backtest: implement metrics and vectorized backtester#10
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marwinsteiner merged 5 commits intomainfrom Feb 22, 2026
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Create src/sysls/backtest/ and tests/backtest/ packages in preparation for metrics and vectorized backtester modules.
Pure, stateless metric functions operating on numpy arrays: - compute_returns / compute_log_returns - sharpe_ratio, sortino_ratio, calmar_ratio - max_drawdown, drawdown_series - total_return, annualized_return, annualized_volatility - win_rate, profit_factor Also defines TradeRecord and BacktestResult Pydantic models, plus summarize_backtest convenience function.
60 tests covering all metric functions with known inputs/outputs, edge cases (empty arrays, single element, all zeros, division by zero), Pydantic model construction, immutability, and JSON serialization round-trips.
profit_factor now returns float('inf') for all-winners (was incorrectly
0.0). Added ConfigDict(ser_json_inf_nan='constants') for JSON round-trip.
Added tests: total-loss annualized return, empty equity summarize.
Updated Sortino docstring to document population-based convention.
vectorbt-inspired backtester operating on numpy arrays: signal conventions (1=long, -1=short, 0=flat), equity curve computation, per-trade PnL extraction, commission and slippage models. run_vectorized_backtest() returns BacktestResult via summarize_backtest. 35 tests covering long/short, commissions, slippage, edge cases.
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Summary
summarize_backtest()convenience builder.TradeRecordandBacktestResultfrozen Pydantic models.run_vectorized_backtest()→BacktestResult.profit_factorreturnsfloat('inf')for all-winners (was incorrectly 0.0). AddedConfigDict(ser_json_inf_nan='constants')for JSON round-trip. Sortino docstring documents population-based convention. Added total-loss and empty-equity edge-case tests.Stats
Test plan