Microsoft Excel 2016 Data Analysis and Business Modeling

Chapter 63. Winters method

You often need to predict future values of a time series, such as monthly costs or monthly product revenues. This is usually difficult because the characteristics of any time series are constantly changing. Exponential smoothing or adaptive methods are usually best suited for forecasting the future values of a time series. In this chapter, I describe the most powerful smoothing method: Winters method (attributed to Peter Winters and Charles Holt). To help you understand how Winters method works, I’ll use it to forecast monthly housing starts in the United States. Housing starts are simply the number of new homes whose construction begins during a month. I’ll begin by describing the three key characteristics of a time ...