Virtual Open Day! 19 November @1PM GMT | Register Now!
Virtual Open Day! 19 November @1PM GMT | Register Now!
Virtual Open Day! 19 November @1PM GMT | Register Now!
Virtual Open Day! 19 November @1PM GMT | Register Now!
Virtual Open Day! 19 November @1PM GMT | Register Now!
Virtual Open Day! 19 November @1PM GMT | Register Now!
10 Credits

Econometrics of Energy Markets

This course will show how energy returns can be modelled, analysed, and forecasted. The aim is to provide understanding and insight into the methods used, as well as explaining the technical details. Econometric modelling and forecasting will be demonstrated using EViews and Matlab software, two powerful tools for econometric analysis; participants will be given the opportunity to learn how to use the software effectively in class.

The course will discuss univariate and multivariate GARCH models for energy returns and the Value at Risk and Global Minimum Variance portfolio used by policy markets, traders and academics to identify the best econometric model of energy returns

​This module can be taken as part of a PG Certificate, PG Diploma or Full Masters Program.

Econometrics of Energy Markets
  • 10 Credits
  • 100 hours of study
  • 15 contact hours
  • 85 hours for private study
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Qualifications accredited by Lancaster University
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Buildable Qualifications
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Learn Around
Your Schedule
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World-Class
Faculty
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Fully Online

Structure

Software

Module Programme

Stationary time series

Session Content
  • Review of the basic concepts of stationary time series
  • Stylized fact of energy returns
  • Short and Long memory dependence in returns time series

Univariate Linear Time series models of energy returns

Session Content
  • ARIMA models
  • Structural time series models
  • Estimating ARIMA models in Eviews and Python

Univariate GARCH models of energy returns

Session Content
  • Short memory GARCH : estimation and testing
  • Long memory GARCH ; estimation and testing
  • Forecasting energy returns with GARCH models

Multivariate GARCH models

Session Content
  • CCC, DCC, BEKK models
  • Estimation of MGARCH Models in Python

Modelling the Value at risk

Session Content
  • Historical approach
  • Parametric approach

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Prerequisites

English Language Requirements

Both Programmes are open to applicants anywhere in the world. We may ask applicants to provide a recognised English language qualification, dependent upon their nationality and where they have studied/worked previously.

 The requirement is an IELTS (Academic) Test with an overall score of at least 6.5, and a minimum of 6.0 in each element of the test. We will also consider other English language qualifications. If their score is below our requirements, they may be eligible for one of Lancaster University's pre-sessional English language programmes.

Academic Requirements

Applicants to the Postgraduate Certificate of Achievement, Postgraduate Certificate, Postgraduate Diploma or full MSc in either programme require either an upper second-class degree in economics, econometrics or related subjects.

Learning Outcomes

Key Skills
  • The modelling of univariate and multivariate time series of energy returns
  • Practical time series modelling using EViews and Python
  • Nonlinear time series models, including volatility modelling and the score-driven approach
  • Forecasting energy price volatilities and correlation
  • Forecasting Value at risk for energy markets:
Desired Skills
  • Understand the nature of time series models and the way they are applied in practice
  • Present, interpret and analyse information and results from EViews and Python

Frequently Asked Questions

Are the courses within either programme conducted synchronously or asynchronously?

All sessions are conducted live and online at a scheduled time, but are also recorded. Students may attend live and watch the recordings back to recap the material or watch the recordings only if unable to attend live. We always advise students to attend live where possible as this will allow them the best opportunity to engage with the content and ask the lecturer's questions.

Is all examination undertaken online or in-person?

All modules are examined through online coursework submissions, you will have the support of your module lecturer/tutor in this poccess.

Do I need to buy any statistical/econometric software?

No, all necessary software is provided to students.

What do I do if I can't attend a course live?

All courses are recorded and available on the LUMS internet platform throughout the current academic year. They can therefore be viewed 24 hours a day.

A Collaboration Like No Other

Timberlake Consultants and Lancaster University Management School (LUMS) Economics department have a longstanding partnership; combining 40+ years of industry expertise with over 50 years of academic excellence. We are delighted to build on this with our micro-credential postgraduate courses.

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