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

57 Pages Posted: 22 Mar 2009 Last revised: 25 Jul 2010

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: July 14, 2010

Abstract

We propose forecasting separately the three components of stock market returns: the dividend-price ratio, earnings growth, and price-earnings ratio growth --- the sum-of-the-parts (SOP) method. Our method exploits the different time-series persistence of the components and obtains out-of-sample R-squares (compared to the historical mean) of more than 1.3% with monthly data and 13.4% with yearly data. This compares with typically negative R-squares obtained in a similar experiment with predictive regressions. The performance of the SOP method comes mainly from the dividend-price ratio and earnings growth components and the robustness of the method is due to its low estimation error. An investor who timed the market using our method would have had a Sharpe ratio gain of 0.3.

Keywords: Equity premium, forecasting, stock market, predictive regression

JEL Classification: G1

Suggested Citation

Ferreira, Miguel A. and Santa-Clara, Pedro, Forecasting Stock Market Returns: The Sum of the Parts is More than the Whole (July 14, 2010). AFA 2010 Atlanta Meetings Paper. Available at SSRN: https://ssrn.com/abstract=1363941 or http://dx.doi.org/10.2139/ssrn.1363941

Miguel Almeida Ferreira

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 )

77 Bastwick Street
London, EC1V 3PZ
United Kingdom

Pedro Santa-Clara (Contact Author)

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 )

77 Bastwick Street
London, EC1V 3PZ
United Kingdom

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