Statistical Methods for High-Frequency Data

July 6 - July 10, 2015

Abstract

In recent years there has been a vast increase in the amount of high-frequency data available, particularly in finance. Their analysis may require methods different from the common ones for time series of regularly spaced data, and there has been an explosion in the literature on this subject. In this course we start from scratch, introducing a probabilistic model for such data, and then turn to estimation in this model, with main emphasis on estimating volatility. Similar techniques to those we present can be applied to estimate leverage effects, realized regressions, semi-variances, doing analyses of variance, detecting jumps, measuring liquidity by measuring the size of the microstructure noise, and many other objects of interest. The applications are mainly in finance, ranging from risk management to options hedging, execution of transactions, portfolio optimization and forecasting. Methodologies based on high-frequency data can also be found in neural science and climatology.

Lecturers

Per Mykland, University of Chicago
Lan Zhang, University of Illinois at Chicago

Credits/Exam

The workload of the course corresponds to 2,5 ECTS. Passing the course is based purely on active participation in lectures as well as exercises.

Location

The course will take place in Auditorium 10 at the H.C. Ørsted Institute, Universitetsparken 5, 2100 Copenhagen, Denmark.

Participants

The course is aimed at PhD students and postdocs with a strong background in probability theory and statistics. Researchers with a diffferent quantitative background are welcome to attend the course.

Registration

Deadline for registration has passed.

Structure

09:15 - 10:30 Lecture 1
10:30 - 10:45 Coffee and fruit
10:45 - 12:00 Lecture 2
12:00 - 13:15 Lunch
13:15 - 14:30 Lecture 3 / Exercises
14:30 - 15:00 Coffee and cake
15:00 - 16:15 Lecture 4 / Exercises

Supplementary literature

  • Y. Ait-Sahalia & J. Jacod, High-Frequency Financial Econometrics, Princeton University Press, 2014.
  • M. Podolskij & M. Vetter, Understanding limit theorems for semimartingales: a short survey, Statistica Neerlandica, Vol. 64, Nr. 3, pp. 329-351, 2010.

Getting here

Several public busses stop at the H.C. Ørsted Institute.

Organisers

  • Emil S. Jørgensen (contact person)
  • Michael Sørensen