Forecasting Earnings Using k-Nearest Neighbor Matching

69 Pages Posted: 19 Feb 2021

See all articles by Peter D. Easton

Peter D. Easton

University of Notre Dame - Department of Accountancy

Martin M. Kapons

Tilburg University

Steven J. Monahan

University of Utah; INSEAD

Harm H. Schütt

Tilburg University - Tilburg School of Economics and Management

Eric H. Weisbrod

University of Kansas - School of Business

Date Written: November 30, 2020

Abstract

We use the k-nearest neighbors (i.e., k-NN) algorithm to forecast a firm’s annual earnings by matching its recent trend in annual earnings to historical earnings sequences of “neighbor” firms. Our forecasts are more accurate than forecasts obtained from the random walk, the regression model developed by Hou, van Dijk and Zhang (2012), other regression models and the matching approach described in Blouin, Core and Guay (2010). The k-NN model is superior to these alternative models both when analysts’ forecasts are available and when they are not. Further, for firm-years with I/B/E/S earnings data available, the accuracy of k-NN forecasts of I/B/E/S earnings is similar to the accuracy of analysts’ forecasts. The k-NN model is also superior to a random forest classifier that we use to choose the best model ex-ante. Finally, we find that our forecasts of earnings changes have a positive association with 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 Schütt, Harm H. and Weisbrod, Eric H., Forecasting Earnings Using k-Nearest Neighbor Matching (November 30, 2020). 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

Tilburg University ( email )

P.O. Box 90153
Tilburg, DC Noord-Brabant 5000 LE
Netherlands

Steven J. Monahan

University of Utah ( email )

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

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/

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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