Over the past two decades several countries around the world have liberalized their energy markets, with the result that the risk for utilities, energy producers and commodity market operators has increased substantially. In this new environment, accurate modelling and forecasting of energy demand and prices has become of key importance for all market players to plan their short- and long-term operations. This course provides a review of and a practical guide to several major econometric methodologies to modelling the stylised facts of the energy prices and demand time series, via regression and cointegration analysis, univariate and multivariate GARCH models. Practical demonstrations will be conducted using Stata.
- 50% Theory, 20% Demonstration and 30% Practical
Modelling demand and energy prices (electricity, crude oil, natural gas):
Session 1 & 2:
Session 3 & 4:
- Introduction to energy time series: seasonality, normality, stationarity, autocorrelation, heteroscedasticity and model selection
- Univariate time series models for energy data (AR, MA, ARMA, ARIMA)
- Empirical application 1: Model selection and estimation in practice
- Long-run relationships in energy: applying cointegration analysis to model the determinants of energy demand and to evaluate energy markets integration
- Empirical application 2: An empirical application of cointegration techniques to model electricity demand
Modelling energy prices volatility (electricity, crude oil, natural gas):
Sessions 1 & 2:
Sessions 2 & 3:
- Univariate ARCH and GARCH models: ARCH, GARCH, GARCH-in-mean, asymmetric GARCH models, news impact curve, alternative GARCH specifications
- Empirical Application 3: Fitting ARCH and GARCH models
- Multivariate GARCH. Modelling cross-markets correlations and testing for volatility spillovers between energy markets
- Empirical Application 4: Testing for spillover effects between European electricity markets
09:30-11:00 Session 1
11:00-11:15 Tea/coffee break
11:15-12:45 Session 2
14:00-15:15 Session 3
15:15-15:30 Tea/coffee break
15:30-17:00 Session 4
Principal texts for pre-course reading:
- C. Brooks (2014). Introductory Econometrics for Finance. Cambridge University Press, 3rd Edition.
Principal texts for post-course reading:
Several academic papers will be suggested during the course to complement the syllabus.
Basic knowledge of statistics and econometrics.
For full Training Courses Terms & Conditions please click here.
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.