Time Series Forecasting in Python

3 Going on a random walk

This chapter covers

• Identifying a random walk process
• Understanding the ACF function
• Classifying differencing, stationarity, and white noise
• Using the ACF plot and differencing to identify a random walk
• Forecasting a random walk

In the previous chapter, we compared different naive forecasting methods and learned that they often serve as benchmarks for more sophisticated models. However, there are instances where the simplest methods will yield the best forecasts. This is the case when we face a random walk process.

In this chapter, you will learn what a random walk process is, how to recognize it, and how to make forecasts using random walk models. Along the way, we will look at the concepts of differencing, stationarity, ...