Curved Architectural Structure

Econometrics of High
Frequency Data

The purpose of this course is to provide students with an introduction to various methods applicable to high-frequency financial data. This includes the study of the statistical properties of these series such as heteroskedasticity, periodicity, the presence of jumps and microstructure noise.

 

Different methods will be discussed such as GARCH models, the estimation of the intraday periodicity in volatility, jumps tests but also various non-parametric estimators of the class of the realized volatility

This module can be taken as part of a PG Certificate, PG Diploma or Full Masters Program. 

Key Skills

The basic properties of high-frequency financial series.

The main continuous time processes.

The identification of jumps in high-frequency financial series.

The calculation of the daily volatility from intra-day data.

By the end of this course, participants should have knowledge and ability to: 

Desired Skills

Understand research papers focusing on intraday financial data.

Estimate realized volatility and bi-power variation. Apply basic statistical techniques to analyse intraday financial data.

Test the presence of discontinuities in intraday prices.

Estimate the intraday periodicity volatility. Understand the concept of Epps effect.

By the end of this course, students should be able to: 

Structure

 

Econometrics of High Frequency Data is an elective 10 credit course and therefore students are expected to input approximately 100 hours of study into the course.

 

The total number of contact hours is 15 hours. This leaves 85 hours for private study.

Lectures

 

 

 

This module consists of 2- hour lectures per day, for 5 consecutive days, plus a 1 - hour tutorial per day.

 There will be optional clinics on the last day of the course.