From raw factor data
to a live multi-factor book.
What a cross-sectional alpha factor is, how one becomes a market-neutral portfolio, and how uncorrelated factors composite into a stronger book — each step backed by a runnable notebook, so nothing is a black box.
An alpha factor is a predictive measurement
A factor is alpha because it is predictive — a measurement that carries information about future cross-sectional returns, not just a description of the past.
The raw input is a single metric measured across the whole universe — 400+ digital assets, point-in-time, updated hourly. Think a dates × assets matrix of one number per asset per moment (liquidity, funding, flow, on-chain supply, and so on).
AlphaLens quantifies how well that measurement ranks tomorrow's winners and losers — the honest test of whether a factor is really predictive.
A cross-sectional factor becomes a market-neutral book
To turn the raw factor into a portfolio, rank every asset by its factor value and translate those ranks into weights: long the top, short the bottom.
It is called cross-sectional precisely because you score assets against each other — which lets you build a market-neutral book whose dollar weights net to zero. The return comes from the spread between winners and losers, not from the direction of the market.
Positions are scaled by inverse volatility and rebalanced daily, so a single factor already trades as a self-contained, risk-targeted strategy.
Compositing uncorrelated factors builds a stronger book
No single factor wins every regime. Because the factors are largely uncorrelated, blending them diversifies away factor-specific drawdowns while keeping the alpha — the classic free lunch of combining independent bets.
Averaging the target weights of seven orthogonal factors gives the 7 Factor Composite: a market-neutral portfolio with materially higher risk-adjusted return than any of its parts.
| MOMX | CRYX | RFLW | MRGN | ALT | MR | MRX | |
|---|---|---|---|---|---|---|---|
| MOMX | 1.00 | -0.02 | 0.32 | 0.19 | 0.35 | 0.12 | 0.30 |
| CRYX | -0.02 | 1.00 | -0.04 | 0.26 | 0.17 | 0.10 | 0.13 |
| RFLW | 0.32 | -0.04 | 1.00 | -0.07 | 0.24 | 0.07 | 0.07 |
| MRGN | 0.19 | 0.26 | -0.07 | 1.00 | 0.26 | -0.02 | 0.19 |
| ALT | 0.35 | 0.17 | 0.24 | 0.26 | 1.00 | 0.11 | 0.23 |
| MR | 0.12 | 0.10 | 0.07 | -0.02 | 0.11 | 1.00 | 0.34 |
| MRX | 0.30 | 0.13 | 0.07 | 0.19 | 0.23 | 0.34 | 1.00 |
Prove it on your desk with a two-week POC
Browse the full catalog and the data room — factsheets, raw factor data, portfolio returns and the API — then tell us which factors you want to evaluate. We switch you live for two weeks so you can backtest and paper-trade against point-in-time data before committing.
Licensing that scales with your AUM
Pricing scales with assets under management, from $4,990/mo + VAT — a starting point, not a checkout. Final pricing is set at our discretion based on coverage and use case, and every licence is agreed with the desk.
Ready to put factors into production?
Start a two-week POC, or talk through coverage, SLA terms and AUM-based pricing with the team.