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Essays on Asset Pricing and Econometrics

This 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. / Economics

Identiferoai:union.ndltd.org:harvard.edu/oai:dash.harvard.edu:1/12269843
Date06 June 2014
CreatorsJin, Tao
ContributorsBarro, Robert J., Campbell, John Y.
PublisherHarvard University
Source SetsHarvard University
Languageen_US
Detected LanguageEnglish
TypeThesis or Dissertation
Rightsopen

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