Simple Exponential Smoothing: An Overlooked Transformation for Improving Forecasting Acuity
Year: 2026
Type: article
Abstract: ABSTRACT : Context Our Capsule Characterization of Forecasting is: Forecasting Models provide the critical intel needed by the Planning Committee [PC] to service their charge of providing tactical and strategic guidance to the organization. The critical element of this capsule characterization is: The Forecasting Acuity of the Extrapolations of the Forecasting Model [FM]. Herein lies a conundrum, as the SES-FM only produces Interpolations. There has never been a case where the PC was interested in Interpolations produced by any FM! Repurposing the SES-FM. We find that the: Simple Exponential [a]Smoothing] FM: where: a is the Smoothing Constant, noted as: [SEaS] used as a Y-Variate Smoothing Transform is an excellent tool in the panoply of the forecaster. Focus We examined the following three SEaS Models: {(i) The Excel-, (ii) The PENN State- & (iii) The SAS[JMP]-Versions}. Results Using firm sample from the S&P500, we illustrate how to use these SEaS Models to present to the Planning Committee the decision-context where managerial actions could effect the changes in the AIS-configuration to move certain Y-Variates to mirror the smoothed versions and thus, over time to improve forecasting acuity of the firm that, in turn, would likely improve the market position of the firm.
Authors: Moncef Belhadjali, Edward J. Lusk
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7170033996
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