mirror of
https://github.com/robertmartin8/PyPortfolioOpt.git
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89 lines
1.7 KiB
Plaintext
89 lines
1.7 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Hierarchical Risk Parity Portfolio\n",
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"\n"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"from pypfopt import HRPOpt, risk_models, plotting, DiscreteAllocation\n",
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"\n",
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"\n",
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"df = pd.read_csv(\"tests/stock_prices.csv\", parse_dates=True, index_col=\"date\")\n",
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"print(df.shape)\n",
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"df.tail()\n"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"returns = risk_models.returns_from_prices(df)\n",
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"hrp = HRPOpt(returns)\n",
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"weights = hrp.optimize()\n",
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"hrp.portfolio_performance(verbose=True);"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"plotting.plot_dendrogram(hrp);"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"da = DiscreteAllocation(weights, df.iloc[-1], total_portfolio_value=10000)\n",
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"w, leftover = da.lp_portfolio()"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"plotting.plot_weights(weights);"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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