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.
Prerequisites
Please note to take this course you must first have completed Time Series Econometrics and Forecasting.
Delivery
This module consists of 2-hour lectures per day for 5 days, plus a 1-hour tutorial per day. There will be optional clinics on the last day of the course.
Study Hours
Approximately 100 hours of study, of which 15 are contact hours and 85 are private study.
Software Used
OxMetrics 9
Credits
10 CATS credits
Programme Faculty
Programme Faculty
Key Outcomes
- —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
Desired Skills
- —Understand research papers focusing on intraday financial data
- —Estimate realized volatility and bi-power variation
- —Test the presence of discontinuities in intraday prices
- —Estimate the intraday periodicity in the volatility
- —Understand the concept of Epps effect
- —Calculate realized correlations
- —Apply basic statistical techniques to analyse intraday financial data
- —Work effectively both individually and within a team environment
Lecture Programme
- WK 01
Lecture 1: Introduction: Stylized facts for (Intraday) Financial Returns
- WK 02
Lecture 2: Univariate GARCH models
- WK 03
Lecture 3: Non-parametric volatility
- WK 04
Lecture 4: Intraday periodicity
- WK 05
Lecture 5: Jumps
Assessment
Online coursework submission with the support of your module lecturer and tutor. All sessions are conducted live online at a scheduled time and recorded for review.