This document provides an overview of simple exponential smoothing, a technique for forecasting future values based on past observations. It describes the basic smoothing equation used in the method and notes that simple exponential smoothing is best for data without trends or seasonality. The document then outlines the steps for applying simple exponential smoothing, including setting objectives, building a model using software, evaluating the model's accuracy, and using the model to generate forecasts. An example using mortgage rate data demonstrates how to implement the method.

1. Simple Exponential SmoothingLesson #3Simple Exponential Smoothing MethodCopyright 2010 DeepThought, Inc.1

2. Simple Exponential SmoothingModel IntroductionA simple smoothing technique

3. Estimates a smoothing equation

4. Uses the estimated smoothing equation to forecast future values

5. Method format:

6. F(t+1) = a × X(t) + (1-a) × F(t)Copyright 2010 DeepThought, Inc.2

7. Simple Exponential SmoothingModel DetailsMethod characteristics

8. Fits a smoothing equation to data

9. Estimating a smoothing equation which minimizes the errors between actual data points and model estimates

10. When to use method

11. Data has no trend or seasonality

12. Data is stationary

13. When not to use

14. Data exhibits pattern such as trend, seasonality, cyclicalityCopyright 2010 DeepThought, Inc.3

15. Simple Exponential SmoothingForecasting StepsSet an objectiveBuild modelEvaluate modelUse modelCopyright 2010 DeepThought, Inc.4