Beating a Random Walk

45 Pages Posted: 21 Sep 2017 Last revised: 8 Aug 2018

See all articles by Peter D. Easton

Peter D. Easton

University of Notre Dame - Department of Accountancy

Peter Kelly

University of Notre Dame

Andreas Neuhierl

University of Notre Dame - Department of Finance

Date Written: August 7, 2018

Abstract

As a crucial input to many valuation models, earnings forecasts are important to many practitioners and academics. Unfortunately, there is a large sample of firms that analysts do not cover, and analysts’ earnings forecasts are less accurate than a random walk at long horizons. Recent work by Hou, van Dijk, and Zhang (2012) and Li and Mohanram (2014) suggested the use of cross-sectional models to produce earnings forecasts. Several studies immediately used these models because of the obvious advantage that forecasts can be formed for a sample that is much greater than the sample of firms covered by analysts. Unfortunately, these models also produce earnings forecasts significantly worse than random walk forecasts. We present a simple and intuitive modification to these models – the use of quantile rather than OLS regressions in the prediction model – that produces earnings forecasts significantly better than a random walk. Subsequent analysis suggests that this simple modification produces earnings forecasts that lead to more accurate return forecasts, and better represents market expectations.

Keywords: earnings, forecasts

JEL Classification: G14

Suggested Citation

Easton, Peter D. and Kelly, Peter and Neuhierl, Andreas, Beating a Random Walk (August 7, 2018). Available at SSRN: https://ssrn.com/abstract=3040354 or http://dx.doi.org/10.2139/ssrn.3040354

Peter D. Easton

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)

Peter Kelly (Contact Author)

University of Notre Dame ( email )

251 Mendoza
South Bend, IN 46637
United States

Andreas Neuhierl

University of Notre Dame - Department of Finance ( email )

P.O. Box 399
Notre Dame, IN 46556-0399
United States

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