Mastering Python for Finance - Second Edition

Checking for stationarity

There are a number of ways to check whether time series data is stationary or non-stationary:

• Through visualizations: You can review a time series graph for obvious indication of trends or seasonality.
• Through statistical summaries: You can review the statistical summaries of your data significant differences. For example, you can partition your time series data and compare the mean and variance of each group.
• Through statistical tests: You can use statistical tests such as the Augmented Dickey-Fuller Test to check if stationarity expectations have been met or violated.