Breakout Trading

import pandas as pd
import numpy as np

def detect_breakout(df: pd.DataFrame, lookback: int = 20, vol_mult: float = 1.5):
    """Detect price breakouts with volume confirmation."""
    df['highest'] = df['high'].rolling(lookback).max().shift(1)
    df['lowest'] = df['low'].rolling(lookback).min().shift(1)
    df['avg_vol'] = df['volume'].rolling(lookback).mean().shift(1)
    
    # Breakout conditions
    bullish = (df['close'] > df['highest']) & \
              (df['volume'] > df['avg_vol'] * vol_mult)
    bearish = (df['close'] < df['lowest']) & \
              (df['volume'] > df['avg_vol'] * vol_mult)
    
    df['breakout_signal'] = 0
    df.loc[bullish, 'breakout_signal'] = 1   # Bullish breakout
    df.loc[bearish, 'breakout_signal'] = -1  # Bearish breakout
    return df

//+------------------------------------------------------------------+
//| Breakout Detection Function                                        |
//+------------------------------------------------------------------+
bool DetectBreakout(string symbol, ENUM_TIMEFRAMES tf, int lookback = 20)
{
    double highest = iHigh(symbol, tf, iHighest(symbol, tf, MODE_HIGH, lookback, 1));
    double lowest = iLow(symbol, tf, iLowest(symbol, tf, MODE_LOW, lookback, 1));
    double currentClose = iClose(symbol, tf, 0);
    double prevClose = iClose(symbol, tf, 1);
    
    // Get volume data
    long currentVol = iVolume(symbol, tf, 0);
    double avgVol = 0;
    for(int i = 1; i <= 20; i++)
        avgVol += iVolume(symbol, tf, i);
    avgVol /= 20;
    
    bool volumeConfirm = (currentVol > avgVol * 1.5);
    
    // Bullish breakout
    if(currentClose > highest && prevClose <= highest && volumeConfirm)
        return true;
    
    // Bearish breakout  
    if(currentClose < lowest && prevClose >= lowest && volumeConfirm)
        return true;
    
    return false;
}