Statistical Methods for High-Frequency Data
July 6 - July 10, 2015
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.
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.
The course will take place in Auditorium 10 at the H.C. Ørsted Institute, Universitetsparken 5, 2100 Copenhagen, Denmark.
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.
Deadline for registration has passed.
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
Please find the tentative course syllabus, including exercise sheets, here.
- 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.
Several public busses stop at the H.C. Ørsted Institute. For more information, click here.
- Emil S. Jørgensen (contact person)
- Michael Sørensen