How Useful are Historical Data for Forecasting the Long-Run Equity Return Distribution?

18 Pages Posted: 6 Oct 2011

See all articles by John M. Maheu

John M. Maheu

McMaster University - Michael G. DeGroote School of Business; RCEA

Thomas H. McCurdy

University of Toronto - Rotman School of Management; Center for Interuniversity Research and Analysis on Organization (CIRANO)

Multiple version iconThere are 2 versions of this paper

Date Written: October 5, 2011

Abstract

We provide an approach to forecasting the long-run (unconditional) distribution of equity returns making optimal use of historical data in the presence of structural breaks. Our focus is on learning about breaks in real time and assessing their impact on out-of-sample density forecasts. Forecasts use a probability weighted average of submodels, each of which is estimated over a different history of data. The empirical results strongly reject ignoring structural change or using a fixed-length moving window. The shape of the long-run distribution is affected by breaks, which has implications for risk management and long-run investment decisions.

Keywords: Bayesian Learning, Density Forecasts, Market Returns, Model Risk, Parameter Uncertainty, Structural Change

Suggested Citation

Maheu, John M. and McCurdy, Thomas H., How Useful are Historical Data for Forecasting the Long-Run Equity Return Distribution? (October 5, 2011). Journal of Business and Economic Statistics, Vol. 27, No. 1, January 2009. Available at SSRN: https://ssrn.com/abstract=1939474

John M. Maheu

McMaster University - Michael G. DeGroote School of Business ( email )

1280 Main Street West
Hamilton, Ontario L8S 4M4
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HOME PAGE: http://profs.degroote.mcmaster.ca/ads/maheujm/

RCEA

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HOME PAGE: http://www.rcfea.org/

Thomas H. McCurdy (Contact Author)

University of Toronto - Rotman School of Management ( email )

105 St. George Street
Toronto, Ontario M5S 3E6 M5S1S4
Canada
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416-971-3048 (Fax)

HOME PAGE: http://www-2.rotman.utoronto.ca/~tmccurdy

Center for Interuniversity Research and Analysis on Organization (CIRANO)

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Montreal H3C 3J7, Quebec
Canada

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