Non-stationarity

Non-stationarity refers to a situation where the statistical properties of a system or data, such as its average or variability, change over time. In simple terms, it means patterns or behaviors are not consistent; for example, a stock market may have different trends and volatility now compared to a few years ago. Recognizing non-stationarity is important because it affects how we analyze and predict data—methods assuming stability over time may not work well when the data is non-stationary. It often indicates that underlying factors influencing the data evolve, making it more complex to model and understand.