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@yhilpisch
Last active November 9, 2021 13:50
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<img src='http://hilpisch.com/tpq_logo.png' width=\"300px\" align=\"right\">"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# FPQ Bootcamp &mdash; Day 3"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Backtesting of Strategies**"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Financial Data"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"from pylab import plt\n",
"plt.style.use('seaborn')\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"raw = pd.read_csv('http://hilpisch.com/tr_eikon_eod_data.csv',\n",
" index_col=0, parse_dates=True)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"DatetimeIndex: 1972 entries, 2010-01-04 to 2017-10-31\n",
"Data columns (total 12 columns):\n",
"AAPL.O 1972 non-null float64\n",
"MSFT.O 1972 non-null float64\n",
"INTC.O 1972 non-null float64\n",
"AMZN.O 1972 non-null float64\n",
"GS.N 1972 non-null float64\n",
"SPY 1972 non-null float64\n",
".SPX 1972 non-null float64\n",
".VIX 1972 non-null float64\n",
"EUR= 1972 non-null float64\n",
"XAU= 1972 non-null float64\n",
"GDX 1972 non-null float64\n",
"GLD 1972 non-null float64\n",
"dtypes: float64(12)\n",
"memory usage: 200.3 KB\n"
]
}
],
"source": [
"raw.info()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## SMA-based Trading Strategy"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"sym = 'AAPL.O'"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"data = pd.DataFrame(raw[sym])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" 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>AAPL.O</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date</th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2010-01-04</th>\n",
" <td>30.572827</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-05</th>\n",
" <td>30.625684</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-06</th>\n",
" <td>30.138541</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-07</th>\n",
" <td>30.082827</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-08</th>\n",
" <td>30.282827</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" AAPL.O\n",
"Date \n",
"2010-01-04 30.572827\n",
"2010-01-05 30.625684\n",
"2010-01-06 30.138541\n",
"2010-01-07 30.082827\n",
"2010-01-08 30.282827"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"data['SMA1'] = data[sym].rolling(42).mean()\n",
"data['SMA2'] = data[sym].rolling(252).mean()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
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ICdIDEBzY/JJAua2SfeUHSAiKI9wQNiD3tWdnUf7F56j0euJu+hWqDnKaHU+O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gAa9+2hfusWcidPImv21ST36dPhzxAREZGTU0F1iurqWwC46/oJPPiHlW3T7336H1Q1VpPQdycJ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\nEKmgEhEREQmRCioRERGREP1/XyLl2BFH+jAAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10e1c89b0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data.plot(figsize=(10, 6));"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" 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>AAPL.O</th>\n",
" <th>SMA1</th>\n",
" <th>SMA2</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2010-01-04</th>\n",
" <td>30.572827</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-05</th>\n",
" <td>30.625684</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-06</th>\n",
" <td>30.138541</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-07</th>\n",
" <td>30.082827</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-08</th>\n",
" <td>30.282827</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" AAPL.O SMA1 SMA2\n",
"Date \n",
"2010-01-04 30.572827 NaN NaN\n",
"2010-01-05 30.625684 NaN NaN\n",
"2010-01-06 30.138541 NaN NaN\n",
"2010-01-07 30.082827 NaN NaN\n",
"2010-01-08 30.282827 NaN NaN"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"data.dropna(inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" 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>AAPL.O</th>\n",
" <th>SMA1</th>\n",
" <th>SMA2</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2010-12-31</th>\n",
" <td>46.079954</td>\n",
" <td>45.280967</td>\n",
" <td>37.120735</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-03</th>\n",
" <td>47.081381</td>\n",
" <td>45.349708</td>\n",
" <td>37.186246</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-04</th>\n",
" <td>47.327096</td>\n",
" <td>45.412599</td>\n",
" <td>37.252521</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-05</th>\n",
" <td>47.714238</td>\n",
" <td>45.466102</td>\n",
" <td>37.322266</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-06</th>\n",
" <td>47.675667</td>\n",
" <td>45.522565</td>\n",
" <td>37.392079</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" AAPL.O SMA1 SMA2\n",
"Date \n",
"2010-12-31 46.079954 45.280967 37.120735\n",
"2011-01-03 47.081381 45.349708 37.186246\n",
"2011-01-04 47.327096 45.412599 37.252521\n",
"2011-01-05 47.714238 45.466102 37.322266\n",
"2011-01-06 47.675667 45.522565 37.392079"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"# long only trading strategy\n",
"# data['Position'] = np.where(data['SMA1'] > data['SMA2'], 1, 0)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"# long-short trading strategy\n",
"data['Position'] = np.where(data['SMA1'] > data['SMA2'], 1, -1)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
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Sxph3hVDNeeNTSdLQmLdUVwYuaUDqcCKpw3tUORpzXVzuRB1ZomoycEmSSlfD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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11733f550>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data['Position'].plot(figsize=(10, 6));"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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yAMbEeSYEvmxCLxpavSMH8FwmTHiXBHRCCCGEcCsqs3D7K7+5n9emt/rg290A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+fIEQJeD1anE3tiIvbEZBzJyZLkV4h2yFca0dkkoBNtqq33sq+gkpT4yMYxdF6/lwNVh8h2ZTE8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\nJ4SxhKLL9fV/VH399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"text/plain": [
"<matplotlib.figure.Figure at 0x117400ac8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data.plot(figsize=(10, 6), secondary_y='Position');"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"data['Returns'] = np.log(data[sym] / data[sym].shift(1))"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" 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>AAPL.O</th>\n",
" <th>SMA1</th>\n",
" <th>SMA2</th>\n",
" <th>Position</th>\n",
" <th>Returns</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",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2010-12-31</th>\n",
" <td>46.079954</td>\n",
" <td>45.280967</td>\n",
" <td>37.120735</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-03</th>\n",
" <td>47.081381</td>\n",
" <td>45.349708</td>\n",
" <td>37.186246</td>\n",
" <td>1</td>\n",
" <td>0.021500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-04</th>\n",
" <td>47.327096</td>\n",
" <td>45.412599</td>\n",
" <td>37.252521</td>\n",
" <td>1</td>\n",
" <td>0.005205</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-05</th>\n",
" <td>47.714238</td>\n",
" <td>45.466102</td>\n",
" <td>37.322266</td>\n",
" <td>1</td>\n",
" <td>0.008147</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-06</th>\n",
" <td>47.675667</td>\n",
" <td>45.522565</td>\n",
" <td>37.392079</td>\n",
" <td>1</td>\n",
" <td>-0.000809</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" AAPL.O SMA1 SMA2 Position Returns\n",
"Date \n",
"2010-12-31 46.079954 45.280967 37.120735 1 NaN\n",
"2011-01-03 47.081381 45.349708 37.186246 1 0.021500\n",
"2011-01-04 47.327096 45.412599 37.252521 1 0.005205\n",
"2011-01-05 47.714238 45.466102 37.322266 1 0.008147\n",
"2011-01-06 47.675667 45.522565 37.392079 1 -0.000809"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"data['Strategy'] = data['Position'].shift(1) * data['Returns']"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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SRpPskz0a6j3a6psDg8qJY1IDetb969uDfs8NRv+AVS2ZJCGEGJmafYKk5Vuf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\nEYAESUIIIYQQAfw/kji30UNkccUAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11742ca90>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data[['Returns', 'Strategy']].dropna().cumsum(\n",
" ).apply(np.exp).plot(figsize=(10, 6));"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Random Walk Hypothesis"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"lags = 5"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"cols = []\n",
"for lag in range(1, lags+1):\n",
" col = 'lag_%d' % lag\n",
" data[col] = data[sym].shift(lag)\n",
" cols.append(col)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>AAPL.O</th>\n",
" <th>SMA1</th>\n",
" <th>SMA2</th>\n",
" <th>Position</th>\n",
" <th>Returns</th>\n",
" <th>Strategy</th>\n",
" <th>lag_1</th>\n",
" <th>lag_2</th>\n",
" <th>lag_3</th>\n",
" <th>lag_4</th>\n",
" <th>lag_5</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",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2010-12-31</th>\n",
" <td>46.079954</td>\n",
" <td>45.280967</td>\n",
" <td>37.120735</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-03</th>\n",
" <td>47.081381</td>\n",
" <td>45.349708</td>\n",
" <td>37.186246</td>\n",
" <td>1</td>\n",
" <td>0.021500</td>\n",
" <td>0.021500</td>\n",
" <td>46.079954</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-04</th>\n",
" <td>47.327096</td>\n",
" <td>45.412599</td>\n",
" <td>37.252521</td>\n",
" <td>1</td>\n",
" <td>0.005205</td>\n",
" <td>0.005205</td>\n",
" <td>47.081381</td>\n",
" <td>46.079954</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-05</th>\n",
" <td>47.714238</td>\n",
" <td>45.466102</td>\n",
" <td>37.322266</td>\n",
" <td>1</td>\n",
" <td>0.008147</td>\n",
" <td>0.008147</td>\n",
" <td>47.327096</td>\n",
" <td>47.081381</td>\n",
" <td>46.079954</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-06</th>\n",
" <td>47.675667</td>\n",
" <td>45.522565</td>\n",
" <td>37.392079</td>\n",
" <td>1</td>\n",
" <td>-0.000809</td>\n",
" <td>-0.000809</td>\n",
" <td>47.714238</td>\n",
" <td>47.327096</td>\n",
" <td>47.081381</td>\n",
" <td>46.079954</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-07</th>\n",
" <td>48.017095</td>\n",
" <td>45.582089</td>\n",
" <td>37.462453</td>\n",
" <td>1</td>\n",
" <td>0.007136</td>\n",
" <td>0.007136</td>\n",
" <td>47.675667</td>\n",
" <td>47.714238</td>\n",
" <td>47.327096</td>\n",
" <td>47.081381</td>\n",
" <td>46.079954</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-10</th>\n",
" <td>48.922094</td>\n",
" <td>45.671800</td>\n",
" <td>37.537478</td>\n",
" <td>1</td>\n",
" <td>0.018672</td>\n",
" <td>0.018672</td>\n",
" <td>48.017095</td>\n",
" <td>47.675667</td>\n",
" <td>47.714238</td>\n",
" <td>47.327096</td>\n",
" <td>47.081381</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-11</th>\n",
" <td>48.805665</td>\n",
" <td>45.752106</td>\n",
" <td>37.613397</td>\n",
" <td>1</td>\n",
" <td>-0.002383</td>\n",
" <td>-0.002383</td>\n",
" <td>48.922094</td>\n",
" <td>48.017095</td>\n",
" <td>47.675667</td>\n",
" <td>47.714238</td>\n",
" <td>47.327096</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-12</th>\n",
" <td>49.202808</td>\n",
" <td>45.846544</td>\n",
" <td>37.689230</td>\n",
" <td>1</td>\n",
" <td>0.008104</td>\n",
" <td>0.008104</td>\n",
" <td>48.805665</td>\n",
" <td>48.922094</td>\n",
" <td>48.017095</td>\n",
" <td>47.675667</td>\n",
" <td>47.714238</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" AAPL.O SMA1 SMA2 Position Returns Strategy \\\n",
"Date \n",
"2010-12-31 46.079954 45.280967 37.120735 1 NaN NaN \n",
"2011-01-03 47.081381 45.349708 37.186246 1 0.021500 0.021500 \n",
"2011-01-04 47.327096 45.412599 37.252521 1 0.005205 0.005205 \n",
"2011-01-05 47.714238 45.466102 37.322266 1 0.008147 0.008147 \n",
"2011-01-06 47.675667 45.522565 37.392079 1 -0.000809 -0.000809 \n",
"2011-01-07 48.017095 45.582089 37.462453 1 0.007136 0.007136 \n",
"2011-01-10 48.922094 45.671800 37.537478 1 0.018672 0.018672 \n",
"2011-01-11 48.805665 45.752106 37.613397 1 -0.002383 -0.002383 \n",
"2011-01-12 49.202808 45.846544 37.689230 1 0.008104 0.008104 \n",
"\n",
" lag_1 lag_2 lag_3 lag_4 lag_5 \n",
"Date \n",
"2010-12-31 NaN NaN NaN NaN NaN \n",
"2011-01-03 46.079954 NaN NaN NaN NaN \n",
"2011-01-04 47.081381 46.079954 NaN NaN NaN \n",
"2011-01-05 47.327096 47.081381 46.079954 NaN NaN \n",
"2011-01-06 47.714238 47.327096 47.081381 46.079954 NaN \n",
"2011-01-07 47.675667 47.714238 47.327096 47.081381 46.079954 \n",
"2011-01-10 48.017095 47.675667 47.714238 47.327096 47.081381 \n",
"2011-01-11 48.922094 48.017095 47.675667 47.714238 47.327096 \n",
"2011-01-12 48.805665 48.922094 48.017095 47.675667 47.714238 "
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head(9)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"data.dropna(inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['lag_1', 'lag_2', 'lag_3', 'lag_4', 'lag_5']"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cols"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
"reg = np.linalg.lstsq(data[cols], data[sym])[0]"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"pred = np.dot(data[cols], reg)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 47.70719727, 48.05020152, 48.97640036, 48.8014763 ,\n",
" 49.22375215, 49.43113911, 49.80624008, 48.66291941,\n",
" 48.45097492, 47.59071501])"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pred[:10]"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
"data['Prediction'] = pred"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
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odlc20uTZE9t3dRFQFbkTJ6tPU09iStGkLvtwpElAJYQQQoi0NQajSW1z7E8BxBY07mzI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\nAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1173c5c18>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data[[sym, 'Prediction']].plot(figsize=(10, 6));"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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NQATw1UHOe0lV1f3ez8DUZnFPAwXFjXR2uVkxJxH9GdV1d1f733DimTKTI/n2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\nf1zqOhvQ0PpVmNfpdGxYmoL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3XZJDZ5ebx7cexePp/mFp6eji988fxF6mEKIPY3fjh73d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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10947d710>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data[[sym, 'Prediction']].iloc[-50:].plot(figsize=(10, 6));"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 1.02371 , -0.04833252, -0.00929219, 0.05219537, -0.01758613])"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"reg"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Predicting Market Returns"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
"data = pd.DataFrame(raw[sym])"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"data['Returns'] = np.log(data[sym] / data[sym].shift(1))"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
"lags = 10"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [],
"source": [
"cols = []\n",
"for lag in range(1, lags+1):\n",
" col = 'lag_%d' % lag\n",
" data[col] = data['Returns'].shift(lag)\n",
" cols.append(col)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" 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>AAPL.O</th>\n",
" <th>Returns</th>\n",
" <th>lag_1</th>\n",
" <th>lag_2</th>\n",
" <th>lag_3</th>\n",
" <th>lag_4</th>\n",
" <th>lag_5</th>\n",
" <th>lag_6</th>\n",
" <th>lag_7</th>\n",
" <th>lag_8</th>\n",
" <th>lag_9</th>\n",
" <th>lag_10</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",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2010-01-04</th>\n",
" <td>30.572827</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-05</th>\n",
" <td>30.625684</td>\n",
" <td>0.001727</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-06</th>\n",
" <td>30.138541</td>\n",
" <td>-0.016034</td>\n",
" <td>0.001727</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-07</th>\n",
" <td>30.082827</td>\n",
" <td>-0.001850</td>\n",
" <td>-0.016034</td>\n",
" <td>0.001727</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-08</th>\n",
" <td>30.282827</td>\n",
" <td>0.006626</td>\n",
" <td>-0.001850</td>\n",
" <td>-0.016034</td>\n",
" <td>0.001727</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-11</th>\n",
" <td>30.015684</td>\n",
" <td>-0.008861</td>\n",
" <td>0.006626</td>\n",
" <td>-0.001850</td>\n",
" <td>-0.016034</td>\n",
" <td>0.001727</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-12</th>\n",
" <td>29.674256</td>\n",
" <td>-0.011440</td>\n",
" <td>-0.008861</td>\n",
" <td>0.006626</td>\n",
" <td>-0.001850</td>\n",
" <td>-0.016034</td>\n",
" <td>0.001727</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" AAPL.O Returns lag_1 lag_2 lag_3 lag_4 \\\n",
"Date \n",
"2010-01-04 30.572827 NaN NaN NaN NaN NaN \n",
"2010-01-05 30.625684 0.001727 NaN NaN NaN NaN \n",
"2010-01-06 30.138541 -0.016034 0.001727 NaN NaN NaN \n",
"2010-01-07 30.082827 -0.001850 -0.016034 0.001727 NaN NaN \n",
"2010-01-08 30.282827 0.006626 -0.001850 -0.016034 0.001727 NaN \n",
"2010-01-11 30.015684 -0.008861 0.006626 -0.001850 -0.016034 0.001727 \n",
"2010-01-12 29.674256 -0.011440 -0.008861 0.006626 -0.001850 -0.016034 \n",
"\n",
" lag_5 lag_6 lag_7 lag_8 lag_9 lag_10 \n",
"Date \n",
"2010-01-04 NaN NaN NaN NaN NaN NaN \n",
"2010-01-05 NaN NaN NaN NaN NaN NaN \n",
"2010-01-06 NaN NaN NaN NaN NaN NaN \n",
"2010-01-07 NaN NaN NaN NaN NaN NaN \n",
"2010-01-08 NaN NaN NaN NaN NaN NaN \n",
"2010-01-11 NaN NaN NaN NaN NaN NaN \n",
"2010-01-12 0.001727 NaN NaN NaN NaN NaN "
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head(7)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [],
"source": [
"data.dropna(inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [],
"source": [
"reg = np.linalg.lstsq(data[cols], data['Returns'])[0]"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 0.03111127, 0.00334222, -0.04501275, 0.02606918, -0.02330581,\n",
" 0.00587711, 0.00423416, -0.0492475 , 0.01206904, 0.02382406])"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"reg"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [],
"source": [
"data['Prediction'] = np.dot(data[cols], reg)"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" 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>AAPL.O</th>\n",
" <th>Returns</th>\n",
" <th>lag_1</th>\n",
" <th>lag_2</th>\n",
" <th>lag_3</th>\n",
" <th>lag_4</th>\n",
" <th>lag_5</th>\n",
" <th>lag_6</th>\n",
" <th>lag_7</th>\n",
" <th>lag_8</th>\n",
" <th>lag_9</th>\n",
" <th>lag_10</th>\n",
" <th>Prediction</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",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2010-01-20</th>\n",
" <td>30.246398</td>\n",
" <td>-0.015536</td>\n",
" <td>0.043288</td>\n",
" <td>-0.016853</td>\n",
" <td>-0.005808</td>\n",
" <td>0.014007</td>\n",
" <td>-0.011440</td>\n",
" <td>-0.008861</td>\n",
" <td>0.006626</td>\n",
" <td>-0.001850</td>\n",
" <td>-0.016034</td>\n",
" <td>0.001727</td>\n",
" <td>0.002098</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-21</th>\n",
" <td>29.724542</td>\n",
" <td>-0.017404</td>\n",
" <td>-0.015536</td>\n",
" <td>0.043288</td>\n",
" <td>-0.016853</td>\n",
" <td>-0.005808</td>\n",
" <td>0.014007</td>\n",
" <td>-0.011440</td>\n",
" <td>-0.008861</td>\n",
" <td>0.006626</td>\n",
" <td>-0.001850</td>\n",
" <td>-0.016034</td>\n",
" <td>-0.000893</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-22</th>\n",
" <td>28.249972</td>\n",
" <td>-0.050881</td>\n",
" <td>-0.017404</td>\n",
" <td>-0.015536</td>\n",
" <td>0.043288</td>\n",
" <td>-0.016853</td>\n",
" <td>-0.005808</td>\n",
" <td>0.014007</td>\n",
" <td>-0.011440</td>\n",
" <td>-0.008861</td>\n",
" <td>0.006626</td>\n",
" <td>-0.001850</td>\n",
" <td>-0.002340</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-25</th>\n",
" <td>29.010685</td>\n",
" <td>0.026572</td>\n",
" <td>-0.050881</td>\n",
" <td>-0.017404</td>\n",
" <td>-0.015536</td>\n",
" <td>0.043288</td>\n",
" <td>-0.016853</td>\n",
" <td>-0.005808</td>\n",
" <td>0.014007</td>\n",
" <td>-0.011440</td>\n",
" <td>-0.008861</td>\n",
" <td>0.006626</td>\n",
" <td>0.001219</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-26</th>\n",
" <td>29.419971</td>\n",
" <td>0.014009</td>\n",
" <td>0.026572</td>\n",
" <td>-0.050881</td>\n",
" <td>-0.017404</td>\n",
" <td>-0.015536</td>\n",
" <td>0.043288</td>\n",
" <td>-0.016853</td>\n",
" <td>-0.005808</td>\n",
" <td>0.014007</td>\n",
" <td>-0.011440</td>\n",
" <td>-0.008861</td>\n",
" <td>-0.001136</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" AAPL.O Returns lag_1 lag_2 lag_3 lag_4 \\\n",
"Date \n",
"2010-01-20 30.246398 -0.015536 0.043288 -0.016853 -0.005808 0.014007 \n",
"2010-01-21 29.724542 -0.017404 -0.015536 0.043288 -0.016853 -0.005808 \n",
"2010-01-22 28.249972 -0.050881 -0.017404 -0.015536 0.043288 -0.016853 \n",
"2010-01-25 29.010685 0.026572 -0.050881 -0.017404 -0.015536 0.043288 \n",
"2010-01-26 29.419971 0.014009 0.026572 -0.050881 -0.017404 -0.015536 \n",
"\n",
" lag_5 lag_6 lag_7 lag_8 lag_9 lag_10 \\\n",
"Date \n",
"2010-01-20 -0.011440 -0.008861 0.006626 -0.001850 -0.016034 0.001727 \n",
"2010-01-21 0.014007 -0.011440 -0.008861 0.006626 -0.001850 -0.016034 \n",
"2010-01-22 -0.005808 0.014007 -0.011440 -0.008861 0.006626 -0.001850 \n",
"2010-01-25 -0.016853 -0.005808 0.014007 -0.011440 -0.008861 0.006626 \n",
"2010-01-26 0.043288 -0.016853 -0.005808 0.014007 -0.011440 -0.008861 \n",
"\n",
" Prediction \n",
"Date \n",
"2010-01-20 0.002098 \n",
"2010-01-21 -0.000893 \n",
"2010-01-22 -0.002340 \n",
"2010-01-25 0.001219 \n",
"2010-01-26 -0.001136 "
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Returns 0.000870\n",
"Prediction -0.000008\n",
"dtype: float64"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data[['Returns', 'Prediction']].mean()"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
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XVDdFIxtVS4oJjvcE6oHc2jfXBOAkq3ClOy2EhXeSxrlMWHrSsVRoFZcjO/Jw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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1173b9358>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data[['Returns', 'Prediction']].plot(figsize=(10, 6));"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Date\n",
"2010-01-20 -1.0\n",
"2010-01-21 1.0\n",
"2010-01-22 1.0\n",
"2010-01-25 1.0\n",
"2010-01-26 -1.0\n",
"2010-01-27 1.0\n",
"2010-01-28 1.0\n",
"2010-01-29 1.0\n",
"2010-02-01 -1.0\n",
"dtype: float64"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.sign(data['Returns'] * data['Prediction']).head(9)"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
" 1.0 1018\n",
"-1.0 941\n",
" 0.0 2\n",
"dtype: int64"
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.sign(data['Returns'] * data['Prediction']).value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [],
"source": [
"data['Position'] = np.sign(data['Prediction'])"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [],
"source": [
"data['Strategy'] = data['Position'] * data['Returns']"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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Ds6OF+zY8qrYGnj7y5FCFJnpAEichhAgjuyv38+CPT/Je2/R9p+JEp9Vzgfks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\n/wcrIZ25rwpkRgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1175c9cf8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data[['Returns', 'Strategy']].dropna().cumsum(\n",
" ).apply(np.exp).plot(figsize=(10, 6));"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Predicting Market Direction by OLS Regression"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [],
"source": [
"data = pd.DataFrame(raw[sym])"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [],
"source": [
"data['Returns'] = np.log(data[sym] / data[sym].shift(1))"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [],
"source": [
"lags = 10"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [],
"source": [
"cols = []\n",
"for lag in range(1, lags+1):\n",
" col = 'lag_%d' % lag\n",
" data[col] = data['Returns'].shift(lag)\n",
" cols.append(col)"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" 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>AAPL.O</th>\n",
" <th>Returns</th>\n",
" <th>lag_1</th>\n",
" <th>lag_2</th>\n",
" <th>lag_3</th>\n",
" <th>lag_4</th>\n",
" <th>lag_5</th>\n",
" <th>lag_6</th>\n",
" <th>lag_7</th>\n",
" <th>lag_8</th>\n",
" <th>lag_9</th>\n",
" <th>lag_10</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",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2010-01-04</th>\n",
" <td>30.572827</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-05</th>\n",
" <td>30.625684</td>\n",
" <td>0.001727</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-06</th>\n",
" <td>30.138541</td>\n",
" <td>-0.016034</td>\n",
" <td>0.001727</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-07</th>\n",
" <td>30.082827</td>\n",
" <td>-0.001850</td>\n",
" <td>-0.016034</td>\n",
" <td>0.001727</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-08</th>\n",
" <td>30.282827</td>\n",
" <td>0.006626</td>\n",
" <td>-0.001850</td>\n",
" <td>-0.016034</td>\n",
" <td>0.001727</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-11</th>\n",
" <td>30.015684</td>\n",
" <td>-0.008861</td>\n",
" <td>0.006626</td>\n",
" <td>-0.001850</td>\n",
" <td>-0.016034</td>\n",
" <td>0.001727</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-12</th>\n",
" <td>29.674256</td>\n",
" <td>-0.011440</td>\n",
" <td>-0.008861</td>\n",
" <td>0.006626</td>\n",
" <td>-0.001850</td>\n",
" <td>-0.016034</td>\n",
" <td>0.001727</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" AAPL.O Returns lag_1 lag_2 lag_3 lag_4 \\\n",
"Date \n",
"2010-01-04 30.572827 NaN NaN NaN NaN NaN \n",
"2010-01-05 30.625684 0.001727 NaN NaN NaN NaN \n",
"2010-01-06 30.138541 -0.016034 0.001727 NaN NaN NaN \n",
"2010-01-07 30.082827 -0.001850 -0.016034 0.001727 NaN NaN \n",
"2010-01-08 30.282827 0.006626 -0.001850 -0.016034 0.001727 NaN \n",
"2010-01-11 30.015684 -0.008861 0.006626 -0.001850 -0.016034 0.001727 \n",
"2010-01-12 29.674256 -0.011440 -0.008861 0.006626 -0.001850 -0.016034 \n",
"\n",
" lag_5 lag_6 lag_7 lag_8 lag_9 lag_10 \n",
"Date \n",
"2010-01-04 NaN NaN NaN NaN NaN NaN \n",
"2010-01-05 NaN NaN NaN NaN NaN NaN \n",
"2010-01-06 NaN NaN NaN NaN NaN NaN \n",
"2010-01-07 NaN NaN NaN NaN NaN NaN \n",
"2010-01-08 NaN NaN NaN NaN NaN NaN \n",
"2010-01-11 NaN NaN NaN NaN NaN NaN \n",
"2010-01-12 0.001727 NaN NaN NaN NaN NaN "
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head(7)"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [],
"source": [
"data.dropna(inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [],
"source": [
"reg = np.linalg.lstsq(np.sign(data[cols]), np.sign(data['Returns']))[0]"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 0.00670948, 0.01403302, -0.01830729, 0.03852732, 0.01533263,\n",
" 0.0140773 , 0.02070633, -0.02076601, 0.01890585, 0.01623588])"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"reg"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [],
"source": [
"data['Prediction'] = np.dot(data[cols], reg)"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" 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>AAPL.O</th>\n",
" <th>Returns</th>\n",
" <th>lag_1</th>\n",
" <th>lag_2</th>\n",
" <th>lag_3</th>\n",
" <th>lag_4</th>\n",
" <th>lag_5</th>\n",
" <th>lag_6</th>\n",
" <th>lag_7</th>\n",
" <th>lag_8</th>\n",
" <th>lag_9</th>\n",
" <th>lag_10</th>\n",
" <th>Prediction</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",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2010-01-20</th>\n",
" <td>30.246398</td>\n",
" <td>-0.015536</td>\n",
" <td>0.043288</td>\n",
" <td>-0.016853</td>\n",
" <td>-0.005808</td>\n",
" <td>0.014007</td>\n",
" <td>-0.011440</td>\n",
" <td>-0.008861</td>\n",
" <td>0.006626</td>\n",
" <td>-0.001850</td>\n",
" <td>-0.016034</td>\n",
" <td>0.001727</td>\n",
" <td>0.000300</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-21</th>\n",
" <td>29.724542</td>\n",
" <td>-0.017404</td>\n",
" <td>-0.015536</td>\n",
" <td>0.043288</td>\n",
" <td>-0.016853</td>\n",
" <td>-0.005808</td>\n",
" <td>0.014007</td>\n",
" <td>-0.011440</td>\n",
" <td>-0.008861</td>\n",
" <td>0.006626</td>\n",
" <td>-0.001850</td>\n",
" <td>-0.016034</td>\n",
" <td>0.000025</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-22</th>\n",
" <td>28.249972</td>\n",
" <td>-0.050881</td>\n",
" <td>-0.017404</td>\n",
" <td>-0.015536</td>\n",
" <td>0.043288</td>\n",
" <td>-0.016853</td>\n",
" <td>-0.005808</td>\n",
" <td>0.014007</td>\n",
" <td>-0.011440</td>\n",
" <td>-0.008861</td>\n",
" <td>0.006626</td>\n",
" <td>-0.001850</td>\n",
" <td>-0.001626</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-25</th>\n",
" <td>29.010685</td>\n",
" <td>0.026572</td>\n",
" <td>-0.050881</td>\n",
" <td>-0.017404</td>\n",
" <td>-0.015536</td>\n",
" <td>0.043288</td>\n",
" <td>-0.016853</td>\n",
" <td>-0.005808</td>\n",
" <td>0.014007</td>\n",
" <td>-0.011440</td>\n",
" <td>-0.008861</td>\n",
" <td>0.006626</td>\n",
" <td>0.001494</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-26</th>\n",
" <td>29.419971</td>\n",
" <td>0.014009</td>\n",
" <td>0.026572</td>\n",
" <td>-0.050881</td>\n",
" <td>-0.017404</td>\n",
" <td>-0.015536</td>\n",
" <td>0.043288</td>\n",
" <td>-0.016853</td>\n",
" <td>-0.005808</td>\n",
" <td>0.014007</td>\n",
" <td>-0.011440</td>\n",
" <td>-0.008861</td>\n",
" <td>-0.001160</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" AAPL.O Returns lag_1 lag_2 lag_3 lag_4 \\\n",
"Date \n",
"2010-01-20 30.246398 -0.015536 0.043288 -0.016853 -0.005808 0.014007 \n",
"2010-01-21 29.724542 -0.017404 -0.015536 0.043288 -0.016853 -0.005808 \n",
"2010-01-22 28.249972 -0.050881 -0.017404 -0.015536 0.043288 -0.016853 \n",
"2010-01-25 29.010685 0.026572 -0.050881 -0.017404 -0.015536 0.043288 \n",
"2010-01-26 29.419971 0.014009 0.026572 -0.050881 -0.017404 -0.015536 \n",
"\n",
" lag_5 lag_6 lag_7 lag_8 lag_9 lag_10 \\\n",
"Date \n",
"2010-01-20 -0.011440 -0.008861 0.006626 -0.001850 -0.016034 0.001727 \n",
"2010-01-21 0.014007 -0.011440 -0.008861 0.006626 -0.001850 -0.016034 \n",
"2010-01-22 -0.005808 0.014007 -0.011440 -0.008861 0.006626 -0.001850 \n",
"2010-01-25 -0.016853 -0.005808 0.014007 -0.011440 -0.008861 0.006626 \n",
"2010-01-26 0.043288 -0.016853 -0.005808 0.014007 -0.011440 -0.008861 \n",
"\n",
" Prediction \n",
"Date \n",
"2010-01-20 0.000300 \n",
"2010-01-21 0.000025 \n",
"2010-01-22 -0.001626 \n",
"2010-01-25 0.001494 \n",
"2010-01-26 -0.001160 "
]
},
"execution_count": 58,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Returns 0.00087\n",
"Prediction 0.00009\n",
"dtype: float64"
]
},
"execution_count": 59,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data[['Returns', 'Prediction']].mean()"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [
{
"data": {
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Y0Xt2dw/LykI4HHP8/tkgG+WQKbyQ6FDtyJbue+iVgd17KRUrABgeCov1Ic13cRJpdh4a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\n4CIiIiIKGQMuIiIiopD9f+PT3zUBLUfUAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11791c780>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data[['Returns', 'Prediction']].plot(figsize=(10, 6));"
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Date\n",
"2010-01-20 -1.0\n",
"2010-01-21 -1.0\n",
"2010-01-22 1.0\n",
"2010-01-25 1.0\n",
"2010-01-26 -1.0\n",
"2010-01-27 1.0\n",
"2010-01-28 1.0\n",
"2010-01-29 1.0\n",
"2010-02-01 -1.0\n",
"dtype: float64"
]
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.sign(data['Returns'] * data['Prediction']).head(9)"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
" 1.0 1042\n",
"-1.0 917\n",
" 0.0 2\n",
"dtype: int64"
]
},
"execution_count": 62,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.sign(data['Returns'] * data['Prediction']).value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [],
"source": [
"data['Position'] = np.sign(data['Prediction'])"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [],
"source": [
"data['Strategy'] = data['Position'] * data['Returns']"
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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4ixGXW8Hh9PDR2v1Bzzh2avQLanYbJFmtVguAzWZbGPHWCCGEEFG0t9G3Iuuy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\nUQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1174555c0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data[['Returns', 'Strategy']].dropna().cumsum(\n",
" ).apply(np.exp).plot(figsize=(10, 6));"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Returns 0.25467\n",
"Strategy 0.25447\n",
"dtype: float64"
]
},
"execution_count": 66,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data[['Returns', 'Strategy']].std() * 252 ** 0.5"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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LwE8Q6SDR5UfMhSuxHDLvq828GvUkSOCyFNIKJEurrw3NjlJs9y1Ld1Us4Z+vrcKdL69M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\nAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x117a4b278>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data[['Returns', 'Strategy']].plot(figsize=(10, 6));"
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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KAKCTQAUA0EmgAgDoJFABAHQSqAAAOglUAACdZiZdALC13H7/k6suO3Dy+TFWAjA99FAB\nAHQSqAAAOglUAACd3EMFbMieo0eSuE8KYCV6qAAAOglUAACdBCoAgE4CFQBAJ4EKAKCTQAUA0Emg\nAgDoJFABAHQysCdwnhcfAwxHDxUAQCeBCgCg09CX/KrquSSnBx//e5J/luShJOeSHGut/aP+8gAA\npt9Qgaqq3p4krbUbl837z0l+PMl/S/Jvqmp/a+33RlEkAMA0G7aH6l1JLq+qY4N93Jfk0tbaySSp\nqqNJ3ptEoAIAtr1hA9VrSX4lySNJ/lySI0leXrb8TJIfWm8n+/ZdnpmZS4YsgbXMzc1OuoQdb0sd\ngyeeSJIcOHliwoXsPGs9WbnkiQduHUMlo7Wlzv9tSPuP37CB6ltJvtNaW0jyrao6neQHli2fzf8f\nsFZ06tRrQ349a5mbm838/JlJl7GjbbVjsOf065MuYUfZaHB95uprk2RLnUvJ1jv/txvtv3nWCqrD\nPuV3e5IHkqSq/nSSy5O8WlVXV9WuJAeTHB9y3wAAW8qwPVSPJvlCVf1OkoUsBqy3kvyrJJdk8Sm/\nr4+mRACA6TZUoGqtnU3ykyssendfOQAAW4+BPQEAOglUAACdBCoAgE4CFQBAJ4EKAKCTQAUA0Emg\nAgDoJFABAHQSqAAAOglUAACdhn2XH7DF3H7/k6suO3Dy+TFWArD9CFQAU+rAyRNJkj1H31h1nbMH\nbx5XOcAaXPIDAOgkUAEAdBKoAAA6CVQAAJ3clA7b2J6jR85Pe5Jv63ro8OrH7pnnLk2SHLr7pnGV\nA6xADxUAQCeBCgCgk0AFANBJoAIA6CRQAQB0EqgAADoJVAAAnQQqAIBOAhUAQCcjpQNsc8tHzF/N\n2YM3j6ES2L4EKoAt7MDJE0mSPUffmHAlsLMJVLBFbaTXAYDxEKhgG1jr5bnsDBs9B+78wLs2uRLY\nmQQqmGK33//kqssOnBSiAKaFp/wAADrpoQLYQVa7NPjMc5eenz50903jKge2DT1UAACdBCoAgE4u\n+cGErHXDOQBbi0AFY7R87Ki1ntJ75uprx1EOnLc0QGiy9iChRlSHlQlUAIyd1+Gw3QhUMIWW9xYA\nMP0EKgA2bKlnaa2R2ZcuWW90+AVDObAdCFQwsNGbxP1gZ7vzKiO4eCMNVFW1O8nnkrwryRtJfqa1\n9p1RfgdcaCNBaK0QtPQX9yhvEn//x76y4nyvi2EnWLpk/fCHXbpm5xh1D9XfSPL21tpfqap3J3kg\nya0j/g6YKMMdwHhs9MnDjXCDO5tt18LCwsh2VlUPJjnRWvv1wef/1Vr7M6utPz9/ZnRfvore3out\naG5uNvPzZ8b6ncuf2Om9t2IjT/8s5/IEMG0u9j6yUZrE74DNNE1PhM7Nze5abdmoA9UjSR5rrR0Z\nfH4hyQ+11s6N7EsAAKbMqF8980qS2eX7F6YAgO1u1IHqqSR/LUkG91D9/oj3DwAwdUZ9U/rjSf5q\nVf1ukl1JPjTi/QMATJ2R3kMFALATjfqSHwDAjiNQAQB08uqZLaqqLkvyL5P8iSRnkvx0a21+hfV+\nOMlvttb+wuDzDyb5YpLLkvzvJB9qrb02tsK3kY0cg6q6N8ktSc4luau1dqKq9id5Ism3B6s93Fr7\n0vgq39rWeyNDVX04yd/JYpt/qrX228770Rmy/X8gybeSfGOw2uOttYfGW/n2sJE3klTVXJLfTfIX\nW2v/d6O/L+ijh2rr+miS32+tvSfJv0hyz4UrVNVtSX49yQ8um/0LSb442O65LP7gYzhrHoNBcLoh\nyXVJPpjks4NF+5M82Fq7cfBPmLo459/IkOTuLL6RIUlSVX8yyd9L8qNJDib5x1V1aZz3ozRM++9P\n8q+XnfPC1PBWbf8kqaqDSY4lecey2ev+vqCfQLV1XZ/k3w6mjyR53wrrnMriL/SL3Y6NWa8tr09y\nrLW20Fp7IcnM4C/Ha5LcUlVfq6pHq2o2XIzz7d5a+49J/vKyZdcmeaq19kZr7XSS7yT5S3Hej9Iw\n7X9Nkv1V9dWq+nJV/alxF72NrNX+SfJWFs/v/7PSNnH+bxqX/LaAqvrbSf7+BbP/MMnpwfSZJHsv\n3K619tuD7ZfPvmK97fh+Qx6DK5K8tOzz0jonkjzSWnu2qj6R5N4k/2DkRW9fy8/hJHmzqmYGgwhf\nuGypzZ33ozNM+//XJM+21v59Vf2tJJ9O8oFxFbzNrNX+aa39u8TP/UkQqLaA1tqjSR5dPq+qfiPf\nG5V+NsnLG9zd0mj2r1/kdjvakMfgwjcHLK3zeGttad3Hs/jLhY1b640Mq7W58350hmn/rydZumft\n8SS/uNlFbmPDvJFk+TbO/03ikt/WdX5U+iQ3Jzm+ydvx/dZry6eSHKyq3VV1VRZ/8L2Y5GhVXTtY\n571Jnh1LtdvHWm9kOJHkPVX19qram+TPZ/FGaOf96AzT/o8k+fHBOs75PsO8kcT5PwZ6qLauh5P8\nWlX9TpKzSX4ySarql5Mcbq2dWGW7Tw22+3CSF5e2YyjrHoOqOp7k6Sz+8XLHYLuPJvlMVZ1N8t0k\nHxl75Vvb972Roap+Nsl3Wmu/VVW/msVfGLuTfGLwlJPzfnSGaf+7kxyqqr+b5NUkPzOp4reBNdt/\nlW1W/FnFaBkpHQCgk0t+AACdBCoAgE4CFQBAJ4EKAKCTQAUA0EmgAgDoJFABAHQSqAAAOv0/ie1O\nxsKEx/IAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x117ca5f28>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = data['Returns'].hist(bins=45, figsize=(10, 6))\n",
"data['Strategy'].hist(bins=45, ax=ax, alpha=0.3, color='r');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Predicting Market Direction by Machine Learning"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {},
"outputs": [],
"source": [
"data = pd.DataFrame(raw[sym])"
]
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {},
"outputs": [],
"source": [
"data['Returns'] = np.log(data[sym] / data[sym].shift(1))"
]
},
{
"cell_type": "code",
"execution_count": 71,
"metadata": {},
"outputs": [],
"source": [
"lags = 5"
]
},
{
"cell_type": "code",
"execution_count": 72,
"metadata": {},
"outputs": [],
"source": [
"cols = []\n",
"for lag in range(1, lags+1):\n",
" col = 'lag_%d' % lag\n",
" # data[col] = np.sign(data['Returns'].shift(lag))\n",
" data[col] = np.where(data['Returns'].shift(lag) > 0, 1, 0)\n",
" cols.append(col)"
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" 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>AAPL.O</th>\n",
" <th>Returns</th>\n",
" <th>lag_1</th>\n",
" <th>lag_2</th>\n",
" <th>lag_3</th>\n",
" <th>lag_4</th>\n",
" <th>lag_5</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",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2010-01-04</th>\n",
" <td>30.572827</td>\n",
" <td>NaN</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-05</th>\n",
" <td>30.625684</td>\n",
" <td>0.001727</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-06</th>\n",
" <td>30.138541</td>\n",
" <td>-0.016034</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-07</th>\n",
" <td>30.082827</td>\n",
" <td>-0.001850</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-08</th>\n",
" <td>30.282827</td>\n",
" <td>0.006626</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-11</th>\n",
" <td>30.015684</td>\n",
" <td>-0.008861</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-12</th>\n",
" <td>29.674256</td>\n",
" <td>-0.011440</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" AAPL.O Returns lag_1 lag_2 lag_3 lag_4 lag_5\n",
"Date \n",
"2010-01-04 30.572827 NaN 0 0 0 0 0\n",
"2010-01-05 30.625684 0.001727 0 0 0 0 0\n",
"2010-01-06 30.138541 -0.016034 1 0 0 0 0\n",
"2010-01-07 30.082827 -0.001850 0 1 0 0 0\n",
"2010-01-08 30.282827 0.006626 0 0 1 0 0\n",
"2010-01-11 30.015684 -0.008861 1 0 0 1 0\n",
"2010-01-12 29.674256 -0.011440 0 1 0 0 1"
]
},
"execution_count": 73,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head(7)"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {},
"outputs": [],
"source": [
"data.dropna(inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {},
"outputs": [],
"source": [
"from sklearn import linear_model"
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {},
"outputs": [],
"source": [
"model = linear_model.LogisticRegression(C=100)"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"LogisticRegression(C=100, class_weight=None, dual=False, fit_intercept=True,\n",
" intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,\n",
" penalty='l2', random_state=None, solver='liblinear', tol=0.0001,\n",
" verbose=0, warm_start=False)"
]
},
"execution_count": 77,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"model.fit(data[cols], np.sign(data['Returns']))"
]
},
{
"cell_type": "code",
"execution_count": 78,
"metadata": {},
"outputs": [],
"source": [
"data['Prediction'] = model.predict(data[cols])"
]
},
{
"cell_type": "code",
"execution_count": 79,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" 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>AAPL.O</th>\n",
" <th>Returns</th>\n",
" <th>lag_1</th>\n",
" <th>lag_2</th>\n",
" <th>lag_3</th>\n",
" <th>lag_4</th>\n",
" <th>lag_5</th>\n",
" <th>Prediction</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",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2010-01-05</th>\n",
" <td>30.625684</td>\n",
" <td>0.001727</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-06</th>\n",
" <td>30.138541</td>\n",
" <td>-0.016034</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-07</th>\n",
" <td>30.082827</td>\n",
" <td>-0.001850</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-08</th>\n",
" <td>30.282827</td>\n",
" <td>0.006626</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-11</th>\n",
" <td>30.015684</td>\n",
" <td>-0.008861</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" AAPL.O Returns lag_1 lag_2 lag_3 lag_4 lag_5 Prediction\n",
"Date \n",
"2010-01-05 30.625684 0.001727 0 0 0 0 0 1.0\n",
"2010-01-06 30.138541 -0.016034 1 0 0 0 0 1.0\n",
"2010-01-07 30.082827 -0.001850 0 1 0 0 0 1.0\n",
"2010-01-08 30.282827 0.006626 0 0 1 0 0 -1.0\n",
"2010-01-11 30.015684 -0.008861 1 0 0 1 0 1.0"
]
},
"execution_count": 79,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
" 1.0 1058\n",
"-1.0 911\n",
" 0.0 2\n",
"dtype: int64"
]
},
"execution_count": 80,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.sign(data['Returns'] * data['Prediction']).value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 81,
"metadata": {},
"outputs": [],
"source": [
"data['Strategy'] = data['Prediction'] * data['Returns']"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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0HZ1xx9oHfPbXHNnQpcBpe+kuXtn1trZ/+7w/8sbu9/zqXYmBqVuBk8Vi+cJs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\no/8HnkPOhJyiUWUAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1a19b3d240>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data[['Returns', 'Strategy']].dropna().cumsum(\n",
" ).apply(np.exp).plot(figsize=(10, 6));"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Digitization of Features"
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {},
"outputs": [],
"source": [
"data = pd.DataFrame(raw[sym])"
]
},
{
"cell_type": "code",
"execution_count": 84,
"metadata": {},
"outputs": [],
"source": [
"data['Returns'] = np.log(data[sym] / data[sym].shift(1))"
]
},
{
"cell_type": "code",
"execution_count": 85,
"metadata": {},
"outputs": [],
"source": [
"lags = 5"
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([3, 2, 0, 1, 2, 1, 0, 3, 1, 0, 3, 0, 0, 0, 3, 3, 2, 0, 0, 3])"
]
},
"execution_count": 86,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.digitize(data['Returns'], bins=[-0.01, 0, 0.01])[:20]"
]
},
{
"cell_type": "code",
"execution_count": 87,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(0.00086759197334427293, 0.016047916326656784)"
]
},
"execution_count": 87,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mu = data['Returns'].mean()\n",
"std = data['Returns'].std()\n",
"mu, std"
]
},
{
"cell_type": "code",
"execution_count": 88,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([3, 2, 0, 1, 2, 1, 1, 2, 1, 0, 3, 0, 0, 0, 3, 2, 2, 0, 0, 2])"
]
},
"execution_count": 88,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.digitize(data['Returns'], bins=[mu - std, mu, mu + std])[:20]"
]
},
{
"cell_type": "code",
"execution_count": 89,
"metadata": {},
"outputs": [],
"source": [
"cols = []\n",
"for lag in range(1, lags+1):\n",
" col = 'lag_%d' % lag\n",
" #data[col] = np.digitize(data['Returns'].shift(lag),\n",
" # bins=[mu - std, mu, mu + std])\n",
" data[col] = np.digitize(data['Returns'].shift(lag),\n",
" bins=[-0.01, 0, 0.01])\n",
" cols.append(col)"
]
},
{
"cell_type": "code",
"execution_count": 90,
"metadata": {},
"outputs": [],
"source": [
"data.dropna(inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 91,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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" vertical-align: middle;\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>AAPL.O</th>\n",
" <th>Returns</th>\n",
" <th>lag_1</th>\n",
" <th>lag_2</th>\n",
" <th>lag_3</th>\n",
" <th>lag_4</th>\n",
" <th>lag_5</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",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2010-01-05</th>\n",
" <td>30.625684</td>\n",
" <td>0.001727</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-06</th>\n",
" <td>30.138541</td>\n",
" <td>-0.016034</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-07</th>\n",
" <td>30.082827</td>\n",
" <td>-0.001850</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-08</th>\n",
" <td>30.282827</td>\n",
" <td>0.006626</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-11</th>\n",
" <td>30.015684</td>\n",
" <td>-0.008861</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-12</th>\n",
" <td>29.674256</td>\n",
" <td>-0.011440</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-13</th>\n",
" <td>30.092827</td>\n",
" <td>0.014007</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-14</th>\n",
" <td>29.918542</td>\n",
" <td>-0.005808</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-15</th>\n",
" <td>29.418542</td>\n",
" <td>-0.016853</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" AAPL.O Returns lag_1 lag_2 lag_3 lag_4 lag_5\n",
"Date \n",
"2010-01-05 30.625684 0.001727 3 3 3 3 3\n",
"2010-01-06 30.138541 -0.016034 2 3 3 3 3\n",
"2010-01-07 30.082827 -0.001850 0 2 3 3 3\n",
"2010-01-08 30.282827 0.006626 1 0 2 3 3\n",
"2010-01-11 30.015684 -0.008861 2 1 0 2 3\n",
"2010-01-12 29.674256 -0.011440 1 2 1 0 2\n",
"2010-01-13 30.092827 0.014007 0 1 2 1 0\n",
"2010-01-14 29.918542 -0.005808 3 0 1 2 1\n",
"2010-01-15 29.418542 -0.016853 1 3 0 1 2"
]
},
"execution_count": 91,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head(9)"
]
},
{
"cell_type": "code",
"execution_count": 92,
"metadata": {},
"outputs": [],
"source": [
"# model = linear_model.LogisticRegression(C=100000)"
]
},
{
"cell_type": "code",
"execution_count": 93,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.svm import SVC"
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {},
"outputs": [],
"source": [
"model = SVC() # support vector machines"
]
},
{
"cell_type": "code",
"execution_count": 95,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
" decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
" max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
" tol=0.001, verbose=False)"
]
},
"execution_count": 95,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"model.fit(data[cols], np.sign(data['Returns']))"
]
},
{
"cell_type": "code",
"execution_count": 96,
"metadata": {},
"outputs": [],
"source": [
"data['Prediction'] = model.predict(data[cols])"
]
},
{
"cell_type": "code",
"execution_count": 97,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" 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>AAPL.O</th>\n",
" <th>Returns</th>\n",
" <th>lag_1</th>\n",
" <th>lag_2</th>\n",
" <th>lag_3</th>\n",
" <th>lag_4</th>\n",
" <th>lag_5</th>\n",
" <th>Prediction</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",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2010-01-05</th>\n",
" <td>30.625684</td>\n",
" <td>0.001727</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-06</th>\n",
" <td>30.138541</td>\n",
" <td>-0.016034</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-07</th>\n",
" <td>30.082827</td>\n",
" <td>-0.001850</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-08</th>\n",
" <td>30.282827</td>\n",
" <td>0.006626</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>-1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-01-11</th>\n",
" <td>30.015684</td>\n",
" <td>-0.008861</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" AAPL.O Returns lag_1 lag_2 lag_3 lag_4 lag_5 Prediction\n",
"Date \n",
"2010-01-05 30.625684 0.001727 3 3 3 3 3 1.0\n",
"2010-01-06 30.138541 -0.016034 2 3 3 3 3 1.0\n",
"2010-01-07 30.082827 -0.001850 0 2 3 3 3 1.0\n",
"2010-01-08 30.282827 0.006626 1 0 2 3 3 -1.0\n",
"2010-01-11 30.015684 -0.008861 2 1 0 2 3 1.0"
]
},
"execution_count": 97,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 98,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
" 1.0 1169\n",
"-1.0 800\n",
" 0.0 2\n",
"dtype: int64"
]
},
"execution_count": 98,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.sign(data['Returns'] * data['Prediction']).value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 99,
"metadata": {},
"outputs": [],
"source": [
"data['Strategy'] = data['Prediction'] * data['Returns']"
]
},
{
"cell_type": "code",
"execution_count": 100,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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i1hSsp7R+tfD4+iUQGnRmqG5b/fID80bMwev3UuYqx2KxdOga0v00VCciIn1a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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1a19be04a8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data[['Returns', 'Strategy']].dropna().cumsum(\n",
" ).apply(np.exp).plot(figsize=(10, 6));"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<img src='http://hilpisch.com/tpq_logo.png' width=\"300px\" align=\"right\">"
]
}
],
"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": "3.6.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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