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python-for-finances/portfolios-simulation/portfolios_simulation.ipynb
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feat: add portfolios simulation
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Libraries Installation"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 31,
feat: add portfolios simulation
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\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;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
"\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\n",
"\n",
"\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;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
"\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\n",
"\n",
"\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;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
"\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\n",
"\n",
"\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;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
"\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\n"
]
}
],
"source": [
"!pip install yfinance -q\n",
"!pip install pandas -q\n",
"!pip install numpy -q\n",
"!pip install matplotlib -q"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 33,
feat: add portfolios simulation
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"metadata": {},
"outputs": [],
"source": [
"import yfinance as yf\n",
"import pandas as pd\n",
"import numpy as np"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Setup portfolio"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 50,
feat: add portfolios simulation
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"metadata": {},
"outputs": [],
feat: sample of Riskfolio Lib
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"source": [
"amount_to_invest = 50_000.0\n",
"assets = [\"PETR3.SA\", \"CMIG3.SA\", \"CPLE6.SA\", \"RANI3.SA\", \"TAEE11.SA\", \"FESA4.SA\", \"UNIP6.SA\"]\n",
"weights = [32.5183, 18.4078, 12.6776, 11.1030, 10.3605, 9.1889, 5.7439]"
]
feat: add portfolios simulation
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},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 51,
"metadata": {},
"outputs": [],
"source": [
"if sum(weights) != 100.0:\n",
" sum(weights)"
]
},
{
"cell_type": "code",
"execution_count": 52,
feat: add portfolios simulation
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"metadata": {},
"outputs": [],
"source": [
"buy_orders = {\n",
feat: sample of Riskfolio Lib
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" asset: (weights / 100) * amount_to_invest\n",
" for asset, weights in zip(assets, weights)\n",
feat: add portfolios simulation
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"}"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 53,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'PETR3.SA': 16259.150000000003,\n",
" 'CMIG3.SA': 9203.900000000001,\n",
" 'CPLE6.SA': 6338.8,\n",
" 'RANI3.SA': 5551.5,\n",
" 'TAEE11.SA': 5180.25,\n",
" 'FESA4.SA': 4594.45,\n",
" 'UNIP6.SA': 2871.95}"
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"buy_orders"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [],
"source": [
"if sum(buy_orders.values()) != amount_to_invest:\n",
" sum(buy_orders.values())"
]
},
{
"cell_type": "code",
"execution_count": 55,
feat: add portfolios simulation
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"metadata": {},
"outputs": [],
"source": [
"assets = list(buy_orders.keys())"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 56,
feat: add portfolios simulation
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"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
feat: sample of Riskfolio Lib
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"['PETR3.SA',\n",
" 'CMIG3.SA',\n",
" 'CPLE6.SA',\n",
" 'RANI3.SA',\n",
" 'TAEE11.SA',\n",
" 'FESA4.SA',\n",
" 'UNIP6.SA']"
feat: add portfolios simulation
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]
},
feat: sample of Riskfolio Lib
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"execution_count": 56,
feat: add portfolios simulation
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"assets"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 57,
feat: add portfolios simulation
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"metadata": {},
"outputs": [],
"source": [
"total_invested = sum(buy_orders.values())"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 58,
feat: add portfolios simulation
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"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
feat: sample of Riskfolio Lib
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"50000.0"
feat: add portfolios simulation
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]
},
feat: sample of Riskfolio Lib
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"execution_count": 58,
feat: add portfolios simulation
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"total_invested"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Import financial assets data"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 59,
feat: add portfolios simulation
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"metadata": {},
"outputs": [],
"source": [
feat: sample of Riskfolio Lib
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"start = \"2017-02-01\"\n",
feat: add portfolios simulation
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"\n",
"assets_history_price = yf.download(assets, start=start, progress=False)[\"Adj Close\"]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Dummy portfolio simulation"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 60,
feat: add portfolios simulation
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"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
feat: sample of Riskfolio Lib
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"CMIG3.SA 4.455539\n",
"CPLE6.SA 1.778329\n",
"FESA4.SA 6.051053\n",
"PETR3.SA 6.434494\n",
"RANI3.SA 2.162255\n",
"TAEE11.SA 11.382806\n",
"UNIP6.SA 2.045254\n",
"Name: 2017-02-01 00:00:00, dtype: float64"
feat: add portfolios simulation
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]
},
feat: sample of Riskfolio Lib
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"execution_count": 60,
feat: add portfolios simulation
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"first_line = assets_history_price.iloc[0]\n",
"first_line"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 61,
feat: add portfolios simulation
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"metadata": {},
"outputs": [],
"source": [
"buy_orders_df = pd.Series(data = buy_orders, index=assets)"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 62,
feat: add portfolios simulation
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"metadata": {},
"outputs": [],
"source": [
"number_of_shares = round(buy_orders_df / first_line, 0)"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 63,
feat: add portfolios simulation
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"metadata": {},
"outputs": [],
"source": [
"net_worth = assets_history_price * number_of_shares"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 64,
feat: add portfolios simulation
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"metadata": {},
"outputs": [],
"source": [
"net_worth[\"Total net worth\"] = net_worth.sum(axis=1)"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 65,
feat: add portfolios simulation
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"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
feat: sample of Riskfolio Lib
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" <th>CMIG3.SA</th>\n",
" <th>CPLE6.SA</th>\n",
" <th>FESA4.SA</th>\n",
" <th>PETR3.SA</th>\n",
" <th>RANI3.SA</th>\n",
" <th>TAEE11.SA</th>\n",
" <th>UNIP6.SA</th>\n",
feat: add portfolios simulation
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" <th>Total net worth</th>\n",
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" <tr>\n",
" <th>Date</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
feat: sample of Riskfolio Lib
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" <th>2017-02-01</th>\n",
" <td>9205.144042</td>\n",
" <td>6337.965883</td>\n",
" <td>4592.748901</td>\n",
" <td>16259.967590</td>\n",
" <td>5550.509322</td>\n",
" <td>5179.176650</td>\n",
" <td>2871.536605</td>\n",
" <td>49997.048993</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
feat: sample of Riskfolio Lib
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" <th>2017-02-02</th>\n",
" <td>9615.273934</td>\n",
" <td>6465.322914</td>\n",
" <td>4614.160777</td>\n",
" <td>16038.055955</td>\n",
" <td>5550.509322</td>\n",
" <td>5222.037277</td>\n",
" <td>2855.359305</td>\n",
" <td>50360.719485</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
feat: sample of Riskfolio Lib
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" <th>2017-02-03</th>\n",
" <td>9906.921354</td>\n",
" <td>6517.062172</td>\n",
" <td>4603.454839</td>\n",
" <td>16481.878019</td>\n",
" <td>5550.509322</td>\n",
" <td>5231.563163</td>\n",
" <td>2851.314646</td>\n",
" <td>51142.703515</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
feat: sample of Riskfolio Lib
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" <th>2017-02-06</th>\n",
" <td>9788.441837</td>\n",
" <td>6415.574983</td>\n",
" <td>4571.338111</td>\n",
" <td>16108.668256</td>\n",
" <td>5530.758809</td>\n",
" <td>5164.888473</td>\n",
" <td>2891.758229</td>\n",
" <td>50471.428698</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
feat: sample of Riskfolio Lib
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" <th>2017-02-07</th>\n",
" <td>9742.872944</td>\n",
" <td>6495.171587</td>\n",
" <td>4603.454839</td>\n",
" <td>15906.927777</td>\n",
" <td>5550.509322</td>\n",
" <td>5131.551127</td>\n",
" <td>2871.536605</td>\n",
" <td>50302.024201</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-04</th>\n",
feat: sample of Riskfolio Lib
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" <td>39171.358109</td>\n",
" <td>30579.119728</td>\n",
" <td>38784.898842</td>\n",
" <td>83087.762699</td>\n",
" <td>27004.221810</td>\n",
" <td>16191.813316</td>\n",
" <td>114720.838715</td>\n",
" <td>349540.013219</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
" <th>2023-08-07</th>\n",
feat: sample of Riskfolio Lib
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" <td>38572.220158</td>\n",
" <td>30757.320408</td>\n",
" <td>37570.500000</td>\n",
" <td>83643.696144</td>\n",
" <td>28085.397628</td>\n",
" <td>16125.270538</td>\n",
" <td>113007.957001</td>\n",
" <td>347762.361876</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
" <th>2023-08-08</th>\n",
feat: sample of Riskfolio Lib
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" <td>39150.701576</td>\n",
" <td>30792.961224</td>\n",
" <td>36963.300579</td>\n",
" <td>83593.164627</td>\n",
" <td>27312.880881</td>\n",
" <td>16066.050625</td>\n",
" <td>112320.000000</td>\n",
" <td>346199.059512</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-09</th>\n",
" <td>40183.701576</td>\n",
" <td>30935.521088</td>\n",
" <td>36750.778610</td>\n",
" <td>84553.417686</td>\n",
" <td>27595.250000</td>\n",
" <td>15783.949375</td>\n",
" <td>112221.720428</td>\n",
" <td>348024.338764</td>\n",
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" <tr>\n",
" <th>2023-08-11</th>\n",
" <td>40948.119370</td>\n",
" <td>32325.478912</td>\n",
" <td>34299.208958</td>\n",
" <td>84578.693085</td>\n",
" <td>27466.899510</td>\n",
" <td>15847.650833</td>\n",
" <td>108725.763428</td>\n",
" <td>344191.814095</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" </tbody>\n",
"</table>\n",
feat: sample of Riskfolio Lib
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"<p>1625 rows × 8 columns</p>\n",
feat: add portfolios simulation
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"</div>"
],
"text/plain": [
feat: sample of Riskfolio Lib
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" CMIG3.SA CPLE6.SA FESA4.SA PETR3.SA \\\n",
"Date \n",
"2017-02-01 9205.144042 6337.965883 4592.748901 16259.967590 \n",
"2017-02-02 9615.273934 6465.322914 4614.160777 16038.055955 \n",
"2017-02-03 9906.921354 6517.062172 4603.454839 16481.878019 \n",
"2017-02-06 9788.441837 6415.574983 4571.338111 16108.668256 \n",
"2017-02-07 9742.872944 6495.171587 4603.454839 15906.927777 \n",
"... ... ... ... ... \n",
"2023-08-04 39171.358109 30579.119728 38784.898842 83087.762699 \n",
"2023-08-07 38572.220158 30757.320408 37570.500000 83643.696144 \n",
"2023-08-08 39150.701576 30792.961224 36963.300579 83593.164627 \n",
"2023-08-09 40183.701576 30935.521088 36750.778610 84553.417686 \n",
"2023-08-11 40948.119370 32325.478912 34299.208958 84578.693085 \n",
feat: add portfolios simulation
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"\n",
feat: sample of Riskfolio Lib
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" RANI3.SA TAEE11.SA UNIP6.SA Total net worth \n",
"Date \n",
"2017-02-01 5550.509322 5179.176650 2871.536605 49997.048993 \n",
"2017-02-02 5550.509322 5222.037277 2855.359305 50360.719485 \n",
"2017-02-03 5550.509322 5231.563163 2851.314646 51142.703515 \n",
"2017-02-06 5530.758809 5164.888473 2891.758229 50471.428698 \n",
"2017-02-07 5550.509322 5131.551127 2871.536605 50302.024201 \n",
"... ... ... ... ... \n",
"2023-08-04 27004.221810 16191.813316 114720.838715 349540.013219 \n",
"2023-08-07 28085.397628 16125.270538 113007.957001 347762.361876 \n",
"2023-08-08 27312.880881 16066.050625 112320.000000 346199.059512 \n",
"2023-08-09 27595.250000 15783.949375 112221.720428 348024.338764 \n",
"2023-08-11 27466.899510 15847.650833 108725.763428 344191.814095 \n",
feat: add portfolios simulation
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"\n",
feat: sample of Riskfolio Lib
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"[1625 rows x 8 columns]"
feat: add portfolios simulation
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]
},
feat: sample of Riskfolio Lib
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"execution_count": 65,
feat: add portfolios simulation
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"net_worth"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Comparison with IBOV"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 66,
feat: add portfolios simulation
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"metadata": {},
"outputs": [],
"source": [
"ibov = yf.download(\"^BVSP\", start=start, progress=False)[\"Adj Close\"]"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 67,
feat: add portfolios simulation
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"metadata": {},
"outputs": [],
"source": [
"ibov_df = pd.DataFrame(ibov)"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 68,
feat: add portfolios simulation
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"metadata": {},
"outputs": [],
"source": [
"ibov_df.rename(columns={\"Adj Close\": \"IBOV\"}, inplace=True)"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 69,
feat: add portfolios simulation
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"metadata": {},
"outputs": [],
"source": [
"comparison = pd.merge(ibov_df, net_worth, how = \"inner\", on = \"Date\")"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 70,
feat: add portfolios simulation
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"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>IBOV</th>\n",
feat: sample of Riskfolio Lib
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" <th>CMIG3.SA</th>\n",
" <th>CPLE6.SA</th>\n",
" <th>FESA4.SA</th>\n",
" <th>PETR3.SA</th>\n",
" <th>RANI3.SA</th>\n",
" <th>TAEE11.SA</th>\n",
" <th>UNIP6.SA</th>\n",
feat: add portfolios simulation
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" <th>Total net worth</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
feat: sample of Riskfolio Lib
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" <th>2017-02-01</th>\n",
" <td>64836.000000</td>\n",
" <td>9205.144042</td>\n",
" <td>6337.965883</td>\n",
" <td>4592.748901</td>\n",
" <td>16259.967590</td>\n",
" <td>5550.509322</td>\n",
" <td>5179.176650</td>\n",
" <td>2871.536605</td>\n",
" <td>49997.048993</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
feat: sample of Riskfolio Lib
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" <th>2017-02-02</th>\n",
" <td>64578.000000</td>\n",
" <td>9615.273934</td>\n",
" <td>6465.322914</td>\n",
" <td>4614.160777</td>\n",
" <td>16038.055955</td>\n",
" <td>5550.509322</td>\n",
" <td>5222.037277</td>\n",
" <td>2855.359305</td>\n",
" <td>50360.719485</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
feat: sample of Riskfolio Lib
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" <th>2017-02-03</th>\n",
" <td>64954.000000</td>\n",
" <td>9906.921354</td>\n",
" <td>6517.062172</td>\n",
" <td>4603.454839</td>\n",
" <td>16481.878019</td>\n",
" <td>5550.509322</td>\n",
" <td>5231.563163</td>\n",
" <td>2851.314646</td>\n",
" <td>51142.703515</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
feat: sample of Riskfolio Lib
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" <th>2017-02-06</th>\n",
" <td>63993.000000</td>\n",
" <td>9788.441837</td>\n",
" <td>6415.574983</td>\n",
" <td>4571.338111</td>\n",
" <td>16108.668256</td>\n",
" <td>5530.758809</td>\n",
" <td>5164.888473</td>\n",
" <td>2891.758229</td>\n",
" <td>50471.428698</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
feat: sample of Riskfolio Lib
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" <th>2017-02-07</th>\n",
" <td>64199.000000</td>\n",
" <td>9742.872944</td>\n",
" <td>6495.171587</td>\n",
" <td>4603.454839</td>\n",
" <td>15906.927777</td>\n",
" <td>5550.509322</td>\n",
" <td>5131.551127</td>\n",
" <td>2871.536605</td>\n",
" <td>50302.024201</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-04</th>\n",
" <td>119508.000000</td>\n",
feat: sample of Riskfolio Lib
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" <td>39171.358109</td>\n",
" <td>30579.119728</td>\n",
" <td>38784.898842</td>\n",
" <td>83087.762699</td>\n",
" <td>27004.221810</td>\n",
" <td>16191.813316</td>\n",
" <td>114720.838715</td>\n",
" <td>349540.013219</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-07</th>\n",
" <td>119380.000000</td>\n",
" <td>38572.220158</td>\n",
" <td>30757.320408</td>\n",
" <td>37570.500000</td>\n",
" <td>83643.696144</td>\n",
" <td>28085.397628</td>\n",
" <td>16125.270538</td>\n",
" <td>113007.957001</td>\n",
" <td>347762.361876</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
" <th>2023-08-08</th>\n",
feat: sample of Riskfolio Lib
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" <td>119090.000000</td>\n",
" <td>39150.701576</td>\n",
" <td>30792.961224</td>\n",
" <td>36963.300579</td>\n",
" <td>83593.164627</td>\n",
" <td>27312.880881</td>\n",
" <td>16066.050625</td>\n",
" <td>112320.000000</td>\n",
" <td>346199.059512</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-09</th>\n",
" <td>118409.000000</td>\n",
" <td>40183.701576</td>\n",
" <td>30935.521088</td>\n",
" <td>36750.778610</td>\n",
" <td>84553.417686</td>\n",
" <td>27595.250000</td>\n",
" <td>15783.949375</td>\n",
" <td>112221.720428</td>\n",
" <td>348024.338764</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-11</th>\n",
" <td>118065.140625</td>\n",
" <td>40948.119370</td>\n",
" <td>32325.478912</td>\n",
" <td>34299.208958</td>\n",
" <td>84578.693085</td>\n",
" <td>27466.899510</td>\n",
" <td>15847.650833</td>\n",
" <td>108725.763428</td>\n",
" <td>344191.814095</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" </tbody>\n",
"</table>\n",
feat: sample of Riskfolio Lib
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"<p>1617 rows × 9 columns</p>\n",
feat: add portfolios simulation
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"</div>"
],
"text/plain": [
feat: sample of Riskfolio Lib
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" IBOV CMIG3.SA CPLE6.SA FESA4.SA \\\n",
"Date \n",
"2017-02-01 64836.000000 9205.144042 6337.965883 4592.748901 \n",
"2017-02-02 64578.000000 9615.273934 6465.322914 4614.160777 \n",
"2017-02-03 64954.000000 9906.921354 6517.062172 4603.454839 \n",
"2017-02-06 63993.000000 9788.441837 6415.574983 4571.338111 \n",
"2017-02-07 64199.000000 9742.872944 6495.171587 4603.454839 \n",
"... ... ... ... ... \n",
"2023-08-04 119508.000000 39171.358109 30579.119728 38784.898842 \n",
"2023-08-07 119380.000000 38572.220158 30757.320408 37570.500000 \n",
"2023-08-08 119090.000000 39150.701576 30792.961224 36963.300579 \n",
"2023-08-09 118409.000000 40183.701576 30935.521088 36750.778610 \n",
"2023-08-11 118065.140625 40948.119370 32325.478912 34299.208958 \n",
feat: add portfolios simulation
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"\n",
feat: sample of Riskfolio Lib
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" PETR3.SA RANI3.SA TAEE11.SA UNIP6.SA \\\n",
"Date \n",
"2017-02-01 16259.967590 5550.509322 5179.176650 2871.536605 \n",
"2017-02-02 16038.055955 5550.509322 5222.037277 2855.359305 \n",
"2017-02-03 16481.878019 5550.509322 5231.563163 2851.314646 \n",
"2017-02-06 16108.668256 5530.758809 5164.888473 2891.758229 \n",
"2017-02-07 15906.927777 5550.509322 5131.551127 2871.536605 \n",
"... ... ... ... ... \n",
"2023-08-04 83087.762699 27004.221810 16191.813316 114720.838715 \n",
"2023-08-07 83643.696144 28085.397628 16125.270538 113007.957001 \n",
"2023-08-08 83593.164627 27312.880881 16066.050625 112320.000000 \n",
"2023-08-09 84553.417686 27595.250000 15783.949375 112221.720428 \n",
"2023-08-11 84578.693085 27466.899510 15847.650833 108725.763428 \n",
feat: add portfolios simulation
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"\n",
" Total net worth \n",
"Date \n",
feat: sample of Riskfolio Lib
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"2017-02-01 49997.048993 \n",
"2017-02-02 50360.719485 \n",
"2017-02-03 51142.703515 \n",
"2017-02-06 50471.428698 \n",
"2017-02-07 50302.024201 \n",
feat: add portfolios simulation
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"... ... \n",
feat: sample of Riskfolio Lib
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"2023-08-04 349540.013219 \n",
"2023-08-07 347762.361876 \n",
"2023-08-08 346199.059512 \n",
"2023-08-09 348024.338764 \n",
"2023-08-11 344191.814095 \n",
feat: add portfolios simulation
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"\n",
feat: sample of Riskfolio Lib
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"[1617 rows x 9 columns]"
feat: add portfolios simulation
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]
},
feat: sample of Riskfolio Lib
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"execution_count": 70,
feat: add portfolios simulation
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"comparison"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Data normalization (data scaling)"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 71,
feat: add portfolios simulation
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"metadata": {},
"outputs": [],
"source": [
"comparison = comparison.dropna()\n",
"comparison_scaling = comparison / comparison.iloc[0]"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
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"execution_count": 72,
feat: add portfolios simulation
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"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
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" vertical-align: top;\n",
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" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>IBOV</th>\n",
feat: sample of Riskfolio Lib
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" <th>CMIG3.SA</th>\n",
" <th>CPLE6.SA</th>\n",
" <th>FESA4.SA</th>\n",
" <th>PETR3.SA</th>\n",
" <th>RANI3.SA</th>\n",
" <th>TAEE11.SA</th>\n",
" <th>UNIP6.SA</th>\n",
feat: add portfolios simulation
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" <th>Total net worth</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
feat: sample of Riskfolio Lib
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" <th>2017-02-01</th>\n",
feat: add portfolios simulation
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" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
feat: sample of Riskfolio Lib
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" <th>2017-02-02</th>\n",
" <td>0.996021</td>\n",
" <td>1.044554</td>\n",
" <td>1.020094</td>\n",
" <td>1.004662</td>\n",
" <td>0.986352</td>\n",
feat: add portfolios simulation
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" <td>1.000000</td>\n",
feat: sample of Riskfolio Lib
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" <td>1.008276</td>\n",
" <td>0.994366</td>\n",
" <td>1.007274</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
feat: sample of Riskfolio Lib
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" <th>2017-02-03</th>\n",
" <td>1.001820</td>\n",
" <td>1.076238</td>\n",
" <td>1.028258</td>\n",
" <td>1.002331</td>\n",
" <td>1.013648</td>\n",
" <td>1.000000</td>\n",
" <td>1.010115</td>\n",
" <td>0.992958</td>\n",
" <td>1.022914</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
feat: sample of Riskfolio Lib
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" <th>2017-02-06</th>\n",
" <td>0.986998</td>\n",
" <td>1.063367</td>\n",
" <td>1.012245</td>\n",
" <td>0.995338</td>\n",
" <td>0.990695</td>\n",
" <td>0.996442</td>\n",
" <td>0.997241</td>\n",
" <td>1.007042</td>\n",
" <td>1.009488</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
feat: sample of Riskfolio Lib
2023-08-11 18:40:26 -03:00
" <th>2017-02-07</th>\n",
" <td>0.990175</td>\n",
" <td>1.058416</td>\n",
" <td>1.024804</td>\n",
" <td>1.002331</td>\n",
" <td>0.978288</td>\n",
" <td>1.000000</td>\n",
" <td>0.990804</td>\n",
" <td>1.000000</td>\n",
" <td>1.006100</td>\n",
feat: add portfolios simulation
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" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-04</th>\n",
feat: sample of Riskfolio Lib
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" <td>1.843235</td>\n",
" <td>4.255377</td>\n",
" <td>4.824753</td>\n",
" <td>8.444812</td>\n",
" <td>5.109959</td>\n",
" <td>4.865179</td>\n",
" <td>3.126330</td>\n",
" <td>39.951028</td>\n",
" <td>6.991213</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-07</th>\n",
" <td>1.841261</td>\n",
" <td>4.190290</td>\n",
" <td>4.852869</td>\n",
" <td>8.180395</td>\n",
" <td>5.144149</td>\n",
" <td>5.059968</td>\n",
" <td>3.113481</td>\n",
" <td>39.354524</td>\n",
" <td>6.955658</td>\n",
feat: add portfolios simulation
2023-08-08 16:00:39 -03:00
" </tr>\n",
" <tr>\n",
" <th>2023-08-08</th>\n",
feat: sample of Riskfolio Lib
2023-08-11 18:40:26 -03:00
" <td>1.836788</td>\n",
" <td>4.253133</td>\n",
" <td>4.858493</td>\n",
" <td>8.048187</td>\n",
" <td>5.141041</td>\n",
" <td>4.920788</td>\n",
" <td>3.102047</td>\n",
" <td>39.114946</td>\n",
" <td>6.924390</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-09</th>\n",
" <td>1.826285</td>\n",
" <td>4.365353</td>\n",
" <td>4.880986</td>\n",
" <td>8.001913</td>\n",
" <td>5.200098</td>\n",
" <td>4.971661</td>\n",
" <td>3.047579</td>\n",
" <td>39.080721</td>\n",
" <td>6.960898</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023-08-11</th>\n",
" <td>1.820981</td>\n",
" <td>4.448395</td>\n",
" <td>5.100292</td>\n",
" <td>7.468122</td>\n",
" <td>5.201652</td>\n",
" <td>4.948537</td>\n",
" <td>3.059878</td>\n",
" <td>37.863269</td>\n",
" <td>6.884243</td>\n",
feat: add portfolios simulation
2023-08-08 16:00:39 -03:00
" </tr>\n",
" </tbody>\n",
"</table>\n",
feat: sample of Riskfolio Lib
2023-08-11 18:40:26 -03:00
"<p>1616 rows × 9 columns</p>\n",
feat: add portfolios simulation
2023-08-08 16:00:39 -03:00
"</div>"
],
"text/plain": [
feat: sample of Riskfolio Lib
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" IBOV CMIG3.SA CPLE6.SA FESA4.SA PETR3.SA RANI3.SA \\\n",
"Date \n",
"2017-02-01 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 \n",
"2017-02-02 0.996021 1.044554 1.020094 1.004662 0.986352 1.000000 \n",
"2017-02-03 1.001820 1.076238 1.028258 1.002331 1.013648 1.000000 \n",
"2017-02-06 0.986998 1.063367 1.012245 0.995338 0.990695 0.996442 \n",
"2017-02-07 0.990175 1.058416 1.024804 1.002331 0.978288 1.000000 \n",
"... ... ... ... ... ... ... \n",
"2023-08-04 1.843235 4.255377 4.824753 8.444812 5.109959 4.865179 \n",
"2023-08-07 1.841261 4.190290 4.852869 8.180395 5.144149 5.059968 \n",
"2023-08-08 1.836788 4.253133 4.858493 8.048187 5.141041 4.920788 \n",
"2023-08-09 1.826285 4.365353 4.880986 8.001913 5.200098 4.971661 \n",
"2023-08-11 1.820981 4.448395 5.100292 7.468122 5.201652 4.948537 \n",
feat: add portfolios simulation
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"\n",
feat: sample of Riskfolio Lib
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" TAEE11.SA UNIP6.SA Total net worth \n",
"Date \n",
"2017-02-01 1.000000 1.000000 1.000000 \n",
"2017-02-02 1.008276 0.994366 1.007274 \n",
"2017-02-03 1.010115 0.992958 1.022914 \n",
"2017-02-06 0.997241 1.007042 1.009488 \n",
"2017-02-07 0.990804 1.000000 1.006100 \n",
"... ... ... ... \n",
"2023-08-04 3.126330 39.951028 6.991213 \n",
"2023-08-07 3.113481 39.354524 6.955658 \n",
"2023-08-08 3.102047 39.114946 6.924390 \n",
"2023-08-09 3.047579 39.080721 6.960898 \n",
"2023-08-11 3.059878 37.863269 6.884243 \n",
feat: add portfolios simulation
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"\n",
feat: sample of Riskfolio Lib
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"[1616 rows x 9 columns]"
feat: add portfolios simulation
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]
},
feat: sample of Riskfolio Lib
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"execution_count": 72,
feat: add portfolios simulation
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"comparison_scaling"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
2023-08-11 18:40:26 -03:00
"execution_count": 73,
feat: add portfolios simulation
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"metadata": {},
"outputs": [
{
"data": {
feat: sample of Riskfolio Lib
2023-08-11 18:40:26 -03:00
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAh8AAAGVCAYAAABenpPyAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAADINklEQVR4nOzdd3jTVdvA8W/SvaG7pUChUFr23nsLKmBRQIYg8ry4BRVFfR4BcQ9EGQqW4UBkLxFRZEPZZZUNBUpbKIXu3eT9o+ZH0qST7t6f68pF8punpW3u3Oec+6i0Wq0WIYQQQogyoi7vBgghhBCiepHgQwghhBBlSoIPIYQQQpQpCT6EEEIIUaYk+BBCCCFEmZLgQwghhBBlSoIPIYQQQpQpCT6EEEIIUabMy7sBuWk0GiIjI3FwcEClUpV3c4QQQghRCFqtlsTERLy9vVGr889tVLjgIzIyktq1a5d3M4QQQghRDDdv3sTHxyffYypc8OHg4ADkNN7R0bGcWyOEEEKIwkhISKB27drK+3h+KlzwoetqcXR0lOBDCCGEqGQKM2RCBpwKIYQQokxJ8CGEEEKIMiXBhxBCCCHKVIUb81EYWq2WrKwssrOzy7spogqysLDAzMysvJshhBBVVqULPjIyMoiKiiIlJaW8myKqKJVKhY+PD/b29uXdFCGEqJIqVfCh0Wi4du0aZmZmeHt7Y2lpKYXIRInSarXExMQQERFBw4YNJQMihBCloFIFHxkZGWg0GmrXro2trW15N0dUUW5uboSHh5OZmSnBhxBClIJKOeC0oLKtQjwMyaYJIUTpkndxIYQQQpQpCT6EEEIIUaYq1ZgPIYQQoqykpqayd+9erK2t6dixI5aWluXdpCpDMh9lZPz48QwdOlR5rlKplIeLiwsDBw7k1KlTBudkZ2czZ84cmjVrhrW1NTVr1uSRRx5h//79yjGPPfYYAwcONHnPvXv3olKpjK4rhBCiYKdPn+bAgQP8888/hIWFlXdzqhQJPsrJwIEDiYqKIioqih07dmBubs6jjz6q7NdqtYwcOZJZs2bx6quvcu7cOXbt2kXt2rXp2bMnGzZsAGDixIn89ddfREREGN1j6dKltG3blubNm5fVlyWEEFVGcnKy8vzo0aMkJCSUY2uqlkrf7aLVaknNLJ9KpzYWZsWeGWFlZYWnpycAnp6evP3223Tr1o2YmBjc3NxYtWoVa9asYdOmTTz22GPKeYsWLSI2NpbnnnuOfv368eijj+Lm5sayZct47733lOOSkpJYvXo1n3/++cN9kUIIUU2lpaUpzyMiIvjuu++YNm1aObao6qj0wUdqZjaN//dnudw7bNYAbC0f/luYlJTEzz//TIMGDXBxcQFgxYoV+Pv7GwQeOq+//jrr1q3jr7/+YujQoYwbN45ly5bx7rvvKsHQ6tWryc7OZtSoUQ/dPiGEqI70gw9AKmuXIOl2KSdbtmzB3t4ee3t7HBwc2LRpE7/99ptSw+TixYsEBgaaPFe3/eLFiwA8++yzXLlyhd27dyvHLF26lKCgIJycnEr5KxFCiKopd/AhSk6lz3zYWJgRNmtAud27uHr16sXChQsBuH//PgsWLOCRRx7h8OHD1K1bF8jpUiqMgIAAOnfuzJIlS+jZsyeXL19m7969zJo1q9jtE0KI6k6Cj9JT6YMPlUpVIl0fZc3Ozo4GDRoor3/44QecnJxYvHgxs2fPxt/fn3Pnzpk8V7fd399f2TZx4kRefvll5s+fz9KlS/Hz86NHjx6l+0UIIUQVJsFH6ZFulwpCpVKhVqtJTU0FYOTIkVy6dInNmzcbHfvll1/i4uJCv379lG1PPfUUarWaFStW8OOPP/Lss89KmXAhhHgIGo2mvJtQZVW+lEEVkZ6eTnR0NJDT7TJv3jySkpKUAaYjR45k9erVPPPMM3z++ef06dOHhIQE5s+fz6ZNm1i9ejV2dnbK9ezt7RkxYgTTp08nISGB8ePHl8eXJYQQVUZhu75F0UnwUU62bduGl5cXAA4ODgQEBLB69Wp69uwJ5GRCVq1axddff82cOXN44YUXsLa2plOnTuzatYsuXboYXXPixIkEBwczaNAgvL29y/LLEUKIKuPKlSvExMRI5qMUqbQVLLRLSEjAycmJ+Ph4HB0dDfalpaVx7do16tWrh7W1dTm1UFR18nMmRPU2Y8aMPPf997//xcys+JMNqrL83r9zkzEfQgghRCFlZmaWdxOqBAk+hBBCiEKS4KNkFCn4mDFjhsGCaCqVioCAAGV/WloaL774Ii4uLtjb2xMUFMTt27dLvNFCCCFEeZBxICWjyJmPJk2aKAuiRUVFsW/fPmXflClT2Lx5M6tXr2b37t1ERkbyxBNPlGiDhRBCiPIiwUfJKPJsF3Nzc2VBNH3x8fEEBwezYsUKevfuDeSU+A4MDCQkJISOHTs+fGuFEEKIUlTQHIwKNkej0ipy5uPSpUt4e3tTv359Ro8ezY0bNwA4duwYmZmZ9O3bVzk2ICCAOnXqcPDgwTyvl56eTkJCgsFDCCGEKA8FZTYk81EyihR8dOjQgWXLlrFt2zYWLlzItWvX6NatG4mJiURHR2NpaUmNGjUMzvHw8FCKaZny8ccf4+TkpDxq165drC9ECCGEeFgFBReS+SgZRep2eeSRR5TnzZs3p0OHDtStW5dVq1ZhY2NTrAZMnz6dqVOnKq8TEhIkABFCCFEusrOz890vwUfJeKiptjVq1MDf35/Lly/j6elJRkYGcXFxBsfcvn3b5BgRHSsrKxwdHQ0eQgghRHkwlfnQ/+At3S4l46GCj6SkJK5cuYKXlxdt2rTBwsKCHTt2KPsvXLjAjRs36NSp00M3tCqIjo7m5Zdfpn79+lhZWVG7dm0ee+wx5Xvm6+uLSqVi5cqVRuc2adIElUrFsmXLlG2+vr58/fXXBsedOHGCESNG4OXlhZWVFXXr1uXRRx9l8+bNSsQeGxvLwIED8fb2Vtrx0ksvFTjeZvfu3fTu3RtnZ2dsbW1p2LAhzzzzDBkZGUbH/t///R9mZmasXr26iN8lIYQoP6ZWsm3cuDEODg6AZD5KSpGCjzfeeIPdu3cTHh7OgQMHGDZsGGZmZowaNQonJycmTpzI1KlT2blzJ8eOHWPChAl06tRJZroA4eHhtGnThn/++YfPP/+c06dPs23bNnr16sWLL76oHFe7dm2WLl1qcG5ISAjR0dEGC8mZsnHjRjp27EhSUhLLly/n3LlzbNu2jWHDhvHee+8RHx8PgFqtZsiQIWzatImLFy+ybNky/v77byZPnpzntcPCwhg4cCBt27Zlz549nD59mm+//RZLS0ujNGVKSgorV65k2rRpLFmypKjfKiGEKDeJiYlG28zNzZVVwiXzUTKKNOYjIiKCUaNGERsbi5ubG127diUkJAQ3NzcA5syZg1qtJigoiPT0dAYMGMCCBQtKpeGVzQsvvIBKpeLw4cMGQUSTJk149tlnldejR49mzpw53Lx5Uxn7smTJEkaPHs2PP/6Y5/WTk5OZOHEigwcPZt26dQb7AgMDmThxohKx16xZk+eff17ZX7duXV544QU+//zzPK+/fft2PD09+eyzz5Rtfn5+DBw40OjY1atX07hxY95++228vb0NvhYhhKjIcgcfjz/+ODY2NkrwIZmPklGkzMfKlSuJjIwkPT2diIgIVq5ciZ+fn7Lf2tqa+fPnc+/ePZKTk1m3bl2+4z1KhFYLGcnl8yjkD+G9e/fYtm0bL774osnshf4MIQ8PDwYMGMDy5cuBnCzCb7/9ZhCgmLJ9+3ZiY2OZNm1ansfofnlyi4yMZN26dfTo0SPPcz09PYmKimLPnj35tgMgODiYMWPG4OTkxCOPPGLQVSSEEBVZ7uCjVatWQE7GGCT4KClFLjJW4WSmwEfltHz8O5FgmX9XCMDly5fRarUGpejz8+yzz/L666/z7rvvsmbNGvz8/GjZsmW+51y8eBGARo0aKduOHDlCr169lNcrV67k0UcfVV6PGjWKjRs3kpqaymOPPcYPP/yQ5/WffPJJ/vzzT3r06IGnpycdO3akT58+jBs3zmCQ8KV
feat: add portfolios simulation
2023-08-08 16:00:39 -03:00
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"comparison_scaling.plot();"
]
},
{
"cell_type": "code",
feat: sample of Riskfolio Lib
2023-08-11 18:40:26 -03:00
"execution_count": 74,
feat: add portfolios simulation
2023-08-08 16:00:39 -03:00
"metadata": {},
"outputs": [
{
"data": {
feat: sample of Riskfolio Lib
2023-08-11 18:40:26 -03:00
"image/png": "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
feat: add portfolios simulation
2023-08-08 16:00:39 -03:00
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"comparison_scaling[[\"IBOV\", \"Total net worth\"]].plot();"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "venv",
"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": "3.10.11"
},
"orig_nbformat": 4
},
"nbformat": 4,
"nbformat_minor": 2
}
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