[POSTPONED] A robust high frequency financial econometrics

Abstract: Motivated by some problems in high frequency financial econometrics, using an in-fill argument, the properties of the sample median of a sequence of events are established both for the case of a fixed period of time and for a period which shrinks as the sample size grows.  The results are used to study the properties of volatility and regression type estimators under stochastic volatility.

Bio: Neil Shephard’s broad research interests are in econometrics, finance and statistics, with a particular focus on financial econometrics.   He has made significant advances in developing simulation based inference methods for online learning and has contributed methods to allow the mainstream use of high frequency financial data in economics.

He joined the Harvard faculty in 2013 as Professor of Economics and of Statistics, holding the position equally between the Economics Department and the Statistics Departments.  He was chair of the Harvard University’s Department of Statistics from 2015 to 2022.   In 2018 he became the Frank B. Baird, Jr. Professor of Science, still working in the Economics and Statistics Departments.

Professor Shephard is a fellow of the Econometric Society, the British Academy, the Society for Financial Econometrics and the International Association for Applied Econometrics.  Professor Shephard was a faculty member at the London School of Economics from 1988-1993 and Nuffield College, Oxford from 1991 to 2013.  He received his Ph.D. from the LSE in 1990.