Tutorial: Building a Custom Trading Strategy

Learn how to combine FinanceLib's indicators to build your own trading strategy.

Strategy: RSI + MACD + Bollinger Bands

from financelib import Stock
from financelib.trading.algo_trade import rsi, macd, bollinger_bands

def analyze_with_strategy(symbol: str, period: str = "6mo") -> dict:
    """Multi-indicator strategy combining RSI, MACD, and Bollinger Bands."""
    stock = Stock(symbol)
    df = stock.get_historical_data(period=period)

    if df is None or len(df) < 50:
        return {"error": "Insufficient data"}

    close = df["Close"]
    price = float(close.iloc[-1])

    # Calculate indicators
    rsi_values = rsi(close, period=14)
    macd_line, signal_line = macd(close)
    bb_upper, bb_middle, bb_lower = bollinger_bands(close)

    current_rsi = float(rsi_values.iloc[-1])
    current_macd = float(macd_line.iloc[-1])
    current_signal = float(signal_line.iloc[-1])

    # Score each indicator
    score = 0
    reasons = []

    # RSI
    if current_rsi < 30:
        score += 2
        reasons.append(f"RSI oversold ({current_rsi:.1f})")
    elif current_rsi < 40:
        score += 1
        reasons.append(f"RSI approaching oversold ({current_rsi:.1f})")
    elif current_rsi > 70:
        score -= 2
        reasons.append(f"RSI overbought ({current_rsi:.1f})")

    # MACD
    if current_macd > current_signal:
        score += 1
        reasons.append("MACD bullish crossover")
    else:
        score -= 1
        reasons.append("MACD bearish")

    # Bollinger Bands
    if price < float(bb_lower.iloc[-1]):
        score += 2
        reasons.append("Price below lower BB")
    elif price > float(bb_upper.iloc[-1]):
        score -= 2
        reasons.append("Price above upper BB")

    # Generate signal
    if score >= 3:
        signal = "STRONG BUY"
    elif score >= 1:
        signal = "BUY"
    elif score <= -3:
        signal = "STRONG SELL"
    elif score <= -1:
        signal = "SELL"
    else:
        signal = "HOLD"

    return {
        "symbol": symbol,
        "price": price,
        "signal": signal,
        "score": score,
        "rsi": current_rsi,
        "macd": current_macd,
        "reasons": reasons,
    }


# Run on BIST stocks
for symbol in ["THYAO.IS", "GARAN.IS", "ASELS.IS"]:
    result = analyze_with_strategy(symbol)
    print(f"{result['symbol']}: {result['signal']} (score: {result['score']})")
    for reason in result['reasons']:
        print(f"  - {reason}")

Using the BIST Bot

from financelib.trading import _get_bist_bot
BISTTradeBotv1 = _get_bist_bot()

bot = BISTTradeBotv1(paper_trading=True, initial_balance=100000)

# Scan and auto-trade
signals = bot.scan_common_stocks()
for signal in signals:
    if signal["signal"] in ("BUY", "SELL"):
        bot.execute_paper_trade(
            signal["symbol"],
            signal["signal"],
            signal["current_price"],
        )

# Check portfolio
summary = bot.get_portfolio_summary()
print(f"Total Value: {summary['total_value']:.2f} TRY")
print(f"P&L: {summary['total_pnl']:+.2f} TRY ({summary['total_pnl_pct']:+.2f}%)")