feat: strat_supertrend_initial_backtest.ipynb

notebooks/strat_supertrend_initial_backtest.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "247ae640",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%\n",
+    "# filename: strat_supertrend_initial_backtest.ipynb\n",
+    "\n",
+    "# --- 1. Imports and Setup ---\n",
+    "import os\n",
+    "\n",
+    "import pandas as pd\n",
+    "import pandas_ta as ta  # noqa: F401\n",
+    "import plotly.graph_objects as go\n",
+    "import vectorbt as vbt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7486f4f9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%\n",
+    "# --- 2. Configuration and Data Loading ---\n",
+    "\n",
+    "# --- Path Configuration ---\n",
+    "project_root = os.path.abspath(os.path.join(os.getcwd(), \"..\"))\n",
+    "data_dir = os.path.join(project_root, \"data\", \"parquet\")\n",
+    "# Make sure this filename matches the file you copied into the data/parquet directory\n",
+    "DATA_FILENAME = \"EURUSD_M15_2024-09-14_to_2025-09-14.parquet\"\n",
+    "file_path = os.path.join(data_dir, DATA_FILENAME)\n",
+    "\n",
+    "# --- Strategy Parameters ---\n",
+    "SUPERTREND_PERIOD = 7\n",
+    "SUPERTREND_MULTIPLIER = 3.0\n",
+    "\n",
+    "# --- Data Loading ---\n",
+    "print(f\"Loading data from: {file_path}\")\n",
+    "try:\n",
+    "    price_data = pd.read_parquet(file_path)\n",
+    "    price_data.set_index('Time', inplace=True)\n",
+    "    print(\"Data loaded successfully and index set.\")\n",
+    "except FileNotFoundError:\n",
+    "    print(f\"ERROR: File not found at '{file_path}'.\")\n",
+    "    # Stop execution if data is not found\n",
+    "    exit()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ed3dcc21",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%\n",
+    "# --- 3. Indicator Calculation ---\n",
+    "print(f\"Calculating Supertrend with period={SUPERTREND_PERIOD} and multiplier={SUPERTREND_MULTIPLIER}...\")\n",
+    "\n",
+    "# Use pandas-ta to calculate the Supertrend indicator\n",
+    "# It conveniently returns multiple columns, including the trend direction and the line itself.\n",
+    "price_data.ta.supertrend(\n",
+    "    length=SUPERTREND_PERIOD,\n",
+    "    multiplier=SUPERTREND_MULTIPLIER,\n",
+    "    append=True\n",
+    ")\n",
+    "\n",
+    "# For clarity, let's rename the supertrend line column\n",
+    "# The default name is SUPERT_7_3.0\n",
+    "supertrend_col_name = f\"SUPERT_{SUPERTREND_PERIOD}_{SUPERTREND_MULTIPLIER}\"\n",
+    "price_data.rename(columns={supertrend_col_name: 'supertrend_line'}, inplace=True)\n",
+    "\n",
+    "print(\"Supertrend calculation complete.\")\n",
+    "print(price_data.tail())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "778fdcaa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%\n",
+    "# --- 4. Strategy Logic & Signal Generation ---\n",
+    "print(\"Generating trading signals...\")\n",
+    "\n",
+    "# The signal is when the Close price crosses the Supertrend line.\n",
+    "# We use vectorbt's built-in signal functions for this.\n",
+    "entries = price_data['Close'].vbt.crossed_above(price_data['supertrend_line'])\n",
+    "exits = price_data['Close'].vbt.crossed_below(price_data['supertrend_line'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "895de355",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%\n",
+    "# --- 5. Backtesting and Analysis ---\n",
+    "print(\"Running backtest with vectorbt...\")\n",
+    "\n",
+    "# Create the portfolio from the generated signals\n",
+    "portfolio = vbt.Portfolio.from_signals(\n",
+    "    price_data['Close'],\n",
+    "    entries,\n",
+    "    exits,\n",
+    "    freq='15min', # Set the frequency of the data (15 minutes)\n",
+    "    init_cash=10000,\n",
+    "    fees=0.0001,    # Example fee: 0.01%\n",
+    "    slippage=0.0001 # Example slippage: 0.01%\n",
+    ")\n",
+    "\n",
+    "# Print the performance statistics\n",
+    "print(\"\\n--- Backtest Results ---\")\n",
+    "print(portfolio.stats())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "04ff5766",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%\n",
+    "# --- 6. Visualization (Optimized and Corrected) ---\n",
+    "print(\"\\nGenerating plot...\")\n",
+    "\n",
+    "# --- Performance Optimization for Plotting ---\n",
+    "# To avoid browser slowdowns, we will only plot the last 3 months of data.\n",
+    "# We use the modern `.loc` slicing method instead of the deprecated `.last()`.\n",
+    "print(\"Selecting the last 3 months of data for visualization...\")\n",
+    "end_date = price_data.index[-1]\n",
+    "start_date_plot = end_date - pd.DateOffset(months=3)\n",
+    "plot_data = price_data.loc[start_date_plot:]\n",
+    "\n",
+    "# --- Re-run Backtest on the Sliced Data for Clean Plotting ---\n",
+    "# This is the most robust way to get a portfolio object that matches the plot data.\n",
+    "# It's extremely fast, so there's no significant performance cost.\n",
+    "print(\"Running a quick backtest on the sliced data for plotting...\")\n",
+    "plot_entries = entries.loc[plot_data.index]\n",
+    "plot_exits = exits.loc[plot_data.index]\n",
+    "\n",
+    "plot_portfolio = vbt.Portfolio.from_signals(\n",
+    "    plot_data['Close'],\n",
+    "    plot_entries,\n",
+    "    plot_exits,\n",
+    "    freq='15min', # Use the corrected frequency string\n",
+    "    init_cash=10000,\n",
+    "    fees=0.0001,\n",
+    "    slippage=0.0001\n",
+    ")\n",
+    "\n",
+    "# --- Layered Plotting ---\n",
+    "# Step 1: Create the base candlestick chart from the SLICED data\n",
+    "fig = plot_data.vbt.ohlc.plot(\n",
+    "    title_text=f'Supertrend Strategy on {DATA_FILENAME} (Last 3 Months)',\n",
+    "    template='plotly_dark'\n",
+    ")\n",
+    "\n",
+    "# Step 2: Add the Supertrend line from the SLICED data\n",
+    "fig.add_trace(\n",
+    "    go.Scatter(\n",
+    "        x=plot_data.index,\n",
+    "        y=plot_data['supertrend_line'],\n",
+    "        mode='lines',\n",
+    "        name='Supertrend Line',\n",
+    "        line=dict(color='yellow', width=1.5)\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "# Step 3: Add the trade markers from the NEWLY created plot_portfolio\n",
+    "plot_portfolio.trades.plot(fig=fig)\n",
+    "\n",
+    "# Step 4: Show the final, combined figure\n",
+    "fig.show()"
+   ]
+  }
+ ],
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+   "display_name": "strategy-optimizer_env",
+   "language": "python",
+   "name": "python3"
+  },
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