| """对照任务（计划书 §9，D15 预注册）：底仓 60% + 网格 40% vs v2.1 同窗口对比。 |
| |
| 底仓子账户 = v2.1 规则原样（引擎 V0=60%；引擎对规模严格线性，已断言校验）。 |
| 网格子账户按 §9.2： |
| 锚点随底仓 ENTRY；档位金额 = 锚点日网格净值/12（本轮固定）； |
| 买入档 = 上一锚点/成交价×(1−0.5×当月σ)（在锚点/成交/恢复时一步算定）； |
| 挂单卖出档 = 成交价×(1+0.5×成交日当月σ)（成交即挂，不重定价）； |
| q_eff≥90 停新买；底仓退出模式停买停挂、并在底仓退出卖出日同步卖 1/3（FIFO）、 |
| 底仓残值清仓日全清；12 档耗尽停用，价格收复最近成交档后重开梯子。 |
| 执行纪律同主任务：收盘触发、次日 PM 成交、单边 0.05%。 |
| |
| 用法：python grid.py |
| 判读（预注册 §9.3）：任一震荡窗口年化增量 < +1% 或任一趋势窗口额外回撤 > 3pp → 不增价值。 |
| """ |
| import csv |
| import json |
| from pathlib import Path |
|
|
| import matplotlib |
| matplotlib.use("Agg") |
| import matplotlib.pyplot as plt |
|
|
| import engine as E |
| from run import one_stats, stats_full |
|
|
| matplotlib.rcParams["font.sans-serif"] = ["Microsoft YaHei", "SimHei", "DejaVu Sans"] |
| matplotlib.rcParams["axes.unicode_minus"] = False |
|
|
| HERE = Path(__file__).resolve().parent |
| START, END = "2013-01-01", "2026-09-07" |
| GRID_SHARE, N_SLOTS, STEP = 0.40, 12, 0.5 |
|
|
| |
| WINDOWS = [("震荡 2015-2016", "2015-01-01", "2016-12-31", "osc"), |
| ("趋势 2013-2015", "2013-01-01", "2015-12-31", "trend"), |
| ("趋势 2022-2024", "2022-01-01", "2024-12-31", "trend")] |
|
|
|
|
| def main(): |
| S = E.build_signals() |
| v2_rows = list(csv.DictReader(open(HERE / "results" / "final" / "curve.csv", encoding="utf-8"))) |
| v2_V = {r["date"]: float(r["V"]) for r in v2_rows} |
| bh_V = {r["date"]: float(r["bh_V"]) for r in v2_rows} |
|
|
| _, _, base_data = E.run(start=START, end=END, target_vol_ann=12.0, |
| V0=(1 - GRID_SHARE) * 10000.0, tag="grid_base") |
| base_curve, base_trades = base_data["curve"], base_data["trades"] |
| base_V = {c["date"]: c["V"] for c in base_curve} |
| |
| lin = max(abs(base_V[c["date"]] - (1 - GRID_SHARE) * v2_V[c["date"]]) / v2_V[c["date"]] |
| for c in base_curve) |
| assert lin < 1e-9, f"底仓与 0.6×v2 不一致: {lin}" |
|
|
| pm = dict(E.load_pm()) |
| days = [(c["date"], pm[c["date"]]) for c in base_curve] |
| entry_px = {t["date"]: t["price"] for t in base_trades if t["reason"] == "ENTRY"} |
| exit_days = {t["date"] for t in base_trades if t["reason"] == "EXIT pace<102"} |
| final_days = {t["date"] for t in base_trades if t["reason"].endswith("+final")} |
| mode_of = {c["date"]: c["mode"] for c in base_curve} |
|
|
| |
| cash = GRID_SHARE * 10000.0 |
| lots = [] |
| next_buy = None |
| lot_amt = None |
| active = False |
| exhausted = False |
| ladder_fills = 0 |
| last_fill = None |
| pending = [] |
| gtrades = [] |
| gcurve = [] |
|
|
| for j, (d, px) in enumerate(days): |
| ym = d[:7] |
| s = S["sig"].get(ym) |
| q_eff = E.month_q_eff(S, S["qrows"], ym) |
| exiting = mode_of.get(d, "IN") == "EXITING" |
|
|
| |
| still = [] |
| for pj, kind, ref in pending: |
| if pj != j: |
| still.append((pj, kind, ref)) |
| continue |
| if kind == "sell": |
| lot = lots[ref] |
| lot["pending"] = False |
| if exiting or d in exit_days or d in final_days or lot["units"] <= 1e-12: |
| continue |
| amt = lot["units"] * px |
| cash += amt * (1 - E.COST) |
| lot["units"] = 0.0 |
| gtrades.append({"date": d, "action": "GRID_SELL", "reason": "档位+1格", |
| "amount_usd": round(amt, 2), "price": px}) |
| else: |
| if exiting or not active: |
| continue |
| amt = min(ref, cash / (1 + E.COST)) |
| if amt <= 1e-9: |
| continue |
| cash -= amt * (1 + E.COST) |
| lots.append({"units": amt / px, "fill": px, |
| "sell_level": px * (1 + STEP * s), "pending": False}) |
| ladder_fills += 1 |
| last_fill = px |
| next_buy = px * (1 - STEP * s) |
| if ladder_fills >= N_SLOTS: |
| exhausted = True |
| gtrades.append({"date": d, "action": "GRID_BUY", "reason": f"第{ladder_fills}/{N_SLOTS}档", |
| "amount_usd": round(amt, 2), "price": px}) |
| pending = still |
| lots = [l for l in lots if l["units"] > 1e-12] |
|
|
| |
| if d in entry_px: |
| anchor = entry_px[d] |
| lots = [] |
| lot_amt = cash / N_SLOTS |
| active, exhausted, ladder_fills = True, False, 0 |
| last_fill = anchor |
| next_buy = anchor * (1 - STEP * s) if s else None |
| gtrades.append({"date": d, "action": "GRID_ANCHOR", "reason": f"底仓ENTRY 锚{anchor:.0f} 每档{lot_amt:.0f}", |
| "amount_usd": 0, "price": anchor}) |
| elif d in final_days: |
| amt = sum(l["units"] for l in lots) * px |
| if amt > 1e-9: |
| cash += amt * (1 - E.COST) |
| gtrades.append({"date": d, "action": "GRID_SELL", "reason": "底仓残值清仓→网格全清", |
| "amount_usd": round(amt, 2), "price": px}) |
| lots, active, next_buy = [], False, None |
| elif d in exit_days: |
| units = sum(l["units"] for l in lots) |
| target = units / 3.0 |
| rem = target |
| for l in lots: |
| if rem <= 1e-12: |
| break |
| take = min(l["units"], rem) |
| cash += take * px * (1 - E.COST) |
| l["units"] -= take |
| rem -= take |
| lots = [l for l in lots if l["units"] > 1e-12] |
| gtrades.append({"date": d, "action": "GRID_SELL", "reason": "同步退出1/3", |
| "amount_usd": round(target * px, 2), "price": px}) |
|
|
| |
| if active and not exiting and d not in exit_days: |
| for i, l in enumerate(lots): |
| if not l["pending"] and px >= l["sell_level"]: |
| pending.append((j + 1, "sell", i)) |
| l["pending"] = True |
|
|
| |
| if (active and not exiting and not exhausted and ladder_fills < N_SLOTS |
| and next_buy is not None and px <= next_buy |
| and (q_eff is None or q_eff < 90) |
| and not any(k == "buy" for _, k, _ in pending)): |
| pending.append((j + 1, "buy", lot_amt)) |
|
|
| |
| if exhausted and last_fill is not None and px > last_fill: |
| exhausted, ladder_fills = False, 0 |
| next_buy = px * (1 - STEP * s) if s else None |
|
|
| units = sum(l["units"] for l in lots) |
| gcurve.append({"date": d, "grid_V": cash + units * px}) |
|
|
| |
| out = HERE / "results" / "grid" |
| out.mkdir(parents=True, exist_ok=True) |
| dates = [c["date"] for c in gcurve] |
| gV = {c["date"]: c["grid_V"] for c in gcurve} |
| variant = {d: gV[d] + base_V[d] for d in dates} |
| control = {d: base_V[d] + GRID_SHARE * 10000.0 for d in dates} |
|
|
| with open(out / "variant_curve.csv", "w", newline="", encoding="utf-8") as f: |
| w = csv.writer(f) |
| w.writerow(["date", "v2", "variant", "control", "bh", "grid_V"]) |
| for d in dates: |
| w.writerow([d, round(v2_V[d], 4), round(variant[d], 4), |
| round(control[d], 4), round(bh_V[d], 4), round(gV[d], 4)]) |
| with open(out / "grid_trades.csv", "w", newline="", encoding="utf-8") as f: |
| w = csv.DictWriter(f, fieldnames=["date", "action", "reason", "amount_usd", "price"]) |
| w.writeheader() |
| w.writerows(gtrades) |
|
|
| def series(m): |
| return [m[d] for d in dates] |
|
|
| rows, osc_ok, trend_ok = [], True, True |
| for name, lo, hi, kind in WINDOWS: |
| idx = [i for i, d in enumerate(dates) if lo <= d <= hi] |
| seg = lambda m: [m[dates[i]] for i in idx] |
| sv, bv = one_stats(seg(variant)), one_stats(seg(v2_V)) |
| delta = sv["cagr"] - bv["cagr"] |
| extra_dd = abs(sv["maxdd"]) - abs(bv["maxdd"]) |
| ok = (delta >= 0.01) if kind == "osc" else (extra_dd <= 0.03) |
| if kind == "osc": |
| osc_ok = osc_ok and ok |
| else: |
| trend_ok = trend_ok and ok |
| rows.append({"window": name, "kind": kind, "v2_cagr": bv["cagr"], "var_cagr": sv["cagr"], |
| "delta_cagr": delta, "v2_maxdd": bv["maxdd"], "var_maxdd": sv["maxdd"], |
| "extra_dd": extra_dd, "pass": ok}) |
|
|
| summary = {"windows": rows, "osc_all_pass": osc_ok, "trend_all_pass": trend_ok, |
| "verdict": "采纳（v3 候选）" if (osc_ok and trend_ok) else "不增价值，不采纳", |
| "grid_sleeve": one_stats(series(gV)), |
| "full": {"v2": one_stats(series(v2_V)), "variant": one_stats(series(variant)), |
| "control": one_stats(series(control)), "bh": one_stats(series(bh_V))}, |
| "n_grid_trades": sum(1 for t in gtrades if t["action"].startswith("GRID_") |
| and t["action"] != "GRID_ANCHOR")} |
| (out / "grid_summary.json").write_text(json.dumps(summary, ensure_ascii=False, indent=1, default=str), |
| encoding="utf-8") |
|
|
| |
| fig, ax = plt.subplots(figsize=(11.5, 6), dpi=150) |
| ax.plot(dates, series(bh_V), lw=1.1, color="#b8b8b8", label="买入持有") |
| ax.plot(dates, series(v2_V), lw=1.5, color="#c8912a", label="v2.1（100%）") |
| ax.plot(dates, series(control), lw=1.3, color="#4569a0", ls="--", label="0.6×v2 + 40%现金（对照）") |
| ax.plot(dates, series(variant), lw=1.5, color="#7a4ea3", label="底仓60% + 网格40%") |
| ax.set_yscale("log") |
| ax.axvline("2026-01-01", color="#4569a0", ls=":", lw=1) |
| ax.annotate("2026 样本外 →", xy=(0.868, 0.045), xycoords="axes fraction", fontsize=9, color="#4569a0") |
| tick_idx = [i for i, d in enumerate(dates) if d[5:7] == "01" and (i == 0 or dates[i - 1][5:7] != "01")] |
| step = max(1, len(tick_idx) // 8) |
| ax.set_xticks([dates[i] for i in tick_idx[::step]]) |
| ax.set_xticklabels([dates[i][:4] for i in tick_idx[::step]], fontsize=9) |
| ax.set_ylabel("净值（V0 = 10,000，对数轴）", fontsize=10) |
| ax.set_title(f"对照任务：底仓+网格 变体 {dates[0]} → {dates[-1]}（USD，成本后）", fontsize=12) |
| ax.grid(alpha=0.25, which="both") |
| ax.legend(loc="upper left", fontsize=9) |
| fig.tight_layout() |
| fig.savefig(out / "grid_equity.png") |
|
|
| |
| gs = summary["grid_sleeve"] |
| print(f"网格子账户: {summary['n_grid_trades']} 笔 期末 {series(gV)[-1]:.0f}（V0 4,000） " |
| f"年化 {gs['cagr']:+.2%} 回撤 {gs['maxdd']:.1%}") |
| print(f"{'窗口':16}{'v2年化':>9}{'变体年化':>9}{'增量':>8}{'v2回撤':>9}{'变体回撤':>9}{'额外回撤':>10} 判定") |
| for r in rows: |
| print(f"{r['window']:16}{r['v2_cagr']:>+9.1%}{r['var_cagr']:>+9.1%}{r['delta_cagr']:>+8.1%}" |
| f"{r['v2_maxdd']:>9.1%}{r['var_maxdd']:>9.1%}{r['extra_dd']:>+9.1f}pp " |
| f"{'PASS' if r['pass'] else 'FAIL'}") |
| print(f"判读（预注册 §9.3）: {summary['verdict']}") |
| f_ = summary["full"] |
| print(f"全期: v2 {f_['v2']['cagr']:+.1%}/回撤{f_['v2']['maxdd']:.1%} " |
| f"变体 {f_['variant']['cagr']:+.1%}/回撤{f_['variant']['maxdd']:.1%} " |
| f"对照 {f_['control']['cagr']:+.1%}/回撤{f_['control']['maxdd']:.1%} " |
| f"持有 {f_['bh']['cagr']:+.1%}/回撤{f_['bh']['maxdd']:.1%}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
