Simple Exponential Smoothing: An Overlooked Transformation for Improving Forecasting Acuity

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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-22
DOI
https://doi.org/10.5281/zenodo.21485707
Primary Topic
Forecasting Techniques and Applications
Type
article
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article

Simple Exponential Smoothing: An Overlooked Transformation for Improving Forecasting Acuity

Moncef Belhadjali, Edward J. Lusk
Zenodo (CERN European Organization for Nuclear Research)
Forecasting Techniques and Applications
article

Simple Exponential Smoothing: An Overlooked Transformation for Improving Forecasting Acuity

Moncef Belhadjali, Edward J. Lusk
article en

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.

Zenodo (CERN European Organization for Nuclear Research)
Norfolk State University (US), SUNY Plattsburgh (US)
Openalex Percentile: Top 5%
Forecasting Techniques and Applications
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Simple Exponential Smoothing: An Overlooked Transformation for Improving Forecasting Acuity — Moncef Belhadjali, Edward J. Lusk · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS