Maximum-Likelihood Estimation of Continuous-Time Models with Applications to Stochastic Volatility, Term Structure and Other Asset Pricing Models (Part II)

Prof. Yacine Aït-Sahalia

Princeton University

About the Speaker

Yacine Aït-Sahalia is the Otto Hack 1903 Professor of Finance and Economics at Princeton University. His primary area of research is financial econometrics. Prior to that, he was an Assistant Professor (1993–1996), Associate Professor (1996–1998) and Professor of Finance (1998) at the University of Chicago Booth School of Business.

He received his undergraduate degree from École Polytechnique in Paris, France in 1987 and from École Nationale des Statistiques et de l’Administration Economique in 1989, and his Ph.D. in Economics from the Massachusetts Institute of Technology in 1993.

He has served as Editor of the Review of Financial Studies (2003–2006), Co-Editor of the Journal of Econometrics (since 2012), and Associate Editor of the Annals of Statistics (2003–2006), Econometrica (2007–2013), the Journal of Finance (2007–2010), Finance and Stochastics (1996–2011), the Journal of Econometrics (1999–2012) and the Journal of Financial Econometrics (2001–2011). He served as Director of the Western Finance Association (2003–2006) and is a Research Associate for the National Bureau of Economic Research (since 1995).

Abstract

These two lectures will describe recent developments to estimate and test continuous-time models in finance using discrete observations on the underlying asset price, or derivative securities' prices, all in closed form for arbitrary specification of the model. Both parametric and nonparametric methods are described. All these methods share a common focus on the transition density as the central object for inference and testing of the model.