Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
