INTRODUCTION TO EMPIRICAL FINANCE
Instructor: Eric Ghysels
This course is intended for PhD students in finance and related fields. It is designed to teach
students how to conduct empirical research in asset pricing. The goal is that students become
familiar with the issues at stake in empirical asset pricing, the methodologies used, the
classic papers as well as the recent
contributions, and be able to analyze and evaluate new research effectively. Finally, students are expected
to acquire the skills to conduct and present original empirical research in finance.
Material from the following books will be used throughout the course:
John Y. Campbell, Andrew W. Lo and A. Craig MacKinlay, The Econometrics of Financial Markets, Princeton University Press, 1997.
John Cochrane, Asset Pricing,
Alastair Hall, Generalized Method of Moments, Oxford
University Press, 2005.
Kenneth J. Singleton, Empirical Dynamic Asset Pricing: Model
Specification and Econometric Assessment, Princeton
University Press, 2006.
Michael Johannes and Nicholas Polson, Bayesian Computation: Markov Chain Monte Carlo
and Particle Filtering, Unpublished Manuscript, 2010.
In addition to the books we will also assign journal articles
(most downloadable from JSTOR and/or UNC e-journal links).
This year the course will focus on four broad topics that will be covered in detail. They are (1) GMM estimation and applications to asset pricing, (2) models of asset price volatility - discrete and continuous time, (3) affine term structure models, and (4) Bayesian MCMC methods applied to empirical asset pricing.
Prerequisites are: Econ 770, 771 and Busi 880. This means students must have basic knowledge of
financial economics and econometrics at the level of first year PhD courses. Knowledge of the material in Econ
871 (Time Series) is beneficial.