回測陷阱：新手最容易踩的
7個坑

# ❌ 錯誤寫法：前視偏誤 df['sma5'] = df['close'].rolling(5).mean() df['signal'] = np.where(df['close'] > df['sma5'], 1, -1) # 這裡用當天收盤價計算的SMA來做當天的交易決策！ # ✅ 正確寫法：使用昨天的指標 df['sma5'] = df['close'].rolling(5).mean().shift(1) df['signal'] = np.where(df['close'] > df['sma5'], 1, -1)

# ❌ 過擬合的參數優化 best_params = {} for fast in range(5, 20): # 測試15個快線參數 for slow in range(20, 50): # 測試30個慢線參數 for stop in np.arange(1.0, 5.0, 0.1): # 測試40個止損 profit = backtest(fast, slow, stop) if profit > best_profit: best_params = (fast, slow, stop) # 總共測試了 15×30×40 = 18000 種組合！ # ✅ 合理的參數範圍 fast_range = [5, 10, 15] # 只測試幾個典型值 slow_range = [20, 30, 40] stop_range = [2.0, 3.0, 4.0] # 總共只有 27 種組合