What is statistical arbitrage?
Statistical arbitrage refers to a trading strategy that aims to exploit perceived pricing inefficiencies in financial markets using statistical and quantitative methods. This strategy relies on sophisticated statistical models and analysis to identify deviations from expected relationships or patterns among securities. Traders employing statistical arbitrage seek to take advantage of these temporary mispricings by simultaneously buying undervalued securities and selling overvalued ones, with the expectation that the prices will eventually converge. The goal is to generate profits based on statistical probabilities and market inefficiencies rather than relying on predicting the direction of the broader market.
Arbitrage: the simultaneous purchase and sale of equivalent assets or of the same asset in multiple markets in order to exploit a temporary discrepancy in prices.
In finance, statistical arbitrage (often abbreviated as Stat Arb or StatArb) is a class of short-term financial trading strategies that employ mean reversion models involving broadly diversified portfolios of securities (hundreds to thousands) held for short periods of time (generally seconds to days). These strategies are supported by substantial mathematical, computational, and trading platforms.
Broadly speaking, StatArb is actually any strategy that is bottom-up, beta-neutral in approach and uses statistical/econometric techniques in order to provide signals for execution. Signals are often generated through a contrarian mean reversion principle but can also be designed using such factors as lead/lag effects, corporate activity, short-term momentum, etc. This is usually referred to as a multi-factor approach to StatArb.