src/main.txt

# main.py

from utils.logger import setup_logger
from utils.data_loader import fetch_stock_data
from indicators.rsi import rsi
from indicators.sma import sma
from indicators.macd import macd
from strategy.rule_based_strategy import generate_signals
from utils.backtester import backtest_signals

import pandas as pd
import matplotlib.pyplot as plt

# ---------------------- Configuration ----------------------
STOCK = 'RELIANCE.NS'
START_DATE = '2024-02-01'

# Indicator Parameters
RSI_PERIOD = 14
SMA_SHORT = 20
SMA_LONG = 50

# Backtest Settings
INITIAL_CASH = 100000
# -----------------------------------------------------------


def main():
    # Initialize Logger
    setup_logger()

    print(f"\nFetching data for {STOCK}...")
    df = fetch_stock_data(STOCK, start_date=START_DATE)

    if df.empty:
        print("No data available. Exiting.")
        return

    print("Calculating indicators...")
    df['RSI'] = rsi(df, period=RSI_PERIOD)
    df['SMA20'] = sma(df, period=SMA_SHORT)
    df['SMA50'] = sma(df, period=SMA_LONG)
    df['MACD'], df['MACD_signal'], df['MACD_hist'] = macd(df)

    print("Generating signals...")
    df = generate_signals(df, rsi_col='RSI', sma_short_col='SMA20', sma_long_col='SMA50')

    print("Backtesting strategy...")
    results = backtest_signals(df, signal_col='Signal', price_col='Close', initial_cash=INITIAL_CASH)

    final_equity = results['Total'].iloc[-1]
    print(f"\n✅ Final Portfolio Value: ₹{final_equity:,.2f}")

    # Plotting equity curve
    plt.figure(figsize=(12, 6))
    results['Total'].plot(label='Equity Curve', color='green')
    results['Close'].plot(label='Close Price', secondary_y=True, alpha=0.3)
    plt.title(f"Backtest Results for {STOCK}")
    plt.legend()
    plt.tight_layout()
    plt.show()


if __name__ == "__main__":
    main()