Forecasting Earnings Using k-Nearest Neighbors

48 Pages Posted: 19 Feb 2021 Last revised: 21 Sep 2021

See all articles by Peter D. Easton

Peter D. Easton

University of Notre Dame - Department of Accountancy

Martin M. Kapons

University of Amsterdam - Amsterdam Business School

Steven J. Monahan

INSEAD; University of Utah

Harm H. Schütt

Tilburg University - Tilburg School of Economics and Management

Eric H. Weisbrod

University of Kansas - School of Business

Date Written: July 26, 2021

Abstract

We use a simple k-nearest neighbors (k-NN) model to forecast a subject firm’s annual earnings by matching its recent earnings history to earnings histories of comparable firms, and then extrapolating the forecast from the comparable firms’ lead earnings. Out-of-sample forecasts generated by our model are more accurate than forecasts generated by the random walk; more complicated k-NN models; the matching approach developed by Blouin, Core, and Guay (2010); and popular regression models. These results are robust. Our model’s superiority holds for different error metrics, for firms that are followed by analysts and firms that are not, and for different forecast horizons. Our model also generates a novel ex ante indicator of forecast inaccuracy. This indicator, which equals the interquartile range of the comparable firms’ lead earnings, is reliable and useful. It predicts forecast accuracy and it identifies situations when our forecasts are strong (weak) predictors of future stock returns.

Keywords: earnings, forecasting, machine learning

JEL Classification: C21, C53, G17, M41

Suggested Citation

Easton, Peter D. and Kapons, Martin M. and Monahan, Steven J. and Monahan, Steven J. and Schütt, Harm H. and Weisbrod, Eric H., Forecasting Earnings Using k-Nearest Neighbors (July 26, 2021). Available at SSRN: https://ssrn.com/abstract=3752238 or http://dx.doi.org/10.2139/ssrn.3752238

Peter D. Easton (Contact Author)

University of Notre Dame - Department of Accountancy ( email )

Mendoza College of Business
Notre Dame, IN 46556-5646
United States
574-631-6096 (Phone)
574-631-5127 (Fax)

Martin M. Kapons

University of Amsterdam - Amsterdam Business School ( email )

Spui 21
Amsterdam, 1018 WB
Netherlands

Steven J. Monahan

INSEAD ( email )

Boulevard de Constance
PMLS 1.24
F-7705 Fontainebleau Cedex, 77305
France
+33 1 60 72 92 14 (Phone)
+33 1 60 72 92 53 (Fax)

HOME PAGE: http://www.insead.edu/facultyresearch/faculty/profiles/smonahan/

University of Utah ( email )

1645 E Campus Center Dr
Salt Lake City, UT 84112-9303
United States

Harm H. Schütt

Tilburg University - Tilburg School of Economics and Management ( email )

PO Box 90153
Tilburg, 5000 LE Ti
Netherlands

Eric H. Weisbrod

University of Kansas - School of Business ( email )

1300 Sunnyside Avenue
Lawrence, KS 66045
United States

HOME PAGE: http://https://business.ku.edu/eric-weisbrod

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