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High Frequency Financial Econometrics using Matlab

  • Location: Lancaster University Management School
  • Duration: 2 days
  • Software: Matlab
  • Level: Intermediate, Introductory
  • Delivered By: Rodrigo Hizmeri; Vasileios Pappas
  • Topic:
High Frequency Financial Econometrics using Matlab

Course Overview

COURSE DATE: 25-26 April 2018

This course provides an in-depth training in using Matlab in the analysis of high freuqncy financial data. Advances in computer power and data technology have led to the introduction of high frequency data. These data are vital in understanding issues pertaining to market microstructure noise, and permits the calculation of non-parametric intraday measures of variation that are superior to parametric measures based on daily data. The sheer size of this type of data often pause huge challenges to both researchers and practitioners. As such this course aims, using Matlab and state of the art high frequency data from TICKDATA database to highlight the best techniques and practices to overcome the empirical challenges of analysing high frequency data.

General Objectives: 

  • To demonstrate the empirical techniques and methods employed to analyse high frequency data with special emphasis on the calculation of realised measures, forecasting and Monte Carlo methods and design

Specific Objectives:

  • Learn how to write efficient codes in Matlab
  • Be able to create your own functions in Matlab
  • Learn how to compute realised measures of volatility and generate forecasts
  • Develop an understanding of the theoretical foundations and mathematical models of continuous / discontinuous time modelling
  • Monte Carlo Methods, Design and Implementation

Course Agenda

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
  • Stylizised facts (Normality, persistence and noise)
  • Intra-day periodicty 
  • Leverage effects
  • Jump estimation and identification
  • Forecasting using short and long memory specifications
  • Monte Carlo Simulations

Terms & Conditions

  • Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
  • Additional discounts are available for multiple registrations.
  • Cost includes course materials, lunch and refreshments.
  • Delegates are provided with temporary licences for the principal software package(s) used in the delivery of the course. It is essential that these temporary training licenses are installed on your computers prior to the start of the course. We can provide laptops to attendees. Prior notice is required and additional charges will apply.
  • Should you need assistance in locating hotel accommodation in the immediate vicinity of the course location, please notify us at the time of booking.
  • Payment of course fees required prior to the course start date.
  • Registration closes 5-calendar days prior to the start of the course.
    • 100% fee returned for cancellations made more than 28-calendar days prior to start of the course.
    • 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
    • No fee returned for cancellations made less than 14-calendar days prior to the start of the course.

The number of attendees is restricted. Please register early to guarantee your place.

  •  CommercialAcademicStudent
    2-day pass (25/04/2018 - 26/04/2018)

All prices exclude VAT or local taxes where applicable.

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