memonkey01/grafico_velas.ipynb

## grafico_velas.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Gráficos de Velas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Autor: Guillermo Izquierdo  \n",
    "Este código es para fines educativos exclusivamente  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "El funcionamiento es básico, cada vela puede ser roja(negra) (el precio de una acción , futuro, índice o divisa ha caído) o verde(blanca) (el precio ha subido respecto al inicio de esa misma vela), un rectángulo (cuerpo de la vela, cuerpo real) nos indica la variación desde la apertura al cierre, y una línea que lo cruza(sombra) nos indica el máximo y el mínimo."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![title](img/Ejemplo_Velas_Principal.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from pandas_datareader import data as pdr\n",
    "from mpl_finance import candlestick2_ochl\n",
    "import datetime as date\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "enddate = date.datetime(2018,11,1)\n",
    "startdate = date.datetime(2018,1,1)\n",
    "tick = '^MXX'\n",
    "ipc = pdr.get_data_yahoo(tick, start = startdate, end = enddate)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</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>2018-01-02</th>\n",
       "      <td>50083.019531</td>\n",
       "      <td>49328.601562</td>\n",
       "      <td>49376.261719</td>\n",
       "      <td>50033.949219</td>\n",
       "      <td>103387800</td>\n",
       "      <td>50033.949219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03</th>\n",
       "      <td>50093.308594</td>\n",
       "      <td>49735.910156</td>\n",
       "      <td>50093.308594</td>\n",
       "      <td>49782.230469</td>\n",
       "      <td>140912700</td>\n",
       "      <td>49782.230469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-04</th>\n",
       "      <td>50128.468750</td>\n",
       "      <td>49704.250000</td>\n",
       "      <td>49800.359375</td>\n",
       "      <td>49744.621094</td>\n",
       "      <td>177259000</td>\n",
       "      <td>49744.621094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-05</th>\n",
       "      <td>50079.031250</td>\n",
       "      <td>49712.539062</td>\n",
       "      <td>49929.519531</td>\n",
       "      <td>49887.738281</td>\n",
       "      <td>151467900</td>\n",
       "      <td>49887.738281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-08</th>\n",
       "      <td>50233.621094</td>\n",
       "      <td>49891.070312</td>\n",
       "      <td>49916.570312</td>\n",
       "      <td>49995.570312</td>\n",
       "      <td>145968200</td>\n",
       "      <td>49995.570312</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    High           Low          Open         Close     Volume  \\\n",
       "Date                                                                            \n",
       "2018-01-02  50083.019531  49328.601562  49376.261719  50033.949219  103387800   \n",
       "2018-01-03  50093.308594  49735.910156  50093.308594  49782.230469  140912700   \n",
       "2018-01-04  50128.468750  49704.250000  49800.359375  49744.621094  177259000   \n",
       "2018-01-05  50079.031250  49712.539062  49929.519531  49887.738281  151467900   \n",
       "2018-01-08  50233.621094  49891.070312  49916.570312  49995.570312  145968200   \n",
       "\n",
       "               Adj Close  \n",
       "Date                      \n",
       "2018-01-02  50033.949219  \n",
       "2018-01-03  49782.230469  \n",
       "2018-01-04  49744.621094  \n",
       "2018-01-05  49887.738281  \n",
       "2018-01-08  49995.570312  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipc.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Ij0TEsYg4WpQ9IiJujYhPFn8bRXlExGsj4kREfDgivrPjfXYXy38yInZ3lD+5eP8TxWtj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\n+FhnQUTsAC7oWu5ngWZmPh44AOwvln0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      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(16,8))\n",
    "ax1 = plt.subplot()\n",
    "candlestick2_ochl(ax1, ipc.Open, ipc.Close, ipc.High, ipc.Low, width=0.5, colorup='g', colordown='r', alpha=0.75)\n",
    "plt.grid(True)\n",
    "fig.autofmt_xdate()\n",
    "plt.title('Gráfico de Velas del IPC')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Patrones comunes en gráficos de velas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![title](img/doji.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "El **Doji** es un tipo de vela que refleja indecisión en el mercado por parte de los inversionistas, estos no definen el inicio o final de una tendencia, más bien representa incertidumbre en el mercado. Aunque se encuentran en el techo de una tendencia alcista o en el piso de una tendencia bajista, podrían dar indicios de que el siguiente movimiento será en dirección contraria o solo un descanso en la tendencia, es importante conocer el comportamiento de la vela que se presente al siguiente día."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![title](img/dragonfly-doji.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "El **doji Dragonfly** es un poderoso indicador de reversión y apunta a grandes movimientos por delante.\n",
    "La apertura y el cierre de la vela están en o cerca del máximo del día. La sombra puede variar en longitud, pero suele ser bastante larga."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![title](img/hammer.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " La vela **Hammer** es uno de esos patrones de velas de doble sentido. Puede ser un patrón de inversión alcista, que ocurre cerca del mínimo de una tendencia. Pero también puede ocurrir durante la tendencia bajista."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![title](img/three-green-soldiers.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Este patrón de vela llamado **Tres Soldados** crea una escalera para precios más altos. Es un patrón de inversión alcista formado por tres velas.\n",
    "Las tres velas son verdes, cada vela consecutiva se abre dentro del cuerpo real de la vela anterior.\n",
    "El cierre de cada día lleva al mercado a nuevos máximos, lo que indica que una tendencia alcista está a punto de despegar."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "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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