37 lines
1.3 KiB
Python
37 lines
1.3 KiB
Python
import numpy as np
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import pandas as pd
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TRADING_DAYS_PER_YEAR = 252
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def summarize_equity_window(equity: pd.Series, strategy: str, window_years: int | float) -> dict:
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"""Summarize a strategy equity curve over a trailing trading-day window."""
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window_days = max(int(window_years * TRADING_DAYS_PER_YEAR), 1)
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window_equity = equity.tail(window_days + 1).dropna()
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if len(window_equity) < 2:
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return {
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"strategy": strategy,
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"window_years": window_years,
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"CAGR": np.nan,
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"Sharpe": np.nan,
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"MaxDD": np.nan,
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"TotalRet": np.nan,
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}
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daily = window_equity.pct_change(fill_method=None).dropna()
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total_ret = window_equity.iloc[-1] / window_equity.iloc[0] - 1
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years = len(daily) / TRADING_DAYS_PER_YEAR
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cagr = (window_equity.iloc[-1] / window_equity.iloc[0]) ** (1 / years) - 1 if years > 0 else np.nan
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vol = daily.std() * np.sqrt(TRADING_DAYS_PER_YEAR)
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sharpe = (daily.mean() * TRADING_DAYS_PER_YEAR) / vol if vol > 0 else 0.0
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max_dd = (window_equity / window_equity.cummax() - 1).min()
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return {
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"strategy": strategy,
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"window_years": window_years,
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"CAGR": cagr,
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"Sharpe": sharpe,
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"MaxDD": max_dd,
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"TotalRet": total_ret,
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}
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