Non-Stationarity in Markets

Non-stationarity in markets refers to the fact that the statistical properties of financial time series, such as mean and variance, change over time. Unlike many physical systems, market data is not constant, making it difficult to apply standard statistical models.

In cryptocurrency, regime shifts occur frequently due to regulatory changes, protocol updates, and shifts in liquidity. A model that works during a bull market may fail completely during a crash because the underlying dynamics have changed.

Dealing with non-stationarity requires adaptive models that can update their parameters as market conditions evolve. This is a core challenge in quantitative finance and derivative pricing.

Ignoring non-stationarity is a common cause of model failure. Successful traders build systems that are resilient to these structural changes.