The half-life of alpha
Every signal is a depreciating asset. The interesting question is not whether it decays but whether your machinery turns over faster than your information does.
All models are wrong, but some are useful.
A quantitative signal is a claim about the future that the market is in the business of falsifying. The moment a forecast is formed it begins to leak into prices — through your own trading, through everyone else who found the same regularity, through the slow arbitrage of disclosure. What remains is conventionally measured as the decay of the information coefficient: the correlation between forecast and realized return, tracked as the forecast ages.1
The decay is not uniform across families. Flow-driven signals are spent in days; estimate revisions persist for weeks; slower cross-sectional effects like momentum survive for months. The differences are large enough that they should drive system design, not tuning.
Signal decay by family
Information remaining as a forecast ages, three representative families, 2016–2026
Three consequences follow. First, a signal's half-life bounds its useful rebalance frequency from below: rebalancing a momentum book daily buys transaction costs and nothing else. Second, half-life bounds capacity from above — a fast signal can only be monetized in the size the market will absorb inside its window. Third, and least appreciated, the half-life must be measured after your own participation, because execution is itself a disclosure.2
What the families look like
| family | horizon | half-life | capacity | gross ic |
|---|---|---|---|---|
| order-flow imbalance | intraday–days | 8d | low | 0.081 |
| earnings revisions | weeks | 40d | medium | 0.043 |
| price momentum | months | 118d | high | 0.027 |
The table understates how different the engineering is. A fast book is an execution problem wearing a research costume; a slow book is a tax and drift problem wearing one. Treating them as one system with one rebalance cadence quietly averages away the edge of both.
The cost of trading your own decay
Net of costs, the relationship between rebalance frequency and realized Sharpe is a hump, not a slope. Trade too rarely and you hold stale forecasts; trade too often and you pay the spread to refresh information the market already had.
The rebalance hump
Net Sharpe of a blended book by rebalance frequency, after modeled costs
The peak sits wherever your slowest surviving signal says it should — which is why the honest version of this chart has to be recomputed every time the signal mix changes, and why it belongs in the deployment checklist rather than in a slide from two years ago.
None of this is exotic. It is bookkeeping — the same discipline as reconciliation, applied to information instead of positions. The systems that survive are the ones that treat alpha as inventory with an expiry date, and build the plumbing to mark it to market.