如何用 Python 做动量选股（相对强弱排名）？找出近期最强势的股票

import pandas as pd
from alphafeed import AlphaFeed

af = AlphaFeed()                                        # 读取 ALPHAFEED_API_KEY
q = af.quotes.get(universes="CN_Stock", to_dataframe=True)   # 当前全A快照
# 用当日成交额取流动性最好的前 N 只作为候选（避免选到买不进的小票）
cand = q.sort_values("amount", ascending=False)["symbol"].head(200).tolist()

def momentum_rank(symbols, lookback=20, count=30):
    af = AlphaFeed()
    bt = af.klines.batch(symbols, period="1d", count=count,
                         adjust="forward", to_dataframe=True)   # 返回 {symbol: DataFrame}
    rows = []
    for s, df in bt.items():
        df = df.sort_values("trade_date")
        if len(df) < lookback + 1:
            continue
        ret = df["close"].iloc[-1] / df["close"].iloc[-1 - lookback] - 1   # N 日区间收益
        rows.append({"symbol": s, "name": df["name"].iloc[-1], "ret_Nd": round(float(ret), 4)})
    res = pd.DataFrame(rows).sort_values("ret_Nd", ascending=False).reset_index(drop=True)
    res.insert(0, "rank", range(1, len(res) + 1))
    return res

rank = momentum_rank(cand, lookback=20, count=30)
print(rank.head(10).to_string(index=False))

def multi_period(symbols):
    r20 = momentum_rank(symbols, lookback=20, count=40).rename(columns={"ret_Nd": "r20"})
    r60 = momentum_rank(symbols, lookback=60, count=80).rename(columns={"ret_Nd": "r60"})
    m = r20.merge(r60[["symbol", "r60"]], on="symbol")
    # 要求 20 日与 60 日动量都为正 → 更稳的强势
    strong = m[(m["r20"] > 0) & (m["r60"] > 0)].sort_values("r20", ascending=False)
    return strong

print(multi_period(cand).head(10).to_string(index=False))