Toolkit, not catalog — and why that matters
Factor libraries come in two shapes. Curated catalogs publish a fixed list of factors with stamped IC, ICIR, half-life, and turnover numbers — usually on one specific universe and cost model. Composable toolkits give you the building blocks so you can build the factor yourself and measure it on your own setup. Keel's component registry is the building-block shape: signals, transforms, regime detectors and aggregators that you compose into a strategy and backtest. It does not stamp IC numbers on them, and that is worth understanding: IC and decay numbers depend on universe definition, cost model, lookback window, and rebalance horizon — a single stamped number reads cleanly but only tells the truth on one specific setup.
The 218 components, by category
The component registry has 218 entries decorated with @register_component. They break down roughly as follows.
| Category | Examples |
|---|---|
| Momentum signals | Cross-sectional momentum at multiple lookbacks; time-series momentum; risk-adjusted momentum. |
| Trend signals | EMA/SMA crossovers, MACD-style, channel breakouts, trend strength scoring. |
| Volatility signals | Realized vol, vol-of-vol, vol regime indicators, Garman-Klass, ATR-based. |
| Volume / liquidity signals | Volume rank, dollar volume, volume z-score, OI-weighted scoring. |
| Statistical signals | Z-score and percentile rank transforms used as direct signals. |
| Logic signals | Breakout detectors, mean-reversion triggers, threshold gates. |
| Regime detectors | FundingLevelRegime, FundingDispersionRegime, plus vol-, trend-, and correlation-based regimes. |
| Portfolio aggregators (~20) | Forecast weighting, rank normalization, sign-split long/short, equal-weight, inverse-vol. |
| Transforms (~16) | Rolling normalization, smoothing, lag, decay, regime gates and scalers, signal-combiners. |
The remainder are data loaders, risk overlays (vol targeting, position caps, gross and net leverage limits), execution operators (buffered rebalancer, neutralization), and utility components that wire pipelines together. Every one is composable — you can stack them in arbitrary order, branch them, and store intermediate values for inspection.
Evaluating a factor
Five diagnostics decide whether a factor deserves a place in a strategy. Keel does not compute them for you — run them wherever your factor values live — but read them before any backtest, and compute them on exactly the values the strategy will trade, or you are measuring a different signal.
- Information coefficient (Pearson and Spearman). Per-bar cross-sectional correlation between factor and forward return at a chosen horizon. Spearman default.
- Rolling IC and ICIR-equivalent stability. Sliding-window mean and standard deviation of IC. Sharpe-style ratio. Distinguishes truly informative factors from lucky ones.
- Half-life and decay curve. Bars until IC halves; full IC-by-horizon plot. Sets the natural rebalance horizon and reveals whether you have a fast or slow signal.
- Quantile spread. Forward return of top decile minus bottom decile. Tests monotonicity — many high-IC factors lack a clean monotone payoff, which is a warning sign.
- Turnover and cost sensitivity. What fraction of the cross-section changes deciles per bar, and what the quantile spread looks like net of realistic fees and slippage. The honest filter that kills the prettiest paper factors.
Hyperliquid-tuned defaults
The components ship with defaults appropriate for HL perp data: price bars from 5 minutes up off a 1-minute grid, 1-hour settled funding, ~200 markets, fee schedule from the HL maker/taker tiers. Funding is a first-class input, not a footnote. Data loaders standardize units across the universe so cross-sectional rankings are comparing apples to apples. The regime detectors are conditioned on HL-specific regime structure, not transplanted from equity research.
The implication: a momentum or carry factor you build with Keel components is HL-shaped by default. You can change the defaults for a different venue if you ever leave HL — but Keel is built for the case where you do not.
Reading someone else's factor numbers
When a catalog does publish IC, ICIR, half-life, decay curve and turnover per factor, ask four questions before trusting it: which universe (and with what minimum history), which cost model, which forward horizon, and which sample period. A momentum factor stamped on a top-20 universe during a trending year tells you little about a top-100 universe in a choppy one. Published factor diagnostics like these may come to Keel in the future; wherever you read them, the four questions come first.
Try it
Browse the 218 components, compose a factor into a strategy, and backtest it against the HL universe with fees, slippage and hourly funding.