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options_backtester/backtester/examples/2legs_example.ipynb
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Juan Pablo Amoroso 0e55dd51e5 Refactored pyfolio notebook
2020-03-20 13:35:30 -03:00

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import sys\n",
"\n",
"BACKTESTER_DIR = os.path.realpath(os.path.join(os.getcwd(), '..', '..'))\n",
"DATA_DIR = os.path.join(BACKTESTER_DIR, 'data')\n",
"OPTIONS_DATA = os.path.join(DATA_DIR, 'options_data_clean_v2.h5')\n",
"STOCKS_DATA = os.path.join(DATA_DIR, 'ivy_5assets.csv')\n",
"\n",
"sys.path.append(BACKTESTER_DIR) # Add backtester base dir to $PYTHONPATH"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/jamoroso/.local/share/virtualenvs/backtester_options-33KCFJeg/lib/python3.7/site-packages/pandas_datareader/compat/__init__.py:7: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
" from pandas.util.testing import assert_frame_equal\n",
"/Users/jamoroso/.local/share/virtualenvs/backtester_options-33KCFJeg/lib/python3.7/site-packages/pyfolio/pos.py:27: UserWarning: Module \"zipline.assets\" not found; mutltipliers will not be applied to position notionals.\n",
" 'Module \"zipline.assets\" not found; mutltipliers will not be applied' +\n"
]
}
],
"source": [
"import pyfolio as pf\n",
"\n",
"from backtester import Backtest, Type, Direction, Stock\n",
"from backtester.strategy import Strategy, StrategyLeg\n",
"from backtester.datahandler import HistoricalOptionsData, TiingoData\n",
"\n",
"# Cleaned up data\n",
"options_data = HistoricalOptionsData(\n",
" OPTIONS_DATA,\n",
" key=\"/SPX\",\n",
" where='quotedate >= \"2012-01-01\" & quotedate <= \"2014-01-01\"')\n",
"options_schema = options_data.schema"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Strategy(legs=[StrategyLeg(name=leg_1, type=Type.PUT, direction=Direction.BUY, entry_filter=Filter(query='((type == 'put') & (ask > 0)) & ((underlying == 'SPX') & (dte >= 60))'), exit_filter=Filter(query='(type == 'put') & (dte <= 30)')), StrategyLeg(name=leg_2, type=Type.CALL, direction=Direction.BUY, entry_filter=Filter(query='((type == 'call') & (ask > 0)) & ((underlying == 'SPX') & (dte >= 60))'), exit_filter=Filter(query='(type == 'call') & (dte <= 30)'))], exit_thresholds=(inf, inf))"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"put_otm = Strategy(options_schema)\n",
"\n",
"leg_1 = StrategyLeg(\"leg_1\", options_schema, option_type=Type.PUT, direction=Direction.BUY)\n",
"leg_1.entry_filter = (options_schema.underlying == \"SPX\") & (options_schema.dte >= 60)\n",
"leg_1.exit_filter = (options_schema.dte <= 30)\n",
"\n",
"leg_2 = StrategyLeg(\"leg_2\", options_schema, option_type=Type.CALL, direction=Direction.BUY)\n",
"leg_2.entry_filter = (options_schema.underlying == \"SPX\") & (options_schema.dte >= 60)\n",
"leg_2.exit_filter = (options_schema.dte <= 30)\n",
"put_otm.add_legs([leg_1, leg_2])"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"asset_data = TiingoData(STOCKS_DATA)\n",
"asset_data._data = asset_data.query('date >= \"2012-01-01\" & date <= \"2014-01-01\"')\n",
"\n",
"VTI = Stock(\"VTI\", 0.2)\n",
"VEU = Stock(\"VEU\", 0.2)\n",
"BND = Stock(\"BND\", 0.2)\n",
"VNQ = Stock(\"VNQ\", 0.2)\n",
"DBC = Stock(\"DBC\", 0.2)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"0% [██████████████████████████████] 100% | ETA: 00:00:00\n",
"Total time elapsed: 00:00:07\n"
]
},
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>total capital</th>\n",
" <th>cash</th>\n",
" <th>VTI</th>\n",
" <th>VEU</th>\n",
" <th>BND</th>\n",
" <th>VNQ</th>\n",
" <th>DBC</th>\n",
" <th>options qty</th>\n",
" <th>calls capital</th>\n",
" <th>puts capital</th>\n",
" <th>stocks qty</th>\n",
" <th>options capital</th>\n",
" <th>stocks capital</th>\n",
" <th>% change</th>\n",
" <th>accumulated return</th>\n",
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" <tr>\n",
" <th>2010-01-03</th>\n",
" <td>1.000000e+06</td>\n",
" <td>1000000.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <th>2012-01-03</th>\n",
" <td>9.978700e+05</td>\n",
" <td>2233.455073</td>\n",
" <td>193990.075633</td>\n",
" <td>193976.304225</td>\n",
" <td>193986.878802</td>\n",
" <td>193966.992283</td>\n",
" <td>193976.293985</td>\n",
" <td>6.0</td>\n",
" <td>25740.0</td>\n",
" <td>0.0</td>\n",
" <td>24257.0</td>\n",
" <td>25740.0</td>\n",
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" <tr>\n",
" <th>2012-01-04</th>\n",
" <td>9.949656e+05</td>\n",
" <td>2233.455073</td>\n",
" <td>194079.321182</td>\n",
" <td>193451.915101</td>\n",
" <td>194080.052134</td>\n",
" <td>190650.750322</td>\n",
" <td>195450.064670</td>\n",
" <td>6.0</td>\n",
" <td>25020.0</td>\n",
" <td>0.0</td>\n",
" <td>24257.0</td>\n",
" <td>25020.0</td>\n",
" <td>9.677121e+05</td>\n",
" <td>-0.002911</td>\n",
" <td>0.994966</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012-01-05</th>\n",
" <td>9.927494e+05</td>\n",
" <td>2233.455073</td>\n",
" <td>194942.028158</td>\n",
" <td>191259.015126</td>\n",
" <td>194010.172135</td>\n",
" <td>192441.520981</td>\n",
" <td>192783.241526</td>\n",
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" <th>2012-01-06</th>\n",
" <td>9.887005e+05</td>\n",
" <td>2233.455073</td>\n",
" <td>194495.800412</td>\n",
" <td>188827.756460</td>\n",
" <td>194126.638801</td>\n",
" <td>191811.435009</td>\n",
" <td>193625.396202</td>\n",
" <td>6.0</td>\n",
" <td>23580.0</td>\n",
" <td>0.0</td>\n",
" <td>24257.0</td>\n",
" <td>23580.0</td>\n",
" <td>9.628870e+05</td>\n",
" <td>-0.004079</td>\n",
" <td>0.988700</td>\n",
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" <tr>\n",
" <th>...</th>\n",
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" <th>2013-12-24</th>\n",
" <td>1.276243e+06</td>\n",
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" <td>248730.685735</td>\n",
" <td>246256.243708</td>\n",
" <td>242926.387533</td>\n",
" <td>245754.530575</td>\n",
" <td>246032.446280</td>\n",
" <td>7.0</td>\n",
" <td>46270.0</td>\n",
" <td>0.0</td>\n",
" <td>27125.0</td>\n",
" <td>46270.0</td>\n",
" <td>1.229700e+06</td>\n",
" <td>0.003401</td>\n",
" <td>1.276243</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013-12-26</th>\n",
" <td>1.282165e+06</td>\n",
" <td>273.097958</td>\n",
" <td>249907.026341</td>\n",
" <td>247293.424036</td>\n",
" <td>242562.316514</td>\n",
" <td>245944.449069</td>\n",
" <td>246414.781084</td>\n",
" <td>7.0</td>\n",
" <td>49770.0</td>\n",
" <td>0.0</td>\n",
" <td>27125.0</td>\n",
" <td>49770.0</td>\n",
" <td>1.232122e+06</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>2013-12-27</th>\n",
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" <td>249750.180927</td>\n",
" <td>248281.214826</td>\n",
" <td>242562.316514</td>\n",
" <td>246476.220851</td>\n",
" <td>247083.866990</td>\n",
" <td>7.0</td>\n",
" <td>49840.0</td>\n",
" <td>0.0</td>\n",
" <td>27125.0</td>\n",
" <td>49840.0</td>\n",
" <td>1.234154e+06</td>\n",
" <td>0.001639</td>\n",
" <td>1.284267</td>\n",
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" <tr>\n",
" <th>2013-12-30</th>\n",
" <td>1.284806e+06</td>\n",
" <td>273.097958</td>\n",
" <td>249828.603634</td>\n",
" <td>249565.342851</td>\n",
" <td>242956.726785</td>\n",
" <td>246552.188248</td>\n",
" <td>245650.111476</td>\n",
" <td>7.0</td>\n",
" <td>49980.0</td>\n",
" <td>0.0</td>\n",
" <td>27125.0</td>\n",
" <td>49980.0</td>\n",
" <td>1.234553e+06</td>\n",
" <td>0.000420</td>\n",
" <td>1.284806</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013-12-31</th>\n",
" <td>1.288826e+06</td>\n",
" <td>273.097958</td>\n",
" <td>250743.535215</td>\n",
" <td>250553.133640</td>\n",
" <td>242865.709030</td>\n",
" <td>245222.758794</td>\n",
" <td>245267.776672</td>\n",
" <td>7.0</td>\n",
" <td>53900.0</td>\n",
" <td>0.0</td>\n",
" <td>27125.0</td>\n",
" <td>53900.0</td>\n",
" <td>1.234653e+06</td>\n",
" <td>0.003129</td>\n",
" <td>1.288826</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>503 rows × 15 columns</p>\n",
"</div>"
],
"text/plain": [
" total capital cash VTI VEU \\\n",
"2010-01-03 1.000000e+06 1000000.000000 NaN NaN \n",
"2012-01-03 9.978700e+05 2233.455073 193990.075633 193976.304225 \n",
"2012-01-04 9.949656e+05 2233.455073 194079.321182 193451.915101 \n",
"2012-01-05 9.927494e+05 2233.455073 194942.028158 191259.015126 \n",
"2012-01-06 9.887005e+05 2233.455073 194495.800412 188827.756460 \n",
"... ... ... ... ... \n",
"2013-12-24 1.276243e+06 273.097958 248730.685735 246256.243708 \n",
"2013-12-26 1.282165e+06 273.097958 249907.026341 247293.424036 \n",
"2013-12-27 1.284267e+06 273.097958 249750.180927 248281.214826 \n",
"2013-12-30 1.284806e+06 273.097958 249828.603634 249565.342851 \n",
"2013-12-31 1.288826e+06 273.097958 250743.535215 250553.133640 \n",
"\n",
" BND VNQ DBC options qty \\\n",
"2010-01-03 NaN NaN NaN NaN \n",
"2012-01-03 193986.878802 193966.992283 193976.293985 6.0 \n",
"2012-01-04 194080.052134 190650.750322 195450.064670 6.0 \n",
"2012-01-05 194010.172135 192441.520981 192783.241526 6.0 \n",
"2012-01-06 194126.638801 191811.435009 193625.396202 6.0 \n",
"... ... ... ... ... \n",
"2013-12-24 242926.387533 245754.530575 246032.446280 7.0 \n",
"2013-12-26 242562.316514 245944.449069 246414.781084 7.0 \n",
"2013-12-27 242562.316514 246476.220851 247083.866990 7.0 \n",
"2013-12-30 242956.726785 246552.188248 245650.111476 7.0 \n",
"2013-12-31 242865.709030 245222.758794 245267.776672 7.0 \n",
"\n",
" calls capital puts capital stocks qty options capital \\\n",
"2010-01-03 NaN NaN NaN 0.0 \n",
"2012-01-03 25740.0 0.0 24257.0 25740.0 \n",
"2012-01-04 25020.0 0.0 24257.0 25020.0 \n",
"2012-01-05 25080.0 0.0 24257.0 25080.0 \n",
"2012-01-06 23580.0 0.0 24257.0 23580.0 \n",
"... ... ... ... ... \n",
"2013-12-24 46270.0 0.0 27125.0 46270.0 \n",
"2013-12-26 49770.0 0.0 27125.0 49770.0 \n",
"2013-12-27 49840.0 0.0 27125.0 49840.0 \n",
"2013-12-30 49980.0 0.0 27125.0 49980.0 \n",
"2013-12-31 53900.0 0.0 27125.0 53900.0 \n",
"\n",
" stocks capital % change accumulated return \n",
"2010-01-03 0.000000e+00 NaN NaN \n",
"2012-01-03 9.698965e+05 -0.002130 0.997870 \n",
"2012-01-04 9.677121e+05 -0.002911 0.994966 \n",
"2012-01-05 9.654360e+05 -0.002227 0.992749 \n",
"2012-01-06 9.628870e+05 -0.004079 0.988700 \n",
"... ... ... ... \n",
"2013-12-24 1.229700e+06 0.003401 1.276243 \n",
"2013-12-26 1.232122e+06 0.004640 1.282165 \n",
"2013-12-27 1.234154e+06 0.001639 1.284267 \n",
"2013-12-30 1.234553e+06 0.000420 1.284806 \n",
"2013-12-31 1.234653e+06 0.003129 1.288826 \n",
"\n",
"[503 rows x 15 columns]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"allocation = {'cash': 0, 'stocks': 97, 'options': 3}\n",
"\n",
"bt = Backtest(allocation=allocation)\n",
"bt.options_data = options_data\n",
"bt.options_strategy = put_otm\n",
"\n",
"bt.stocks = [VTI, VEU, BND, VNQ, DBC]\n",
"bt.stocks_data = asset_data\n",
"\n",
"bt.run(rebalance_freq=1)\n",
"bt.balance"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\"><th>Start date</th><td colspan=2>2012-01-03</td></tr>\n",
" <tr style=\"text-align: right;\"><th>End date</th><td colspan=2>2013-12-31</td></tr>\n",
" <tr style=\"text-align: right;\"><th>Total months</th><td colspan=2>23</td></tr>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Backtest</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Annual return</th>\n",
" <td>13.6%</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Cumulative returns</th>\n",
" <td>28.9%</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Annual volatility</th>\n",
" <td>14.3%</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Sharpe ratio</th>\n",
" <td>0.96</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Calmar ratio</th>\n",
" <td>1.14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Stability</th>\n",
" <td>0.83</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Max drawdown</th>\n",
" <td>-11.9%</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Omega ratio</th>\n",
" <td>1.18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Sortino ratio</th>\n",
" <td>1.37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Skew</th>\n",
" <td>-0.52</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Kurtosis</th>\n",
" <td>3.88</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Tail ratio</th>\n",
" <td>0.97</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Daily value at risk</th>\n",
" <td>-1.7%</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>"
],
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"output_type": "error",
"traceback": [
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"\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-6-ea8302e3d94e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mpf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcreate_returns_tear_sheet\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreturns\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbalance\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'% change'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdropna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m~/.local/share/virtualenvs/backtester_options-33KCFJeg/lib/python3.7/site-packages/pyfolio/plotting.py\u001b[0m in \u001b[0;36mcall_w_context\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 50\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mset_context\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 51\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mplotting_context\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxes_style\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 52\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 53\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 54\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/.local/share/virtualenvs/backtester_options-33KCFJeg/lib/python3.7/site-packages/pyfolio/tears.py\u001b[0m in \u001b[0;36mcreate_returns_tear_sheet\u001b[0;34m(returns, positions, transactions, live_start_date, cone_std, benchmark_rets, bootstrap, turnover_denom, header_rows, return_fig)\u001b[0m\n\u001b[1;32m 502\u001b[0m header_rows=header_rows)\n\u001b[1;32m 503\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 504\u001b[0;31m \u001b[0mplotting\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow_worst_drawdown_periods\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreturns\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 505\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 506\u001b[0m \u001b[0mvertical_sections\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m11\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/.local/share/virtualenvs/backtester_options-33KCFJeg/lib/python3.7/site-packages/pyfolio/plotting.py\u001b[0m in \u001b[0;36mshow_worst_drawdown_periods\u001b[0;34m(returns, top)\u001b[0m\n\u001b[1;32m 1662\u001b[0m \"\"\"\n\u001b[1;32m 1663\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1664\u001b[0;31m \u001b[0mdrawdown_df\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtimeseries\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgen_drawdown_table\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreturns\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtop\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1665\u001b[0m utils.print_table(\n\u001b[1;32m 1666\u001b[0m \u001b[0mdrawdown_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Net drawdown in %'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mascending\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/.local/share/virtualenvs/backtester_options-33KCFJeg/lib/python3.7/site-packages/pyfolio/timeseries.py\u001b[0m in \u001b[0;36mgen_drawdown_table\u001b[0;34m(returns, top)\u001b[0m\n\u001b[1;32m 1006\u001b[0m df_drawdowns.loc[i, 'Peak date'] = (peak.to_pydatetime()\n\u001b[1;32m 1007\u001b[0m .strftime('%Y-%m-%d'))\n\u001b[0;32m-> 1008\u001b[0;31m df_drawdowns.loc[i, 'Valley date'] = (valley.to_pydatetime()\n\u001b[0m\u001b[1;32m 1009\u001b[0m .strftime('%Y-%m-%d'))\n\u001b[1;32m 1010\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrecovery\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mAttributeError\u001b[0m: 'numpy.int64' object has no attribute 'to_pydatetime'"
]
}
],
"source": [
"pf.create_returns_tear_sheet(returns=bt.balance['% change'].dropna())"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.7.5"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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