85 lines
2.8 KiB
Python
85 lines
2.8 KiB
Python
from __future__ import annotations
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from typing import Any
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from backend.features.screener.engine import execute_formula
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MINIMUM_STABLE_SAMPLES = 20
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FORWARD_TRADING_DAYS = 3
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def rolling_backtest(
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snapshots: list[dict[str, Any]], formula: dict[str, Any]
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) -> dict[str, Any]:
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returns: list[float] = []
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evaluated_dates: list[str] = []
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for index in range(max(0, len(snapshots) - FORWARD_TRADING_DAYS)):
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current = snapshots[index]
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future = snapshots[index + FORWARD_TRADING_DAYS]
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outcome = execute_formula(current["rows"], formula, current["coverage"])
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if outcome["status"] not in {"completed", "no_signal"}:
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continue
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evaluated_dates.append(str(current["trade_date"]))
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future_closes = {
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str(row.get("identifier")): _positive(row.get("close"))
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for row in future["rows"]
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}
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for candidate in outcome["items"]:
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entry = _positive(candidate.get("close"))
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future_close = future_closes.get(str(candidate.get("identifier")))
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if entry is None or future_close is None:
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continue
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returns.append((future_close / entry - 1) * 100)
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sample_size = len(returns)
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stable = sample_size >= MINIMUM_STABLE_SAMPLES
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period_start = evaluated_dates[0] if evaluated_dates else None
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period_end = evaluated_dates[-1] if evaluated_dates else None
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return {
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"sample_size": sample_size,
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"evaluated_dates": len(evaluated_dates),
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"stable": stable,
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"win_rate": (
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round(sum(value > 0 for value in returns) / sample_size * 100, 1)
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if stable
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else None
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),
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"average_return_3d": (
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round(sum(returns) / sample_size, 2) if stable else None
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),
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"period_start": period_start,
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"period_end": period_end,
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"message": (
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"历史估计已达到最低样本要求"
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if stable
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else (
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f"小样本：当前{sample_size}个有效样本，"
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f"满{MINIMUM_STABLE_SAMPLES}个后显示胜率与平均收益"
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)
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),
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}
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def attach_historical_estimate(
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run: dict[str, Any], backtest: dict[str, Any] | None
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) -> dict[str, Any]:
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run["backtest"] = backtest
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if not backtest or not backtest.get("stable"):
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return run
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win_rate = float(backtest["win_rate"])
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for item in run.get("items") or []:
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score = item.get("score_display")
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item["historical_estimate"] = (
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round(win_rate * 0.65 + float(score) * 0.35, 1)
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if isinstance(score, (int, float))
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else None
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)
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return run
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def _positive(value: Any) -> float | None:
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try:
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number = float(value)
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except (TypeError, ValueError):
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return None
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return number if number > 0 else None
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