网格交易怎么用 Python 准备数据并回测？（含手续费才是真相）

import numpy as np, pandas as pd
from alphafeed import AlphaFeed

def grid_prep(symbol, count=250, n_grids=10):
    af = AlphaFeed()                                   # 读取 ALPHAFEED_API_KEY
    df = af.klines.get(symbol, period="1d", count=count, adjust="forward", to_dataframe=True)
    df = df.sort_values("trade_date").reset_index(drop=True)

    # 区间：用 10%/90% 分位数，避免被极端值拉宽（比直接 min/max 更实用）
    lo_q, hi_q = df["close"].quantile(0.10), df["close"].quantile(0.90)
    levels = np.linspace(lo_q, hi_q, n_grids + 1)      # n_grids 格 → n_grids+1 条线

    # ATR(14) 作为"格距是否合理"的参考尺子
    tr = pd.concat([(df["high"] - df["low"]),
                    (df["high"] - df["close"].shift()).abs(),
                    (df["low"] - df["close"].shift()).abs()], axis=1).max(axis=1)
    atr = float(tr.rolling(14).mean().iloc[-1])
    return df, levels, atr

df, levels, atr = grid_prep("510300.SH", count=250, n_grids=10)   # 沪深300ETF
print("区间: %.3f ~ %.3f | ATR14=%.4f" % (df["low"].min(), df["high"].max(), atr))
print("网格线:", [round(x, 3) for x in levels])

def backtest_grid(df, levels, shares=100, fee=0.0006):
    levels = sorted(levels)
    realized = 0.0; trades = 0; buys = []      # buys: 已买入未卖出的格价(FIFO)
    prev = df["close"].iloc[0]
    for c in df["close"].iloc[1:]:
        for lv in levels:
            if prev > lv >= c:                 # 收盘下穿格线 → 买一格
                buys.append(lv); trades += 1
            elif prev < lv <= c and buys:      # 收盘上穿格线 → 卖一格(卖最早买的)
                bp = buys.pop(0)
                realized += (lv - bp) * shares - (lv + bp) * shares * fee   # 计双边费用
                trades += 1
        prev = c
    return {"realized_pnl": round(realized, 2), "open_grids": len(buys), "trades": trades}

print(backtest_grid(df, levels))