- Add --cov and --cov-fail-under=50 to CI pytest command
- Replace hardcoded avg_holding_days=5.0 with FIFO-based calculation
from actual trade datetime pairs (handles int and Timestamp types)
- Vectorize _datetime_to_int using pd.to_datetime().strftime()
instead of Python for-loop (~100-200x faster on large arrays)
- Add 3 new test cases: weighted holding days, no datetime fallback,
only-buys edge case
- pyproject.toml: add mypy overrides for pandas/tabulate/matplotlib stubs,
disable strict checking for vendored MyTT library
- config.py: use cast() for dict[str, Any] .get() returns
- beichi.py: widen _calc_bi_force param to BI | XD, import XD
- backtest/cli.py: split combo/single strategy into separate typed variables
- backtest/combo.py: add bool_array() helper for numpy return types
- chanlun/analyser.py: type ignore for pandas row access, fix dict type arg
- unified.py: change fields param from object to Any
- ex/mac_client.py: add type args to list literals
- cli/cmd_offline.py: wrap int market as Market enum before API call
- cli/cmd_chanlun.py: fix dict type arg
- offline/write_*.py: explicit int() cast for struct.unpack returns
- MyTT.py: fix line-too-long comments, UP038 isinstance syntax
- tests: fix E712 (==False → ~mask), E741 (noqa), F841, import sorting
- ruff format applied across codebase
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Previous formula was: max(absolute_drawdown) / initial_capital, which
exceeds 100% when the portfolio grows then drops (e.g. from 600k to 300k
on a 100k initial = 300% drawdown, which is nonsensical).
Fixed to use drawdown_pct (drawdown / peak) which is always in [0, 1].
This correctly measures the maximum percentage drop from the highest
equity peak, matching the standard financial definition.
Also added regression test: test_max_drawdown_never_exceeds_100_pct.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
- Implement PerformanceAnalyzer class with compute() method
- Calculate 19 performance metrics: total_return, annual_return, max_drawdown,
max_dd_duration, sharpe, sortino, calmar, trade statistics, and volatility
- Handle edge cases: empty data, no negative returns (sortino=999), no drawdown (calmar=999)
- Add 20 comprehensive unit tests covering all metrics
- Type annotations use NDArray pattern for mypy strict compliance
- All tests pass, mypy and ruff checks clean
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Justin Gu