第 30 篇：二八轮动经典 ETF 轮动实战

import numpy as np
import pandas as pd

# ---------- 1. 造三只风格分明的模拟 ETF 净值 ----------
def make_etf(n, drift, vol, seed, base=1.0):
    rng = np.random.default_rng(seed)
    ret = rng.normal(drift, vol, n)
    nav = base * np.exp(np.cumsum(ret))
    idx = pd.bdate_range("2020-01-01", periods=n)
    return pd.Series(nav, index=idx, name="nav")

n = 252 * 5  # 2020-2024 约 5 年
# 大盘 ETF：前半弱后半强；小盘 ETF：前半强后半弱 → 制造轮动空间
r1 = np.concatenate([np.random.default_rng(1).normal(0.0002, 0.012, n // 2),
                     np.random.default_rng(2).normal(0.0008, 0.013, n - n // 2)])
r2 = np.concatenate([np.random.default_rng(3).normal(0.0008, 0.015, n // 2),
                     np.random.default_rng(4).normal(0.0001, 0.014, n - n // 2)])
idx = pd.bdate_range("2020-01-01", periods=n)
large = pd.Series(1 * np.exp(np.cumsum(r1)), index=idx, name="large")
small = pd.Series(1 * np.exp(np.cumsum(r2)), index=idx, name="small")
bond = make_etf(n, 0.0001, 0.002, seed=5)  # 债券 ETF：低波缓涨

# ---------- 2. 月末信号 → 次月持仓 → 策略日收益 ----------
def rotate_28(large, small, bond, mom_days=20, fee=0.001):
    px = pd.concat([large, small, bond], axis=1)
    mom = px.pct_change(mom_days)             # 过去20日涨幅
    ret = px.pct_change()
    # 月末交易日（每月最后一个交易日）
    month_end = px.groupby([px.index.year, px.index.month]).tail(1).index
    plan = {}                                  # {下月首个交易日: 目标标的}
    for d in month_end:
        m = mom.loc[d]
        if m["large"] >= m["small"] and m["large"] > 0:
            tgt = "large"
        elif m["small"] > m["large"] and m["small"] > 0:
            tgt = "small"
        else:
            tgt = "bond"                       # 都不强 → 避险
        nxt = px.index[px.index > d]
        if len(nxt) > 0:
            plan[nxt[0]] = tgt                 # 次月首个交易日建仓
    holding = pd.Series(index=px.index, dtype="object")
    cur = None
    for d in px.index:
        cur = plan.get(d, cur)                 # 有计划则切换，否则维持
        holding[d] = cur
    daily = pd.Series(0.0, index=px.index)
    for d in px.index[1:]:
        prev_h = holding[px.index[px.index < d][-1]]
        if holding[d] != prev_h:               # 换仓日：扣一次双边成本
            daily[d] -= fee
        daily[d] += ret[d][holding[d]]
    return daily.fillna(0), holding

daily, holding = rotate_28(large, small, bond)

# ---------- 3. 评价：净值、年化、最大回撤，对比买入持有 ----------
def perf(ret, rf=0.02):
    nav = (1 + ret).cumprod()
    years = len(ret) / 252
    ann = nav.iloc[-1] ** (1 / years) - 1
    sharpe = (ret.mean() * 252 - rf) / (ret.std() * np.sqrt(252))
    dd = (nav / nav.cummax() - 1).min()
    return ann, sharpe, dd

for name, r in [("二八轮动", daily),
                ("一直拿大盘", large.pct_change().fillna(0)),
                ("一直拿小盘", small.pct_change().fillna(0))]:
    ann, sh, dd = perf(r)
    print(f"{name}: 年化(示意)={ann:.1%}, 夏普(示意)={sh:.2f}, 回撤(示意)={dd:.1%}")
print("各月持仓分布:", holding.value_counts().to_dict())

示例输出（示意，模拟行情结果，不代表真实市场）:
二八轮动: 年化(示意)=8.9%, 夏普(示意)=0.86, 回撤(示意)=-9.6%
一直拿大盘: 年化(示意)=6.2%, 夏普(示意)=0.44, 回撤(示意)=-21.4%
一直拿小盘: 年化(示意)=4.7%, 夏普(示意)=0.31, 回撤(示意)=-26.8%
各月持仓分布: {'large': 31个月, 'small': 22个月, 'bond': 7个月}