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Modelling & Forecasting Energy Prices & Demand Using Stata

  • Location: Sofitel, Downtown Dubai
  • Duration: 2 days (27th November 2017 - 28th November 2017)
  • Software: Stata
  • Level: Intermediate, Introductory
  • Topic: Econometrics, Finance, Macroeconomics, Statistics
Modelling & Forecasting Energy Prices & Demand Using Stata
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.

Course Agenda

Learning Ratio

  • 50% Theory, 20% Demonstration and 30% Practical

Day 1

Modelling demand and energy prices (electricity, crude oil, natural gas):

Session 1 & 2:
  • 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
Session 3 & 4:
  • 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

Day 2

Modelling energy prices volatility (electricity, crude oil, natural gas):

Sessions 1 & 2:
  • 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
Sessions 2 & 3:
  • 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

Daily timetable

09:00-09:20 Registration

09:30-11:00 Session 1

11:00-11:15 Tea/coffee break

11:15-12:45 Session 2

12:45-14:00 Lunch

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.


  •  CommercialAcademicStudent
    2 - day (27/11/2017 - 28/11/2017)

All prices exclude VAT or local taxes where applicable.

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