High Frequency Market Making
Abstract
In this lecture, the speaker will propose a model of dynamic trading where a strategic high frequency trader receives an imperfect signal about the future order flow, and exploits speed advantage to act as a market maker. The speaker will also characterize the optimal market making policy of the high frequency trader analytically and illustrate that it generates endogenous order cancellations. The model predicts that high frequency traders provide more liquidity as they get faster and shy away from it as volatility or competition increases due to higher risk of their stale quotes being picked by arbitrageurs. Finally, the speaker will also provide the first formal model-based analysis of the impact of various policies designed to regulate high frequency trading. (joint work with M. SAGLAM)
About the speaker
Prof. Yacine Ait-Sahalia received his PhD in Economics from Massachusetts Institute of Technology in 1993. He joined the University of Chicago afterwards as an Assistant Professor in Finance and moved to Princeton University in 1998. He is currently the Otto A. Hack 1903 Professor of Finance and Economics in Princeton.
Prof. Ait-Sahalia’s research focuses on the estimation of continuous-time models in financial economics. His primary contributions include the development of nonparametric methods for estimating and testing these models, of expansions to implement maximum-likelihood estimation of arbitrary models using discrete data, and numerous advances in the estimation and testing of models using high frequency data with a focus on understanding the role and importance of jumps.
Prof. Ait-Sahalia was elected the Alfred P. Sloan Research Fellow in 1998 and John Simon Guggenheim Memorial Foundation Fellow in 2008. He was also elected a Fellow of the Econometric Society in 2002, of the Institute of Mathematical Statistics in 2004, of the American Statistical Association in 2008 and of the Society for Financial Econometrics in 2013. He has also been editor of the Review of Financial Studies, and is currently co-Managing Editor of the Journal of Econometrics.
