Information Coefficient (IC): How to Measure Quant Signal Skill
The Information Coefficient (IC) measures how well a quant signal’s forecasts predict realized returns — rank vs Pearson IC, the link to the…
Quantitative Signal Research
In-depth explainers on signal attribution, alpha decay, market microstructure, and the methods quant teams use to keep their edge — sourced, and written for people who actually run the models.
The Information Coefficient (IC) measures how well a quant signal’s forecasts predict realized returns — rank vs Pearson IC, the link to the…
The Information Ratio (IR) measures active return per unit of active risk — how reliably a strategy beats its benchmark. What counts as a go…
Factor decay is the tendency of documented factor premia — value, size, momentum — to weaken once they are published and crowded. What the M…
Statistical arbitrage is a family of market-neutral strategies that profit from temporary, statistically identified mispricings between rela…
Pairs trading is the canonical statistical-arbitrage strategy: find two cointegrated securities, trade the spread between them when it diver…
Discover how trading signals lose their edge over time and what savvy investors can do to stay ahead.
Fundamentals
The working definitions and core methods behind micro-alpha research, so you can reason about weak signals on solid ground.
Machine Learning & Technology
How ML methods and the tooling behind them apply to signal detection, alpha research, and systematic execution.
Market Analysis
How signals behave once they meet live markets: impact, decay, liquidity, regime shifts, and cross-asset structure.
Portfolio Construction
How to turn a book of individual signals into one coherent portfolio: attribution, correlation, sizing, and risk.
Signal Research & Discovery
How to source, build, validate, and monitor predictive signals before they earn a place in a live book.
Strategy Implementation
Turning a validated signal into a live strategy: aggregation, execution, costs, backtesting, and the systems underneath.
Quant signal glossary
The vocabulary of quantitative signal research — each term defined precisely, cross-linked to the guides that use it.
Interactive tool
Enter a signal’s information coefficient at several horizons and get its estimated half-life, a fitted decay curve, and a rebalancing guide — instantly, in the browser.
VPIN estimates the toxicity of order flow — the risk that liquidity providers are being adversely selected — from volume-bucketed trade imba…
Order flow imbalance measures the net buying pressure in the limit order book — and explains short-horizon price moves more reliably than tr…
Kyle’s lambda is the price-impact coefficient at the heart of market microstructure — how far the price moves per unit of net order flow. Wh…
The Amihud illiquidity ratio measures how much a security’s price moves per dollar traded, using nothing more than daily returns and volume.…
Fractional differentiation makes a price series stationary while preserving the maximum possible memory — resolving the dilemma that taking …
Pairs trading is the canonical statistical-arbitrage strategy: find two cointegrated securities, trade the spread between them when it diver…
Statistical arbitrage is a family of market-neutral strategies that profit from temporary, statistically identified mispricings between rela…
Factor decay is the tendency of documented factor premia — value, size, momentum — to weaken once they are published and crowded. What the M…
The Information Ratio (IR) measures active return per unit of active risk — how reliably a strategy beats its benchmark. What counts as a go…
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