{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 01-Les bases de Research avec Quantopian\n",
"\n",
"**N'oubliez pas que ce notebook ne fonctionnera que sur Quantopian ! Créez un compte et téléversez (upload) le fichier de ce notebook. Ces commandes et fonctions ne fonctionneront que sur la plateforme de trading Quantopian !**\n",
"\n",
"Notez qu'une grande partie du texte écrit dans ce notebook en Markdown provient directement des documents et tutoriels Quantopian, regardez les bien aussi, ils sont bien faits !\n",
"\n",
"## Research\n",
"\n",
"Le format notebook nous permet de rassembler facilement les informations sur les différents titres au sein de la plateforme Quantopian. Il faut garder à l'esprit que cela est différent de la plateforme de codage de base de Quantopian, qui se concentre sur la mise en œuvre effective et le backtesting des stratégies de trading."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"# PAS BESOIN D'UTILISER LA COMMANDE MAGIQUE SUR QUANTOPIAN !"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"## Obtenir des informations\n",
"\n",
"Passons en revue quelques fonctions clés :\n",
"\n",
"* get_pricing()\n",
"* symbols()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## get_pricing()\n",
"\n",
"La fonction `get_pricing` permet d'accéder à 12 ans de données sur le prix des actions américaines : les mêmes données que celles utilisées par le backtester Quantopian.\n",
"\n",
"`get_pricing` retourne un objet Pandas. Il peut s'agir d'un dataframe ou d'une série, selon les valeurs d'entrée. "
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"mcdon = get_pricing('MCD',\n",
" start_date='2017-01-01', \n",
" end_date = '2017-02-01', \n",
" frequency='minute')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
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" \n",
" \n",
" | \n",
" open_price | \n",
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" | 2017-01-03 14:31:00+00:00 | \n",
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