Spaces:
Runtime error
Runtime error
File size: 2,654 Bytes
8f1601b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 | from __future__ import annotations
import pandas as pd
from backtest.vol_backtest import backtest_realized_vol_signal
def optimize_volatility_signal(
prices: pd.Series,
signal: str = "long_vol",
short_windows: tuple[int, ...] = (5, 10, 15),
long_windows: tuple[int, ...] = (20, 30, 60),
holding_days_options: tuple[int, ...] = (3, 5, 10),
) -> dict:
runs = []
for short_window in short_windows:
for long_window in long_windows:
if short_window >= long_window:
continue
for holding_days in holding_days_options:
result = backtest_realized_vol_signal(
prices=prices,
short_window=short_window,
long_window=long_window,
holding_days=holding_days,
signal=signal,
)
runs.append(
{
"short_window": short_window,
"long_window": long_window,
"holding_days": holding_days,
"trade_count": result["trade_count"],
"win_rate": result["win_rate"],
"total_return_proxy": result["total_return_proxy"],
"max_drawdown_proxy": result["max_drawdown_proxy"],
"avg_trade_pnl_proxy": result["avg_trade_pnl_proxy"],
}
)
runs.sort(
key=lambda run: (
run["total_return_proxy"],
-abs(run["max_drawdown_proxy"]),
run["win_rate"],
),
reverse=True,
)
best = runs[0] if runs else None
baseline = next(
(
run
for run in runs
if run["short_window"] == 10 and run["long_window"] == 30 and run["holding_days"] == 5
),
runs[0] if runs else None,
)
return {
"signal": signal,
"best": best,
"baseline": baseline,
"top_runs": runs[:10],
"metrics_delta": (
{
"total_return_proxy_delta": best["total_return_proxy"] - baseline["total_return_proxy"],
"win_rate_delta": best["win_rate"] - baseline["win_rate"],
"max_drawdown_proxy_delta": best["max_drawdown_proxy"] - baseline["max_drawdown_proxy"],
}
if best and baseline
else None
),
"anti_overfit_note": (
"This is an in-sample parameter scan. Use walk-forward or out-of-sample validation "
"before trusting optimized parameters."
),
}
|