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The nonlinear multidimensional relationship between stock returns and the macroeconomy

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We use nonparametric dimension-reduction methods to extract from a set of 15 macroeconomic variables the risk factors that are priced in the stock market. The dominant factor moves with the business cycle but, because it is a nonlinear function of observed macroeconomic variables, it captures a rich set of interactions. Low-credit risk and low-inflationary expectations have a greater positive effect on stock returns when leading macroeconomic indicators are high relative to current economic activity, i.e. early in the business cycle as the economy emerges from recession. High-stock returns also arise in periods when the economy is booming relative to its leading indicators, but such periods tend to portend crashes.
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Keywords: C39; G12; asset pricing; business cycle; curse of dimensionality; data visualization

Document Type: Research Article

Affiliations: 1: Bates White, LLC, Washington, DC, 20005, United States 2: Department of Agricultural and Resource Economics, University of California, Davis, CA, 95616, United States

Publication date: 01 December 2013

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