Essays on Asset Pricing and Econometrics
CitationJin, Tao. 2014. Essays on Asset Pricing and Econometrics. Doctoral dissertation, Harvard University.
AbstractThis dissertation presents three essays on asset pricing and econometrics. The first chapter identifies rare events and long-run risks simultaneously from a rich data set (the Barro-Ursua macroeconomic data set) and evaluates their contributions to asset pricing in a unified framework. The proposed model of rare events and long-run risks is estimated using a Bayesian Markov-chain Monte-Carlo method, and the estimates for the disaster process are closer to the data than those in the previous studies. Major evaluation results in asset pricing include: (1) for the unleveraged annual equity premium, the predicted values are 4.8%, 4.2%, and 1.0%, respectively; (2) for the Sharpe ratio, the values are 0.72, 0.66, and 0.15, respectively.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:12269843
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