121 lines
5.1 KiB
Python
121 lines
5.1 KiB
Python
"""未了结仓位的浮动亏损轨迹 + "时间止损"反事实对照（只做分析，不改策略代码）。
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用法： py -3.14 -B analysis/etf/drawdown.py
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"""
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import sys
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from pathlib import Path
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HERE = Path(__file__).resolve().parent
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sys.path.insert(0, str(HERE))
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# Windows 控制台默认 GBK，报告里用了「−」等字符，统一切到 UTF-8 输出。
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try:
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sys.stdout.reconfigure(encoding="utf-8", errors="replace")
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except Exception:
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pass
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from analysis import round_trips # noqa: E402
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from backtest import SYMBOLS, analyze, fetch_daily, simulate # noqa: E402
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data = {code: fetch_daily(code) for code in SYMBOLS}
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result = simulate(data)
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stats = analyze(result)
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by_date = {code: {bar["date"]: bar for bar in data[code]} for code in data}
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# 逐日还原：每个标的的"本轮累计净买入成本"与"当前持仓量"
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cost = {code: 0.0 for code in data}
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volume = {code: 0 for code in data}
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fills_by_day = {}
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for fill in result["fills"]:
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fills_by_day.setdefault(fill.day.strftime("%Y%m%d"), []).append(fill)
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track = {code: [] for code in data}
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for day, equity, market_value, cash in result["curve"]:
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stamp = day.strftime("%Y%m%d")
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for fill in fills_by_day.get(stamp, []):
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amount = fill.price * fill.volume
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if fill.side == "BUY":
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cost[fill.code] += amount
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volume[fill.code] += fill.volume
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else:
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# 卖出按比例冲减成本基数（与均价法一致）
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if volume[fill.code] > 0:
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ratio = fill.volume / volume[fill.code]
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cost[fill.code] *= max(0.0, 1 - ratio)
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volume[fill.code] -= fill.volume
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for code in data:
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bar = by_date[code].get(stamp)
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if bar is None:
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continue
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track[code].append((day, cost[code], bar["close"], volume[code]))
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print("== 持仓期间的浮动盈亏（均价法：市值 − 本轮累计净买入成本）==")
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print(f"{'标的':11} {'持仓天数':>8} {'最长连续浮亏天数':>16} {'最深浮亏':>10} {'最深浮亏%':>10} {'期末浮亏':>10}")
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for code in data:
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rows = [(day, c, close, vol) for day, c, close, vol in track[code] if vol > 0 and c > 0]
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if not rows:
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print(f"{code:11} {0:8} {'-':>16} {'-':>10} {'-':>10} {'-':>10}")
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continue
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pnl = [(day, close * vol - c, (close * vol - c) / c * 100) for day, c, close, vol in rows]
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longest = cur = 0
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for _, amount, _ in pnl:
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cur = cur + 1 if amount < 0 else 0
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longest = max(longest, cur)
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worst_amt = min(p[1] for p in pnl)
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worst_pct = min(p[2] for p in pnl)
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print(f"{code:11} {len(rows):8} {longest:16} {worst_amt:10.0f} {worst_pct:9.2f}% {pnl[-1][1]:10.0f}")
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print()
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print("== 持有天数分布（完整轮次）==")
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trips = round_trips(result["fills"])
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buckets = {"≤1天": 0, "2-3天": 0, "4-7天": 0, "8-15天": 0, ">15天": 0}
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for t in trips:
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d = t.days
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key = "≤1天" if d <= 1 else "2-3天" if d <= 3 else "4-7天" if d <= 7 else "8-15天" if d <= 15 else ">15天"
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buckets[key] += 1
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print(" ", buckets)
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print()
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print("== 时间止损反事实：把浮亏且持有超过 N 天的仓位按当日收盘价平掉 ==")
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print(f"{'规则':22} {'权益变动':>10} {'收益率':>7} {'最大回撤':>8} {'占用ROI':>8} {'佣金':>8} {'强平次数':>8}")
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def with_time_stop(limit: int) -> tuple[float, int]:
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"""在没有时间止损的结果上，找出"浮亏且连续持有 > limit 天"的仓位并按其后的实际
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主出口价格之差估算影响（近似：直接扣掉该仓位到期末的浮亏差额）。"""
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stops = 0
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delta = 0.0
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for code in data:
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rows = [(day, c, close, vol) for day, c, close, vol in track[code] if vol > 0 and c > 0]
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if not rows:
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continue
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start = rows[0][0]
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for index, (day, c, close, vol) in enumerate(rows):
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held = (day - start).days
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if held > limit and close * vol - c < 0:
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# 反事实：在当天以收盘价平掉，之后不再持有该标的
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loss = close * vol - c
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final_close = rows[-1][2]
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avoid = (final_close - close) * vol
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delta += loss * 0 - avoid # 平仓后避免了后续价格变动
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stops += 1
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break
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return delta, stops
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for limit in (0, 5, 10, 20):
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if limit == 0:
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print(f"{'不止损（现配置）':22} {stats['final_equity'] - 500000:10.2f} {stats['return_pct']:6.2f}% "
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f"{stats['max_dd_pct']:7.2f}% "
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f"{(stats['final_equity'] - 500000) / stats['avg_deployed'] * 100:7.2f}% "
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f"{stats['fees']:8.2f} {0:8}")
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continue
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delta, stops = with_time_stop(limit)
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equity = stats["final_equity"] - 500000 + delta
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print(f"{'持有>' + str(limit) + '天且浮亏即平':22} {equity:10.2f} {equity / 500000 * 100:6.2f}% "
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f"{stats['max_dd_pct']:7.2f}% {equity / stats['avg_deployed'] * 100:7.2f}% "
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f"{stats['fees']:8.2f} {stops:8}")
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print()
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print("注：上表是「平仓后不再持有该标的」的粗略反事实，只用于判断时间止损的方向性收益，")
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print(" 不是精确回测（未重算后续轮次与资金复用）。")
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