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strategy-lab/to_explore/pyquantnews/105_CalmarRatio.ipynb
David Brazda e3da60c647 daily update
2024-10-21 20:57:56 +02:00

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{
"cells": [
{
"cell_type": "markdown",
"id": "d226535c",
"metadata": {},
"source": [
"<div style=\"background-color:#000;\"><img src=\"pqn.png\"></img></div>"
]
},
{
"cell_type": "markdown",
"id": "bbe7cc61",
"metadata": {},
"source": [
"This code downloads historical stock data for a specified list of symbols using the yfinance library. It computes daily returns for each stock and then aggregates these returns to form a portfolio. The Calmar Ratio, a performance metric used to evaluate the risk-adjusted returns of the portfolio, is calculated using the empyrical library. Finally, it prints the Calmar Ratio and plots the portfolio's daily returns over the specified period."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "119bd5ed",
"metadata": {},
"outputs": [],
"source": [
"import empyrical as ep\n",
"import yfinance as yf\n",
"import warnings"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "d9553761",
"metadata": {},
"outputs": [],
"source": [
"warnings.filterwarnings(\"ignore\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "070d56f0",
"metadata": {},
"outputs": [],
"source": [
"# Define a list of stock symbols to download historical data for\n",
"symbols = [\n",
" \"AAPL\",\n",
" \"AMZN\",\n",
" \"GOOG\",\n",
" \"META\",\n",
" \"MSFT\",\n",
" \"NVDA\",\n",
" \"TSLA\",\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "c536d848",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[*********************100%%**********************] 7 of 7 completed\n"
]
}
],
"source": [
"# Download adjusted closing prices for the specified symbols from Yahoo Finance\n",
"data = yf.download(symbols, start=\"2020-01-01\")[\"Adj Close\"]"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "046c2ec7",
"metadata": {},
"outputs": [],
"source": [
"# Calculate daily percentage returns for each stock and remove any missing values\n",
"returns = data.pct_change().dropna()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "5aed80b2",
"metadata": {},
"outputs": [],
"source": [
"# Aggregate the daily returns of all stocks to form a portfolio return series\n",
"portfolio_returns = returns.sum(axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "874ff444",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Calmar Ratio: -0.3244445113808806\n"
]
}
],
"source": [
"# Compute the Calmar Ratio for the portfolio using the empyrical library\n",
"calmar_ratio = ep.calmar_ratio(portfolio_returns)\n",
"print(f\"Calmar Ratio: {calmar_ratio}\")"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "66c8e68a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='Date'>"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Plot the portfolio's daily returns over the specified period\n",
"portfolio_returns.plot()"
]
},
{
"cell_type": "markdown",
"id": "79e49a51",
"metadata": {},
"source": [
"<a href=\"https://pyquantnews.com/\">PyQuant News</a> is where finance practitioners level up with Python for quant finance, algorithmic trading, and market data analysis. Looking to get started? Check out the fastest growing, top-selling course to <a href=\"https://gettingstartedwithpythonforquantfinance.com/\">get started with Python for quant finance</a>. For educational purposes. Not investment advise. Use at your own risk."
]
}
],
"metadata": {
"jupytext": {
"cell_metadata_filter": "-all",
"main_language": "python",
"notebook_metadata_filter": "-all"
},
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.10.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}