Forecasting Stock Market Returns: The Sum of the Parts is More than the Whole

34 Pages Posted: 29 Dec 2008 Last revised: 20 Jan 2009

See all articles by Miguel A. Ferreira

Miguel A. Ferreira

Nova School of Business and Economics; European Corporate Governance Institute (ECGI); Centre for Economic Policy Research (CEPR)

Pedro Santa-Clara

New University of Lisbon - Nova School of Business and Economics; National Bureau of Economic Research (NBER); Centre for Economic Policy Research (CEPR)

Multiple version iconThere are 3 versions of this paper

Date Written: December 2008

Abstract

We propose forecasting separately the three components of stock market returns: dividend yield, earnings growth, and price-earnings ratio growth. We obtain out-of-sample R-square coefficients (relative to the historical mean) of nearly 1.6% with monthly data and 16.7% with yearly data using the most common predictors suggested in the literature. This compares with typically negative R-squares obtained in a similar experiment by Goyal and Welch (2008). An investor who timed the market with our approach would have had a certainty equivalent gain of as much as 2.3% per year and a Sharpe ratio 77% higher relative to the historical mean. We conclude that there is substantial predictability in equity returns and that it would have been possible to time the market in real time.

Suggested Citation

Ferreira, Miguel Almeida and Santa-Clara, Pedro, Forecasting Stock Market Returns: The Sum of the Parts is More than the Whole (December 2008). NBER Working Paper No. w14571. Available at SSRN: https://ssrn.com/abstract=1320797

Miguel Almeida Ferreira (Contact Author)

Nova School of Business and Economics ( email )

Campus de Campolide
Lisbon, 1099-032
Portugal

European Corporate Governance Institute (ECGI) ( email )

c/o ECARES ULB CP 114
B-1050 Brussels
Belgium

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

Pedro Santa-Clara

New University of Lisbon - Nova School of Business and Economics ( email )

Lisbon
Portugal

HOME PAGE: http://docentes.fe.unl.pt/~psc/

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

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