Mean Reversion Processes

Mean reversion processes are models that assume an asset's price or volatility will eventually return to its long-term average level. This concept is central to many trading strategies, including pair trading and statistical arbitrage.

When an asset deviates significantly from its mean, a mean-reversion strategy assumes the price will move back toward that average. In cryptocurrency, this is often applied to interest rates, funding rates, or the price relationship between correlated assets.

These processes are modeled using stochastic differential equations, such as the Ornstein-Uhlenbeck process. They provide a structural basis for identifying trading opportunities when markets appear overextended.

However, they also carry risk, as prices can remain far from their mean for extended periods, leading to significant losses. Successful application requires careful calibration and an understanding of the factors driving the mean.

It is a powerful tool for traders looking to exploit temporary inefficiencies in market pricing.