YahooFinance_StockBreakouts_Backtester.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Python Function for Stock Breakouts Backtester\n",
        "\n",
        "Prepared by Marvin Rubia ([My LinkedIn](https://www.linkedin.com/in/marvinrubia08/))"
      ],
      "metadata": {
        "id": "Ih6Y3vLLcjOB"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Install yahoo-fin library"
      ],
      "metadata": {
        "id": "6FYLzi_Tg8uK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install yahoo-fin"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qy4zuw3iJbZt",
        "outputId": "03190999-f726-4831-97d2-02a4b43fa39d"
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          "text": [
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          ]
        }
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    },
    {
      "cell_type": "markdown",
      "source": [
        "## Code the breakout backtesting function"
      ],
      "metadata": {
        "id": "-gKHb9nVhCX5"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 85,
      "metadata": {
        "id": "pN51MPngKGqs"
      },
      "outputs": [],
      "source": [
        "def breakout_profitability(ticker):\n",
        "  '''A function that returns a histogram and probabilistic information for all breakouts of a stock using its historical daily prices'''\n",
        "\n",
        "  # Import libraries\n",
        "  from yahoo_fin.stock_info import get_data\n",
        "  import pandas as pd\n",
        "  import numpy as np\n",
        "  import seaborn as sns\n",
        "  import matplotlib.pyplot as plt\n",
        "\n",
        "  ## PREPARE OUR DATAFRAME FOR ANALYSIS\n",
        "  # Get the historical weekly prices from the specified start date and end date (both YYYY-mm-dd)\n",
        "  hist = get_data(ticker, index_as_date=False)\n",
        "\n",
        "  # Drop the adjusted close column\n",
        "  prices = hist.drop(['adjclose'], axis=1)\n",
        "\n",
        "  # Get the selling pressure, which is distance between high and close\n",
        "  prices['SellingPressure'] = prices['high'] - prices['close']\n",
        "\n",
        "  # Get the length of candle's body (from open to close)\n",
        "  prices['O-to-C'] = prices['close'] - prices['open']\n",
        "\n",
        "  # Get the rolling mean of the candle's body for recent 20 candles\n",
        "  prices['OC-20D-Mean'] = prices['O-to-C'].rolling(20).mean()\n",
        "\n",
        "  # Get the % increase or decrease of the current body length from the rolling mean\n",
        "  prices['OC-%-from-20D-Mean'] = 100*(prices['O-to-C'] - prices['OC-20D-Mean'])/prices['OC-20D-Mean']\n",
        "\n",
        "  # Get the maximum OC compared to the recent 10 candles\n",
        "  prices['MaxOC_Prev10'] = prices['O-to-C'].rolling(10).max()\n",
        "\n",
        "  # Get the rolling mean of volume for the recent 20 candles\n",
        "  prices['Volume-20D-Mean'] = prices['volume'].rolling(20).mean()\n",
        "\n",
        "  # Get the % increase or decrease of the current volume from the rolling mean\n",
        "  prices['Volume-%-from-20D-Mean'] = 100*(prices['volume'] - prices['Volume-20D-Mean'])/prices['Volume-20D-Mean']\n",
        "\n",
        "  # Drop the null values for the first 19 rows, where no mean can be computed yet.\n",
        "  prices = prices.dropna()\n",
        "\n",
        "  # Rearrange columns\n",
        "  prices = prices[['ticker', 'date', 'open', 'high', 'low', 'close',\n",
        "                   'O-to-C', 'OC-20D-Mean', 'volume', 'Volume-20D-Mean',\n",
        "                   'MaxOC_Prev10', 'SellingPressure', 'OC-%-from-20D-Mean',\n",
        "                   'Volume-%-from-20D-Mean',\n",
        "                  ]]\n",
        "\n",
        "  # Select the subset of dataframe where breakout conditions apply\n",
        "  # Conditions: 1. green candle, 2. candle's body is longest in 10 days,\n",
        "  # 3. breakout volume is 50% higher than the rolling 20-day average, and\n",
        "  # 4. breakout candle has body that is 100% higher than the rolling 20-day average\n",
        "\n",
        "  condition = (prices['O-to-C'] > 0.0) & (prices['O-to-C'] == prices['MaxOC_Prev10']) & (prices['OC-%-from-20D-Mean'] >= 100.0) & (prices['SellingPressure']/prices['O-to-C'] <= 0.40) & (prices['Volume-%-from-20D-Mean'] >= 50.0)\n",
        "\n",
        "  breakouts = prices[condition]\n",
        "\n",
        "  ## GET THE PROFIT (OR LOSS) PER CANDLE\n",
        "  # Get the index (from the dataframe) of each breakout row, which is necessary for looping later\n",
        "  breakouts_indices = breakouts.index.tolist()\n",
        "\n",
        "  profits = []\n",
        "  for index in breakouts_indices:\n",
        "    # For a given breakout candle index, slice the historical prices dataframe 10 rows RIGHT AFTER the breakout row\n",
        "    ten_rows_after_a_breakout = prices.iloc[index+1:index+11]\n",
        "\n",
        "    # Compute the highest price within the next 10 days RIGHT AFTER the breakout candle\n",
        "    highest_price_within10days = ten_rows_after_a_breakout['high'].max()\n",
        "\n",
        "    # Compute the lowest price within the next 10 days RIGHT AFTER the breakout candle\n",
        "    lowest_price_within10days = ten_rows_after_a_breakout['low'].min()\n",
        "\n",
        "    # Get the row index corresponding for the highest_price_within10days\n",
        "    highest_price_index = ten_rows_after_a_breakout[ten_rows_after_a_breakout['high'] == highest_price_within10days].index[0]\n",
        "\n",
        "    # Get the row index corresponding for the lowest_price_within10days\n",
        "    lowest_price_index = ten_rows_after_a_breakout[ten_rows_after_a_breakout['low'] == lowest_price_within10days].index[0]\n",
        "\n",
        "    # Calculate our Buy Price, which is the breakout candle's close\n",
        "    breakout_close = breakouts.loc[index, 'close']\n",
        "\n",
        "    # Calculate our Stop Loss Price, which is the breakout candle's open\n",
        "    breakout_open = breakouts.loc[index, 'open']\n",
        "\n",
        "    ## GET THE PROFITS:\n",
        "    # If lowest_price_index is lower (or earlier) than highest_price_index, then we sold at stop loss before reaching the highest_price_within10days\n",
        "    # This counts as negative profit (a loss)\n",
        "\n",
        "    # If highest_price_index is lower (or earlier) than the lowest_price_index, this should count as a win\n",
        "    # This means we were able to exit with a profit before the stock goes to the stop loss within 10 days\n",
        "\n",
        "    if lowest_price_within10days <= breakout_open:\n",
        "      if highest_price_index < lowest_price_index:\n",
        "        profit = round(100*(highest_price_within10days - breakout_close)/breakout_close, 2)\n",
        "        profits.append(profit)\n",
        "\n",
        "      elif lowest_price_index <= highest_price_index:\n",
        "        profit = round(100*(breakout_open - breakout_close)/breakout_close, 2)\n",
        "        profits.append(profit)\n",
        "\n",
        "    else:\n",
        "      profit = round(100*(highest_price_within10days - breakout_close)/breakout_close, 2)\n",
        "      profits.append(profit)\n",
        "\n",
        "  ## GET PROFIT PER TYPE TO CALCULATE SOME PROBABILITIES\n",
        "  wins = []\n",
        "  breakevens = []\n",
        "  losses = []\n",
        "  for profit in profits:\n",
        "    if profit > 0.0:\n",
        "      wins.append(profit)\n",
        "    elif profit == 0.0:\n",
        "      breakevens.append(profit)\n",
        "    elif profit < 0.0:\n",
        "      losses.append(profit)\n",
        "\n",
        "  # Calculate some trading probabilities\n",
        "  win_rate = round(100*len(wins)/len(profits), 2)\n",
        "  breakeven_rate = round(100*len(breakevens)/len(profits), 2)\n",
        "  loss_rate = round(100*len(losses)/len(profits), 2)\n",
        "\n",
        "  ave_positive_profit = round(sum(wins)/len(wins), 2)\n",
        "  ave_negative_profit = round(sum(losses)/len(losses), 2)\n",
        "\n",
        "  # VISUALIZE DISTRIBUTION OF PROFITS\n",
        "  sns.histplot(pd.Series(profits), bins=20)\n",
        "  plt.title(f\"Distribution of Breakout Profits for {ticker.upper()}\")\n",
        "  plt.text(0.95, 0.95, f\"Total Breakouts: {len(profits)} \\n Ave. Positive Profit: {ave_positive_profit}% \\n Ave. Negative Profit: {ave_negative_profit}% \\n Win Rate: {win_rate}% \\n Loss Rate: {loss_rate}% \\n Breakeven Rate: {breakeven_rate}%\",\n",
        "           ha='right', va='top', transform=plt.gca().transAxes)\n",
        "  plt.ylabel('Number of Breakouts')\n",
        "  plt.xlabel('Profit (%)')\n",
        "  plt.show()\n",
        "\n",
        "  # Supply other information, in addition to the chart, for the output\n",
        "  # NOTE: breakout_dates are in timestamp, so we have to convert to date format\n",
        "  breakout_dates = pd.to_datetime(breakouts['date'])\n",
        "  earliest_breakout = breakout_dates.min().strftime('%Y-%m-%d')\n",
        "  latest_breaktout = breakout_dates.max().strftime('%Y-%m-%d')\n",
        "\n",
        "  supplementary_info = f\"Additional Info: The first breakout for {ticker} was observed on {earliest_breakout} while the most recent breakout was on {latest_breaktout}. The holding period for each breakout trade is maximum of 10 days.\"\n",
        "\n",
        "  return supplementary_info"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Use the `breakout_profitability()` function"
      ],
      "metadata": {
        "id": "rJZQXfdahLzb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "breakout_profitability('GOOGL')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "id": "IvqneCOyKY9w",
        "outputId": "099d03ad-be98-4ad0-8b23-35bde806dbb4"
      },
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Additional Info: The first breakout for GOOGL was observed on 2004-09-28 while the most recent breakout was on 2023-05-10. The holding period for each breakout trade is maximum of 10 days.'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 86
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "breakout_profitability('AAPL')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "id": "aVAD9PQsJX6O",
        "outputId": "fecf8dea-c9b6-459b-817b-b54a052a28d9"
      },
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Additional Info: The first breakout for AAPL was observed on 1982-10-06 while the most recent breakout was on 2022-10-28. The holding period for each breakout trade is maximum of 10 days.'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 87
        }
      ]
    }
  ]
}