Judgmental extrapolation and the salience of change

Judgmental extrapolation and the salience of change People may often forecast using cognitive procedures that resemble formal time‐series extrapolation models. A model of judgmental extrapolation based on exponential smoothing is proposed in which the setting of the trend parameter is hypothesized to depend upon the relative salience of the successive changes. The salience hypothesis was first tested with exponential series by the use of a framing manipulation. As predicted, focusing the subjects' attention on the changes led to more accurate forecasts. In two investment simulation studies, the salience hypothesis was further examined by varying the statistical properties of the price changes. As predicted, subjects were more likely to sell as prices fell and to buy as prices rose (1) as the sample size of similar changes increased; (2) when the variance of the changes was low; and (3) when the absolute value of the mean change was high. Conditions that may influence judgmental forecasting processes are discussed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Forecasting Wiley

Judgmental extrapolation and the salience of change

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Publisher
Wiley
Copyright
Copyright © 1990 John Wiley & Sons, Ltd.
ISSN
0277-6693
eISSN
1099-131X
DOI
10.1002/for.3980090405
Publisher site
See Article on Publisher Site

Abstract

People may often forecast using cognitive procedures that resemble formal time‐series extrapolation models. A model of judgmental extrapolation based on exponential smoothing is proposed in which the setting of the trend parameter is hypothesized to depend upon the relative salience of the successive changes. The salience hypothesis was first tested with exponential series by the use of a framing manipulation. As predicted, focusing the subjects' attention on the changes led to more accurate forecasts. In two investment simulation studies, the salience hypothesis was further examined by varying the statistical properties of the price changes. As predicted, subjects were more likely to sell as prices fell and to buy as prices rose (1) as the sample size of similar changes increased; (2) when the variance of the changes was low; and (3) when the absolute value of the mean change was high. Conditions that may influence judgmental forecasting processes are discussed.

Journal

Journal of ForecastingWiley

Published: Jul 1, 1990

References

  • Accuracy of judgmental forecasting of time series
    Carbone, Carbone; Gorr, Gorr
  • Does the stock market overreact?
    De Bondt, De Bondt; Thaler, Thaler
  • Judgmental forecasting of univariate time‐series
    Harvey, Harvey
  • An exploration of some practical issues in the use of quantitative forecasting models
    Lawrence, Lawrence
  • The accuracy of extrapolation (time series) methods: Results of a forecasting competition
    Makridakis, Makridakis; Andersen, Andersen; Carbone, Carbone; Fildes, Fildes; Hibon, Hibon; Lewandowski, Lewandowski; Newton, Newton; Parzen, Parzen; Winkler, Winkler

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