ADJUSTED EXPONENTIAL SMOOTHING FORECASTING METHOD Prepared by Dan Milewski November 29, 2005

Tutorial Outline 1.Defining the Method 2.When to Use the Method 3.How to Use the Method 4.An Example 5.An Exercise 6.Summary 7.Readings List

Defining the Method A Forecasting Model: Predicts future levels of a variable Can be either quantitative or qualitative

Defining the Method Exponential Smoothing: Quantitative forecasting method Weighted average of two variables

Defining the Method Adjusted Trend adjustment factor included Better at picking up on trends

Defining the Method So, combined,…. Adjusted Exponential Smoothing Forecasting Method: A method that uses measurable, historical data observations, to make forecasts by calculating the weighted average of the current period’s actual value and forecast, with a trend adjustment added in

When to Use the Method Preferred Scenario: –When a trend is present Good Scenario: –When there’s a cyclical or seasonal pattern Least-effective Scenario –Working with random variations

When to Use the Method

Manufacturing Firms: –To forecast demand Service Organizations: –To forecast customer arrival patterns Financial Analysts: –To forecast revenues and profits Investors: –To forecast economic indicators

How to Use the Method Exponential Smoothing: F t+1 =  D t + (1 - )F t Where… F t +1 =forecast for next period F t +1 =forecast for next period D t =actual value for present period D t =actual value for present period F t =previously determined forecast for present period F t =previously determined forecast for present period  =weighting factor (between 0 and 1)  =weighting factor (between 0 and 1)

How to Use the Method Adjusted Exponential Smoothing: AF t+1 = F t+1 + T t+1 Where… T t +1 = (F t+1 – F t ) + (1 - ) T t T t +1 = (F t+1 – F t ) + (1 - ) T t = trend factor for the next period = trend factor for the next period T t = trend factor for the current period T t = trend factor for the current period = smoothing constant for the trend = smoothing constant for the trend adjustment factor adjustment factor (just add a trend adjustment factor)

How to Use the Method Points to Consider: To start, pick an unadjusted forecastTo start, pick an unadjusted forecast In period 1, trend equals 0In period 1, trend equals

An Example 2005 U.S. Housing Starts (monthly):

An Example 2005 U.S. Housing Starts (monthly):

An Exercise Using the adjusted exponential smoothing forecasting method and the following data… –Predict Q sales revenues for Intel Where = 0.4 and = 0.7 –Predict Q net income for Intel Where = 0.2 and =

An Exercise Intel Quarterly Sales Revenue

An Exercise Intel Quarterly Net Income

An Exercise Which series of data best fits with this method? What makes this so? What other financial data could be predicted accurately with this method?

Summary Adjusted Exponential Smoothing Forecasting Method: Quantitative forecasting model Highly accurate Best when trends exist

Readings List Gardner, Jr., E.S. Exponential Smoothing: The State of the Art. Journal of Forecasting. April 1985, Vol. 3, Iss. 1. Jain, Chaman L. Business Forecasting Practices in The Journal of Business Forecasting Methods & Systems. Fall 2004, Vol. 23, Iss