Mastering Python for Finance - Second Edition

Stationarity and non-stationarity

In empirical time series studies, price movements are observed to drift toward some long-term mean, either upwards or downwards. A stationary time series is one whose statistical properties, such as mean, variance, and autocorrelation, are constant over time. Conversely, observations on non-stationary time series data have their statistical properties change over time, mostly likely due to trends, seasonality, presence of a unit root, or a combination of all three.

In time series analysis, it is assumed that the data of the underlying process is stationary. Otherwise, modeling from non-stationary data may produce unpredictable results. This would lead to a condition known as spurious regression. Spurious ...