43 lines
1.1 KiB
Python
43 lines
1.1 KiB
Python
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from __future__ import annotations
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from itertools import product
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import pandas as pd
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from .engine import EngineConfig, run_factor_engine, summary_metrics
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def optimize_grid(
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df: pd.DataFrame,
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factor_expression: str,
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freqs: list[str],
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long_qs: list[float],
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short_qs: list[float],
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long_short_options: list[bool],
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) -> pd.DataFrame:
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rows = []
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for freq, lq, sq, ls in product(freqs, long_qs, short_qs, long_short_options):
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cfg = EngineConfig(
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factor_expression=factor_expression,
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rebalance_frequency=freq,
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long_quantile=lq,
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short_quantile=sq,
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long_short=ls,
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)
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curve, _ = run_factor_engine(df, cfg)
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m = summary_metrics(curve)
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rows.append(
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{
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"rebalance_frequency": freq,
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"long_quantile": lq,
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"short_quantile": sq,
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"long_short": ls,
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**m,
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}
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)
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out = pd.DataFrame(rows)
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if out.empty:
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return out
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return out.sort_values(["sharpe", "cagr"], ascending=[False, False]).reset_index(drop=True)
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