Forecasting Energy Prices and Volatility (Online)

Forecasting Energy Prices and Volatility (Online)

Posted on

Start Date

End Date

Type

Professional training

Reference Number

D-EF38-OL

Certifications & Titles

Certificate of participation

Study Options

Part Time

Fees

Regular fees: 355 - 675 EUR

Comment:

Kindly note:

  1. To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year.
  2. Fees are subject to VAT (applied at the current Italian rate of 22%). Under current EU fiscal regulations, VAT will not however applied to companies, Institutions or Universities providing a valid tax registration number. 
  3. The number of participants is limited to 8. Places, will be allocated on a first come, first serve basis. The course will be officially confirmed, when at least 5 individuals are enrolled.
  4. Course fees cover: course materials (handouts and datasets to be used during the course), a temporary licence of EViews valid for 30 days from the beginning of the course.

Funding Options

Students have access to discounted courses fees

Modelling and forecasting of energy prices and volatility has become of utmost importance in the current turbulent times.  Furthermore, the statistical charateristics of energy data, which tends to follow periodic patterns and exhibit spikes, non-constant means and non-constant variances, renders the task of forecasting energy prices somewhat challenging. In our "Forecasting Energy Prices and Volatility with EViews” course, we provide participants with the specific analytical tools to undertake a rigorous and in- depth analysis of prices in international energy markets. As such, the programme covers a wide range of econometric methods currently available to researchers and practitioners, such as: i) univariate and multivariate time series models to estimate and forecast prices and ii) univariate and multivariate GARCH models for the estimation and forecast of price volatility.

 

Program Overview: 

Session I: Models for Energy Prices

  1. Analysis of energy prices time series: 
  2. Stationarity;
  3. Autocorrelation;
  4. Conditional heteroscedasticity;
  5. Fat tails;
  6. Univariate time series models for forecasting energy prices (ARMA, ARIMA, ARFIMA, SARIMA);
  7. Vector autoregressive (VAR) models for forecasting energy prices and for understanding interdependences between energy markets.

Session II: Models for Energy Price Volatility

  1. ARCH, GARCH, GARCH-in-mean and IGARCH models for energy prices volatility;
  2. Inverse leverage effect in energy markets; 
  3. Estimating asymmetric GARCH models (SAARCH, EGARCH, GJR, TGARCH, APARCH);
  4. Modelling cross-markets correlations and testing for volatility spillovers with MGARCH models: Diagonal VECH (DVECH), Constant Conditional Correlation (CCC), Dynamic Conditional Correlation (DCC) models.

Course Leader:

Dr. Elisabetta Pellini

Course Prerequisites:

Participants should have a knowledge of the inferential statistics and introductory econometric methods illustrated in Brooks (2019).

During the course participants will be simultaneously introduced to the econometric software EViews. Attendees do not need therefore, any previous knowledge of the software.

Course Structure:

The course will take place online via TStat Training's Virtual Classroom Portal. To facilitate the transition to an online format, the course programme has been transformed into 2 sessions running from 4.00 pm to 19.30 pm Central European Time (CET) on the 12th-13th of April 2021.

In common with TStat’s training philosophy, throughout the course the theoretical sessions are reinforced by case study examples, in which the course tutor discusses current research issues, highlighting potential pitfalls and the advantages of individual techniques. The intuition behind the choice and implementation of a specific technique is of the utmost importance. In this manner, course leaders are able to bridge the “often difficult” gap between abstract theoretical methodologies, and the practical issues one encounters when dealing with real data. At the end of the course, participants are expected to be able to autonomously implement the theories and methodologies discussed in the course.

 

 

More Information

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Full Name
Cover Letter
Password
Your Account Password

Attendance

Online

Posted on

Start Date

End Date

Type

Professional training

Reference Number

D-EF38-OL

Certifications & Titles

Certificate of participation

Study Options

Part Time

Fees

Regular fees: 355 - 675 EUR

Comment:

Kindly note:

  1. To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year.
  2. Fees are subject to VAT (applied at the current Italian rate of 22%). Under current EU fiscal regulations, VAT will not however applied to companies, Institutions or Universities providing a valid tax registration number. 
  3. The number of participants is limited to 8. Places, will be allocated on a first come, first serve basis. The course will be officially confirmed, when at least 5 individuals are enrolled.
  4. Course fees cover: course materials (handouts and datasets to be used during the course), a temporary licence of EViews valid for 30 days from the beginning of the course.

Funding Options

Students have access to discounted courses fees