Maximizing Predictability in the Stock and Bond Markets

60 Pages Posted: 25 Jul 2000 Last revised: 28 Sep 2022

See all articles by Andrew W. Lo

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Laboratory for Financial Engineering

A. Craig Mackinlay

University of Pennsylvania - The Wharton School, Finance Department

Date Written: February 1995

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.

Suggested Citation

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

Andrew W. Lo (Contact Author)

Massachusetts Institute of Technology (MIT) - Laboratory for Financial Engineering ( email )

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Archie Craig MacKinlay

University of Pennsylvania - The Wharton School, Finance Department ( email )

The Wharton School
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Philadelphia, PA 19104
United States
215-898-5309 (Phone)

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