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MAXIMIZING PREDICTABILITY IN THE STOCK AND BOND MARKETS

Published online by Cambridge University Press:  02 March 2005

ANDREW W. LO  and
A. CRAIG MACKINLAY
ANDREW W. LO
Affiliation:
Sloan School of Management, Massachusetts Institute of Technology
A. CRAIG MACKINLAY
Affiliation:
The Wharton School, University of Pennsylvania
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Extract

We construct portfolios of stocks and bonds that are maximally predictable with respect to a set of ex-ante observable economic variables, and show that these levels of predictability are statistically significant, even after controlling for data-snooping biases. We disaggregate the sources of predictability by using several asset groups — sector portfolios, market-capitalization portfolios, and stock/bond/utility portfolios — and find that the sources of maximal predictability shift considerably across asset classes and sectors as the return horizon changes. Using three out-of-sample measures of predictability — forecast errors, Merton's market-timing measure, and the profitability of asset-allocation strategies based on maximizing predictability — we show that the predictability of the maximally predictable portfolio is genuine and economically significant.

Keywords

PredictabilityStocksBondsPortfolio ManagementMaximally Predictable Portfolio
Type
Research Article
Information
Macroeconomic Dynamics , Volume 1 , Issue 1 , January 1997 , pp. 102 - 134
Copyright
© 1997 Cambridge University Press

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