Empirical Asset Pricing With Many Assets and Short Time Series
34 Pages Posted: 28 Nov 2018
Date Written: October 31, 2018
We construct tracking portfolios consisting of a large number of assets for macroeconomic factors using the L_2-boosting algorithm. We use these tracking portfolios as instruments to estimate factor risk prices. The same learning algorithm also provides the weights of a mean-variance efficient portfolio. With this additional input we compute the Hansen-Jagannathan distance to compare how alternative models fit the cross-section. We apply the method to 900 portfolio return series in the Kenneth French data library. While macro factors fail to explain most cross-sectional variation, we find that both consumption and inflation risk are priced.
Keywords: Boosting, Asset Pricing Tests, Hansen-Jagannathan Distance
JEL Classification: G12, C44, C55
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