Un peu d'analyse financière avec Python 3.4.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <font color=\"#B40404\">Un peu d'analyse financière avec Python 3.4</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color=\"#084B8A\">Qu'est ce que vous apprendrai dans ce tutoriel</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "- Analyse des séries chronologiques avec Pandas\n",
    "- Utilisation de Google Trends pour prédire les mouvements du marché\n",
    "- Construire votre propre stratégie de trading en utilisant Zipline\n",
    "- Stratégies de négociation communes:\n",
    "    - trading Momentum\n",
    "    - Retour à la moyenne"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color=\"#084B8A\">Les différentes étapes vers une stratégie de négociation réussie</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. L'analyse des données\n",
    "    - Pandas + Matplotlib (Partie I)\n",
    "2. Stratégie backtest\n",
    "    - Pandas peuvent être utilisés, mais de nombreuses limites (Partie II )\n",
    "    - Zipline (Partie III )\n",
    "3. tratégie de test Forward\n",
    "    - Trivial sur Quantopian (Partie IV )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color=\"#084B8A\">Bases de Pandas (Analyse de données)</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<iframe src=http://pandas.pydata.org width=800 height=350></iframe>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.core.display import HTML\n",
    "HTML(\"<iframe src=http://pandas.pydata.org width=800 height=350></iframe>\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.16.2'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import datetime\n",
    "\n",
    "import pandas as pd\n",
    "import pandas.io.data\n",
    "from pandas import Series, DataFrame\n",
    "pd.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.4.3'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import numpy as np\n",
    "mpl.rc('figure', figsize=(8, 7))\n",
    "mpl.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color=\"#084B8A\">Création / Chargement de données - séries chronologiques</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- De construction Python\n",
    "- De Yahoo finance\n",
    "- De fichiers CSV"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <font color=\"#585858\">De construction Python</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    1\n",
       "b    2\n",
       "c    3\n",
       "d    4\n",
       "e    5\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "labels = ['a', 'b', 'c', 'd', 'e']\n",
    "s = Series([1, 2, 3, 4, 5], index=labels)\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'b' in s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s['b']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mapping = s.to_dict()\n",
    "mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    1\n",
       "b    2\n",
       "c    3\n",
       "d    4\n",
       "e    5\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Series(mapping)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <font color=\"#585858\">De Yahoo finance</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006-10-02</th>\n",
       "      <td>75.100003</td>\n",
       "      <td>75.870001</td>\n",
       "      <td>74.299998</td>\n",
       "      <td>74.859998</td>\n",
       "      <td>178159800</td>\n",
       "      <td>9.903863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-03</th>\n",
       "      <td>74.450002</td>\n",
       "      <td>74.950000</td>\n",
       "      <td>73.190000</td>\n",
       "      <td>74.080000</td>\n",
       "      <td>197677200</td>\n",
       "      <td>9.800671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-04</th>\n",
       "      <td>74.100000</td>\n",
       "      <td>75.459998</td>\n",
       "      <td>73.159999</td>\n",
       "      <td>75.380003</td>\n",
       "      <td>207270700</td>\n",
       "      <td>9.972659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-05</th>\n",
       "      <td>74.529997</td>\n",
       "      <td>76.160001</td>\n",
       "      <td>74.130001</td>\n",
       "      <td>74.829997</td>\n",
       "      <td>170970800</td>\n",
       "      <td>9.899894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-06</th>\n",
       "      <td>74.420001</td>\n",
       "      <td>75.040002</td>\n",
       "      <td>73.810000</td>\n",
       "      <td>74.220003</td>\n",
       "      <td>116739700</td>\n",
       "      <td>9.819193</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open       High        Low      Close     Volume  Adj Close\n",
       "Date                                                                        \n",
       "2006-10-02  75.100003  75.870001  74.299998  74.859998  178159800   9.903863\n",
       "2006-10-03  74.450002  74.950000  73.190000  74.080000  197677200   9.800671\n",
       "2006-10-04  74.100000  75.459998  73.159999  75.380003  207270700   9.972659\n",
       "2006-10-05  74.529997  76.160001  74.130001  74.829997  170970800   9.899894\n",
       "2006-10-06  74.420001  75.040002  73.810000  74.220003  116739700   9.819193"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aapl = pd.io.data.get_data_yahoo('AAPL', \n",
    "                                 start=datetime.datetime(2006, 10, 1), \n",
    "                                 end=datetime.datetime(2012, 1, 1))\n",
    "aapl.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <font color=\"#585858\">De fichiers CSV</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006-10-02</th>\n",
       "      <td>75.100003</td>\n",
       "      <td>75.870001</td>\n",
       "      <td>74.299998</td>\n",
       "      <td>74.859998</td>\n",
       "      <td>178159800</td>\n",
       "      <td>9.903863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-03</th>\n",
       "      <td>74.450002</td>\n",
       "      <td>74.950000</td>\n",
       "      <td>73.190000</td>\n",
       "      <td>74.080000</td>\n",
       "      <td>197677200</td>\n",
       "      <td>9.800671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-04</th>\n",
       "      <td>74.100000</td>\n",
       "      <td>75.459998</td>\n",
       "      <td>73.159999</td>\n",
       "      <td>75.380003</td>\n",
       "      <td>207270700</td>\n",
       "      <td>9.972659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-05</th>\n",
       "      <td>74.529997</td>\n",
       "      <td>76.160001</td>\n",
       "      <td>74.130001</td>\n",
       "      <td>74.829997</td>\n",
       "      <td>170970800</td>\n",
       "      <td>9.899894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-06</th>\n",
       "      <td>74.420001</td>\n",
       "      <td>75.040002</td>\n",
       "      <td>73.810000</td>\n",
       "      <td>74.220003</td>\n",
       "      <td>116739700</td>\n",
       "      <td>9.819193</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open       High        Low      Close     Volume  Adj Close\n",
       "Date                                                                        \n",
       "2006-10-02  75.100003  75.870001  74.299998  74.859998  178159800   9.903863\n",
       "2006-10-03  74.450002  74.950000  73.190000  74.080000  197677200   9.800671\n",
       "2006-10-04  74.100000  75.459998  73.159999  75.380003  207270700   9.972659\n",
       "2006-10-05  74.529997  76.160001  74.130001  74.829997  170970800   9.899894\n",
       "2006-10-06  74.420001  75.040002  73.810000  74.220003  116739700   9.819193"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aapl.to_csv('aapl_ohlc.csv')\n",
    "aapl.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006-10-02</th>\n",
       "      <td>75.100003</td>\n",
       "      <td>75.870001</td>\n",
       "      <td>74.299998</td>\n",
       "      <td>74.859998</td>\n",
       "      <td>178159800</td>\n",
       "      <td>9.903863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-03</th>\n",
       "      <td>74.450002</td>\n",
       "      <td>74.950000</td>\n",
       "      <td>73.190000</td>\n",
       "      <td>74.080000</td>\n",
       "      <td>197677200</td>\n",
       "      <td>9.800671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-04</th>\n",
       "      <td>74.100000</td>\n",
       "      <td>75.459998</td>\n",
       "      <td>73.159999</td>\n",
       "      <td>75.380003</td>\n",
       "      <td>207270700</td>\n",
       "      <td>9.972659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-05</th>\n",
       "      <td>74.529997</td>\n",
       "      <td>76.160001</td>\n",
       "      <td>74.130001</td>\n",
       "      <td>74.829997</td>\n",
       "      <td>170970800</td>\n",
       "      <td>9.899894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-06</th>\n",
       "      <td>74.420001</td>\n",
       "      <td>75.040002</td>\n",
       "      <td>73.810000</td>\n",
       "      <td>74.220003</td>\n",
       "      <td>116739700</td>\n",
       "      <td>9.819193</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open       High        Low      Close     Volume  Adj Close\n",
       "Date                                                                        \n",
       "2006-10-02  75.100003  75.870001  74.299998  74.859998  178159800   9.903863\n",
       "2006-10-03  74.450002  74.950000  73.190000  74.080000  197677200   9.800671\n",
       "2006-10-04  74.100000  75.459998  73.159999  75.380003  207270700   9.972659\n",
       "2006-10-05  74.529997  76.160001  74.130001  74.829997  170970800   9.899894\n",
       "2006-10-06  74.420001  75.040002  73.810000  74.220003  116739700   9.819193"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Location = r'/Users/moi/Desktop/FOLDERS/SOFWARES & SCRIPTS/PYTHON/Tutoriels/Applications Python 3.4/aapl_ohlc.csv'\n",
    "df = pd.read_csv(Location, index_col='Date', parse_dates=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2006-10-02', '2006-10-03', '2006-10-04', '2006-10-05',\n",
       "               '2006-10-06', '2006-10-09', '2006-10-10', '2006-10-11',\n",
       "               '2006-10-12', '2006-10-13', \n",
       "               ...\n",
       "               '2011-12-16', '2011-12-19', '2011-12-20', '2011-12-21',\n",
       "               '2011-12-22', '2011-12-23', '2011-12-27', '2011-12-28',\n",
       "               '2011-12-29', '2011-12-30'],\n",
       "              dtype='datetime64[ns]', name='Date', length=1323, freq=None, tz=None)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color=\"#084B8A\">Séries et dataframe : Premiers pas</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Indexation\n",
    "- Découpage\n",
    "- Création de nouvelles colonnes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2011-12-16    381.019989\n",
       "2011-12-19    382.210003\n",
       "2011-12-20    395.949997\n",
       "2011-12-21    396.450008\n",
       "2011-12-22    398.550003\n",
       "2011-12-23    403.330006\n",
       "2011-12-27    406.529999\n",
       "2011-12-28    402.640003\n",
       "2011-12-29    405.120007\n",
       "2011-12-30    405.000004\n",
       "Name: Close, dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts = df['Close'][-10:]\n",
    "ts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Un dataframe est une collection de série d'objets. Le découpage d'une colonne du dataframe retourne une série."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(ts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2011-12-23 00:00:00')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date = ts.index[5]\n",
    "date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "403.33000600000003"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts[date]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "403.33000600000003"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts[5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nous pouvons également sélectionner plusieurs colonnes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006-10-02</th>\n",
       "      <td>75.100003</td>\n",
       "      <td>74.859998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-03</th>\n",
       "      <td>74.450002</td>\n",
       "      <td>74.080000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-04</th>\n",
       "      <td>74.100000</td>\n",
       "      <td>75.380003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-05</th>\n",
       "      <td>74.529997</td>\n",
       "      <td>74.829997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-06</th>\n",
       "      <td>74.420001</td>\n",
       "      <td>74.220003</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open      Close\n",
       "Date                            \n",
       "2006-10-02  75.100003  74.859998\n",
       "2006-10-03  74.450002  74.080000\n",
       "2006-10-04  74.100000  75.380003\n",
       "2006-10-05  74.529997  74.829997\n",
       "2006-10-06  74.420001  74.220003"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['Open','Close']].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "De nouvelles colonnes peuvent être ajoutées à la volée."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>diff</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>2006-10-02</th>\n",
       "      <td>75.100003</td>\n",
       "      <td>75.870001</td>\n",
       "      <td>74.299998</td>\n",
       "      <td>74.859998</td>\n",
       "      <td>178159800</td>\n",
       "      <td>9.903863</td>\n",
       "      <td>0.240005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-03</th>\n",
       "      <td>74.450002</td>\n",
       "      <td>74.950000</td>\n",
       "      <td>73.190000</td>\n",
       "      <td>74.080000</td>\n",
       "      <td>197677200</td>\n",
       "      <td>9.800671</td>\n",
       "      <td>0.370002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-04</th>\n",
       "      <td>74.100000</td>\n",
       "      <td>75.459998</td>\n",
       "      <td>73.159999</td>\n",
       "      <td>75.380003</td>\n",
       "      <td>207270700</td>\n",
       "      <td>9.972659</td>\n",
       "      <td>-1.280003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-05</th>\n",
       "      <td>74.529997</td>\n",
       "      <td>76.160001</td>\n",
       "      <td>74.130001</td>\n",
       "      <td>74.829997</td>\n",
       "      <td>170970800</td>\n",
       "      <td>9.899894</td>\n",
       "      <td>-0.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-06</th>\n",
       "      <td>74.420001</td>\n",
       "      <td>75.040002</td>\n",
       "      <td>73.810000</td>\n",
       "      <td>74.220003</td>\n",
       "      <td>116739700</td>\n",
       "      <td>9.819193</td>\n",
       "      <td>0.199998</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open       High        Low      Close     Volume  Adj Close  \\\n",
       "Date                                                                           \n",
       "2006-10-02  75.100003  75.870001  74.299998  74.859998  178159800   9.903863   \n",
       "2006-10-03  74.450002  74.950000  73.190000  74.080000  197677200   9.800671   \n",
       "2006-10-04  74.100000  75.459998  73.159999  75.380003  207270700   9.972659   \n",
       "2006-10-05  74.529997  76.160001  74.130001  74.829997  170970800   9.899894   \n",
       "2006-10-06  74.420001  75.040002  73.810000  74.220003  116739700   9.819193   \n",
       "\n",
       "                diff  \n",
       "Date                  \n",
       "2006-10-02  0.240005  \n",
       "2006-10-03  0.370002  \n",
       "2006-10-04 -1.280003  \n",
       "2006-10-05 -0.300000  \n",
       "2006-10-06  0.199998  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['diff'] = df.Open - df.Close\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "...et supprimées à la volée."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006-10-02</th>\n",
       "      <td>75.100003</td>\n",
       "      <td>75.870001</td>\n",
       "      <td>74.299998</td>\n",
       "      <td>74.859998</td>\n",
       "      <td>178159800</td>\n",
       "      <td>9.903863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-03</th>\n",
       "      <td>74.450002</td>\n",
       "      <td>74.950000</td>\n",
       "      <td>73.190000</td>\n",
       "      <td>74.080000</td>\n",
       "      <td>197677200</td>\n",
       "      <td>9.800671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-04</th>\n",
       "      <td>74.100000</td>\n",
       "      <td>75.459998</td>\n",
       "      <td>73.159999</td>\n",
       "      <td>75.380003</td>\n",
       "      <td>207270700</td>\n",
       "      <td>9.972659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-05</th>\n",
       "      <td>74.529997</td>\n",
       "      <td>76.160001</td>\n",
       "      <td>74.130001</td>\n",
       "      <td>74.829997</td>\n",
       "      <td>170970800</td>\n",
       "      <td>9.899894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-06</th>\n",
       "      <td>74.420001</td>\n",
       "      <td>75.040002</td>\n",
       "      <td>73.810000</td>\n",
       "      <td>74.220003</td>\n",
       "      <td>116739700</td>\n",
       "      <td>9.819193</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open       High        Low      Close     Volume  Adj Close\n",
       "Date                                                                        \n",
       "2006-10-02  75.100003  75.870001  74.299998  74.859998  178159800   9.903863\n",
       "2006-10-03  74.450002  74.950000  73.190000  74.080000  197677200   9.800671\n",
       "2006-10-04  74.100000  75.459998  73.159999  75.380003  207270700   9.972659\n",
       "2006-10-05  74.529997  76.160001  74.130001  74.829997  170970800   9.899894\n",
       "2006-10-06  74.420001  75.040002  73.810000  74.220003  116739700   9.819193"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "del df['diff']\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color=\"#084B8A\">Calculs financiers généraux</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Moyenne mobile\n",
    "- Résultats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "close_px = df['Adj Close']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2011-12-16    51.425441\n",
       "2011-12-19    51.390183\n",
       "2011-12-20    51.357704\n",
       "2011-12-21    51.353338\n",
       "2011-12-22    51.346558\n",
       "2011-12-23    51.342059\n",
       "2011-12-27    51.347285\n",
       "2011-12-28    51.340207\n",
       "2011-12-29    51.368684\n",
       "2011-12-30    51.393788\n",
       "dtype: float64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mavg = pd.rolling_mean(close_px, 40)\n",
    "mavg[-10:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2006-10-02         NaN\n",
       "2006-10-03   -0.010419\n",
       "2006-10-04    0.017549\n",
       "2006-10-05   -0.007296\n",
       "2006-10-06   -0.008152\n",
       "Name: Adj Close, dtype: float64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rets = close_px / close_px.shift(1) - 1\n",
    "rets.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ou encore .pct_change()."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2006-10-02         NaN\n",
       "2006-10-03   -0.010419\n",
       "2006-10-04    0.017549\n",
       "2006-10-05   -0.007296\n",
       "2006-10-06   -0.008152\n",
       "Name: Adj Close, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "close_px.pct_change().head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color=\"#084B8A\">Tracés Basiques</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Les series et les DataFrames ont une commande commune .plot() (utilise Matplotlib en fait)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x104ca4860>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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PgauGYXyilJoAVDUMI8fAKQm4QghhX926wbRp1osXAFxOuEzLOS258toVnByd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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109551978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "close_px.plot(label='AAPL')\n",
    "mavg.plot(label='mavg')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## <font color=\"#084B8A\">Facultatif : Si on a du temps ... </font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>GE</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>IBM</th>\n",
       "      <th>KO</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>PEP</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>28.313195</td>\n",
       "      <td>12.556963</td>\n",
       "      <td>313.062468</td>\n",
       "      <td>115.385996</td>\n",
       "      <td>23.689561</td>\n",
       "      <td>26.227603</td>\n",
       "      <td>50.953113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>28.362145</td>\n",
       "      <td>12.621983</td>\n",
       "      <td>311.683844</td>\n",
       "      <td>113.992138</td>\n",
       "      <td>23.402993</td>\n",
       "      <td>26.236076</td>\n",
       "      <td>51.568809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>27.911008</td>\n",
       "      <td>12.556963</td>\n",
       "      <td>303.826685</td>\n",
       "      <td>113.251641</td>\n",
       "      <td>23.394688</td>\n",
       "      <td>26.075067</td>\n",
       "      <td>51.052955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>27.859412</td>\n",
       "      <td>13.207162</td>\n",
       "      <td>296.753749</td>\n",
       "      <td>112.859619</td>\n",
       "      <td>23.336543</td>\n",
       "      <td>25.803894</td>\n",
       "      <td>50.728467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>28.044630</td>\n",
       "      <td>13.491624</td>\n",
       "      <td>300.709808</td>\n",
       "      <td>113.992138</td>\n",
       "      <td>22.904616</td>\n",
       "      <td>25.981851</td>\n",
       "      <td>50.562061</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 AAPL         GE        GOOG         IBM         KO  \\\n",
       "Date                                                                  \n",
       "2010-01-04  28.313195  12.556963  313.062468  115.385996  23.689561   \n",
       "2010-01-05  28.362145  12.621983  311.683844  113.992138  23.402993   \n",
       "2010-01-06  27.911008  12.556963  303.826685  113.251641  23.394688   \n",
       "2010-01-07  27.859412  13.207162  296.753749  112.859619  23.336543   \n",
       "2010-01-08  28.044630  13.491624  300.709808  113.992138  22.904616   \n",
       "\n",
       "                 MSFT        PEP  \n",
       "Date                              \n",
       "2010-01-04  26.227603  50.953113  \n",
       "2010-01-05  26.236076  51.568809  \n",
       "2010-01-06  26.075067  51.052955  \n",
       "2010-01-07  25.803894  50.728467  \n",
       "2010-01-08  25.981851  50.562061  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.io.data.get_data_yahoo(['AAPL', 'GE', 'GOOG', 'IBM', 'KO', 'MSFT', 'PEP'], \n",
    "                               start=datetime.datetime(2010, 1, 1), \n",
    "                               end=datetime.datetime(2013, 1, 1))['Adj Close']\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "rets = df.pct_change()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x109372400>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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paQGwimSBni6amp4vYYuidABX0dBwC6+//jqjo6fjVggkrziPHt3uHbvVu/Uy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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x103316d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(rets.PEP, rets.KO)\n",
    "plt.xlabel('Returns PEP')\n",
    "plt.ylabel('Returns KO')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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uQymDpqZKfL6PAEfw+wf47GcfIz6+nRdffIe2tlgMYxhIwOMpmLAHZggzJffj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JBLOQKzOEEEIIwYNf/xp27YLbblNZqiGEEEIIC42QYBZCCCGEgKq59nd/B4WFqv7cL3+52CMK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\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Fhc20tweqsR16CDZ/iooO8vrrJzh7VhIVpScrK4be3lu97nDfunGrV+fz1FM/pKVlPi5X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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109318cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.scatter_matrix(rets, diagonal='kde', figsize=(10, 10));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>GE</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>IBM</th>\n",
       "      <th>KO</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>PEP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAPL</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.457052</td>\n",
       "      <td>0.533387</td>\n",
       "      <td>0.501587</td>\n",
       "      <td>0.388007</td>\n",
       "      <td>0.472767</td>\n",
       "      <td>0.308964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GE</th>\n",
       "      <td>0.457052</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.462696</td>\n",
       "      <td>0.609330</td>\n",
       "      <td>0.593856</td>\n",
       "      <td>0.600065</td>\n",
       "      <td>0.533503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GOOG</th>\n",
       "      <td>0.533387</td>\n",
       "      <td>0.462696</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.470778</td>\n",
       "      <td>0.404099</td>\n",
       "      <td>0.472851</td>\n",
       "      <td>0.329938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IBM</th>\n",
       "      <td>0.501587</td>\n",
       "      <td>0.609330</td>\n",
       "      <td>0.470778</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.601483</td>\n",
       "      <td>0.646124</td>\n",
       "      <td>0.491088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KO</th>\n",
       "      <td>0.388007</td>\n",
       "      <td>0.593856</td>\n",
       "      <td>0.404099</td>\n",
       "      <td>0.601483</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.523480</td>\n",
       "      <td>0.635843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSFT</th>\n",
       "      <td>0.472767</td>\n",
       "      <td>0.600065</td>\n",
       "      <td>0.472851</td>\n",
       "      <td>0.646124</td>\n",
       "      <td>0.523480</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.477424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PEP</th>\n",
       "      <td>0.308964</td>\n",
       "      <td>0.533503</td>\n",
       "      <td>0.329938</td>\n",
       "      <td>0.491088</td>\n",
       "      <td>0.635843</td>\n",
       "      <td>0.477424</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          AAPL        GE      GOOG       IBM        KO      MSFT       PEP\n",
       "AAPL  1.000000  0.457052  0.533387  0.501587  0.388007  0.472767  0.308964\n",
       "GE    0.457052  1.000000  0.462696  0.609330  0.593856  0.600065  0.533503\n",
       "GOOG  0.533387  0.462696  1.000000  0.470778  0.404099  0.472851  0.329938\n",
       "IBM   0.501587  0.609330  0.470778  1.000000  0.601483  0.646124  0.491088\n",
       "KO    0.388007  0.593856  0.404099  0.601483  1.000000  0.523480  0.635843\n",
       "MSFT  0.472767  0.600065  0.472851  0.646124  0.523480  1.000000  0.477424\n",
       "PEP   0.308964  0.533503  0.329938  0.491088  0.635843  0.477424  1.000000"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr = rets.corr()\n",
    "corr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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aYCVJnTFJ12AtEUuSdhpJViS5PMkVSU4e0u8Pk2xO8rz5HjvNDFaS1BltloiT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\nzEj9Q0uEwJ4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109b05780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(corr, cmap='hot', interpolation='none')\n",
    "plt.colorbar()\n",
    "plt.xticks(range(len(corr)), corr.columns)\n",
    "plt.yticks(range(len(corr)), corr.columns);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Une chose à la quelle nous nous intéressons souvent est la relation entre les rendements attendus et le risque que nous prenons. Souvent, il y a un compromis entre les deux.\n",
    "\n",
    "Ici, nous utilisons plt.annotate de mettre des étiquettes sur le nuage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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GESNG0qlTp3yfVNIOaOhJitsMCBFxd0rp3FrWQwDY7ddBMCBoT5VSYt26dWzY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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10cd78438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(rets.mean(), rets.std())\n",
    "plt.xlabel('Expected returns')\n",
    "plt.ylabel('Risk')\n",
    "for label, x, y in zip(rets.columns, rets.mean(), rets.std()):\n",
    "    plt.annotate(\n",
    "        label, \n",
    "        xy = (x, y), xytext = (20, -20),\n",
    "        textcoords = 'offset points', ha = 'right', va = 'bottom',\n",
    "        bbox = dict(boxstyle = 'round,pad=0.5', fc = 'yellow', alpha = 0.5),\n",
    "        arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color=\"#084B8A\">L'alignement des données et le traitement des valeurs manquantes</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Join, merge, concatenate\n",
    "- Remplissage des NaNs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Permet de tirer quelques titres de Yahoo finance et construire un dataframe des cours de clôture ajustés ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "series_list = []\n",
    "securities = ['AAPL', 'GOOG', 'IBM', 'MSFT']\n",
    "for security in securities:\n",
    "    s = pd.io.data.get_data_yahoo(security, start=datetime.datetime(2011, 10, 1), end=datetime.datetime(2013, 1, 1))['Adj Close']\n",
    "    s.name = security # Renomme les séries de sorte que cela coincide avec les noms de la liste securities\n",
    "    series_list.append(s)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "pd.concat peut être utilisé pour concaténer plusieurs Series en un seul dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>IBM</th>\n",
       "      <th>MSFT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
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       "      <td>250.699734</td>\n",
       "      <td>157.132258</td>\n",
       "      <td>22.335007</td>\n",
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      ],
      "text/plain": [
       "                 AAPL        GOOG         IBM       MSFT\n",
       "Date                                                    \n",
       "2011-10-03  49.559007  247.512918  155.828357  21.621063\n",
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       "2011-10-07  48.923974  257.303137  164.011397  23.137092"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.concat(series_list, axis=1)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "      <th>AAPL</th>\n",
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      "text/plain": [
       "                 AAPL        GOOG         IBM       MSFT\n",
       "Date                                                    \n",
       "2011-10-03        NaN  247.512918  155.828357  21.621063\n",
       "2011-10-04  49.281181         NaN         NaN        NaN\n",
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       "2011-10-07  48.923974  257.303137  164.011397  23.137092"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.ix[0, 'AAPL'] = np.nan\n",
    "df.ix[1, ['GOOG', 'IBM']] = np.nan\n",
    "df.ix[[1, 2, 3], 'MSFT'] = np.nan\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pandas supporte bien les calculs avec des valeurs manquantes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2011-10-03           NaN\n",
       "2011-10-04           NaN\n",
       "2011-10-05    302.140236\n",
       "2011-10-06    307.023825\n",
       "2011-10-07    306.227111\n",
       "dtype: float64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df.AAPL + df.GOOG).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Une approche générale pour imputer les valeurs manquantes dans les séries chronologiques est le remplissage forward (forward filling)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "      <th>AAPL</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>IBM</th>\n",
       "      <th>MSFT</th>\n",
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      "text/plain": [
       "                 AAPL        GOOG         IBM       MSFT\n",
       "Date                                                    \n",
       "2011-10-03        NaN  247.512918  155.828357  21.621063\n",
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       "2011-10-06  49.925473  257.098352  163.381935  21.621063\n",
       "2011-10-07  48.923974  257.303137  164.011397  23.137092"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.ffill().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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