High-Frequency Financial Econometrics using Matlab

Monday 4 November 2019, 9:00am to Tuesday 5 November 2019, 5:30pm

Venue

The Work Foundation, London, SW1H 0AD - View Map

Open to

External Organisations, Postgraduates, Prospective Students, Public, Staff

Registration

Cost to attend - booking required

Registration Info

To register and for further details please visit the Matlab course website

Event Details

The purpose of this course is to provide an update treatment of the core topics inthe 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
Email

t.aldren@lancaster.ac.uk

Telephone number

+44 1524 510906

Website

http://wp.lancs.ac.uk/matlab-2019/