Cotin Dcx AI trading bot backtest #1417

import numpy as np
import pandas as pd


def run_backtest(
    df: pd.DataFrame, initial_balance: float = 1000.0, fee: float = 0.001
):
    """Simple event-driven backtest loop for AI signal validation.

    df must contain: 'close', 'signal' (1 for Buy, -1 for Sell, 0 for Hold)
    """
    balance = initial_balance
    position = 0.0  # Amount of crypto held
    equity_curve = []

    for i, row in df.iterrows():
        price = row["close"]
        signal = row["signal"]

        # Buy Signal (Entry)
        if signal == 1 and balance > 0:
            position = (balance * (1 - fee)) / price
            balance = 0.0

        # Sell Signal (Exit)
        elif signal == -1 and position > 0:
            balance = (position * price) * (1 - fee)
            position = 0.0

        # Calculate current net portfolio value
        current_value = balance + (position * price)
        equity_curve.append(current_value)

    df["portfolio_val"] = equity_curve
    df["returns"] = df["portfolio_val"].pct_change()

    total_return = (
        df["portfolio_val"].iloc[-1] - initial_balance
    ) / initial_balance
    max_drawdown = (
        (df["portfolio_val"].cummax() - df["portfolio_val"])
        / df["portfolio_val"].cummax()
    ).max()

    return {
        "Final Balance ($)": round(df["portfolio_val"].iloc[-1], 2),
        "Total Return (%)": round(total_return * 100, 2),
        "Max Drawdown (%)": round(max_drawdown * 100, 2),
    }