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update spy_prices and notebooks
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‎cookbook/1-RiskReturnModels.ipynb‎

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"In this section, we compare how well the different risk models predict an out-of-sample covariance matrix, and how well the different returns models predict out-of-sample returns.\n",
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"\n",
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"[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pyportfolio/pyportfolioopt/blob/master/cookbook/1-RiskReturnModels.ipynb)\n",
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"\n",
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"[![Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://github.com/PyPortfolio/PyPortfolioOpt/blob/main/cookbook/1-RiskReturnModels.ipynb)\n",
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"\n",
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"[![Gradient](https://assets.paperspace.io/img/gradient-badge.svg)](https://console.paperspace.com/github/pyportfolio/pyportfolioopt/blob/master/cookbook/1-RiskReturnModels.ipynb)\n",
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"\n",
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"[![Open In SageMaker Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/pyportfolio/pyportfolioopt/blob/master/cookbook/1-RiskReturnModels.ipynb)\n",
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"\n",
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"## Risk models"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "ajpb4cfuzzCd",
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"outputId": "c075b649-0764-4b2d-cd48-65d6a85e7003"
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"outputId": "c075b649-0764-4b2d-cd48-65d6a85e7003",
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"ExecuteTime": {
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"end_time": "2025-11-15T07:38:12.128260Z",
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"start_time": "2025-11-15T07:38:11.505395Z"
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}
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},
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"outputs": [],
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"source": [
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"!pip install pandas numpy matplotlib PyPortfolioOpt\n",
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"import os\n",
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"\n",
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"if not os.path.isdir(\"data\"):\n",
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" os.system(\"git clone https://github.com/pyportfolio/pyportfolioopt.git\")\n",
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" os.chdir(\"PyPortfolioOpt/cookbook\")"
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]
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],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Requirement already satisfied: pandas in /Users/thomasschmelzer/projects/PyPortfolioOpt/.venv/lib/python3.13/site-packages (2.3.3)\r\n",
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"Requirement already satisfied: numpy in /Users/thomasschmelzer/projects/PyPortfolioOpt/.venv/lib/python3.13/site-packages (2.3.4)\r\n",
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"Requirement already satisfied: matplotlib in /Users/thomasschmelzer/projects/PyPortfolioOpt/.venv/lib/python3.13/site-packages (3.10.7)\r\n",
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"Requirement already satisfied: PyPortfolioOpt in /Users/thomasschmelzer/projects/PyPortfolioOpt (1.5.6)\r\n",
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"Requirement already satisfied: python-dateutil>=2.8.2 in /Users/thomasschmelzer/projects/PyPortfolioOpt/.venv/lib/python3.13/site-packages (from pandas) (2.9.0.post0)\r\n",
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"Requirement already satisfied: pytz>=2020.1 in /Users/thomasschmelzer/projects/PyPortfolioOpt/.venv/lib/python3.13/site-packages (from pandas) (2025.2)\r\n",
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"Requirement already satisfied: packaging>=20.0 in /Users/thomasschmelzer/projects/PyPortfolioOpt/.venv/lib/python3.13/site-packages (from matplotlib) (25.0)\r\n",
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"Requirement already satisfied: setuptools in /Users/thomasschmelzer/projects/PyPortfolioOpt/.venv/lib/python3.13/site-packages (from osqp>=1.0.0->cvxpy>=1.1.19->PyPortfolioOpt) (80.9.0)\r\n",
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"\r\n",
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"\u001B[1m[\u001B[0m\u001B[34;49mnotice\u001B[0m\u001B[1;39;49m]\u001B[0m\u001B[39;49m A new release of pip is available: \u001B[0m\u001B[31;49m24.3.1\u001B[0m\u001B[39;49m -> \u001B[0m\u001B[32;49m25.3\u001B[0m\r\n",
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"\u001B[1m[\u001B[0m\u001B[34;49mnotice\u001B[0m\u001B[1;39;49m]\u001B[0m\u001B[39;49m To update, run: \u001B[0m\u001B[32;49mpip install --upgrade pip\u001B[0m\r\n"
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]
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}
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],
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"execution_count": 1
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 35
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"id": "3aAcuLOKzwIT",
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"outputId": "456251e3-a9fd-4e83-8847-44cb43dbb422"
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'1.5.6'"
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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"outputId": "456251e3-a9fd-4e83-8847-44cb43dbb422",
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"ExecuteTime": {
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"end_time": "2025-11-15T07:38:13.282190Z",
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"start_time": "2025-11-15T07:38:12.133749Z"
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}
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],
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},
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"source": [
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"from pypfopt import expected_returns, plotting, risk_models\n",
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"\n",
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"pypfopt.__version__"
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]
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],
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"outputs": [
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{
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"ename": "ModuleNotFoundError",
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"evalue": "No module named 'skbase'",
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"output_type": "error",
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"traceback": [
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"\u001B[31m---------------------------------------------------------------------------\u001B[39m",
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"\u001B[31mModuleNotFoundError\u001B[39m Traceback (most recent call last)",
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"\u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[2]\u001B[39m\u001B[32m, line 5\u001B[39m\n\u001B[32m 2\u001B[39m \u001B[38;5;28;01mimport\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01mnumpy\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mas\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01mnp\u001B[39;00m\n\u001B[32m 3\u001B[39m \u001B[38;5;28;01mimport\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01mpandas\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mas\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01mpd\u001B[39;00m\n\u001B[32m----> \u001B[39m\u001B[32m5\u001B[39m \u001B[38;5;28;01mimport\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01mpypfopt\u001B[39;00m\n\u001B[32m 6\u001B[39m \u001B[38;5;28;01mfrom\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01mpypfopt\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mimport\u001B[39;00m expected_returns, plotting, risk_models\n\u001B[32m 8\u001B[39m pypfopt.__version__\n",
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"\u001B[36mFile \u001B[39m\u001B[32m~/projects/PyPortfolioOpt/pypfopt/__init__.py:7\u001B[39m\n\u001B[32m 1\u001B[39m \u001B[38;5;28;01mfrom\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01m.\u001B[39;00m\u001B[34;01mblack_litterman\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mimport\u001B[39;00m (\n\u001B[32m 2\u001B[39m BlackLittermanModel,\n\u001B[32m 3\u001B[39m market_implied_prior_returns,\n\u001B[32m 4\u001B[39m market_implied_risk_aversion,\n\u001B[32m 5\u001B[39m )\n\u001B[32m 6\u001B[39m \u001B[38;5;28;01mfrom\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01m.\u001B[39;00m\u001B[34;01mcla\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mimport\u001B[39;00m CLA\n\u001B[32m----> \u001B[39m\u001B[32m7\u001B[39m \u001B[38;5;28;01mfrom\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01m.\u001B[39;00m\u001B[34;01mdiscrete_allocation\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mimport\u001B[39;00m DiscreteAllocation, get_latest_prices\n\u001B[32m 8\u001B[39m \u001B[38;5;28;01mfrom\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01m.\u001B[39;00m\u001B[34;01mefficient_frontier\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mimport\u001B[39;00m (\n\u001B[32m 9\u001B[39m EfficientCDaR,\n\u001B[32m 10\u001B[39m EfficientCVaR,\n\u001B[32m 11\u001B[39m EfficientFrontier,\n\u001B[32m 12\u001B[39m EfficientSemivariance,\n\u001B[32m 13\u001B[39m )\n\u001B[32m 14\u001B[39m \u001B[38;5;28;01mfrom\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01m.\u001B[39;00m\u001B[34;01mhierarchical_portfolio\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mimport\u001B[39;00m HRPOpt\n",
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"\u001B[36mFile \u001B[39m\u001B[32m~/projects/PyPortfolioOpt/pypfopt/discrete_allocation.py:12\u001B[39m\n\u001B[32m 10\u001B[39m \u001B[38;5;28;01mimport\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01mnumpy\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mas\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01mnp\u001B[39;00m\n\u001B[32m 11\u001B[39m \u001B[38;5;28;01mimport\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01mpandas\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mas\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01mpd\u001B[39;00m\n\u001B[32m---> \u001B[39m\u001B[32m12\u001B[39m \u001B[38;5;28;01mfrom\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01mskbase\u001B[39;00m\u001B[34;01m.\u001B[39;00m\u001B[34;01mutils\u001B[39;00m\u001B[34;01m.\u001B[39;00m\u001B[34;01mdependencies\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mimport\u001B[39;00m _check_soft_dependencies\n\u001B[32m 14\u001B[39m \u001B[38;5;28;01mfrom\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01m.\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mimport\u001B[39;00m exceptions\n\u001B[32m 17\u001B[39m \u001B[38;5;28;01mdef\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34mget_latest_prices\u001B[39m(prices):\n",
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"\u001B[31mModuleNotFoundError\u001B[39m: No module named 'skbase'"
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]
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}
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],
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"execution_count": 2
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"name": "python3",
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"language": "python"
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"language_info": {
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"codemirror_mode": {

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