Conditional Asset Pricing with a Large Information Set

摘要: Dynamic factors summarize the information in a large number of variables and are therefore intuitively appealing proxies for set available to investors. This paper demonstrates that conditioning on dynamic instead commonly used instruments substantially reduces pricing errors implied by conditional models. further shown exhibit incremental explanatory power over benchmark variables. The results withstand robustness tests carry important implications specification asset models applied research practice.