Flexible learning
Online postgraduate courses
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.
- 10 Credits
- 100 hours of study
- 15 contact hours
- 85 hours for private study
Faculty
Structure
Structure
Econometrics of Energy Markets is an elective 10 credit course and therefore students are expected to input approximately 100 hours of study into the course.
The total number of contact hours is 15 hours. This leaves 85 hours for private study.
Lectures
This module consists of 2- hour lectures per day for 5 days, plus a 1 - hour tutorial per day.
During your private study, you should strike a balance between reading the course material and the recommended textbook. You will also carry out applied exercises using the computer packages.
The dates of each lecture are confirmed closer to the start of each term. If you have any questions about dates, please contact edu@timberlake.co.uk.
EViews
Python
Module Programme
Stationary time series
- 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
- ARIMA models
- Structural time series models
- Estimating ARIMA models in Eviews and Python
Univariate GARCH models of energy returns
- Short memory GARCH : estimation and testing
- Long memory GARCH ; estimation and testing
- Forecasting energy returns with GARCH models
Multivariate GARCH models
- CCC, DCC, BEKK models
- Estimation of MGARCH Models in Python
Modelling the Value at risk
- Historical approach
- Parametric approach
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
- 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:
- 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
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.
All modules are examined through online coursework submissions, you will have the support of your module lecturer/tutor in this poccess.
No, all necessary software is provided to students.
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.
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.
Flexible learning
Online postgraduate courses
Specialist courses
Best-in-field experts
Tailored learning
Career-oriented education
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Flexible learning
Online postgraduate courses
Specialist courses
Best-in-field experts
Tailored learning
Career-oriented education