{
 "metadata": {
  "name": "goog_repl"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "import pandas.io.data\n",
      "import numpy as np\n",
      "\n",
      "delta_t = 3"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "source": [
      "Load data: Dow Jones Industrial Average, S&P500 from yahoo and the google trend weekly averages."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "djia = pd.DataFrame.from_csv('DJIA.csv', index_col='DATE').sort()\n",
      "sp500 = pd.DataFrame(pd.io.data.DataReader(\"^GSPC\", \"yahoo\", start=datetime.datetime(2004, 1, 1), end=datetime.datetime(2011, 4, 1))['Adj Close'], columns=['sp500'])\n",
      "#sp500 = sp500.tshift(1, freq='B')\n",
      "debt = pd.read_csv('debt_google_trend.csv', index_col='date')\n",
      "dija.index = dija.index.to_datetime()\n",
      "djia.rename(columns={'VALUE': 'djia'}, inplace=True)\n",
      "debt.index = debt.index.to_datetime()\n",
      "debt = debt.tshift(2, freq='D') # Moves Saturday to Monday\n",
      "\n",
      "# Load Preis data\n",
      "df = pd.read_csv('PreisMoatStanley_ScientificReports_3_1684_2013.dat', delimiter=' ')\n",
      "columns = ['Google Start Date', 'Google End Date', 'debt', 'DJIA Date', 'DJIA Closing Price']\n",
      "df = df[columns]\n",
      "debt_from_study = df[['debt', 'DJIA Closing Price']]\n",
      "debt_from_study.rename(columns={'debt': 'debt_preis', 'DJIA Closing Price': 'djia_preis'}, inplace=True)\n",
      "debt_from_study.index = df['Google End Date']\n",
      "debt_from_study.index = debt_from_study.index.to_datetime()\n",
      "debt_from_study = debt_from_study.tshift(2, freq='D') # Move from Sat to Monday\n",
      "debt_from_study.head()"
     ],
     "language": "python",
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>debt_preis</th>\n",
        "      <th>djia_preis</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2004-01-12</th>\n",
        "      <td> 0.210000</td>\n",
        "      <td> 10485.18</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2004-01-19</th>\n",
        "      <td> 0.210000</td>\n",
        "      <td> 10528.66</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2004-01-26</th>\n",
        "      <td> 0.210000</td>\n",
        "      <td> 10702.51</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2004-02-02</th>\n",
        "      <td> 0.213333</td>\n",
        "      <td> 10499.18</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2004-02-09</th>\n",
        "      <td> 0.200000</td>\n",
        "      <td> 10579.03</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "output_type": "pyout",
       "prompt_number": 195,
       "text": [
        "            debt_preis  djia_preis\n",
        "2004-01-12    0.210000    10485.18\n",
        "2004-01-19    0.210000    10528.66\n",
        "2004-01-26    0.210000    10702.51\n",
        "2004-02-02    0.213333    10499.18\n",
        "2004-02-09    0.200000    10579.03"
       ]
      }
     ],
     "prompt_number": 195
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Join together into single dataframe.\n",
      "data = pd.concat([debt, sp500, debt_from_study], axis=1).dropna()\n",
      "data.head()"
     ],
     "language": "python",
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>debt</th>\n",
        "      <th>sp500</th>\n",
        "      <th>debt_preis</th>\n",
        "      <th>djia_preis</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2004-01-12</th>\n",
        "      <td> 35</td>\n",
        "      <td> 1127.23</td>\n",
        "      <td> 0.210000</td>\n",
        "      <td> 10485.18</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2004-01-26</th>\n",
        "      <td> 36</td>\n",
        "      <td> 1155.37</td>\n",
        "      <td> 0.210000</td>\n",
        "      <td> 10702.51</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2004-02-02</th>\n",
        "      <td> 37</td>\n",
        "      <td> 1135.26</td>\n",
        "      <td> 0.213333</td>\n",
        "      <td> 10499.18</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2004-02-09</th>\n",
        "      <td> 37</td>\n",
        "      <td> 1139.81</td>\n",
        "      <td> 0.200000</td>\n",
        "      <td> 10579.03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2004-02-23</th>\n",
        "      <td> 35</td>\n",
        "      <td> 1140.99</td>\n",
        "      <td> 0.200000</td>\n",
        "      <td> 10609.62</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "output_type": "pyout",
       "prompt_number": 196,
       "text": [
        "            debt    sp500  debt_preis  djia_preis\n",
        "2004-01-12    35  1127.23    0.210000    10485.18\n",
        "2004-01-26    36  1155.37    0.210000    10702.51\n",
        "2004-02-02    37  1135.26    0.213333    10499.18\n",
        "2004-02-09    37  1139.81    0.200000    10579.03\n",
        "2004-02-23    35  1140.99    0.200000    10609.62"
       ]
      }
     ],
     "prompt_number": 196
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data.debt.plot()\n",
      "data.debt_preis.plot(secondary_y=True)"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 197,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0xa6c546c>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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du5dXX33V6UZceim4u8OUKfD00+3b55ln4PRppw/Z5fz1rzB9umh/cbGwjoWE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\nAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 197
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data['rolling_mean'] = pd.rolling_mean(data.debt, delta_t).shift(1)\n",
      "data['rolling_mean_preis'] = pd.rolling_mean(data.debt_preis, delta_t).shift(1)\n",
      "data.head(10)"
     ],
     "language": "python",
     "outputs": [
      {
       "html": [
        "<pre>\n",
        "&ltclass 'pandas.core.frame.DataFrame'&gt\n",
        "DatetimeIndex: 10 entries, 2004-01-12 00:00:00 to 2004-03-29 00:00:00\n",
        "Data columns (total 11 columns):\n",
        "debt                    10  non-null values\n",
        "sp500                   10  non-null values\n",
        "debt_preis              10  non-null values\n",
        "djia_preis              10  non-null values\n",
        "rolling_mean            7  non-null values\n",
        "rolling_mean_preis      7  non-null values\n",
        "order                   10  non-null values\n",
        "order_preis             10  non-null values\n",
        "log_returns             10  non-null values\n",
        "log_returns_sp          10  non-null values\n",
        "log_returns_new_data    10  non-null values\n",
        "dtypes: float64(9), int64(2)\n",
        "</pre>"
       ],
       "output_type": "pyout",
       "prompt_number": 212,
       "text": [
        "            debt    sp500  debt_preis  djia_preis  rolling_mean  \\\n",
        "2004-01-12    35  1127.23    0.210000    10485.18           NaN   \n",
        "2004-01-26    36  1155.37    0.210000    10702.51           NaN   \n",
        "2004-02-02    37  1135.26    0.213333    10499.18           NaN   \n",
        "2004-02-09    37  1139.81    0.200000    10579.03     36.000000   \n",
        "2004-02-23    35  1140.99    0.200000    10609.62     36.666667   \n",
        "2004-03-01    35  1155.97    0.200000    10678.14     36.333333   \n",
        "2004-03-08    34  1147.20    0.196667    10529.48     35.666667   \n",
        "2004-03-15    34  1104.49    0.196667    10102.89     34.666667   \n",
        "2004-03-22    33  1095.40    0.193333    10064.75     34.333333   \n",
        "2004-03-29    30  1122.47    0.173333    10329.63     33.666667   \n",
        "\n",
        "            rolling_mean_preis  order  order_preis  log_returns  \\\n",
        "2004-01-12                 NaN      0            0     0.000000   \n",
        "2004-01-26                 NaN      0            0     0.000000   \n",
        "2004-02-02                 NaN      0            0     0.000000   \n",
        "2004-02-09            0.211111     -1            1     0.002887   \n",
        "2004-02-23            0.207778      1            1     0.006438   \n",
        "2004-03-01            0.204444      1            1    -0.014020   \n",
        "2004-03-08            0.200000      1            1    -0.041357   \n",
        "2004-03-15            0.198889      1            1    -0.003782   \n",
        "2004-03-22            0.197778      1            1     0.025977   \n",
        "2004-03-29            0.195556      1            1     0.021902   \n",
        "\n",
        "            log_returns_sp  log_returns_new_data  \n",
        "2004-01-12        0.000000              0.000000  \n",
        "2004-01-26        0.000000              0.000000  \n",
        "2004-02-02        0.000000              0.000000  \n",
        "2004-02-09        0.001035             -0.002887  \n",
        "2004-02-23        0.013044              0.006438  \n",
        "2004-03-01       -0.007616             -0.014020  \n",
        "2004-03-08       -0.037941             -0.041357  \n",
        "2004-03-15       -0.008264             -0.003782  \n",
        "2004-03-22        0.024412              0.025977  \n",
        "2004-03-29        0.024726              0.021902  "
       ]
      }
     ],
     "prompt_number": 212
    },
    {
     "cell_type": "markdown",
     "source": [
      "Generate the trading and order signals.\n",
      "From the paper:\n",
      "\"We use Google Trends to determine how many searches n(t \u2013 1) have been carried out for a specific search term such as debt in week t \u2013 1, where Google defines weeks as ending on a Sunday, relative to the total number of searches carried out on Google during that time.\"\n",
      "and\n",
      "\"We implement this strategy by selling the DJIA at the closing price p(t) on the first trading day of week t, if \u0394n(t \u2212 1, \u0394t) > 0, and buying the DJIA at price p(t + 1) at the end of the first trading day of the following week. [...]. If instead \u0394n(t \u2212 1, \u0394t) < 0, then we buy the DJIA at the closing price p(t) on the first trading day of week t and sell the DJIA at price p(t + 1) at the end of the first trading day of the coming week.\""
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data['order'] = 0\n",
      "data['order'][data.debt > data.rolling_mean.shift(1)] = -1 # Shorting if cross-over\n",
      "data['order'][data.debt < data.rolling_mean.shift(1)] = 1 # Buying otherwise.\n",
      "data['order'].ix[:delta_t] = 0\n",
      "\n",
      "data['order_preis'] = 1\n",
      "data['order_preis'][data.debt_preis > data.rolling_mean_preis] = -1 # Shorting if cross-over\n",
      "data['order_preis'][data.debt_preis < data.rolling_mean_preis] = 1 # Buying otherwise.\n",
      "data['order_preis'].ix[:delta_t] = 0\n"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 213
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print \"% of overlapping trading signals from Preis debt data and newly retrieved search data: \", (data.order == data.order_preis).mean()"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "% of overlapping trading signals from Preis debt data and newly retrieved search data:  0.72619047619\n"
       ]
      }
     ],
     "prompt_number": 214
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data.head(10)"
     ],
     "language": "python",
     "outputs": [
      {
       "html": [
        "<pre>\n",
        "&ltclass 'pandas.core.frame.DataFrame'&gt\n",
        "DatetimeIndex: 10 entries, 2004-01-12 00:00:00 to 2004-03-29 00:00:00\n",
        "Data columns (total 11 columns):\n",
        "debt                    10  non-null values\n",
        "sp500                   10  non-null values\n",
        "debt_preis              10  non-null values\n",
        "djia_preis              10  non-null values\n",
        "rolling_mean            7  non-null values\n",
        "rolling_mean_preis      7  non-null values\n",
        "order                   10  non-null values\n",
        "order_preis             10  non-null values\n",
        "log_returns             10  non-null values\n",
        "log_returns_sp          10  non-null values\n",
        "log_returns_new_data    10  non-null values\n",
        "dtypes: float64(9), int64(2)\n",
        "</pre>"
       ],
       "output_type": "pyout",
       "prompt_number": 215,
       "text": [
        "            debt    sp500  debt_preis  djia_preis  rolling_mean  \\\n",
        "2004-01-12    35  1127.23    0.210000    10485.18           NaN   \n",
        "2004-01-26    36  1155.37    0.210000    10702.51           NaN   \n",
        "2004-02-02    37  1135.26    0.213333    10499.18           NaN   \n",
        "2004-02-09    37  1139.81    0.200000    10579.03     36.000000   \n",
        "2004-02-23    35  1140.99    0.200000    10609.62     36.666667   \n",
        "2004-03-01    35  1155.97    0.200000    10678.14     36.333333   \n",
        "2004-03-08    34  1147.20    0.196667    10529.48     35.666667   \n",
        "2004-03-15    34  1104.49    0.196667    10102.89     34.666667   \n",
        "2004-03-22    33  1095.40    0.193333    10064.75     34.333333   \n",
        "2004-03-29    30  1122.47    0.173333    10329.63     33.666667   \n",
        "\n",
        "            rolling_mean_preis  order  order_preis  log_returns  \\\n",
        "2004-01-12                 NaN      0            0     0.000000   \n",
        "2004-01-26                 NaN      0            0     0.000000   \n",
        "2004-02-02                 NaN      0            0     0.000000   \n",
        "2004-02-09            0.211111      0            1     0.002887   \n",
        "2004-02-23            0.207778      1            1     0.006438   \n",
        "2004-03-01            0.204444      1            1    -0.014020   \n",
        "2004-03-08            0.200000      1            1    -0.041357   \n",
        "2004-03-15            0.198889      1            1    -0.003782   \n",
        "2004-03-22            0.197778      1            1     0.025977   \n",
        "2004-03-29            0.195556      1            1     0.021902   \n",
        "\n",
        "            log_returns_sp  log_returns_new_data  \n",
        "2004-01-12        0.000000              0.000000  \n",
        "2004-01-26        0.000000              0.000000  \n",
        "2004-02-02        0.000000              0.000000  \n",
        "2004-02-09        0.001035             -0.002887  \n",
        "2004-02-23        0.013044              0.006438  \n",
        "2004-03-01       -0.007616             -0.014020  \n",
        "2004-03-08       -0.037941             -0.041357  \n",
        "2004-03-15       -0.008264             -0.003782  \n",
        "2004-03-22        0.024412              0.025977  \n",
        "2004-03-29        0.024726              0.021902  "
       ]
      }
     ],
     "prompt_number": 215
    },
    {
     "cell_type": "markdown",
     "source": [
      "From the paper:\n",
      "\"If we take a \u2018short position\u2019\u2014selling at the closing price p(t) and buying back at price p(t + 1)\u2014then the cumulative return R changes by log(p(t)) \u2212 log(p(t + 1)). If we take a \u2018long position\u2019\u2014buying at the closing price p(t) and selling at price p(t + 1)\u2014then the cumulative return R changes by log(p(t + 1)) \u2212 log(p(t)).\""
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Compute log returns using djia and debt search volume from Preis et al.\n",
      "data['log_returns'] = data.order_preis * np.log(data.djia_preis.shift(-1)) - data.order_preis * np.log(data.djia_preis)\n",
      "# Compute log returns using S&P500.\n",
      "data['log_returns_sp'] = data.order_preis * np.log(data.sp500.shift(-1)) - data.order_preis * np.log(data.sp500)\n",
      "# Compute log returns using debt search volume recently extracted from trends\n",
      "data['log_returns_new_data'] = data.order * np.log(data.djia_preis.shift(-1)) - data.order * np.log(data.djia_preis)"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 216
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.figsize(10, 3)\n",
      "(np.exp(data.log_returns.cumsum()) - 1).plot();"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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ZTZsmPWNubnKOKVOksD02VoYPK1dmTxVRfoxKrHSF+MZo164doqKiYGtriz17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\nMWFiRURERFRM/h/El9HTcrUbTQAAAABJRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 217
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.core.display import Image \n",
      "Image(\"http://www.nature.com/srep/2013/130425/srep01684/carousel/srep01684-f2.jpg\")"
     ],
     "language": "python",
     "outputs": [
      {
       "jpeg": 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kyudJ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MmbDM4+5QjyZcfyJcOtlkLSaIhLq2ysa3ELxi4ivXLvHV0WU9njxqsEg8ROLQey7z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\n",
       "output_type": "pyout",
       "prompt_number": 205,
       "text": [
        "<IPython.core.display.Image at 0xb7508ec>"
       ]
      }
     ],
     "prompt_number": 205
    },
    {
     "cell_type": "markdown",
     "source": [
      "Pretty good replication (using same data).\n",
      "\n",
      "Lets see how well the strategy does on search volume data extracted more recently."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.figsize(10, 3)\n",
      "(np.exp(data.log_returns_new_data.cumsum()) - 1).plot();"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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DAMyePRvW1taYMGFCuvOCg4PRs2dP+Pn5wcXFJeMg2CCUiKjAUAooVkz6ThUt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\nKyIiIiIDYWJFREREZCD/D2LKy4qARRtuAAAAAElFTkSuQmCC\n"
      }
     ],
     "prompt_number": 219
    },
    {
     "cell_type": "markdown",
     "source": [
      "Much worse. As seen before there is a qualitative difference between the search data used in Preis and the one that can be downloaded today. This might be expected since the signal is indeed degraded as you mentioned (only 72% of the order decisions match when comparing the two data sources).\n",
      "\n",
      "Finally, lets see how well the strategy (using the Preis signals) would do on S&P500."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.figsize(10, 3)\n",
      "(np.exp(data.log_returns_sp.cumsum()) - 1).plot();"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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      }
     ],
     "prompt_number": 218
    }
   ]
  }
 ]
}