")\n", + "# Store the selected symbol list.\n", + "unique_assets = list(universe_history.index.levels[1].unique())\n", + "print(f\"Mean basket size per day: {universe_size.mean():.1f}\")\n", + "print('')\n", + "print(universe_history.amount.describe().map('{:0.3f}'.format))\n", + "universe_size.plot(title='Daily Universe Size', ylabel='Universe Size');" + ] + }, + { + "cell_type": "markdown", + "id": "e9f0a1b2", + "metadata": {}, + "source": [ + "### Daily Universe Prices\n", + "\n", + "Fetch daily price history for every symbol that appears in the universe." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "c3d4e5f6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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closehighlowopenvolume
symboltime
DNOW VR22RBI5MBFP2025-10-0415.77015.830015.33015.391016905.0
2025-10-0715.91016.260015.82215.861095631.0
2025-10-0815.51015.920015.28515.811093552.0
2025-10-0915.66015.799915.56015.65778108.0
2025-10-1014.69015.680014.69015.56952082.0
.....................
MDLN YYDBHHPS742T2025-12-2544.28045.010043.55043.954363660.0
2025-12-2744.08545.450043.61044.508118252.0
2025-12-3042.09043.800041.73543.575517778.0
2025-12-3141.82043.250041.62042.054102917.0
2026-01-0142.00043.070041.21041.945587994.0
\n", + "

816 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + " close high low open volume\n", + "symbol time \n", + "DNOW VR22RBI5MBFP 2025-10-04 15.770 15.8300 15.330 15.39 1016905.0\n", + " 2025-10-07 15.910 16.2600 15.822 15.86 1095631.0\n", + " 2025-10-08 15.510 15.9200 15.285 15.81 1093552.0\n", + " 2025-10-09 15.660 15.7999 15.560 15.65 778108.0\n", + " 2025-10-10 14.690 15.6800 14.690 15.56 952082.0\n", + "... ... ... ... ... ...\n", + "MDLN YYDBHHPS742T 2025-12-25 44.280 45.0100 43.550 43.95 4363660.0\n", + " 2025-12-27 44.085 45.4500 43.610 44.50 8118252.0\n", + " 2025-12-30 42.090 43.8000 41.735 43.57 5517778.0\n", + " 2025-12-31 41.820 43.2500 41.620 42.05 4102917.0\n", + " 2026-01-01 42.000 43.0700 41.210 41.94 5587994.0\n", + "\n", + "[816 rows x 5 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Extract unique assets\n", + "symbols = list(universe_history.index.get_level_values(1).unique())\n", + "# Fetch daily historical price metrics using the earliest timestamp available in the index.\n", + "history = qb.history(symbols, universe_history.index[0][0] - timedelta(1), qb.time, Resolution.DAILY)\n", + "history" + ] + }, + { + "cell_type": "markdown", + "id": "a7b8c9d0", + "metadata": {}, + "source": [ + "### Align Contract Volume And Returns\n", + "\n", + "Build a joined table of contract dollar volume and future returns." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "3d56c7cd", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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dollarvolumefuturereturn
timesymbol
2025-10-04DNOW VR22RBI5MBFP222382.010.027290
2025-10-08SYK R735QTJ8XC9X450063.660.024027
2025-10-10DNOW VR22RBI5MBFP294421.70-0.087404
2025-11-15SENEA R735QTJ8XC9X798649.200.031759
2025-11-18SENEA R735QTJ8XC9X798649.200.026921
\n", + "
" + ], + "text/plain": [ + " dollarvolume futurereturn\n", + "time symbol \n", + "2025-10-04 DNOW VR22RBI5MBFP 222382.01 0.027290\n", + "2025-10-08 SYK R735QTJ8XC9X 450063.66 0.024027\n", + "2025-10-10 DNOW VR22RBI5MBFP 294421.70 -0.087404\n", + "2025-11-15 SENEA R735QTJ8XC9X 798649.20 0.031759\n", + "2025-11-18 SENEA R735QTJ8XC9X 798649.20 0.026921" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset = (\n", + " universe_history.groupby(level=['time', 'symbol']).agg(dollarvolume=('amount', 'sum'))\n", + " .join(history.open.unstack('symbol').sort_index().pct_change(2, fill_method=None).shift(-2).stack().rename('futurereturn').rename_axis(['time','symbol']), how='inner')\n", + ")\n", + "dataset.head()" + ] + }, + { + "cell_type": "markdown", + "id": "c5d6e7f8", + "metadata": {}, + "source": [ + "### Analyze Relationships Between Factor and Future Returns\n", + "\n", + "Drop the 1% outliers on each side of the factor and fit a line of best fit." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "21099a93", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Factor: dollarvolume\n", + "Observations: 46\n", + "Mean future return: 0.84%\n", + "Alpha: 1.09%\n", + "Beta: -0.00%\n", + "R-squared: 1.94%\n" + ] + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "factor = 'dollarvolume'\n", + "# Assign the factor values.\n", + "x = dataset[factor]\n", + "y = dataset['futurereturn']\n", + "# Drop the 1% outliers on each side of the factor.\n", + "lower, upper = x.quantile([0.01, 0.99])\n", + "mask = x.between(lower, upper)\n", + "x, y = x[mask], y[mask]\n", + "# Fit a simple linear model.\n", + "slope, intercept = np.polyfit(x, y, 1)\n", + "r_squared = x.corr(y) ** 2\n", + "# Print the linear model statistics.\n", + "print(f\"Factor: {factor}\")\n", + "print(f\"Observations: {len(x)}\")\n", + "print(f\"Mean future return: {y.mean():.2%}\")\n", + "print(f\"Alpha: {intercept:.2%}\")\n", + "print(f\"Beta: {slope:.2%}\")\n", + "print(f\"R-squared: {r_squared:.2%}\")\n", + "# Plot the factor values against future returns.\n", + "plt.scatter(x, y, alpha=0.6)\n", + "plt.plot(x.sort_values(), intercept + slope * x.sort_values(), color='tab:red', label='Linear fit')\n", + "plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", + "plt.title(f'{factor} vs Future Return')\n", + "plt.xlabel(factor)\n", + "plt.ylabel('Future Return')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "7ac413aa", + "metadata": {}, + "source": [ + "Create a box plot of dollar-volume quantile buckets compared to future returns." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "c7d8e9f0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Factor: dollarvolume\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Split factor values into quantile buckets.\n", + "buckets = pd.qcut(x, q=5, duplicates='drop')\n", + "# Summarize each bucket with distribution statistics.\n", + "summary = dataset.assign(bucket=buckets).groupby('bucket', observed=True).agg(\n", + " mean_factor=(factor, 'mean'),\n", + " min_future_return=('futurereturn', 'min'),\n", + " max_future_return=('futurereturn', 'max'),\n", + " mean_future_return=('futurereturn', 'mean'),\n", + " std_future_return=('futurereturn', 'std'),\n", + " observations=('futurereturn', 'size')\n", + ").reset_index()\n", + "summary['bucket'] = summary['bucket'].astype(str)\n", + "# Display the bucket summary.\n", + "print(f\"Factor: {factor}\")\n", + "display(summary.style.format({\n", + " 'mean_factor': '{:.3f}',\n", + " 'min_future_return': '{:.2%}',\n", + " 'max_future_return': '{:.2%}',\n", + " 'mean_future_return': '{:.2%}',\n", + " 'std_future_return': '{:.2%}'\n", + "}))\n", + "# Plot the return distribution for each bucket.\n", + "groups = [y[buckets == b].values for b in buckets.cat.categories]\n", + "plt.boxplot(groups, labels=[str(b) for b in buckets.cat.categories])\n", + "plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", + "plt.title(f'Future Return by {factor} Bucket')\n", + "plt.xlabel(f'{factor} Bucket')\n", + "plt.ylabel('Future Return')\n", + "plt.xticks(rotation=45)\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Foundation-Py-Default", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.14" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From b1691c53e7ace07da096398b4c119004d4ade066 Mon Sep 17 00:00:00 2001 From: Rudy Osuna Date: Tue, 2 Jun 2026 15:45:00 -0700 Subject: [PATCH 13/16] Delete project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb --- .../research.ipynb | 767 ------------------ 1 file changed, 767 deletions(-) delete mode 100644 project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb diff --git a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb deleted file mode 100644 index 161de77ea6..0000000000 --- a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb +++ /dev/null @@ -1,767 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "a1b2c3d4", - "metadata": {}, - "source": [ - "![QuantConnect Logo](https://cdn.quantconnect.com/web/i/icon.png)\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "e5f6a7b8", - "metadata": {}, - "source": [ - "## Quiver Government Contracts Research\n", - "\n", - "This notebook studies whether government contract dollar volume helps explain future returns" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "c9d0e1f2", - "metadata": {}, - "outputs": [], - "source": [ - "qb = QuantBook()\n", - "# Daily bars will have an end_time that matches the following midnight.\n", - "qb.settings.daily_precise_end_time = False\n", - "# Anchor the research clock to the start of 2026.\n", - "qb.set_start_date(2026, 1, 1)" - ] - }, - { - "cell_type": "markdown", - "id": "a3b4c5d6", - "metadata": {}, - "source": [ - "### Build a Government Contract Universe\n", - "\n", - "Select assets with frequent, sizable US government contracts, then inspect the returned universe history." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "e7f8a9b0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Shape: (580, 4)\n", - "Columns: ['agency', 'amount', 'description', 'value']\n" - ] - }, - { - "data": { - "text/html": [ - "
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agencyamountdescriptionvalue
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2025-10-04DNOW VR22RBI5MBFPGeneral Services Administration138.6678C10M0138.66
DNOW VR22RBI5MBFPGeneral Services Administration346.6578C10M0346.65
DNOW VR22RBI5MBFPGeneral Services Administration452.85CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...452.85
DNOW VR22RBI5MBFPGeneral Services Administration905.70CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...905.70
DNOW VR22RBI5MBFPGeneral Services Administration374.20CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...374.20
\n", - "
" - ], - "text/plain": [ - " agency amount \\\n", - "time symbol \n", - "2025-10-04 DNOW VR22RBI5MBFP General Services Administration 138.66 \n", - " DNOW VR22RBI5MBFP General Services Administration 346.65 \n", - " DNOW VR22RBI5MBFP General Services Administration 452.85 \n", - " DNOW VR22RBI5MBFP General Services Administration 905.70 \n", - " DNOW VR22RBI5MBFP General Services Administration 374.20 \n", - "\n", - " description \\\n", - "time symbol \n", - "2025-10-04 DNOW VR22RBI5MBFP 78C10M0 \n", - " DNOW VR22RBI5MBFP 78C10M0 \n", - " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", - " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", - " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", - "\n", - " value \n", - "time symbol \n", - "2025-10-04 DNOW VR22RBI5MBFP 138.66 \n", - " DNOW VR22RBI5MBFP 346.65 \n", - " DNOW VR22RBI5MBFP 452.85 \n", - " DNOW VR22RBI5MBFP 905.70 \n", - " DNOW VR22RBI5MBFP 374.20 " - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def select_assets(data: List[QuiverGovernmentContractUniverse]) -> List[Symbol]:\n", - " # Group by ticker and keep names with 3+ contracts totalling over $50K.\n", - " contracts_by_symbol: dict[Symbol, list[QuiverGovernmentContractUniverse]] = {}\n", - " for d in data:\n", - " contracts_by_symbol.setdefault(d.symbol, []).append(d)\n", - " return [s for s, ds in contracts_by_symbol.items()\n", - " if len(ds) >= 3 and sum(x.amount or 0 for x in ds) > 50_000]\n", - "\n", - "# Add the Quiver Government Contract universe.\n", - "universe = qb.add_universe(QuiverGovernmentContractUniverse, select_assets)\n", - "# Request universe history of the last 90 days.\n", - "universe_history = qb.universe_history(universe, qb.time - timedelta(90), qb.time - timedelta(1), flatten=True).rename_axis(['time', 'symbol']).drop(columns=['time'])\n", - "# Print the returned shape and columns.\n", - "print(f\"Shape: {universe_history.shape}\")\n", - "print(f\"Columns: {list(universe_history.columns)}\")\n", - "universe_history.head()" - ] - }, - { - "cell_type": "markdown", - "id": "c1d2e3f4", - "metadata": {}, - "source": [ - "### Universe Diagnostics\n", - "\n", - "Inspects the raw contract amount distribution and visualizes how the daily universe size evolves chronologically." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "a5b6c7d8", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Universe days: 19\n", - "Mean basket size per day: 2.6\n", - "\n", - "count 580.000\n", - "mean 20138.930\n", - "std 105049.143\n", - "min 0.000\n", - "25% 259.200\n", - "50% 618.250\n", - "75% 1741.500\n", - "max 1776510.800\n", - "Name: amount, dtype: object\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Count selected assets by day.\n", - "universe_size = universe_history.reset_index().groupby(['time', 'symbol']).size().groupby('time').size()\n", - "print(f\"Universe days: {len(universe_size)}\")\n", - "# Store the selected symbol list.\n", - "unique_assets = list(universe_history.index.levels[1].unique())\n", - "print(f\"Mean basket size per day: {universe_size.mean():.1f}\")\n", - "print('')\n", - "print(universe_history.amount.describe().map('{:0.3f}'.format))\n", - "universe_size.plot(title='Daily Universe Size', ylabel='Universe Size');" - ] - }, - { - "cell_type": "markdown", - "id": "e9f0a1b2", - "metadata": {}, - "source": [ - "### Daily Universe Prices\n", - "\n", - "Fetch daily price history for every symbol that appears in the universe." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "c3d4e5f6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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closehighlowopenvolume
symboltime
DNOW VR22RBI5MBFP2025-10-0415.77015.830015.33015.391016905.0
2025-10-0715.91016.260015.82215.861095631.0
2025-10-0815.51015.920015.28515.811093552.0
2025-10-0915.66015.799915.56015.65778108.0
2025-10-1014.69015.680014.69015.56952082.0
.....................
MDLN YYDBHHPS742T2025-12-2544.28045.010043.55043.954363660.0
2025-12-2744.08545.450043.61044.508118252.0
2025-12-3042.09043.800041.73543.575517778.0
2025-12-3141.82043.250041.62042.054102917.0
2026-01-0142.00043.070041.21041.945587994.0
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816 rows × 5 columns

\n", - "
" - ], - "text/plain": [ - " close high low open volume\n", - "symbol time \n", - "DNOW VR22RBI5MBFP 2025-10-04 15.770 15.8300 15.330 15.39 1016905.0\n", - " 2025-10-07 15.910 16.2600 15.822 15.86 1095631.0\n", - " 2025-10-08 15.510 15.9200 15.285 15.81 1093552.0\n", - " 2025-10-09 15.660 15.7999 15.560 15.65 778108.0\n", - " 2025-10-10 14.690 15.6800 14.690 15.56 952082.0\n", - "... ... ... ... ... ...\n", - "MDLN YYDBHHPS742T 2025-12-25 44.280 45.0100 43.550 43.95 4363660.0\n", - " 2025-12-27 44.085 45.4500 43.610 44.50 8118252.0\n", - " 2025-12-30 42.090 43.8000 41.735 43.57 5517778.0\n", - " 2025-12-31 41.820 43.2500 41.620 42.05 4102917.0\n", - " 2026-01-01 42.000 43.0700 41.210 41.94 5587994.0\n", - "\n", - "[816 rows x 5 columns]" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Extract unique assets\n", - "symbols = list(universe_history.index.get_level_values(1).unique())\n", - "# Fetch daily historical price metrics using the earliest timestamp available in the index.\n", - "history = qb.history(symbols, universe_history.index[0][0] - timedelta(1), qb.time, Resolution.DAILY)\n", - "history" - ] - }, - { - "cell_type": "markdown", - "id": "a7b8c9d0", - "metadata": {}, - "source": [ - "### Align Contract Volume And Returns\n", - "\n", - "Build a joined table of contract dollar volume and future returns." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "3d56c7cd", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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dollarvolumefuturereturn
timesymbol
2025-10-04DNOW VR22RBI5MBFP222382.010.027290
2025-10-08SYK R735QTJ8XC9X450063.660.024027
2025-10-10DNOW VR22RBI5MBFP294421.70-0.087404
2025-11-15SENEA R735QTJ8XC9X798649.200.031759
2025-11-18SENEA R735QTJ8XC9X798649.200.026921
\n", - "
" - ], - "text/plain": [ - " dollarvolume futurereturn\n", - "time symbol \n", - "2025-10-04 DNOW VR22RBI5MBFP 222382.01 0.027290\n", - "2025-10-08 SYK R735QTJ8XC9X 450063.66 0.024027\n", - "2025-10-10 DNOW VR22RBI5MBFP 294421.70 -0.087404\n", - "2025-11-15 SENEA R735QTJ8XC9X 798649.20 0.031759\n", - "2025-11-18 SENEA R735QTJ8XC9X 798649.20 0.026921" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dataset = (\n", - " universe_history.groupby(level=['time', 'symbol']).agg(dollarvolume=('amount', 'sum'))\n", - " .join(history.open.unstack('symbol').sort_index().pct_change(2, fill_method=None).shift(-2).stack().rename('futurereturn').rename_axis(['time','symbol']), how='inner')\n", - ")\n", - "dataset.head()" - ] - }, - { - "cell_type": "markdown", - "id": "c5d6e7f8", - "metadata": {}, - "source": [ - "### Analyze Relationships Between Factor and Future Returns\n", - "\n", - "Drop the 1% outliers on each side of the factor and fit a line of best fit." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "21099a93", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Factor: dollarvolume\n", - "Observations: 46\n", - "Mean future return: 0.84%\n", - "Alpha: 1.09%\n", - "Beta: -0.00%\n", - "R-squared: 1.94%\n" - ] - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "factor = 'dollarvolume'\n", - "# Assign the factor values.\n", - "x = dataset[factor]\n", - "y = dataset['futurereturn']\n", - "# Drop the 1% outliers on each side of the factor.\n", - "lower, upper = x.quantile([0.01, 0.99])\n", - "mask = x.between(lower, upper)\n", - "x, y = x[mask], y[mask]\n", - "# Fit a simple linear model.\n", - "slope, intercept = np.polyfit(x, y, 1)\n", - "r_squared = x.corr(y) ** 2\n", - "# Print the linear model statistics.\n", - "print(f\"Factor: {factor}\")\n", - "print(f\"Observations: {len(x)}\")\n", - "print(f\"Mean future return: {y.mean():.2%}\")\n", - "print(f\"Alpha: {intercept:.2%}\")\n", - "print(f\"Beta: {slope:.2%}\")\n", - "print(f\"R-squared: {r_squared:.2%}\")\n", - "# Plot the factor values against future returns.\n", - "plt.scatter(x, y, alpha=0.6)\n", - "plt.plot(x.sort_values(), intercept + slope * x.sort_values(), color='tab:red', label='Linear fit')\n", - "plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", - "plt.title(f'{factor} vs Future Return')\n", - "plt.xlabel(factor)\n", - "plt.ylabel('Future Return')\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "7ac413aa", - "metadata": {}, - "source": [ - "Create a box plot of dollar-volume quantile buckets compared to future returns." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "c7d8e9f0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Factor: dollarvolume\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
 bucketmean_factormin_future_returnmax_future_returnmean_future_returnstd_future_returnobservations
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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Split factor values into quantile buckets.\n", - "buckets = pd.qcut(x, q=5, duplicates='drop')\n", - "# Summarize each bucket with distribution statistics.\n", - "summary = dataset.assign(bucket=buckets).groupby('bucket', observed=True).agg(\n", - " mean_factor=(factor, 'mean'),\n", - " min_future_return=('futurereturn', 'min'),\n", - " max_future_return=('futurereturn', 'max'),\n", - " mean_future_return=('futurereturn', 'mean'),\n", - " std_future_return=('futurereturn', 'std'),\n", - " observations=('futurereturn', 'size')\n", - ").reset_index()\n", - "summary['bucket'] = summary['bucket'].astype(str)\n", - "# Display the bucket summary.\n", - "print(f\"Factor: {factor}\")\n", - "display(summary.style.format({\n", - " 'mean_factor': '{:.3f}',\n", - " 'min_future_return': '{:.2%}',\n", - " 'max_future_return': '{:.2%}',\n", - " 'mean_future_return': '{:.2%}',\n", - " 'std_future_return': '{:.2%}'\n", - "}))\n", - "# Plot the return distribution for each bucket.\n", - "groups = [y[buckets == b].values for b in buckets.cat.categories]\n", - "plt.boxplot(groups, labels=[str(b) for b in buckets.cat.categories])\n", - "plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", - "plt.title(f'Future Return by {factor} Bucket')\n", - "plt.xlabel(f'{factor} Bucket')\n", - "plt.ylabel('Future Return')\n", - "plt.xticks(rotation=45)\n", - "plt.show()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Foundation-Py-Default", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.14" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From 7994d79ecb34ef5fe25c3cb0d649d558339185f3 Mon Sep 17 00:00:00 2001 From: Rudy Osuna Date: Tue, 2 Jun 2026 15:45:11 -0700 Subject: [PATCH 14/16] fix --- .../research.ipynb | 767 ++++++++++++++++++ 1 file changed, 767 insertions(+) create mode 100644 project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb diff --git a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb new file mode 100644 index 0000000000..1d3f3e21b1 --- /dev/null +++ b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb @@ -0,0 +1,767 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "a1b2c3d4", + "metadata": {}, + "source": [ + "![QuantConnect Logo](https://cdn.quantconnect.com/web/i/icon.png)\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "e5f6a7b8", + "metadata": {}, + "source": [ + "## Quiver Government Contracts Research\n", + "\n", + "This notebook studies whether government contract dollar volume helps explain future returns" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "c9d0e1f2", + "metadata": {}, + "outputs": [], + "source": [ + "qb = QuantBook()\n", + "# Daily bars will have an end_time that matches the following midnight.\n", + "qb.settings.daily_precise_end_time = False\n", + "# Anchor the research clock to the start of 2026.\n", + "qb.set_start_date(2026, 1, 1)" + ] + }, + { + "cell_type": "markdown", + "id": "a3b4c5d6", + "metadata": {}, + "source": [ + "### Build a Government Contract Universe\n", + "\n", + "Select assets with frequent, sizable US government contracts, then inspect the returned universe history." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "e7f8a9b0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Shape: (580, 4)\n", + "Columns: ['agency', 'amount', 'description', 'value']\n" + ] + }, + { + "data": { + "text/html": [ + "
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agencyamountdescriptionvalue
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2025-10-04DNOW VR22RBI5MBFPGeneral Services Administration138.6678C10M0138.66
DNOW VR22RBI5MBFPGeneral Services Administration346.6578C10M0346.65
DNOW VR22RBI5MBFPGeneral Services Administration452.85CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...452.85
DNOW VR22RBI5MBFPGeneral Services Administration905.70CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...905.70
DNOW VR22RBI5MBFPGeneral Services Administration374.20CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...374.20
\n", + "
" + ], + "text/plain": [ + " agency amount \\\n", + "time symbol \n", + "2025-10-04 DNOW VR22RBI5MBFP General Services Administration 138.66 \n", + " DNOW VR22RBI5MBFP General Services Administration 346.65 \n", + " DNOW VR22RBI5MBFP General Services Administration 452.85 \n", + " DNOW VR22RBI5MBFP General Services Administration 905.70 \n", + " DNOW VR22RBI5MBFP General Services Administration 374.20 \n", + "\n", + " description \\\n", + "time symbol \n", + "2025-10-04 DNOW VR22RBI5MBFP 78C10M0 \n", + " DNOW VR22RBI5MBFP 78C10M0 \n", + " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", + " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", + " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", + "\n", + " value \n", + "time symbol \n", + "2025-10-04 DNOW VR22RBI5MBFP 138.66 \n", + " DNOW VR22RBI5MBFP 346.65 \n", + " DNOW VR22RBI5MBFP 452.85 \n", + " DNOW VR22RBI5MBFP 905.70 \n", + " DNOW VR22RBI5MBFP 374.20 " + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def select_assets(data: List[QuiverGovernmentContractUniverse]) -> List[Symbol]:\n", + " # Group by ticker and keep names with 3+ contracts totalling over $50K.\n", + " contracts_by_symbol: dict[Symbol, list[QuiverGovernmentContractUniverse]] = {}\n", + " for d in data:\n", + " contracts_by_symbol.setdefault(d.symbol, []).append(d)\n", + " return [s for s, ds in contracts_by_symbol.items()\n", + " if len(ds) >= 3 and sum(x.amount or 0 for x in ds) > 50_000]\n", + "\n", + "# Add the Quiver Government Contract universe.\n", + "universe = qb.add_universe(QuiverGovernmentContractUniverse, select_assets)\n", + "# Request universe history of the last 90 days.\n", + "universe_history = qb.universe_history(universe, qb.time - timedelta(90), qb.time - timedelta(1), flatten=True).rename_axis(['time', 'symbol']).drop(columns=['time'])\n", + "# Print the returned shape and columns.\n", + "print(f\"Shape: {universe_history.shape}\")\n", + "print(f\"Columns: {list(universe_history.columns)}\")\n", + "universe_history.head()" + ] + }, + { + "cell_type": "markdown", + "id": "c1d2e3f4", + "metadata": {}, + "source": [ + "### Universe Diagnostics\n", + "\n", + "Inspects the raw contract amount distribution and visualizes how the daily universe size evolves chronologically." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a5b6c7d8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Universe days: 19\n", + "Mean basket size per day: 2.6\n", + "\n", + "count 580.000\n", + "mean 20138.930\n", + "std 105049.143\n", + "min 0.000\n", + "25% 259.200\n", + "50% 618.250\n", + "75% 1741.500\n", + "max 1776510.800\n", + "Name: amount, dtype: object\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Count selected assets by day.\n", + "universe_size = universe_history.reset_index().groupby(['time', 'symbol']).size().groupby('time').size()\n", + "print(f\"Universe days: {len(universe_size)}\")\n", + "# Store the selected symbol list.\n", + "unique_assets = list(universe_history.index.levels[1].unique())\n", + "print(f\"Mean basket size per day: {universe_size.mean():.1f}\")\n", + "print('')\n", + "print(universe_history.amount.describe().map('{:0.3f}'.format))\n", + "universe_size.plot(title='Daily Universe Size', ylabel='Universe Size');" + ] + }, + { + "cell_type": "markdown", + "id": "e9f0a1b2", + "metadata": {}, + "source": [ + "### Daily Universe Prices\n", + "\n", + "Fetch daily price history for every symbol that appears in the universe." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "c3d4e5f6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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closehighlowopenvolume
symboltime
DNOW VR22RBI5MBFP2025-10-0415.77015.830015.33015.391016905.0
2025-10-0715.91016.260015.82215.861095631.0
2025-10-0815.51015.920015.28515.811093552.0
2025-10-0915.66015.799915.56015.65778108.0
2025-10-1014.69015.680014.69015.56952082.0
.....................
MDLN YYDBHHPS742T2025-12-2544.28045.010043.55043.954363660.0
2025-12-2744.08545.450043.61044.508118252.0
2025-12-3042.09043.800041.73543.575517778.0
2025-12-3141.82043.250041.62042.054102917.0
2026-01-0142.00043.070041.21041.945587994.0
\n", + "

816 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + " close high low open volume\n", + "symbol time \n", + "DNOW VR22RBI5MBFP 2025-10-04 15.770 15.8300 15.330 15.39 1016905.0\n", + " 2025-10-07 15.910 16.2600 15.822 15.86 1095631.0\n", + " 2025-10-08 15.510 15.9200 15.285 15.81 1093552.0\n", + " 2025-10-09 15.660 15.7999 15.560 15.65 778108.0\n", + " 2025-10-10 14.690 15.6800 14.690 15.56 952082.0\n", + "... ... ... ... ... ...\n", + "MDLN YYDBHHPS742T 2025-12-25 44.280 45.0100 43.550 43.95 4363660.0\n", + " 2025-12-27 44.085 45.4500 43.610 44.50 8118252.0\n", + " 2025-12-30 42.090 43.8000 41.735 43.57 5517778.0\n", + " 2025-12-31 41.820 43.2500 41.620 42.05 4102917.0\n", + " 2026-01-01 42.000 43.0700 41.210 41.94 5587994.0\n", + "\n", + "[816 rows x 5 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Extract unique assets\n", + "symbols = list(universe_history.index.get_level_values(1).unique())\n", + "# Fetch daily historical price metrics using the earliest timestamp available in the index.\n", + "history = qb.history(symbols, universe_history.index[0][0] - timedelta(1), qb.time, Resolution.DAILY)\n", + "history" + ] + }, + { + "cell_type": "markdown", + "id": "a7b8c9d0", + "metadata": {}, + "source": [ + "### Align Contract Volume And Returns\n", + "\n", + "Build a joined table of contract dollar volume and future returns." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "3d56c7cd", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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dollarvolumefuturereturn
timesymbol
2025-10-04DNOW VR22RBI5MBFP222382.010.027290
2025-10-08SYK R735QTJ8XC9X450063.660.024027
2025-10-10DNOW VR22RBI5MBFP294421.70-0.087404
2025-11-15SENEA R735QTJ8XC9X798649.200.031759
2025-11-18SENEA R735QTJ8XC9X798649.200.026921
\n", + "
" + ], + "text/plain": [ + " dollarvolume futurereturn\n", + "time symbol \n", + "2025-10-04 DNOW VR22RBI5MBFP 222382.01 0.027290\n", + "2025-10-08 SYK R735QTJ8XC9X 450063.66 0.024027\n", + "2025-10-10 DNOW VR22RBI5MBFP 294421.70 -0.087404\n", + "2025-11-15 SENEA R735QTJ8XC9X 798649.20 0.031759\n", + "2025-11-18 SENEA R735QTJ8XC9X 798649.20 0.026921" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset = (\n", + " universe_history.reset_index().groupby(['time', 'symbol']).agg(dollarvolume=('amount', 'sum'))\n", + " .join(history.open.unstack('symbol').sort_index().pct_change(2, fill_method=None).shift(-2).stack().rename('futurereturn').rename_axis(['time','symbol']), how='inner')\n", + ")\n", + "dataset.head()" + ] + }, + { + "cell_type": "markdown", + "id": "c5d6e7f8", + "metadata": {}, + "source": [ + "### Analyze Relationships Between Factor and Future Returns\n", + "\n", + "Drop the 1% outliers on each side of the factor and fit a line of best fit." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "21099a93", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Factor: dollarvolume\n", + "Observations: 46\n", + "Mean future return: 0.84%\n", + "Alpha: 1.09%\n", + "Beta: -0.00%\n", + "R-squared: 1.94%\n" + ] + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "factor = 'dollarvolume'\n", + "# Assign the factor values.\n", + "x = dataset[factor]\n", + "y = dataset['futurereturn']\n", + "# Drop the 1% outliers on each side of the factor.\n", + "lower, upper = x.quantile([0.01, 0.99])\n", + "mask = x.between(lower, upper)\n", + "x, y = x[mask], y[mask]\n", + "# Fit a simple linear model.\n", + "slope, intercept = np.polyfit(x, y, 1)\n", + "r_squared = x.corr(y) ** 2\n", + "# Print the linear model statistics.\n", + "print(f\"Factor: {factor}\")\n", + "print(f\"Observations: {len(x)}\")\n", + "print(f\"Mean future return: {y.mean():.2%}\")\n", + "print(f\"Alpha: {intercept:.2%}\")\n", + "print(f\"Beta: {slope:.2%}\")\n", + "print(f\"R-squared: {r_squared:.2%}\")\n", + "# Plot the factor values against future returns.\n", + "plt.scatter(x, y, alpha=0.6)\n", + "plt.plot(x.sort_values(), intercept + slope * x.sort_values(), color='tab:red', label='Linear fit')\n", + "plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", + "plt.title(f'{factor} vs Future Return')\n", + "plt.xlabel(factor)\n", + "plt.ylabel('Future Return')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "7ac413aa", + "metadata": {}, + "source": [ + "Create a box plot of dollar-volume quantile buckets compared to future returns." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "c7d8e9f0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Factor: dollarvolume\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Split factor values into quantile buckets.\n", + "buckets = pd.qcut(x, q=5, duplicates='drop')\n", + "# Summarize each bucket with distribution statistics.\n", + "summary = dataset.assign(bucket=buckets).groupby('bucket', observed=True).agg(\n", + " mean_factor=(factor, 'mean'),\n", + " min_future_return=('futurereturn', 'min'),\n", + " max_future_return=('futurereturn', 'max'),\n", + " mean_future_return=('futurereturn', 'mean'),\n", + " std_future_return=('futurereturn', 'std'),\n", + " observations=('futurereturn', 'size')\n", + ").reset_index()\n", + "summary['bucket'] = summary['bucket'].astype(str)\n", + "# Display the bucket summary.\n", + "print(f\"Factor: {factor}\")\n", + "display(summary.style.format({\n", + " 'mean_factor': '{:.3f}',\n", + " 'min_future_return': '{:.2%}',\n", + " 'max_future_return': '{:.2%}',\n", + " 'mean_future_return': '{:.2%}',\n", + " 'std_future_return': '{:.2%}'\n", + "}))\n", + "# Plot the return distribution for each bucket.\n", + "groups = [y[buckets == b].values for b in buckets.cat.categories]\n", + "plt.boxplot(groups, labels=[str(b) for b in buckets.cat.categories])\n", + "plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", + "plt.title(f'Future Return by {factor} Bucket')\n", + "plt.xlabel(f'{factor} Bucket')\n", + "plt.ylabel('Future Return')\n", + "plt.xticks(rotation=45)\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Foundation-Py-Default", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.14" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 63f3418dc3588b2263d9c631f2372a3f318eaf38 Mon Sep 17 00:00:00 2001 From: Rudy Osuna Date: Tue, 2 Jun 2026 15:59:00 -0700 Subject: [PATCH 15/16] Delete project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb --- .../research.ipynb | 767 ------------------ 1 file changed, 767 deletions(-) delete mode 100644 project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb diff --git a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb deleted file mode 100644 index 1d3f3e21b1..0000000000 --- a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb +++ /dev/null @@ -1,767 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "a1b2c3d4", - "metadata": {}, - "source": [ - "![QuantConnect Logo](https://cdn.quantconnect.com/web/i/icon.png)\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "e5f6a7b8", - "metadata": {}, - "source": [ - "## Quiver Government Contracts Research\n", - "\n", - "This notebook studies whether government contract dollar volume helps explain future returns" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "c9d0e1f2", - "metadata": {}, - "outputs": [], - "source": [ - "qb = QuantBook()\n", - "# Daily bars will have an end_time that matches the following midnight.\n", - "qb.settings.daily_precise_end_time = False\n", - "# Anchor the research clock to the start of 2026.\n", - "qb.set_start_date(2026, 1, 1)" - ] - }, - { - "cell_type": "markdown", - "id": "a3b4c5d6", - "metadata": {}, - "source": [ - "### Build a Government Contract Universe\n", - "\n", - "Select assets with frequent, sizable US government contracts, then inspect the returned universe history." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "e7f8a9b0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Shape: (580, 4)\n", - "Columns: ['agency', 'amount', 'description', 'value']\n" - ] - }, - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
agencyamountdescriptionvalue
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2025-10-04DNOW VR22RBI5MBFPGeneral Services Administration138.6678C10M0138.66
DNOW VR22RBI5MBFPGeneral Services Administration346.6578C10M0346.65
DNOW VR22RBI5MBFPGeneral Services Administration452.85CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...452.85
DNOW VR22RBI5MBFPGeneral Services Administration905.70CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...905.70
DNOW VR22RBI5MBFPGeneral Services Administration374.20CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...374.20
\n", - "
" - ], - "text/plain": [ - " agency amount \\\n", - "time symbol \n", - "2025-10-04 DNOW VR22RBI5MBFP General Services Administration 138.66 \n", - " DNOW VR22RBI5MBFP General Services Administration 346.65 \n", - " DNOW VR22RBI5MBFP General Services Administration 452.85 \n", - " DNOW VR22RBI5MBFP General Services Administration 905.70 \n", - " DNOW VR22RBI5MBFP General Services Administration 374.20 \n", - "\n", - " description \\\n", - "time symbol \n", - "2025-10-04 DNOW VR22RBI5MBFP 78C10M0 \n", - " DNOW VR22RBI5MBFP 78C10M0 \n", - " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", - " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", - " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", - "\n", - " value \n", - "time symbol \n", - "2025-10-04 DNOW VR22RBI5MBFP 138.66 \n", - " DNOW VR22RBI5MBFP 346.65 \n", - " DNOW VR22RBI5MBFP 452.85 \n", - " DNOW VR22RBI5MBFP 905.70 \n", - " DNOW VR22RBI5MBFP 374.20 " - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def select_assets(data: List[QuiverGovernmentContractUniverse]) -> List[Symbol]:\n", - " # Group by ticker and keep names with 3+ contracts totalling over $50K.\n", - " contracts_by_symbol: dict[Symbol, list[QuiverGovernmentContractUniverse]] = {}\n", - " for d in data:\n", - " contracts_by_symbol.setdefault(d.symbol, []).append(d)\n", - " return [s for s, ds in contracts_by_symbol.items()\n", - " if len(ds) >= 3 and sum(x.amount or 0 for x in ds) > 50_000]\n", - "\n", - "# Add the Quiver Government Contract universe.\n", - "universe = qb.add_universe(QuiverGovernmentContractUniverse, select_assets)\n", - "# Request universe history of the last 90 days.\n", - "universe_history = qb.universe_history(universe, qb.time - timedelta(90), qb.time - timedelta(1), flatten=True).rename_axis(['time', 'symbol']).drop(columns=['time'])\n", - "# Print the returned shape and columns.\n", - "print(f\"Shape: {universe_history.shape}\")\n", - "print(f\"Columns: {list(universe_history.columns)}\")\n", - "universe_history.head()" - ] - }, - { - "cell_type": "markdown", - "id": "c1d2e3f4", - "metadata": {}, - "source": [ - "### Universe Diagnostics\n", - "\n", - "Inspects the raw contract amount distribution and visualizes how the daily universe size evolves chronologically." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "a5b6c7d8", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Universe days: 19\n", - "Mean basket size per day: 2.6\n", - "\n", - "count 580.000\n", - "mean 20138.930\n", - "std 105049.143\n", - "min 0.000\n", - "25% 259.200\n", - "50% 618.250\n", - "75% 1741.500\n", - "max 1776510.800\n", - "Name: amount, dtype: object\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Count selected assets by day.\n", - "universe_size = universe_history.reset_index().groupby(['time', 'symbol']).size().groupby('time').size()\n", - "print(f\"Universe days: {len(universe_size)}\")\n", - "# Store the selected symbol list.\n", - "unique_assets = list(universe_history.index.levels[1].unique())\n", - "print(f\"Mean basket size per day: {universe_size.mean():.1f}\")\n", - "print('')\n", - "print(universe_history.amount.describe().map('{:0.3f}'.format))\n", - "universe_size.plot(title='Daily Universe Size', ylabel='Universe Size');" - ] - }, - { - "cell_type": "markdown", - "id": "e9f0a1b2", - "metadata": {}, - "source": [ - "### Daily Universe Prices\n", - "\n", - "Fetch daily price history for every symbol that appears in the universe." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "c3d4e5f6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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closehighlowopenvolume
symboltime
DNOW VR22RBI5MBFP2025-10-0415.77015.830015.33015.391016905.0
2025-10-0715.91016.260015.82215.861095631.0
2025-10-0815.51015.920015.28515.811093552.0
2025-10-0915.66015.799915.56015.65778108.0
2025-10-1014.69015.680014.69015.56952082.0
.....................
MDLN YYDBHHPS742T2025-12-2544.28045.010043.55043.954363660.0
2025-12-2744.08545.450043.61044.508118252.0
2025-12-3042.09043.800041.73543.575517778.0
2025-12-3141.82043.250041.62042.054102917.0
2026-01-0142.00043.070041.21041.945587994.0
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816 rows × 5 columns

\n", - "
" - ], - "text/plain": [ - " close high low open volume\n", - "symbol time \n", - "DNOW VR22RBI5MBFP 2025-10-04 15.770 15.8300 15.330 15.39 1016905.0\n", - " 2025-10-07 15.910 16.2600 15.822 15.86 1095631.0\n", - " 2025-10-08 15.510 15.9200 15.285 15.81 1093552.0\n", - " 2025-10-09 15.660 15.7999 15.560 15.65 778108.0\n", - " 2025-10-10 14.690 15.6800 14.690 15.56 952082.0\n", - "... ... ... ... ... ...\n", - "MDLN YYDBHHPS742T 2025-12-25 44.280 45.0100 43.550 43.95 4363660.0\n", - " 2025-12-27 44.085 45.4500 43.610 44.50 8118252.0\n", - " 2025-12-30 42.090 43.8000 41.735 43.57 5517778.0\n", - " 2025-12-31 41.820 43.2500 41.620 42.05 4102917.0\n", - " 2026-01-01 42.000 43.0700 41.210 41.94 5587994.0\n", - "\n", - "[816 rows x 5 columns]" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Extract unique assets\n", - "symbols = list(universe_history.index.get_level_values(1).unique())\n", - "# Fetch daily historical price metrics using the earliest timestamp available in the index.\n", - "history = qb.history(symbols, universe_history.index[0][0] - timedelta(1), qb.time, Resolution.DAILY)\n", - "history" - ] - }, - { - "cell_type": "markdown", - "id": "a7b8c9d0", - "metadata": {}, - "source": [ - "### Align Contract Volume And Returns\n", - "\n", - "Build a joined table of contract dollar volume and future returns." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "3d56c7cd", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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dollarvolumefuturereturn
timesymbol
2025-10-04DNOW VR22RBI5MBFP222382.010.027290
2025-10-08SYK R735QTJ8XC9X450063.660.024027
2025-10-10DNOW VR22RBI5MBFP294421.70-0.087404
2025-11-15SENEA R735QTJ8XC9X798649.200.031759
2025-11-18SENEA R735QTJ8XC9X798649.200.026921
\n", - "
" - ], - "text/plain": [ - " dollarvolume futurereturn\n", - "time symbol \n", - "2025-10-04 DNOW VR22RBI5MBFP 222382.01 0.027290\n", - "2025-10-08 SYK R735QTJ8XC9X 450063.66 0.024027\n", - "2025-10-10 DNOW VR22RBI5MBFP 294421.70 -0.087404\n", - "2025-11-15 SENEA R735QTJ8XC9X 798649.20 0.031759\n", - "2025-11-18 SENEA R735QTJ8XC9X 798649.20 0.026921" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dataset = (\n", - " universe_history.reset_index().groupby(['time', 'symbol']).agg(dollarvolume=('amount', 'sum'))\n", - " .join(history.open.unstack('symbol').sort_index().pct_change(2, fill_method=None).shift(-2).stack().rename('futurereturn').rename_axis(['time','symbol']), how='inner')\n", - ")\n", - "dataset.head()" - ] - }, - { - "cell_type": "markdown", - "id": "c5d6e7f8", - "metadata": {}, - "source": [ - "### Analyze Relationships Between Factor and Future Returns\n", - "\n", - "Drop the 1% outliers on each side of the factor and fit a line of best fit." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "21099a93", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Factor: dollarvolume\n", - "Observations: 46\n", - "Mean future return: 0.84%\n", - "Alpha: 1.09%\n", - "Beta: -0.00%\n", - "R-squared: 1.94%\n" - ] - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "factor = 'dollarvolume'\n", - "# Assign the factor values.\n", - "x = dataset[factor]\n", - "y = dataset['futurereturn']\n", - "# Drop the 1% outliers on each side of the factor.\n", - "lower, upper = x.quantile([0.01, 0.99])\n", - "mask = x.between(lower, upper)\n", - "x, y = x[mask], y[mask]\n", - "# Fit a simple linear model.\n", - "slope, intercept = np.polyfit(x, y, 1)\n", - "r_squared = x.corr(y) ** 2\n", - "# Print the linear model statistics.\n", - "print(f\"Factor: {factor}\")\n", - "print(f\"Observations: {len(x)}\")\n", - "print(f\"Mean future return: {y.mean():.2%}\")\n", - "print(f\"Alpha: {intercept:.2%}\")\n", - "print(f\"Beta: {slope:.2%}\")\n", - "print(f\"R-squared: {r_squared:.2%}\")\n", - "# Plot the factor values against future returns.\n", - "plt.scatter(x, y, alpha=0.6)\n", - "plt.plot(x.sort_values(), intercept + slope * x.sort_values(), color='tab:red', label='Linear fit')\n", - "plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", - "plt.title(f'{factor} vs Future Return')\n", - "plt.xlabel(factor)\n", - "plt.ylabel('Future Return')\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "7ac413aa", - "metadata": {}, - "source": [ - "Create a box plot of dollar-volume quantile buckets compared to future returns." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "c7d8e9f0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Factor: dollarvolume\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
 bucketmean_factormin_future_returnmax_future_returnmean_future_returnstd_future_returnobservations
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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Split factor values into quantile buckets.\n", - "buckets = pd.qcut(x, q=5, duplicates='drop')\n", - "# Summarize each bucket with distribution statistics.\n", - "summary = dataset.assign(bucket=buckets).groupby('bucket', observed=True).agg(\n", - " mean_factor=(factor, 'mean'),\n", - " min_future_return=('futurereturn', 'min'),\n", - " max_future_return=('futurereturn', 'max'),\n", - " mean_future_return=('futurereturn', 'mean'),\n", - " std_future_return=('futurereturn', 'std'),\n", - " observations=('futurereturn', 'size')\n", - ").reset_index()\n", - "summary['bucket'] = summary['bucket'].astype(str)\n", - "# Display the bucket summary.\n", - "print(f\"Factor: {factor}\")\n", - "display(summary.style.format({\n", - " 'mean_factor': '{:.3f}',\n", - " 'min_future_return': '{:.2%}',\n", - " 'max_future_return': '{:.2%}',\n", - " 'mean_future_return': '{:.2%}',\n", - " 'std_future_return': '{:.2%}'\n", - "}))\n", - "# Plot the return distribution for each bucket.\n", - "groups = [y[buckets == b].values for b in buckets.cat.categories]\n", - "plt.boxplot(groups, labels=[str(b) for b in buckets.cat.categories])\n", - "plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", - "plt.title(f'Future Return by {factor} Bucket')\n", - "plt.xlabel(f'{factor} Bucket')\n", - "plt.ylabel('Future Return')\n", - "plt.xticks(rotation=45)\n", - "plt.show()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Foundation-Py-Default", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.14" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From 1c81083c86dd35123d1e29f1f7973a0ac0571fcb Mon Sep 17 00:00:00 2001 From: Rudy Osuna Date: Tue, 2 Jun 2026 15:59:07 -0700 Subject: [PATCH 16/16] fix --- .../research.ipynb | 767 ++++++++++++++++++ 1 file changed, 767 insertions(+) create mode 100644 project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb diff --git a/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb new file mode 100644 index 0000000000..87c1920e26 --- /dev/null +++ b/project-templates/python/alternative-data-universe-quivergovernmentcontractuniverse/research.ipynb @@ -0,0 +1,767 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "a1b2c3d4", + "metadata": {}, + "source": [ + "![QuantConnect Logo](https://cdn.quantconnect.com/web/i/icon.png)\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "e5f6a7b8", + "metadata": {}, + "source": [ + "## Quiver Government Contracts Research\n", + "\n", + "This notebook studies whether government contract dollar volume helps explain future returns" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "c9d0e1f2", + "metadata": {}, + "outputs": [], + "source": [ + "qb = QuantBook()\n", + "# Daily bars will have an end_time that matches the following midnight.\n", + "qb.settings.daily_precise_end_time = False\n", + "# Anchor the research clock to the start of 2026.\n", + "qb.set_start_date(2026, 1, 1)" + ] + }, + { + "cell_type": "markdown", + "id": "a3b4c5d6", + "metadata": {}, + "source": [ + "### Build a Government Contract Universe\n", + "\n", + "Select assets with frequent, sizable US government contracts, then inspect the returned universe history." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "e7f8a9b0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Shape: (580, 4)\n", + "Columns: ['agency', 'amount', 'description', 'value']\n" + ] + }, + { + "data": { + "text/html": [ + "
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agencyamountdescriptionvalue
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2025-10-04DNOW VR22RBI5MBFPGeneral Services Administration138.6678C10M0138.66
DNOW VR22RBI5MBFPGeneral Services Administration346.6578C10M0346.65
DNOW VR22RBI5MBFPGeneral Services Administration452.85CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...452.85
DNOW VR22RBI5MBFPGeneral Services Administration905.70CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...905.70
DNOW VR22RBI5MBFPGeneral Services Administration374.20CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C...374.20
\n", + "
" + ], + "text/plain": [ + " agency amount \\\n", + "time symbol \n", + "2025-10-04 DNOW VR22RBI5MBFP General Services Administration 138.66 \n", + " DNOW VR22RBI5MBFP General Services Administration 346.65 \n", + " DNOW VR22RBI5MBFP General Services Administration 452.85 \n", + " DNOW VR22RBI5MBFP General Services Administration 905.70 \n", + " DNOW VR22RBI5MBFP General Services Administration 374.20 \n", + "\n", + " description \\\n", + "time symbol \n", + "2025-10-04 DNOW VR22RBI5MBFP 78C10M0 \n", + " DNOW VR22RBI5MBFP 78C10M0 \n", + " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", + " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", + " DNOW VR22RBI5MBFP CARTRIDGE; TONER I.A.W. HEWLETT PACKARD P/N: C... \n", + "\n", + " value \n", + "time symbol \n", + "2025-10-04 DNOW VR22RBI5MBFP 138.66 \n", + " DNOW VR22RBI5MBFP 346.65 \n", + " DNOW VR22RBI5MBFP 452.85 \n", + " DNOW VR22RBI5MBFP 905.70 \n", + " DNOW VR22RBI5MBFP 374.20 " + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def select_assets(data: List[QuiverGovernmentContractUniverse]) -> List[Symbol]:\n", + " # Group by ticker and keep names with 3+ contracts totalling over $50K.\n", + " contracts_by_symbol: dict[Symbol, list[QuiverGovernmentContractUniverse]] = {}\n", + " for d in data:\n", + " contracts_by_symbol.setdefault(d.symbol, []).append(d)\n", + " return [s for s, ds in contracts_by_symbol.items()\n", + " if len(ds) >= 3 and sum(x.amount or 0 for x in ds) > 50_000]\n", + "\n", + "# Add the Quiver Government Contract universe.\n", + "universe = qb.add_universe(QuiverGovernmentContractUniverse, select_assets)\n", + "# Request universe history of the last 90 days.\n", + "universe_history = qb.universe_history(universe, qb.time - timedelta(90), qb.time - timedelta(1), flatten=True).rename_axis(['time', 'symbol']).drop(columns=['time'])\n", + "# Print the returned shape and columns.\n", + "print(f\"Shape: {universe_history.shape}\")\n", + "print(f\"Columns: {list(universe_history.columns)}\")\n", + "universe_history.head()" + ] + }, + { + "cell_type": "markdown", + "id": "c1d2e3f4", + "metadata": {}, + "source": [ + "### Universe Diagnostics\n", + "\n", + "Inspects the raw contract amount distribution and visualizes how the daily universe size evolves chronologically." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a5b6c7d8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Universe days: 19\n", + "Mean basket size per day: 2.6\n", + "\n", + "count 580.000\n", + "mean 20138.930\n", + "std 105049.143\n", + "min 0.000\n", + "25% 259.200\n", + "50% 618.250\n", + "75% 1741.500\n", + "max 1776510.800\n", + "Name: amount, dtype: object\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Count selected assets by day.\n", + "universe_size = universe_history.reset_index().groupby(['time', 'symbol']).size().groupby('time').size()\n", + "print(f\"Universe days: {len(universe_size)}\")\n", + "# Store the selected symbol list.\n", + "unique_assets = list(universe_history.index.levels[1].unique())\n", + "print(f\"Mean basket size per day: {universe_size.mean():.1f}\")\n", + "print('')\n", + "print(universe_history.amount.describe().map('{:0.3f}'.format))\n", + "universe_size.plot(title='Daily Universe Size', ylabel='Universe Size');" + ] + }, + { + "cell_type": "markdown", + "id": "e9f0a1b2", + "metadata": {}, + "source": [ + "### Daily Universe Prices\n", + "\n", + "Fetch daily price history for every symbol that appears in the universe." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "c3d4e5f6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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closehighlowopenvolume
symboltime
DNOW VR22RBI5MBFP2025-10-0415.77015.830015.33015.391016905.0
2025-10-0715.91016.260015.82215.861095631.0
2025-10-0815.51015.920015.28515.811093552.0
2025-10-0915.66015.799915.56015.65778108.0
2025-10-1014.69015.680014.69015.56952082.0
.....................
MDLN YYDBHHPS742T2025-12-2544.28045.010043.55043.954363660.0
2025-12-2744.08545.450043.61044.508118252.0
2025-12-3042.09043.800041.73543.575517778.0
2025-12-3141.82043.250041.62042.054102917.0
2026-01-0142.00043.070041.21041.945587994.0
\n", + "

816 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + " close high low open volume\n", + "symbol time \n", + "DNOW VR22RBI5MBFP 2025-10-04 15.770 15.8300 15.330 15.39 1016905.0\n", + " 2025-10-07 15.910 16.2600 15.822 15.86 1095631.0\n", + " 2025-10-08 15.510 15.9200 15.285 15.81 1093552.0\n", + " 2025-10-09 15.660 15.7999 15.560 15.65 778108.0\n", + " 2025-10-10 14.690 15.6800 14.690 15.56 952082.0\n", + "... ... ... ... ... ...\n", + "MDLN YYDBHHPS742T 2025-12-25 44.280 45.0100 43.550 43.95 4363660.0\n", + " 2025-12-27 44.085 45.4500 43.610 44.50 8118252.0\n", + " 2025-12-30 42.090 43.8000 41.735 43.57 5517778.0\n", + " 2025-12-31 41.820 43.2500 41.620 42.05 4102917.0\n", + " 2026-01-01 42.000 43.0700 41.210 41.94 5587994.0\n", + "\n", + "[816 rows x 5 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Extract unique assets\n", + "symbols = list(universe_history.index.get_level_values(1).unique())\n", + "# Fetch daily historical price metrics using the earliest timestamp available in the index.\n", + "history = qb.history(symbols, universe_history.index[0][0] - timedelta(1), qb.time, Resolution.DAILY)\n", + "history" + ] + }, + { + "cell_type": "markdown", + "id": "a7b8c9d0", + "metadata": {}, + "source": [ + "### Align Contract Volume And Returns\n", + "\n", + "Build a joined table of contract dollar volume and future returns." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "3d56c7cd", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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dollarvolumefuturereturn
timesymbol
2025-10-04DNOW VR22RBI5MBFP222382.010.027290
2025-10-08SYK R735QTJ8XC9X450063.660.024027
2025-10-10DNOW VR22RBI5MBFP294421.70-0.087404
2025-11-15SENEA R735QTJ8XC9X798649.200.031759
2025-11-18SENEA R735QTJ8XC9X798649.200.026921
\n", + "
" + ], + "text/plain": [ + " dollarvolume futurereturn\n", + "time symbol \n", + "2025-10-04 DNOW VR22RBI5MBFP 222382.01 0.027290\n", + "2025-10-08 SYK R735QTJ8XC9X 450063.66 0.024027\n", + "2025-10-10 DNOW VR22RBI5MBFP 294421.70 -0.087404\n", + "2025-11-15 SENEA R735QTJ8XC9X 798649.20 0.031759\n", + "2025-11-18 SENEA R735QTJ8XC9X 798649.20 0.026921" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset = (\n", + " universe_history.reset_index().groupby(['time', 'symbol']).agg(dollarvolume=('amount', 'sum'))\n", + " .join(history.open.unstack('symbol').sort_index().pct_change(2, fill_method=None).shift(-2).stack().rename('futurereturn'), how='inner')\n", + ")\n", + "dataset.head()" + ] + }, + { + "cell_type": "markdown", + "id": "c5d6e7f8", + "metadata": {}, + "source": [ + "### Analyze Relationships Between Factor and Future Returns\n", + "\n", + "Drop the 1% outliers on each side of the factor and fit a line of best fit." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "21099a93", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Factor: dollarvolume\n", + "Observations: 46\n", + "Mean future return: 0.84%\n", + "Alpha: 1.09%\n", + "Beta: -0.00%\n", + "R-squared: 1.94%\n" + ] + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "factor = 'dollarvolume'\n", + "# Assign the factor values.\n", + "x = dataset[factor]\n", + "y = dataset['futurereturn']\n", + "# Drop the 1% outliers on each side of the factor.\n", + "lower, upper = x.quantile([0.01, 0.99])\n", + "mask = x.between(lower, upper)\n", + "x, y = x[mask], y[mask]\n", + "# Fit a simple linear model.\n", + "slope, intercept = np.polyfit(x, y, 1)\n", + "r_squared = x.corr(y) ** 2\n", + "# Print the linear model statistics.\n", + "print(f\"Factor: {factor}\")\n", + "print(f\"Observations: {len(x)}\")\n", + "print(f\"Mean future return: {y.mean():.2%}\")\n", + "print(f\"Alpha: {intercept:.2%}\")\n", + "print(f\"Beta: {slope:.2%}\")\n", + "print(f\"R-squared: {r_squared:.2%}\")\n", + "# Plot the factor values against future returns.\n", + "plt.scatter(x, y, alpha=0.6)\n", + "plt.plot(x.sort_values(), intercept + slope * x.sort_values(), color='tab:red', label='Linear fit')\n", + "plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", + "plt.title(f'{factor} vs Future Return')\n", + "plt.xlabel(factor)\n", + "plt.ylabel('Future Return')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "7ac413aa", + "metadata": {}, + "source": [ + "Create a box plot of dollar-volume quantile buckets compared to future returns." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "c7d8e9f0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Factor: dollarvolume\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Split factor values into quantile buckets.\n", + "buckets = pd.qcut(x, q=5, duplicates='drop')\n", + "# Summarize each bucket with distribution statistics.\n", + "summary = dataset.assign(bucket=buckets).groupby('bucket', observed=True).agg(\n", + " mean_factor=(factor, 'mean'),\n", + " min_future_return=('futurereturn', 'min'),\n", + " max_future_return=('futurereturn', 'max'),\n", + " mean_future_return=('futurereturn', 'mean'),\n", + " std_future_return=('futurereturn', 'std'),\n", + " observations=('futurereturn', 'size')\n", + ").reset_index()\n", + "summary['bucket'] = summary['bucket'].astype(str)\n", + "# Display the bucket summary.\n", + "print(f\"Factor: {factor}\")\n", + "display(summary.style.format({\n", + " 'mean_factor': '{:.3f}',\n", + " 'min_future_return': '{:.2%}',\n", + " 'max_future_return': '{:.2%}',\n", + " 'mean_future_return': '{:.2%}',\n", + " 'std_future_return': '{:.2%}'\n", + "}))\n", + "# Plot the return distribution for each bucket.\n", + "groups = [y[buckets == b].values for b in buckets.cat.categories]\n", + "plt.boxplot(groups, labels=[str(b) for b in buckets.cat.categories])\n", + "plt.axhline(0, color='black', linewidth=1, alpha=0.4)\n", + "plt.title(f'Future Return by {factor} Bucket')\n", + "plt.xlabel(f'{factor} Bucket')\n", + "plt.ylabel('Future Return')\n", + "plt.xticks(rotation=45)\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Foundation-Py-Default", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.14" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}