Get an introduction to simple exponential smoothing, including how to assemble the forecast equation and optimize forecasts.
- [Instructor] Suppose that you have a sequence of actual financial results, such as your company's annual revenues for several years, and you'd like to forecast how much you're likely to bring in next year. I'll show you a technique that'll make that task very easy to achieve. Hi, my name is Conrad Carlberg. I've been using the forecasting techniques that I describe in this series of lessons for more years than I care to think about. In this course, I'll show you the rationale for exponential smoothing, including its self-correcting nature.
You'll also see how to get a sequence of forecasts going, and perhaps most important, you'll see how to assess the accuracy of your forecasts and how to improve them. As you go through the lessons in this course, you'll find it helpful to be familiar with basic Excel data entry techniques, as well as how to enter formulas in an Excel worksheet. The reason is that Excel is an ideal platform for learning how exponential smoothing works. There are plenty of other applications, such as SAS and R, that you can use to actually conduct your forecasting projects after you have the basics in your hip pocket.
So settle back, mute your cellphone and let's get started.
- Using correlograms to identify the nature of a baseline
- Assembling the forecast equation
- Methods of identifying the first forecast
- Getting a measure of overall forecast accuracy
- Optimizing a smoothing constant by minimizing RMSE