【量化投资从入门到精通 #03】一个策略好不好看哪几个数收益回撤夏普在说什么

import os, datetime, math
from mairui import Client

def get_close_series(mc, code, days=120):
    end   = datetime.date.today().strftime("%Y%m%d")
    start = (datetime.date.today() - datetime.timedelta(days=days)).strftime("%Y%m%d")
    rows  = mc.stock_history(code, "d", "n", st=start, et=end)  # dividend='n' 不复权
    clean = [r for r in rows if r.get("c") is not None and r.get("t")]
    clean.sort(key=lambda r: r["t"])
    return clean

def max_drawdown(close):
    peak, mdd = close[0], 0.0
    for p in close:
        if p > peak: peak = p
        dd = (p - peak) / peak
        if dd < mdd: mdd = dd
    return mdd

def daily_returns(close):
    return [(close[i]-close[i-1])/close[i-1] for i in range(1, len(close))]

def stats(close):
    rets = daily_returns(close); n = len(rets)
    cum = (close[-1]-close[0])/close[0]
    mdd = max_drawdown(close)
    mean = sum(rets)/n
    std  = math.sqrt(sum((r-mean)**2 for r in rets)/n)
    ann_vol = std*math.sqrt(252)
    sharpe  = (mean*252)/(std*math.sqrt(252)) if std>0 else 0.0
    win = sum(1 for r in rets if r>0)/n
    return cum, mdd, ann_vol, sharpe, win

mc = Client("<你的证书>")   # 证书从环境变量读取，不写死在代码里
rows = get_close_series(mc, "000001", days=120)
cum, mdd, ann_vol, sharpe, win = stats([r["c"] for r in rows])
print(f"累计收益率 {cum*100:.2f}%  最大回撤 {mdd*100:.2f}%")
print(f"年化波动率 {ann_vol*100:.2f}%  夏普 {sharpe:.2f}  胜率 {win*100:.2f}%")

累计收益率   :   0.27 %    年化波动率 :  18.04 %
最大回撤     : -12.76 %    夏普(简化) :   0.14
胜率         :  46.91 %  (38/81 个交易日上涨)