MAXIMIZING PREDICTABILITY IN THE STOCK AND BOND MARKETS

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Abstract
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.

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