Training Calendar

Data Science for Financial Markets - Co-Developed with Lancaster University

Online 2 days (12th March 2021 - 13th March 2021) EViews Intermediate, Introductory
Econometrics, Finance, Marketing, Various methods

Overview

This course is co-developed with Lancaster University.

At times of great uncertainty for financial markets, this course provides participants with an understanding of the time series methods involved in modelling and forecasting financial markets volatilities. Participants will learn how to build, estimate and assess alternative models of volatility of financial time series. Each concepts will be explained from an econometric perspective and by means of many examples and applications in EViews

Co movements and correlation of financial returns help to explain crisis transmission in the markets , this course provides participants with an in depth understanding of multivariate GARCH models and their use in forecasting co movements and crisis transmission between financial markets.

Students are eligible for a subsidised place, find out how to apply here.

Course Agenda

This comprehensive webinar is hosted through Zoom and runs over a total of 9 hours, with 4 hours each day (2 in the morning and 2 in the afternoon) with an extra Q&A session on the second day.

Day 1

Session 1: Stylized facts of financial time series - 10:00-12:00 GMT

  • Descriptive stats and leverage effects, non-normal distribution, stationarity, long memory, volatility clustering. The ARCH test.

Session 2: GARCH models for volatilities - 14:00-16:00 GMT

  • GARCH, EGARCH, GJR. Estimation. Testing and Forecasting in Eviews. The ARMA-GARCH framework.

Day 2:

Session 1: Analysing the co-movements of financial returns - 10:00-12:00 GMT

  • MGARCH models advantages and challenges. Estimation , testing and Diagostics in Eviews.

Session 2: Structural breaks in financial markets - 14:00-16:00 GMT

  • What will happen after the COD-19 emergency? Make your own prediction with Eviews.

Q&A Session: 16:00-17:00 GMT

Prerequisites

  • Introductory knowledge of linear regression and time series econometrics.
  • A basic knowledge of EViews is helpful but not necessary.

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.
  • Attendees are provided with temporary licenses for the software(s) used in the course and will be instructed to download and install the software prior to the start of the course.
  • 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 over 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.
  •  CommercialAcademicStudent
    2-Day Pass (12/03/2021 - 13/03/2021)

All prices exclude VAT or local taxes where applicable.

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