This dissertation focuses on the consumption-based asset pricing models developed by Lucas (1978). The first chapter studies the effect of a change in aggregate risk on the prices of bonds and stocks. A decomposition method of the dividend and discount rate effect is defined. Sufficient conditions on preferences are specified such that an increase in risk guarantees a fall in stock prices. In the second chapter, an empirical study examines whether Bayesian learning can help the Lucas-type models predict the low levels of short-term real interest rates in the US. The results show that parameter uncertainty alone cannot resolve the risk-free rate puzzle. The learning process ends too rapidly for parameter uncertainty to play an important role in affecting bond returns. The third chapter investigates whether the downturns of business cycles have caused the falls of real interest rates. A standard Lucas-type model, with an added feature that investors have to learn about the unobservable alternation of business cycles, is calibrated. The simulation technique of the Markov Chain Monte Carlo is used to compute the real interest rates.

About the Author

Dr. Yongli Zhang received his Ph.D. in Economics from the University of California at Santa Barbara in 2007. He is now Assistant Professor at China Economics and Management Academy of the Central University of Finance and Economics in Beijing. His research interest is in the fields of asset pricing, corporate finance and applied econometrics.

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