Professor Lan Zhang : High frequency financial data and the hidden semimartingale model

Posted by , part of the Statistics and Data Science Seminar.

At

Sept. 14, 2005, 3 p.m.

In

SEO 512

Abstract

The availability of high frequency data for financial instruments has opened the possibility of accurately determining volatility in small time periods, such as one day. Recent work on such estimation indicates that it is necessary to treat the data with a hidden semimartingale model, typically by the addition of measurement error. We review the emerging theory on this subject, including two- and multiscale sampling.

Drink, Cake and more are provided.