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

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ADJUSTED EXPONENTIAL SMOOTHING FORECASTING
METHODPrepared by Dan MilewskiNovember 29,
2005
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Tutorial Outline

• Defining the Method
• When to Use the Method
• How to Use the Method
• An Example
• An Exercise
• Summary
• Readings List

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Defining the Method

• A Forecasting Model
• Predicts future levels of a variable
• Can be either quantitative or qualitative

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Defining the Method

• Exponential Smoothing
• Quantitative forecasting method
• Weighted average of two variables

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Defining the Method

• Adjusted
• Trend adjustment factor included
• Better at picking up on trends

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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 periods
  actual value and forecast, with a trend
  adjustment added in.

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When to Use the Method

• Preferred Scenario
• When a trend is present
• Good Scenario
• When theres a cyclical or seasonal pattern
• Least-effective Scenario
• Working with random variations

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When to Use the Method
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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

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How to Use the Method

• Exponential Smoothing
• Ft1 ? Dt (1 - )Ft
• Where
• Ft 1 forecast for next period
• Dt actual value for present period
• Ft previously determined forecast for
  present period
• ? weighting factor (between 0 and
  1)

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How to Use the Method

• Adjusted Exponential Smoothing
• AFt1 Ft1 Tt1
• Where
• Tt 1 (Ft1 Ft ) (1 - ) Tt
• trend factor for the next
  period
• Tt trend factor for the current
  period
• smoothing constant for the
  trend
• adjustment factor
• (just add a trend adjustment factor)

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How to Use the Method

• Points to Consider
• To start, pick an unadjusted forecast
• In period 1, trend equals 0

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An Example

• 2005 U.S. Housing Starts (monthly)

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An Example

• 2005 U.S. Housing Starts (monthly)

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An Exercise

• Using the adjusted exponential smoothing
  forecasting method and the following data
• Predict Q4 2005 sales revenues for Intel
• Where 0.4 and 0.7
• Predict Q4 2005 net income for Intel
• Where 0.2 and 0.6

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An Exercise

• Intel Quarterly Sales Revenue

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An Exercise

• Intel Quarterly Net Income

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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?

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Summary

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

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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
  2003. The Journal of Business Forecasting Methods
  Systems. Fall 2004, Vol. 23, Iss. 3
• http//home.ubalt.edu/ntsbarsh/ECON/lecture6.doc

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