{
    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "# Example usage\n",
                "\n",
                "## Introduction\n",
                "This tutorial will guide you through the process of using the `traders_copilot_mzza_25` package to generate synthetic data, calculate technical indicators, generate trading signals, and visualize the results. By the end of this tutorial, you will be able to:\n",
                "- Generate synthetic financial data.\n",
                "- Calculate Simple Moving Averages (SMA) and Relative Strength Index (RSI).\n",
                "- Generate trading signals based on these indicators.\n",
                "- Visualize the trading signals.\n",
                "\n",
                "## Workflow\n",
                "Before starting, ensure you have poetry installed.\n",
                "\n",
                "You can install the necessary packages using pip:\n",
                "```\n",
                "poetry install"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "### Step 1: Import package"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "First, let's import the necessary modules."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 16,
            "metadata": {},
            "outputs": [],
            "source": [
                "import sys\n",
                "import os\n",
                "sys.path.insert(0, os.path.abspath(\"../src/traders_copilot_mzza_25\"))\n",
                "from data import generate_synthetic_data\n",
                "from generate_signals import generate_signals\n",
                "from indicators import calculate_sma, calculate_rsi\n",
                "from plot_signals import plot_signals"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "### Step 2: Simulate market data\n",
                "\n",
                "generate_synthetic_data function simulate and mock stock market data. To create this data, we just feed the function with start_date and end_date. See the following as a reference."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 17,
            "metadata": {},
            "outputs": [
                {
                    "data": {
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                            "      <th></th>\n",
                            "      <th>Open</th>\n",
                            "      <th>High</th>\n",
                            "      <th>Low</th>\n",
                            "      <th>Close</th>\n",
                            "      <th>Adj Close</th>\n",
                            "      <th>Volume</th>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>Date</th>\n",
                            "      <th></th>\n",
                            "      <th></th>\n",
                            "      <th></th>\n",
                            "      <th></th>\n",
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                            "      <th>2024-01-24 00:00:00.000000000</th>\n",
                            "      <td>99.928843</td>\n",
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                            "      <td>98.751133</td>\n",
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                            "      <td>96.854629</td>\n",
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                            "  </tbody>\n",
                            "</table>\n",
                            "</div>"
                        ],
                        "text/plain": [
                            "                                    Open        High        Low      Close  \\\n",
                            "Date                                                                         \n",
                            "2024-01-24 00:00:00.000000000  99.928843  100.044998  97.405803  99.392452   \n",
                            "2024-01-25 10:59:45.657370517  98.827472  100.329171  97.915188  99.266316   \n",
                            "2024-01-26 21:59:31.314741035  99.092509  100.056103  97.373548  98.581710   \n",
                            "2024-01-28 08:59:16.972111553  98.751133  101.501051  98.076428  99.510424   \n",
                            "2024-01-29 19:59:02.629482071  96.854629   98.765622  95.809883  97.666023   \n",
                            "\n",
                            "                                Adj Close   Volume  \n",
                            "Date                                                \n",
                            "2024-01-24 00:00:00.000000000   98.998517  2326182  \n",
                            "2024-01-25 10:59:45.657370517   99.016852  1158981  \n",
                            "2024-01-26 21:59:31.314741035   99.051793  3750125  \n",
                            "2024-01-28 08:59:16.972111553  100.140903  2286181  \n",
                            "2024-01-29 19:59:02.629482071   98.213417  4476945  "
                        ]
                    },
                    "execution_count": 17,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "data = generate_synthetic_data(start_date='2024-01-24', end_date='2025-01-24')\n",
                "data.head()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "### Step 3: Calculate SMA and RSI \n",
                "Next, we will calculate the 50-day and 200-day Simple Moving Averages (SMA) and the Relative Strength Index (RSI)."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 18,
            "metadata": {},
            "outputs": [
                {
                    "data": {
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                            "      <th></th>\n",
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                            "      <th>SMA_200</th>\n",
                            "      <th>RSI</th>\n",
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                            "    <tr>\n",
                            "      <th>Date</th>\n",
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                        "text/plain": [
                            "                                  SMA_50    SMA_200        RSI\n",
                            "Date                                                          \n",
                            "2025-01-18 04:00:57.370517928  97.137544  95.892522  28.366691\n",
                            "2025-01-19 15:00:43.027888444  97.016632  95.822201  29.214917\n",
                            "2025-01-21 02:00:28.685258964  96.922096  95.747801  29.825972\n",
                            "2025-01-22 13:00:14.342629480  96.815964  95.681511  28.945325\n",
                            "2025-01-24 00:00:00.000000000  96.708851  95.614732  32.431338"
                        ]
                    },
                    "execution_count": 18,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "df = calculate_sma(data)\n",
                "df = calculate_sma(df, window=200)\n",
                "df = calculate_rsi(df)\n",
                "df.tail().iloc[:, -3:]"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "### Step 4: Generating Trading Signals\n",
                "generate_signals function create a new column that help trader decides to buy or sell the stock\n",
                "The following signals help traders make decisions:\n",
                "- Buy Signal: Indicates a potential buying opportunity.\n",
                "- Sell Signal: Indicates a potential selling opportunity\n",
                "Conditions for a buy signal:\n",
                "- SMA_50 > SMA_200: The short-term trend (50-day SMA) is above the long-term trend (200-day SMA), indicating upward momentum.\n",
                "- RSI < 30: The stock is oversold, suggesting a potential price rebound.\n",
                "Conditions for a sell signal:\n",
                "- SMA_50 < SMA_200: The short-term trend is below the long-term trend, indicating downward momentum.\n",
                "- RSI > 70: The stock is overbought, suggesting a potential price decline.\n"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 19,
            "metadata": {},
            "outputs": [
                {
                    "data": {
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                            "      <th>SMA_50</th>\n",
                            "      <th>SMA_200</th>\n",
                            "      <th>RSI</th>\n",
                            "      <th>Signal</th>\n",
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                            "    <tr>\n",
                            "      <th>Date</th>\n",
                            "      <th></th>\n",
                            "      <th></th>\n",
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                            "      <th>2025-01-18 04:00:57.370517928</th>\n",
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                            "      <td>28.366691</td>\n",
                            "      <td>BUY</td>\n",
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                            "      <th>2025-01-19 15:00:43.027888444</th>\n",
                            "      <td>97.016632</td>\n",
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                            "      <td>BUY</td>\n",
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                            "      <th>2025-01-21 02:00:28.685258964</th>\n",
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                            "      <td>BUY</td>\n",
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                            "      <td>BUY</td>\n",
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                            "      <th>2025-01-24 00:00:00.000000000</th>\n",
                            "      <td>96.708851</td>\n",
                            "      <td>95.614732</td>\n",
                            "      <td>32.431338</td>\n",
                            "      <td>HOLD</td>\n",
                            "    </tr>\n",
                            "  </tbody>\n",
                            "</table>\n",
                            "</div>"
                        ],
                        "text/plain": [
                            "                                  SMA_50    SMA_200        RSI Signal\n",
                            "Date                                                                 \n",
                            "2025-01-18 04:00:57.370517928  97.137544  95.892522  28.366691    BUY\n",
                            "2025-01-19 15:00:43.027888444  97.016632  95.822201  29.214917    BUY\n",
                            "2025-01-21 02:00:28.685258964  96.922096  95.747801  29.825972    BUY\n",
                            "2025-01-22 13:00:14.342629480  96.815964  95.681511  28.945325    BUY\n",
                            "2025-01-24 00:00:00.000000000  96.708851  95.614732  32.431338   HOLD"
                        ]
                    },
                    "execution_count": 19,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "df = generate_signals(df)\n",
                "df.tail().iloc[:, -4:]"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "### Step 5: Visualizing Trading Signals\n",
                "\n",
                "For visualization, we can use plot_signals to create a line plot. The chart plots time on x-axis and price on y-axis. Refer to the following code below."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 20,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "Debug: Non-missing Length of Close = 252, Non-missing Length of Date = 252\n"
                    ]
                },
                {
                    "data": {
                        "image/png": 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",
                        "text/plain": [
                            "<Figure size 640x480 with 1 Axes>"
                        ]
                    },
                    "execution_count": 20,
                    "metadata": {},
                    "output_type": "execute_result"
                },
                {
                    "data": {
                        "image/png": 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",
                        "text/plain": [
                            "<Figure size 640x480 with 1 Axes>"
                        ]
                    },
                    "metadata": {},
                    "output_type": "display_data"
                }
            ],
            "source": [
                "df = df.reset_index()\n",
                "df['Date'] =  df['Date'].dt.date\n",
                "plot_signals(df)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Conclusion\n",
                "In this tutorial, we covered how to generate synthetic financial data, calculate technical indicators, generate trading signals, and visualize the results using the traders_copilot_mzza_25 package. You can further explore the package by experimenting with different parameters and indicators."
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Next steps\n",
                "\n",
                "- Try modifying the parameters of the generate_synthetic_data function to see how it affects the generated data.\n",
                "\n",
                "- Experiment with different windows for the SMA and RSI calculations.\n",
                "\n",
                "- Explore additional technical indicators and incorporate them into your analysis.\n",
                "\n"
            ]
        }
    ],
    "metadata": {
        "kernelspec": {
            "display_name": "base",
            "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": "3.11.11"
        }
    },
    "nbformat": 4,
    "nbformat_minor": 4
}