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Maximizing Predictability in the Stock and Bond Markets


Andrew W. Lo


Massachusetts Institute of Technology (MIT) - Sloan School of Management; Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL); National Bureau of Economic Research (NBER)

A. Craig Mackinlay


University of Pennsylvania - Finance Department; National Bureau of Economic Research (NBER)

February 1995

NBER Working Paper No. w5027

Abstract:     
We construct portfolios of stocks and of 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 for predictability by using several asset groups, including industry-sorted 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, we show that the predictability of the maximally predictable portfolio is genuine and economically significant.

Number of Pages in PDF File: 60

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Date posted: July 25, 2000  

Suggested Citation

Lo, Andrew W. and Mackinlay, A. Craig Craig, Maximizing Predictability in the Stock and Bond Markets (February 1995). NBER Working Paper No. w5027. Available at SSRN: http://ssrn.com/abstract=225806

Contact Information

Andrew W. Lo (Contact Author)
Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )
100 Main Street
E62-618
Cambridge, MA 02142
United States
617-253-0920 (Phone)
781 891-9783 (Fax)
HOME PAGE: http://web.mit.edu/alo/www
Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)
Stata Center
Cambridge, MA 02142
United States
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
Archie Craig MacKinlay
University of Pennsylvania - Finance Department ( email )
The Wharton School
3620 Locust Walk
Philadelphia, PA 19104
United States
215-898-5309 (Phone)

National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
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