Files
ftdt-quant-lab/common/metrics.py
T
ramseshk a6905f2691 Fix win_rate() for Kalman Pairs: add net_pnl/gross_pnl field support
Bug: win_rate() only checked pnl_net/pnl_gross/pnl fields,
but Kalman backtests save trades with net_pnl/gross_pnl (underscore-first).
Result: all 4 Kalman assets showed 0% win on 27-35 trades.

After fix:
  BTC: 0% → 45% (16/35)
  ETH: 0% → 47% (16/34)
  HYPE: 0% → 51% (14/27)
  VVV: 0% → 57% (19/33)

Also corrected paper trader coin assignments for Mean Reversion
and Momentum Breakout (was BTC, should be ETH).
2026-08-06 08:26:35 +00:00

47 lines
1.3 KiB
Python

"""
Performance metrics.
Sharpe ratio, Sortino ratio, max drawdown, win rate.
Standard toolbox for evaluating a trading strategy.
"""
import numpy as np
def sharpe(returns: list[float], rf: float = 0.0, periods: int = 365) -> float:
if len(returns) < 2:
return 0.0
excess = np.mean(returns) - rf
std = np.std(returns, ddof=1)
return (excess / std) * np.sqrt(periods) if std > 0 else 0.0
def sortino(returns: list[float], rf: float = 0.0, periods: int = 365) -> float:
if len(returns) < 2:
return 0.0
excess = np.mean(returns) - rf
downside = [r for r in returns if r < 0]
d_std = np.std(downside, ddof=1) if downside else 0.0
return (excess / d_std) * np.sqrt(periods) if d_std > 0 else 0.0
def max_drawdown(equity: list[float]) -> float:
if not equity:
return 0.0
peak = equity[0]
worst = 0.0
for v in equity:
if v > peak:
peak = v
dd = (peak - v) / peak if peak > 0 else 0.0
worst = max(worst, dd)
return worst
def win_rate(trades: list[dict]) -> float:
if not trades:
return 0.0
tp = sum(1 for t in trades if (
(t.get("pnl_net") or t.get("net_pnl") or t.get("pnl_gross") or t.get("gross_pnl") or t.get("pnl", 0)) > 0
))
return tp / len(trades)