Chapter_06_Scalping_using_price_action_strategy.ipynb

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      "name": "EN - AZ chapter 6: Scalping using price action strategy.ipynb",
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      "source": [
        "<p><img alt=\"Colaboratory logo\" height=\"45px\" src=\"https://www.quantreo.com/wp-content/uploads/2021/10/Original-on-Transparent.png\" align=\"left\" hspace=\"10px\" vspace=\"0px\"></p>\n",
        "\n",
        "# Scalping Price Action\n",
        "\n",
        "\n",
        "<br>\n",
        "\n",
        "\n",
        "📈Join our community: https://discord.gg/wXjNPAc5BH\n",
        "\n",
        "📚Read our book: https://www.amazon.com/gp/product/B09HG18CYL \n",
        "\n",
        "🖥️Quantreo's YouTube channel: https://www.youtube.com/channel/UCp7jckfiEglNf_Gj62VR0pw"
      ],
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          "text": [
            "Collecting yfinance\n",
            "  Downloading yfinance-0.1.70-py2.py3-none-any.whl (26 kB)\n",
            "Collecting requests>=2.26\n",
            "  Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB)\n",
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            "\u001b[?25hRequirement already satisfied: multitasking>=0.0.7 in /usr/local/lib/python3.7/dist-packages (from yfinance) (0.0.10)\n",
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            "  Downloading lxml-4.8.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl (6.4 MB)\n",
            "\u001b[K     |████████████████████████████████| 6.4 MB 43.4 MB/s \n",
            "\u001b[?25hRequirement already satisfied: pandas>=0.24.0 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.3.5)\n",
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            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (1.24.3)\n",
            "Installing collected packages: requests, lxml, yfinance\n",
            "  Attempting uninstall: requests\n",
            "    Found existing installation: requests 2.23.0\n",
            "    Uninstalling requests-2.23.0:\n",
            "      Successfully uninstalled requests-2.23.0\n",
            "  Attempting uninstall: lxml\n",
            "    Found existing installation: lxml 4.2.6\n",
            "    Uninstalling lxml-4.2.6:\n",
            "      Successfully uninstalled lxml-4.2.6\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "google-colab 1.0.0 requires requests~=2.23.0, but you have requests 2.27.1 which is incompatible.\n",
            "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\u001b[0m\n",
            "Successfully installed lxml-4.8.0 requests-2.27.1 yfinance-0.1.70\n",
            "Collecting mpl_finance\n",
            "  Downloading mpl_finance-0.10.1-py3-none-any.whl (8.4 kB)\n",
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            "Installing collected packages: mpl-finance\n",
            "Successfully installed mpl-finance-0.10.1\n",
            "Collecting ta\n",
            "  Downloading ta-0.9.0.tar.gz (25 kB)\n",
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            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas->ta) (1.15.0)\n",
            "Building wheels for collected packages: ta\n",
            "  Building wheel for ta (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for ta: filename=ta-0.9.0-py3-none-any.whl size=28908 sha256=f55c0eea5810bff0be1e76be1bd84ba0bdcb59c0f8ed846cb3d6e421c38fdb6b\n",
            "  Stored in directory: /root/.cache/pip/wheels/72/78/64/cc1c01506a1010a9845e9bd7c69333730f7174661228ea4f98\n",
            "Successfully built ta\n",
            "Installing collected packages: ta\n",
            "Successfully installed ta-0.9.0\n"
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        }
      ],
      "source": [
        "!pip install yfinance\n",
        "!pip install mpl_finance\n",
        "!pip install ta"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import yfinance as yf\n",
        "from mpl_finance import candlestick_ohlc\n",
        "import matplotlib.dates as mpl_dates\n",
        "import matplotlib.pyplot as plt\n",
        "import ta"
      ],
      "metadata": {
        "id": "6zdHfNUuY7ec"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# The code here will allow you to switch your graphics to dark mode for those who choose to code in dark mode\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "import matplotlib as mpl\n",
        "from matplotlib import cycler\n",
        "colors = cycler('color',\n",
        "                ['#669FEE', '#66EE91', '#9988DD',\n",
        "                 '#EECC55', '#88BB44', '#FFBBBB'])\n",
        "plt.rc('figure', facecolor='#313233')\n",
        "plt.rc('axes', facecolor=\"#313233\", edgecolor='none',\n",
        "       axisbelow=True, grid=True, prop_cycle=colors,\n",
        "       labelcolor='gray')\n",
        "plt.rc('grid', color='474A4A', linestyle='solid')\n",
        "plt.rc('xtick', color='gray')\n",
        "plt.rc('ytick', direction='out', color='gray')\n",
        "plt.rc('legend', facecolor=\"#313233\", edgecolor=\"#313233\")\n",
        "plt.rc(\"text\", color=\"#C9C9C9\")\n",
        "plt.rcParams['figure.figsize'] = [20, 8]"
      ],
      "metadata": {
        "id": "n3s_jX6hZbD_"
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      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Import the data"
      ],
      "metadata": {
        "id": "j5SHeb5qaXBo"
      }
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      "cell_type": "code",
      "source": [
        "# Import stock prices from Yahoo Finance\n",
        "df = yf.download(\"EURUSD=X\", start=\"2010-01-01\")\n",
        "\n",
        "# Create a Date column to plot the Candlestick later (Not mandatory if you don't want to plot the candlestick)\n",
        "df['Date'] = pd.to_datetime(df.index)\n",
        "df['Date'] = df['Date'].apply(mpl_dates.date2num)\n",
        "\n",
        "# Rename columns\n",
        "df.columns = [\"open\", \"high\", \"low\", \"close\", \"adj close\", \"volume\", \"date\"]\n",
        "df.index.name = \"time\"\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 467
        },
        "id": "Od_uOTNMZbq_",
        "outputId": "578c23ad-5dd3-4fa2-e593-2bfbc91cef98"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ]
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              "      <th>low</th>\n",
              "      <th>close</th>\n",
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              "      <th>2010-01-01</th>\n",
              "      <td>1.432706</td>\n",
              "      <td>1.440196</td>\n",
              "      <td>1.432706</td>\n",
              "      <td>1.438994</td>\n",
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              "      <td>733773.0</td>\n",
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              "      <th>2010-01-04</th>\n",
              "      <td>1.431004</td>\n",
              "      <td>1.445191</td>\n",
              "      <td>1.426208</td>\n",
              "      <td>1.442398</td>\n",
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              "      <td>733776.0</td>\n",
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              "      <th>2010-01-05</th>\n",
              "      <td>1.442710</td>\n",
              "      <td>1.448310</td>\n",
              "      <td>1.435194</td>\n",
              "      <td>1.436596</td>\n",
              "      <td>1.436596</td>\n",
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              "      <td>1.429123</td>\n",
              "      <td>1.440403</td>\n",
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              "      <td>733778.0</td>\n",
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              "      <th>2010-01-07</th>\n",
              "      <td>1.440300</td>\n",
              "      <td>1.444481</td>\n",
              "      <td>1.430206</td>\n",
              "      <td>1.431803</td>\n",
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              "      <th>2022-02-23</th>\n",
              "      <td>1.133055</td>\n",
              "      <td>1.135976</td>\n",
              "      <td>1.130736</td>\n",
              "      <td>1.132913</td>\n",
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              "      <td>738209.0</td>\n",
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              "      <th>2022-02-24</th>\n",
              "      <td>1.130595</td>\n",
              "      <td>1.130595</td>\n",
              "      <td>1.111049</td>\n",
              "      <td>1.130569</td>\n",
              "      <td>1.130569</td>\n",
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              "      <th>2022-02-25</th>\n",
              "      <td>1.119081</td>\n",
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            "text/plain": [
              "                open      high       low     close  adj close  volume      date\n",
              "time                                                                           \n",
              "2010-01-01  1.432706  1.440196  1.432706  1.438994   1.438994       0  733773.0\n",
              "2010-01-04  1.431004  1.445191  1.426208  1.442398   1.442398       0  733776.0\n",
              "2010-01-05  1.442710  1.448310  1.435194  1.436596   1.436596       0  733777.0\n",
              "2010-01-06  1.436596  1.443460  1.429123  1.440403   1.440403       0  733778.0\n",
              "2010-01-07  1.440300  1.444481  1.430206  1.431803   1.431803       0  733779.0\n",
              "...              ...       ...       ...       ...        ...     ...       ...\n",
              "2022-02-23  1.133055  1.135976  1.130736  1.132913   1.132913       0  738209.0\n",
              "2022-02-24  1.130595  1.130595  1.111049  1.130569   1.130569       0  738210.0\n",
              "2022-02-25  1.119081  1.126608  1.116807  1.119069   1.119069       0  738211.0\n",
              "2022-02-28  1.118105  1.124455  1.114318  1.118105   1.118105       0  738214.0\n",
              "2022-03-01  1.122208  1.122586  1.119445  1.121957   1.121957       0  738215.0\n",
              "\n",
              "[3168 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Support & Resistance building"
      ],
      "metadata": {
        "id": "qAOL072u54SZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Create empty columns \n",
        "df[\"support\"] = np.nan\n",
        "df[\"resistance\"] = np.nan\n",
        "\n",
        "# After 5 consequtive decrease of the low, we note this price as a support\n",
        "df.loc[(df[\"low\"].shift(5) > df[\"low\"].shift(4))&\n",
        "       (df[\"low\"].shift(4) > df[\"low\"].shift(3))&\n",
        "       (df[\"low\"].shift(3) > df[\"low\"].shift(2))&\n",
        "       (df[\"low\"].shift(2) > df[\"low\"].shift(1))&\n",
        "       (df[\"low\"].shift(1) > df[\"low\"].shift(0)), \"support\"] = df[\"low\"]\n",
        "\n",
        "\n",
        "# After 5 consequtive increase of the high, we note this price as a resistance\n",
        "df.loc[(df[\"high\"].shift(5) < df[\"high\"].shift(4)) &\n",
        "(df[\"high\"].shift(4) < df[\"high\"].shift(3)) &\n",
        "(df[\"high\"].shift(3) < df[\"high\"].shift(2)) &\n",
        "(df[\"high\"].shift(2) < df[\"high\"].shift(1)) &\n",
        "(df[\"high\"].shift(1) < df[\"high\"].shift(0)), \"resistance\"] = df[\"high\"]"
      ],
      "metadata": {
        "id": "H3BtMR2uaoKC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_bis = df.loc[\"2019\"]\n",
        "\n",
        "# Initialize the graph\n",
        "fig, ax = plt.subplots()\n",
        "\n",
        "# Plot the candlestick\n",
        "candlestick_ohlc(ax,df_bis[[\"date\", \"open\", \"high\", \"low\", \"close\"]].values,width=0.6, \\\n",
        "                  colorup='#57CE95', colordown='#CE5757', alpha=0.8)\n",
        "\n",
        "# Put date as the x axis\n",
        "date_format = mpl_dates.DateFormatter('%d %b %Y')\n",
        "ax.xaxis.set_major_formatter(date_format)\n",
        "fig.autofmt_xdate()\n",
        "fig.tight_layout()\n",
        "\n",
        "# Plot resistances lines\n",
        "for resistance, date in zip(df_bis[\"resistance\"].dropna(), df_bis[\"resistance\"].dropna().index):\n",
        "  plt.hlines(resistance, xmin=date, xmax=df_bis.index[-1], colors='#57CE95', linestyles=\":\", linewidth=3)\n",
        "\n",
        "# Plot supports lines\n",
        "for support, date in zip(df_bis[\"support\"].dropna(), df_bis[\"support\"].dropna().index):\n",
        "  plt.hlines(support, xmin=date, xmax=df_bis.index[-1], colors='#CE5757', linestyles=\":\", linewidth=3)\n",
        "\n",
        "# Show the figure\n",
        "fig.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 541
        },
        "id": "6yMjLIJdpXcy",
        "outputId": "f37a373e-7442-4f3d-f168-f92ed44dd913"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 1440x576 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.loc[\"2019\"]\n",
        "\n",
        "# Initialize the graph\n",
        "fig, ax = plt.subplots()\n",
        "\n",
        "# Plot the candlestick\n",
        "candlestick_ohlc(ax,df[[\"date\", \"open\", \"high\", \"low\", \"close\"]].values,width=0.6, \\\n",
        "                  colorup='#57CE95', colordown='#CE5757', alpha=0.8)\n",
        "\n",
        "# Put date as the x axis\n",
        "date_format = mpl_dates.DateFormatter('%d %b %Y')\n",
        "ax.xaxis.set_major_formatter(date_format)\n",
        "fig.autofmt_xdate()\n",
        "fig.tight_layout()\n",
        "\n",
        "# Plot resistances lines\n",
        "plt.plot(df[\"support\"].fillna(method=\"ffill\"),color='#CE5757', linestyle=\":\", linewidth=3)\n",
        "\n",
        "\n",
        "# Plot supports lines\n",
        "plt.plot(df[\"resistance\"].fillna(method=\"ffill\"),color='#57CE95', linestyle=\":\", linewidth=3)\n",
        "\n",
        "# Show the figure\n",
        "fig.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 604
        },
        "id": "LBPX8a_V83CD",
        "outputId": "106f2d11-bd86-4b2b-bd9b-2acd05a90f42"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x576 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Support & Resistance strategy"
      ],
      "metadata": {
        "id": "YR9r6nXM-lNM"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Create signal column\n",
        "df[\"signal\"] = 0\n",
        "\n",
        "# Smooth the support and resistance to create the strategy\n",
        "df[\"smooth resistance\"] = df[\"resistance\"].fillna(method=\"ffill\")\n",
        "df[\"smooth support\"] = df[\"support\"].fillna(method=\"ffill\")\n",
        "\n",
        "# Create buying conditions\n",
        "condition_1_buy = (df[\"close\"].shift(1) < df[\"smooth resistance\"].shift(1)) &\\\n",
        "                   (df[\"smooth resistance\"]*(1+0.0/100)<df[\"close\"])\n",
        "\n",
        "# Create selling conditions\n",
        "condition_1_sell = (df[\"close\"].shift(1) > df[\"smooth support\"].shift(1)) &\\\n",
        "                   (df[\"smooth support\"]*(1-0.0/100)>df[\"close\"])\n",
        "\n",
        "\n",
        "# Place the signals\n",
        "df.loc[condition_1_buy, \"signal\"] = 1\n",
        "df.loc[condition_1_sell, \"signal\"] = -1"
      ],
      "metadata": {
        "id": "gqITN0kDtuja"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "duration = 5\n",
        "\n",
        "# Compute the percentage of variation of the asset\n",
        "df[\"pct\"] = df[\"close\"].pct_change(1)\n",
        "\n",
        "# Compute the return of the strategy\n",
        "df[\"return\"] = np.array([df[\"pct\"].shift(i) for i in range(duration)]).sum(axis=0) * (df[\"signal\"].shift(duration))\n",
        "\n",
        "\n",
        "df[\"return\"].cumsum().plot(figsize=(15,8))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "id": "0wlxbBzyw6ZY",
        "outputId": "0a2ababc-6e81-47fc-b6db-1b584a886786"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fbc61479f90>"
            ]
          },
          "metadata": {},
          "execution_count": 34
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x576 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Support Resistance + SMA"
      ],
      "metadata": {
        "id": "J2MhnhPiNn_T"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Create Simple moving average 30 days\n",
        "df[\"SMA fast\"] = df[\"close\"].rolling(30).mean()\n",
        "\n",
        "# Create Simple moving average 60 days\n",
        "df[\"SMA slow\"] = df[\"close\"].rolling(60).mean()\n",
        "\n",
        "condition_2_buy = df[\"SMA fast\"] > df[\"SMA slow\"]\n",
        "condition_2_sell = df[\"SMA fast\"] < df[\"SMA slow\"]\n",
        "\n",
        "\n",
        "\n",
        "df[\"signal\"] = 0\n",
        "\n",
        "df.loc[condition_1_buy & condition_2_buy, \"signal\"] = 1\n",
        "df.loc[condition_1_sell & condition_2_sell, \"signal\"] = -1\n",
        "\n",
        "\n",
        "# Compute the percentage of variation of the asset\n",
        "df[\"pct\"] = df[\"close\"].pct_change(1)\n",
        "\n",
        "# Compute the return of the strategy\n",
        "df[\"return\"] = np.array([df[\"pct\"].shift(i) for i in range(duration)]).sum(axis=0) * (df[\"signal\"].shift(duration))\n",
        "\n",
        "df[\"return\"].cumsum().plot(figsize=(15,8))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "id": "BFXml2vsxG5e",
        "outputId": "9dd4f56f-47e0-486b-b7ee-c99f9b174399"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fbc61917390>"
            ]
          },
          "metadata": {},
          "execution_count": 41
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x576 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Support Resistance + SMA + RSI"
      ],
      "metadata": {
        "id": "gb_XC469NsPK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"rsi\"] = ta.momentum.RSIIndicator(df[\"close\"], window=10).rsi()\n",
        "\n",
        "# RSI yersteday\n",
        "df[\"rsi yersteday\"] = df[\"rsi\"].shift(1)\n",
        "\n",
        "df[\"signal\"] = 0\n",
        "condition_3_buy = df[\"rsi\"] < df[\"rsi yersteday\"]\n",
        "\n",
        "condition_3_sell = df[\"rsi\"] > df[\"rsi yersteday\"]\n",
        "\n",
        "\n",
        "\n",
        "df.loc[condition_1_buy & condition_2_buy & condition_3_buy, \"signal\"] = 1\n",
        "df.loc[condition_1_sell & condition_2_sell & condition_3_sell, \"signal\"] = -1\n",
        "\n",
        "\n",
        "# Compute the percentage of variation of the asset\n",
        "df[\"pct\"] = df[\"close\"].pct_change(1)\n",
        "\n",
        "# Compute the return of the strategy\n",
        "df[\"return\"] = np.array([df[\"pct\"].shift(i) for i in range(duration)]).sum(axis=0) * (df[\"signal\"].shift(duration))\n",
        "\n",
        "df[\"return\"].cumsum().plot(figsize=(15,8))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "id": "Mi-G_HgOxuBX",
        "outputId": "0d9825ea-2ec6-4979-af26-0fd684028594"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fbc5e4fd990>"
            ]
          },
          "metadata": {},
          "execution_count": 36
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x576 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Automate the process"
      ],
      "metadata": {
        "id": "rOr8_tv7NyHy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def support_resistance(df, duration=5,spread=0):\n",
        "  \"\"\"THE DATAFRAME NEEDS TO HAVE the following column names: high, low, close\"\"\"\n",
        "\n",
        "  # Support and resistance building\n",
        "  df[\"support\"] = np.nan\n",
        "  df[\"resistance\"] = np.nan\n",
        "\n",
        "  df.loc[(df[\"low\"].shift(5) > df[\"low\"].shift(4)) &\n",
        "        (df[\"low\"].shift(4) > df[\"low\"].shift(3)) &\n",
        "        (df[\"low\"].shift(3) > df[\"low\"].shift(2)) &\n",
        "        (df[\"low\"].shift(2) > df[\"low\"].shift(1)) &\n",
        "        (df[\"low\"].shift(1) > df[\"low\"].shift(0)), \"support\"] = df[\"low\"]\n",
        "\n",
        "\n",
        "  df.loc[(df[\"high\"].shift(5) < df[\"high\"].shift(4)) &\n",
        "  (df[\"high\"].shift(4) < df[\"high\"].shift(3)) &\n",
        "  (df[\"high\"].shift(3) < df[\"high\"].shift(2)) &\n",
        "  (df[\"high\"].shift(2) < df[\"high\"].shift(1)) &\n",
        "  (df[\"high\"].shift(1) < df[\"high\"].shift(0)), \"resistance\"] = df[\"high\"]\n",
        "\n",
        "\n",
        "  # Create Simple moving average 30 days\n",
        "  df[\"SMA fast\"] = df[\"close\"].rolling(30).mean()\n",
        "\n",
        "  # Create Simple moving average 60 days\n",
        "  df[\"SMA slow\"] = df[\"close\"].rolling(60).mean()\n",
        "\n",
        "  df[\"rsi\"] = ta.momentum.RSIIndicator(df[\"close\"], window=10).rsi()\n",
        "\n",
        "  # RSI yersteday\n",
        "  df[\"rsi yersteday\"] = df[\"rsi\"].shift(1)\n",
        "\n",
        "  # Create the signal\n",
        "  df[\"signal\"] = 0\n",
        "\n",
        "  df[\"smooth resistance\"] = df[\"resistance\"].fillna(method=\"ffill\")\n",
        "  df[\"smooth support\"] = df[\"support\"].fillna(method=\"ffill\")\n",
        "\n",
        "\n",
        "  condition_1_buy = (df[\"close\"].shift(1) < df[\"smooth resistance\"].shift(1)) & \\\n",
        "                    (df[\"smooth resistance\"]*(1+0.5/100) < df[\"close\"])\n",
        "  condition_2_buy = df[\"SMA fast\"] > df[\"SMA slow\"]\n",
        "\n",
        "  condition_3_buy = df[\"rsi\"] < df[\"rsi yersteday\"]\n",
        "\n",
        "  condition_1_sell = (df[\"close\"].shift(1) > df[\"smooth support\"].shift(1)) & \\\n",
        "                    (df[\"smooth support\"]*(1+0.5/100) > df[\"close\"])\n",
        "  condition_2_sell = df[\"SMA fast\"] < df[\"SMA slow\"]\n",
        "\n",
        "  condition_3_sell = df[\"rsi\"] > df[\"rsi yersteday\"]\n",
        "\n",
        "\n",
        "\n",
        "  df.loc[condition_1_buy & condition_2_buy & condition_3_buy, \"signal\"] = 1\n",
        "  df.loc[condition_1_sell & condition_2_sell & condition_3_sell, \"signal\"] = -1\n",
        "\n",
        "\n",
        "  # Compute the profits\n",
        "  df[\"pct\"] = df[\"close\"].pct_change(1)\n",
        "\n",
        "  df[\"return\"] = np.array([df[\"pct\"].shift(i) for i in range(duration)]).sum(axis=0) * (df[\"signal\"].shift(duration))\n",
        "  df.loc[df[\"return\"]==-1, \"return\"] = df[\"return\"]-spread\n",
        "  df.loc[df[\"return\"]==1, \"return\"] = df[\"return\"]-spread\n",
        "\n",
        "\n",
        "  return df[\"return\"]"
      ],
      "metadata": {
        "id": "QOtS7BtExE0L"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Preprocessing function\n",
        "\n",
        "def preprocessing_min(name):\n",
        "\n",
        "  # Import the data\n",
        "  df = pd.read_csv(name, delimiter=\"\\t\", index_col=[\"<DATE>\",\"<TIME>\"] , parse_dates=True).dropna()\n",
        "\n",
        "  # Delete the two last columns\n",
        "  df = df.iloc[:,:-2]\n",
        "\n",
        "  # Rename\n",
        "  df.columns = [\"open\", \"high\", \"low\", \"close\", \"volume\"]\n",
        "  #df.index.name = \"time\"\n",
        "  return df"
      ],
      "metadata": {
        "id": "XaU-pHUgZRN_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dfc = preprocessing_min(\"EURUSD_M1.csv\")\n",
        "dfc\n",
        "\n",
        "\n",
        "support_resistance(df).cumsum().plot(figsize=(15,8))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "id": "XZy2dS8eZIMt",
        "outputId": "56f84a61-de01-405f-86fa-b4a576b2f029"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-1049686f-9dd5-40f2-9386-55844fd6b471\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
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              "\n",
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              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>open</th>\n",
              "      <th>high</th>\n",
              "      <th>low</th>\n",
              "      <th>close</th>\n",
              "      <th>volume</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>&lt;DATE&gt;</th>\n",
              "      <th>&lt;TIME&gt;</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 rowspan=\"5\" valign=\"top\">2021-11-17</th>\n",
              "      <th>2022-02-23 16:17:00</th>\n",
              "      <td>1.13006</td>\n",
              "      <td>1.13033</td>\n",
              "      <td>1.13006</td>\n",
              "      <td>1.13023</td>\n",
              "      <td>103.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-02-23 16:18:00</th>\n",
              "      <td>1.13023</td>\n",
              "      <td>1.13029</td>\n",
              "      <td>1.13010</td>\n",
              "      <td>1.13028</td>\n",
              "      <td>53.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-02-23 16:19:00</th>\n",
              "      <td>1.13028</td>\n",
              "      <td>1.13045</td>\n",
              "      <td>1.13027</td>\n",
              "      <td>1.13038</td>\n",
              "      <td>72.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-02-23 16:20:00</th>\n",
              "      <td>1.13037</td>\n",
              "      <td>1.13045</td>\n",
              "      <td>1.13034</td>\n",
              "      <td>1.13039</td>\n",
              "      <td>100.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-02-23 16:21:00</th>\n",
              "      <td>1.13039</td>\n",
              "      <td>1.13044</td>\n",
              "      <td>1.13032</td>\n",
              "      <td>1.13038</td>\n",
              "      <td>45.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">2022-01-25</th>\n",
              "      <th>2022-02-23 10:46:00</th>\n",
              "      <td>1.13038</td>\n",
              "      <td>1.13057</td>\n",
              "      <td>1.13037</td>\n",
              "      <td>1.13050</td>\n",
              "      <td>53.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-02-23 10:47:00</th>\n",
              "      <td>1.13049</td>\n",
              "      <td>1.13058</td>\n",
              "      <td>1.13045</td>\n",
              "      <td>1.13057</td>\n",
              "      <td>71.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-02-23 10:48:00</th>\n",
              "      <td>1.13056</td>\n",
              "      <td>1.13071</td>\n",
              "      <td>1.13056</td>\n",
              "      <td>1.13060</td>\n",
              "      <td>64.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-02-23 10:49:00</th>\n",
              "      <td>1.13060</td>\n",
              "      <td>1.13061</td>\n",
              "      <td>1.13041</td>\n",
              "      <td>1.13042</td>\n",
              "      <td>78.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-02-23 10:50:00</th>\n",
              "      <td>1.13042</td>\n",
              "      <td>1.13064</td>\n",
              "      <td>1.13035</td>\n",
              "      <td>1.13062</td>\n",
              "      <td>92.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>69900 rows × 5 columns</p>\n",
              "</div>\n",
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            ],
            "text/plain": [
              "                                   open     high      low    close  volume\n",
              "<DATE>     <TIME>                                                         \n",
              "2021-11-17 2022-02-23 16:17:00  1.13006  1.13033  1.13006  1.13023   103.0\n",
              "           2022-02-23 16:18:00  1.13023  1.13029  1.13010  1.13028    53.0\n",
              "           2022-02-23 16:19:00  1.13028  1.13045  1.13027  1.13038    72.0\n",
              "           2022-02-23 16:20:00  1.13037  1.13045  1.13034  1.13039   100.0\n",
              "           2022-02-23 16:21:00  1.13039  1.13044  1.13032  1.13038    45.0\n",
              "...                                 ...      ...      ...      ...     ...\n",
              "2022-01-25 2022-02-23 10:46:00  1.13038  1.13057  1.13037  1.13050    53.0\n",
              "           2022-02-23 10:47:00  1.13049  1.13058  1.13045  1.13057    71.0\n",
              "           2022-02-23 10:48:00  1.13056  1.13071  1.13056  1.13060    64.0\n",
              "           2022-02-23 10:49:00  1.13060  1.13061  1.13041  1.13042    78.0\n",
              "           2022-02-23 10:50:00  1.13042  1.13064  1.13035  1.13062    92.0\n",
              "\n",
              "[69900 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# List of assets\n",
        "listnames = [\"EURUSD_M1.csv\", \"AUDCAD_M1.csv\", \"GBPUSD_M1.csv\", \"USDCAD_M1.csv\", \"USDCHF_M1.csv\", \"USDJPY_M1.csv\"]\n",
        "returns = pd.DataFrame()\n",
        "\n",
        "# Compute the return of each strategy\n",
        "for name in listnames:\n",
        "  dfc = preprocessing_min(name)\n",
        "  returns[name] = support_resistance(dfc, duration=10, spread=0.0001)\n",
        "\n",
        "# Plot the results\n",
        "returns.fillna(value=0).cumsum().plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 514
        },
        "id": "B_KYoIeeaZGc",
        "outputId": "87336d2f-cc80-4748-c04e-aaf9bda81479"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fbc5e47f150>"
            ]
          },
          "metadata": {},
          "execution_count": 47
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x576 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Portfolio advantage"
      ],
      "metadata": {
        "id": "I1jOVdbVRAvg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "returns[\"portfolio\"] = returns.sum(axis=1)/returns.shape[1]"
      ],
      "metadata": {
        "id": "81zxGD0r_wKY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def drawdown_function(serie):\n",
        "\n",
        "  # We compute Cumsum of the returns\n",
        "  cum = serie.dropna().cumsum() + 1\n",
        "\n",
        "  # We compute max of the cumsum on the period (accumulate max) # (1,3,5,3,1) --> (1,3,5,5,5)\n",
        "  running_max = np.maximum.accumulate(cum)\n",
        "\n",
        "  # We compute drawdown\n",
        "  drawdown = cum/running_max - 1\n",
        "  return drawdown"
      ],
      "metadata": {
        "id": "Y-tiqI_zcRlf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Empty dataframe\n",
        "values = pd.DataFrame(index=[\"RETURN\", \"DRAWDOWN\", \"RETURN DRAWDOWN RATIO\"])\n",
        "\n",
        "# Compute return/drawdown\n",
        "for col in returns.columns:\n",
        "  ret = (returns[col].dropna().cumsum().iloc[-1])\n",
        "  dd = -np.min(drawdown_function(returns[col].dropna()))\n",
        "  ret_dd = ret/dd\n",
        "  \n",
        "  values[col] = ret,dd,ret_dd\n",
        "\n",
        "values.transpose().sort_values(by=\"RETURN DRAWDOWN RATIO\", ascending=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "3q_4xFIIEnZW",
        "outputId": "5b0bd12c-dce5-4ab5-8e6d-175a8d484994"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-074b674f-bc2e-4245-97c5-add99d08cc82\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>RETURN</th>\n",
              "      <th>DRAWDOWN</th>\n",
              "      <th>RETURN DRAWDOWN RATIO</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>GBPUSD_M1.csv</th>\n",
              "      <td>0.148140</td>\n",
              "      <td>0.034325</td>\n",
              "      <td>4.315870</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>portfolio</th>\n",
              "      <td>0.075286</td>\n",
              "      <td>0.017643</td>\n",
              "      <td>4.267281</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AUDCAD_M1.csv</th>\n",
              "      <td>0.194051</td>\n",
              "      <td>0.050614</td>\n",
              "      <td>3.833980</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>EURUSD_M1.csv</th>\n",
              "      <td>0.099394</td>\n",
              "      <td>0.070223</td>\n",
              "      <td>1.415415</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>USDCHF_M1.csv</th>\n",
              "      <td>0.044210</td>\n",
              "      <td>0.050860</td>\n",
              "      <td>0.869243</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>USDJPY_M1.csv</th>\n",
              "      <td>0.005651</td>\n",
              "      <td>0.062849</td>\n",
              "      <td>0.089915</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>USDCAD_M1.csv</th>\n",
              "      <td>-0.039733</td>\n",
              "      <td>0.087582</td>\n",
              "      <td>-0.453669</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-074b674f-bc2e-4245-97c5-add99d08cc82 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-074b674f-bc2e-4245-97c5-add99d08cc82');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "                 RETURN  DRAWDOWN  RETURN DRAWDOWN RATIO\n",
              "GBPUSD_M1.csv  0.148140  0.034325               4.315870\n",
              "portfolio      0.075286  0.017643               4.267281\n",
              "AUDCAD_M1.csv  0.194051  0.050614               3.833980\n",
              "EURUSD_M1.csv  0.099394  0.070223               1.415415\n",
              "USDCHF_M1.csv  0.044210  0.050860               0.869243\n",
              "USDJPY_M1.csv  0.005651  0.062849               0.089915\n",
              "USDCAD_M1.csv -0.039733  0.087582              -0.453669"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    }
  ]
}