Code Review (Finance-Aware)

Reviews code for financial-domain-specific correctness issues beyond general code quality.

Real Code Reference

• tradinglearn/strategies/macd_strategy.py — generate_signals() uses .shift() to prevent lookahead; verify this is correct
• tradinglearn/backtest/backtester.py — run_backtest() iterates bars sequentially; verify order
• tradinglearn/pytdx2/backtest.py — BacktestEngine has its own execution loop; check for data leakage between train/test

What to Check

• Lookahead bias: verify no future data used in signal calculation (.shift(1) is correct, raw access is suspicious)
• Data leakage: train/test split must be temporal, not random — data[:split_date] train, data[split_date:] test
• Decimal handling: prices in cents vs yuan — K-line returns /1000, quotes return /100
• Survivorship bias: delisted stocks must be in historical universes
• Overfitting: parameter count vs data points ratio, out-of-sample validation
• Transaction costs: commission rate, slippage assumptions must be realistic
• Bid/ask spread: execution at mid-price is unrealistic for illiquid stocks
• Dividend handling: total return should include dividends

Review Process

1. Read strategy logic, understand the core idea
2. Trace data flow from raw prices → indicators → signals → trades
3. Check temporal integrity — no peeking into future at any step
4. Verify metric formulas against standard definitions
5. Assess overfitting risk from parameter count and search space
6. Report findings: critical / warning / suggestion