High-Frequency Financial Econometrics using Matlab
Wednesday 27 May 2020, 9:00am to Thursday 28 May 2020, 5:30pm
Venue
Online eventOpen to
External Organisations, Postgraduates, Public, StaffRegistration
Cost to attend - booking requiredRegistration Info
To register and for further details please visit the Matlab course website
Ticket Price
Academic registration – High Frequency: £600 PhD student registration – High Frequency: £300 Practitioner registration – High Frequency: £950Event Details
The purpose of this online course is to provide an update treatment of the core topics in the modeling of high-frequency data.
Advances in computing and data technology make it possible to observe markets at very fine intervals of time. Using high-frequency data permits the calculation of realized measures which are superior to volatility measures generated from GARCH and stochastic volatility models. However, the processing and financial modeling of high-frequency data remains a challenge to both researchers and practitioners. This course aims to provide guidance on the techniques involved in processing, filtering and modeling such data. Using data from TAQ and TICK- DATA databases, the attendees will have an intensive introduction to both the theoretical and empirical aspects of high-frequency data.
Course Content
The object of the 2-day course is to demonstrate the empirical techniques and methods employed to analyze high-frequency data with special emphasis on the calculation of realized measures, forecasting and Monte Carlo methods and design.
Specific Objectives
- Familiarize with Matlab syntax, functions and write own functions.
- Computation of realized measures of volatility.Introductions to theoretical foundations and mathematical models of continuous/discontinuous time modeling.
- Forecasting techniques.
- Monte Carlo Simulations: Design and implementation.
Day 1:
Fundamentals of programming in Matlab
Importing and exporting data
Descriptive statistics and Density/log-density estimation
Inter and intra-daily plots
Time stamp, frequency conversion and data aggregation
Data bases comparison Tick vs TAQ
Data Types (Equity, Forex and Indices)
Day 2:
Estimation of Quadratic Variation and its Components
Stylized facts (normality, persistence and noise)
Intra-day periodicity
Leverage effect
Jump estimation and identification
Forecasting using short and long memory specifications
Monte Carlo Simulations
Contact Details
Name | Teresa Aldren |
Telephone number |
+44 1524 510906 |
Website |