10_SimpleMultipleStocks.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Simple Multiple Stocks"
      ],
      "metadata": {
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "options(warn=-1) #Ignore Warning"
      ],
      "outputs": [],
      "execution_count": 1,
      "metadata": {
        "collapsed": true,
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          "source_hidden": false,
          "outputs_hidden": false
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          "transient": {
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        "execution": {
          "iopub.status.busy": "2021-06-16T01:38:55.139Z",
          "iopub.execute_input": "2021-06-16T01:38:55.143Z",
          "iopub.status.idle": "2021-06-16T01:38:55.147Z",
          "shell.execute_reply": "2021-06-16T01:38:55.117Z"
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "library(quantmod)"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Loading required package: xts\n",
            "Loading required package: zoo\n",
            "\n",
            "Attaching package: 'zoo'\n",
            "\n",
            "The following objects are masked from 'package:base':\n",
            "\n",
            "    as.Date, as.Date.numeric\n",
            "\n",
            "Loading required package: TTR\n",
            "Registered S3 method overwritten by 'quantmod':\n",
            "  method            from\n",
            "  as.zoo.data.frame zoo \n"
          ]
        }
      ],
      "execution_count": 2,
      "metadata": {
        "collapsed": true,
        "jupyter": {
          "source_hidden": false,
          "outputs_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        },
        "execution": {
          "iopub.status.busy": "2021-06-16T01:38:55.152Z",
          "iopub.execute_input": "2021-06-16T01:38:55.155Z",
          "iopub.status.idle": "2021-06-16T01:38:55.170Z",
          "shell.execute_reply": "2021-06-16T01:38:55.129Z"
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Create new environment\n",
        "data_env <- new.env()\n",
        "# Use getSymbols to load data into the environment\n",
        "getSymbols(c(\"AAPL\", \"AMD\", \"INTC\", \"MSFT\"), env = data_env, auto.assign = TRUE)\n"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "'getSymbols' currently uses auto.assign=TRUE by default, but will\n",
            "use auto.assign=FALSE in 0.5-0. You will still be able to use\n",
            "'loadSymbols' to automatically load data. getOption(\"getSymbols.env\")\n",
            "and getOption(\"getSymbols.auto.assign\") will still be checked for\n",
            "alternate defaults.\n",
            "\n",
            "This message is shown once per session and may be disabled by setting \n",
            "options(\"getSymbols.warning4.0\"=FALSE). See ?getSymbols for details.\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": "<style>\n.list-inline {list-style: none; margin:0; padding: 0}\n.list-inline>li {display: inline-block}\n.list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n</style>\n<ol class=list-inline><li>'AAPL'</li><li>'AMD'</li><li>'INTC'</li><li>'MSFT'</li></ol>\n",
            "text/markdown": "1. 'AAPL'\n2. 'AMD'\n3. 'INTC'\n4. 'MSFT'\n\n\n",
            "text/latex": "\\begin{enumerate*}\n\\item 'AAPL'\n\\item 'AMD'\n\\item 'INTC'\n\\item 'MSFT'\n\\end{enumerate*}\n",
            "text/plain": "[1] \"AAPL\" \"AMD\"  \"INTC\" \"MSFT\""
          },
          "metadata": {}
        }
      ],
      "execution_count": 3,
      "metadata": {
        "collapsed": true,
        "jupyter": {
          "source_hidden": false,
          "outputs_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        },
        "execution": {
          "iopub.status.busy": "2021-06-16T01:38:55.174Z",
          "iopub.execute_input": "2021-06-16T01:38:55.178Z",
          "iopub.status.idle": "2021-06-16T01:38:57.204Z",
          "shell.execute_reply": "2021-06-16T01:38:57.278Z"
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "head(data_env$AAPL, 3)"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "           AAPL.Open AAPL.High AAPL.Low AAPL.Close AAPL.Volume AAPL.Adjusted\n2007-01-03  3.081786  3.092143 2.925000   2.992857  1238319600      2.573566\n2007-01-04  3.001786  3.069643 2.993571   3.059286   847260400      2.630688\n2007-01-05  3.063214  3.078571 3.014286   3.037500   834741600      2.611954"
          },
          "metadata": {}
        }
      ],
      "execution_count": 4,
      "metadata": {
        "collapsed": true,
        "jupyter": {
          "source_hidden": false,
          "outputs_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        },
        "execution": {
          "iopub.status.busy": "2021-06-16T01:38:57.209Z",
          "iopub.execute_input": "2021-06-16T01:38:57.212Z",
          "shell.execute_reply": "2021-06-16T01:38:57.282Z",
          "iopub.status.idle": "2021-06-16T01:38:57.222Z"
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "eapply(data_env, head)"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "$AAPL\n           AAPL.Open AAPL.High AAPL.Low AAPL.Close AAPL.Volume AAPL.Adjusted\n2007-01-03  3.081786  3.092143 2.925000   2.992857  1238319600      2.573566\n2007-01-04  3.001786  3.069643 2.993571   3.059286   847260400      2.630688\n2007-01-05  3.063214  3.078571 3.014286   3.037500   834741600      2.611954\n2007-01-08  3.070000  3.090357 3.045714   3.052500   797106800      2.624853\n2007-01-09  3.087500  3.320714 3.041071   3.306071  3349298400      2.842900\n2007-01-10  3.383929  3.492857 3.337500   3.464286  2952880000      2.978950\n\n$AMD\n           AMD.Open AMD.High AMD.Low AMD.Close AMD.Volume AMD.Adjusted\n2007-01-03    20.08    20.40   19.35     19.52   28350300        19.52\n2007-01-04    19.66    19.86   19.32     19.79   23652500        19.79\n2007-01-05    19.54    19.91   19.54     19.71   15902400        19.71\n2007-01-08    19.71    19.86   19.37     19.47   15814800        19.47\n2007-01-09    19.45    19.71   19.37     19.65   14494200        19.65\n2007-01-10    19.64    20.02   19.50     20.01   19783200        20.01\n\n$MSFT\n           MSFT.Open MSFT.High MSFT.Low MSFT.Close MSFT.Volume MSFT.Adjusted\n2007-01-03     29.91     30.25    29.40      29.86    76935100      21.91154\n2007-01-04     29.70     29.97    29.44      29.81    45774500      21.87483\n2007-01-05     29.63     29.75    29.45      29.64    44607200      21.75009\n2007-01-08     29.65     30.10    29.53      29.93    50220200      21.96289\n2007-01-09     30.00     30.18    29.73      29.96    44636600      21.98492\n2007-01-10     29.80     29.89    29.43      29.66    55017400      21.76477\n\n$INTC\n           INTC.Open INTC.High INTC.Low INTC.Close INTC.Volume INTC.Adjusted\n2007-01-03     20.45     20.88    20.14      20.35    69001200      13.29359\n2007-01-04     20.63     21.33    20.56      21.17    88902300      13.82926\n2007-01-05     21.09     21.15    20.76      21.10    64550800      13.78353\n2007-01-08     21.25     21.34    20.95      21.01    52839100      13.72473\n2007-01-09     21.18     21.21    20.86      21.03    54381000      13.73780\n2007-01-10     21.09     21.62    21.03      21.52    76346900      14.05790\n"
          },
          "metadata": {}
        }
      ],
      "execution_count": 5,
      "metadata": {
        "collapsed": true,
        "jupyter": {
          "source_hidden": false,
          "outputs_hidden": false
        },
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          "transient": {
            "deleting": false
          }
        },
        "execution": {
          "iopub.status.busy": "2021-06-16T01:38:57.227Z",
          "iopub.execute_input": "2021-06-16T01:38:57.231Z",
          "iopub.status.idle": "2021-06-16T01:38:57.239Z",
          "shell.execute_reply": "2021-06-16T01:38:57.286Z"
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Call head on each object in data_env using eapply\n",
        "data_list <- eapply(data_env, head)"
      ],
      "outputs": [],
      "execution_count": 6,
      "metadata": {
        "collapsed": true,
        "jupyter": {
          "source_hidden": false,
          "outputs_hidden": false
        },
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            "deleting": false
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        "execution": {
          "iopub.status.busy": "2021-06-16T01:38:57.244Z",
          "iopub.execute_input": "2021-06-16T01:38:57.248Z",
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          "shell.execute_reply": "2021-06-16T01:38:57.288Z"
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Merge all the list elements into one xts object\n",
        "data_merged <- do.call(merge, data_list)\n"
      ],
      "outputs": [],
      "execution_count": 7,
      "metadata": {
        "collapsed": true,
        "jupyter": {
          "source_hidden": false,
          "outputs_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        },
        "execution": {
          "shell.execute_reply": "2021-06-16T01:38:57.292Z",
          "iopub.status.busy": "2021-06-16T01:38:57.262Z",
          "iopub.execute_input": "2021-06-16T01:38:57.266Z",
          "iopub.status.idle": "2021-06-16T01:38:57.302Z"
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data_ohlc <- OHLC(data_merged)\n",
        "data_ohlc"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "           AAPL.Open AMD.Open MSFT.Open INTC.Open AAPL.High AMD.High MSFT.High\n2007-01-03  3.081786    20.08     29.91     20.45  3.092143    20.40     30.25\n2007-01-04  3.001786    19.66     29.70     20.63  3.069643    19.86     29.97\n2007-01-05  3.063214    19.54     29.63     21.09  3.078571    19.91     29.75\n2007-01-08  3.070000    19.71     29.65     21.25  3.090357    19.86     30.10\n2007-01-09  3.087500    19.45     30.00     21.18  3.320714    19.71     30.18\n2007-01-10  3.383929    19.64     29.80     21.09  3.492857    20.02     29.89\n           INTC.High AAPL.Low AMD.Low MSFT.Low INTC.Low AAPL.Close AMD.Close\n2007-01-03     20.88 2.925000   19.35    29.40    20.14   2.992857     19.52\n2007-01-04     21.33 2.993571   19.32    29.44    20.56   3.059286     19.79\n2007-01-05     21.15 3.014286   19.54    29.45    20.76   3.037500     19.71\n2007-01-08     21.34 3.045714   19.37    29.53    20.95   3.052500     19.47\n2007-01-09     21.21 3.041071   19.37    29.73    20.86   3.306071     19.65\n2007-01-10     21.62 3.337500   19.50    29.43    21.03   3.464286     20.01\n           MSFT.Close INTC.Close\n2007-01-03      29.86      20.35\n2007-01-04      29.81      21.17\n2007-01-05      29.64      21.10\n2007-01-08      29.93      21.01\n2007-01-09      29.96      21.03\n2007-01-10      29.66      21.52"
          },
          "metadata": {}
        }
      ],
      "execution_count": 8,
      "metadata": {
        "collapsed": true,
        "jupyter": {
          "source_hidden": false,
          "outputs_hidden": false
        },
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          "transient": {
            "deleting": false
          }
        },
        "execution": {
          "iopub.status.busy": "2021-06-16T01:38:57.307Z",
          "iopub.execute_input": "2021-06-16T01:38:57.312Z",
          "iopub.status.idle": "2021-06-16T01:38:57.319Z",
          "shell.execute_reply": "2021-06-16T01:38:57.294Z"
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Extract volume column from each object\n",
        "adjusted_list <- lapply(data_env, Ad)\n",
        "# Merge each list element into one object\n",
        "adjusted <- do.call(merge, adjusted_list)\n",
        "head(adjusted)"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "           AAPL.Adjusted AMD.Adjusted MSFT.Adjusted INTC.Adjusted\n2007-01-03      2.573566        19.52      21.91154      13.29359\n2007-01-04      2.630688        19.79      21.87483      13.82926\n2007-01-05      2.611954        19.71      21.75009      13.78353\n2007-01-08      2.624853        19.47      21.96289      13.72473\n2007-01-09      2.842900        19.65      21.98492      13.73780\n2007-01-10      2.978950        20.01      21.76477      14.05790"
          },
          "metadata": {}
        }
      ],
      "execution_count": 9,
      "metadata": {
        "collapsed": true,
        "jupyter": {
          "source_hidden": false,
          "outputs_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        },
        "execution": {
          "iopub.status.busy": "2021-06-16T01:38:57.325Z",
          "iopub.execute_input": "2021-06-16T01:38:57.330Z",
          "iopub.status.idle": "2021-06-16T01:38:57.339Z",
          "shell.execute_reply": "2021-06-16T01:38:57.368Z"
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plot(adjusted)\n",
        "title(\"Stocks Adjusted Close\")\n",
        "legend(x=\"top\", legend=colnames(adjusted))"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "Plot with title \"Stocks Adjusted Close\"",
            "image/png": 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zUwAFKq4d2ANB5rLOugL+OdDa9P5t66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\na+2Exw1A2jIAQFpvl5M6ChnS99SJ4VyoFyNIfdcN9BSAJABS6QA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          },
          "metadata": {}
        }
      ],
      "execution_count": 10,
      "metadata": {
        "collapsed": true,
        "jupyter": {
          "source_hidden": false,
          "outputs_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        },
        "execution": {
          "iopub.status.busy": "2021-06-16T01:38:57.346Z",
          "iopub.execute_input": "2021-06-16T01:38:57.351Z",
          "iopub.status.idle": "2021-06-16T01:38:57.485Z",
          "shell.execute_reply": "2021-06-16T01:38:57.492Z"
        }
      }
    }
  ],
  "metadata": {
    "kernel_info": {
      "name": "python3"
    },
    "language_info": {
      "name": "R",
      "codemirror_mode": "r",
      "pygments_lexer": "r",
      "mimetype": "text/x-r-source",
      "file_extension": ".r",
      "version": "3.6.1"
    },
    "kernelspec": {
      "argv": [
        "C:/Users/Tin Hang/Anaconda3\\python.exe",
        "-m",
        "ipykernel_launcher",
        "-f",
        "{connection_file}"
      ],
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "nteract": {
      "version": "0.28.0"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}