| name | factor-backtest |
| description | Combine a factor library into a composite signal and quintile-backtest it under transaction costs — long-short return, monotonicity, turnover, and tearsheets. Use for the portfolio-level view that single-factor IC does not give. Triggers on "backtest", "composite signal", "combine factors", "long-short return", "portfolio", "quintile", "tearsheet", "transaction costs". |
Factor Backtest
A library of individually-decent factors is not a strategy. This skill combines them into one composite signal and backtests the portfolio that signal implies — the level at which transaction costs and capacity actually bite.
Workflow
1. Combine and backtest
factorminer combine output/run1/factor_library.json \
--data path/to/market_data.csv \
--method all --fit-period train --eval-period test
--method — equal-weight, ic-weighted, orthogonal, or all to compare every method.--fit-period — split used to fit weights / run selection (use train).--eval-period — split used to score the composite (use test).--selection — optional pre-filter: lasso, stepwise, xgboost, or none.--top-k — keep only the top-K factors before combining.
The report gives composite IC Mean, ICIR, Long-Short return, Monotonicity, and Avg Turnover.
2. Generate tearsheets
For the visual portfolio view — quintile returns, IC time series, correlation heatmap:
factorminer -o output/run1 visualize output/run1/factor_library.json \
--data market_data.csv --period test --tearsheet --quintile --correlation
What to look for
- Monotonicity — quintile returns should step up Q1→Q5. A non-monotone composite is fragile regardless of headline IC.
- Long-short return net of turnover — high
Avg Turnover means the gross return is optimistic; FactorMiner's transaction-cost model is what makes the net number honest.
- Method spread — if
orthogonal and equal-weight disagree sharply, the library has redundant or unstable factors; revisit factor-evaluation.
Guardrails
- Fit weights on
train, score on test — never fit and score on the same split.
- The backtest estimates historical behavior; it is not a forward return promise. Present it as a research artifact for review.
- Report net-of-cost numbers as the headline; gross numbers only as context.
