使用Python回测MACD金叉死叉策略的解决步骤

def macd(close, fast=12, slow=26, signal=9):
    ef = close.ewm(span=fast, adjust=False).mean()
    es = close.ewm(span=slow, adjust=False).mean()
    dif = ef - es                                  # 快慢 EMA 之差
    dea = dif.ewm(span=signal, adjust=False).mean()  # DIF 的 EMA
    return dif, dea

from alphafeed import AlphaFeed

af = AlphaFeed(api_key="your-api-key")  # 或 export ALPHAFEED_API_KEY 后 AlphaFeed()

def macd_backtest(symbol, count=500, fee=0.0013):
    df = af.klines.get(symbol, period="1d", count=count,
                       adjust="forward", to_dataframe=True).sort_values("trade_date").reset_index(drop=True)
    dif, dea = macd(df["close"])
    pos, cash, shares, trades = 0, 1.0, 0.0, 0
    for i in range(35, len(df)):                   # 跳过 MACD 预热期
        px = df["close"].iloc[i]
        gold = dif.iloc[i-1] <= dea.iloc[i-1] and dif.iloc[i] > dea.iloc[i]  # 金叉
        dead = dif.iloc[i-1] >= dea.iloc[i-1] and dif.iloc[i] < dea.iloc[i]  # 死叉
        if pos == 0 and gold:
            shares = cash * (1 - fee) / px; cash = 0.0; pos = 1; trades += 1
        elif pos == 1 and dead:
            cash = shares * px * (1 - fee); shares = 0.0; pos = 0
    equity = cash + shares * df["close"].iloc[-1]
    bh = df["close"].iloc[-1] / df["close"].iloc[35]
    return {"strategy_ret_%": round((equity - 1) * 100, 1),
            "buyhold_ret_%": round((bh - 1) * 100, 1), "trades": trades}

for s in ["600519.SH", "000001.SZ", "600036.SH"]:
    print(s, macd_backtest(s))