COURSE LEADER: ELISABETTA PELLINI, GIOVANNI URGA
COURSE ID: D-EF38-OL
LANGUAGE:
The modelling and forecasting of energy prices and volatility has become of utmost importance in the current turbulent times. The statistical features 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.
The objective of TStat’s “Forecasting Energy Prices and Volatility with EViews” course is to provide participants with the specific analytical tools to undertake a rigorous and in- depth analysis of prices in international energy markets. 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.
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.
Researchers and professionals working either: i) in the energy and related sectors, needing to model energy price and demand, and ii) on trading desks in financial institutions. Economists based in research policy institutions. Students and researchers in engineering, econometrics and finance needing to learn the econometrics methods and tools applied in this field.
Participants should have a knowledge of the inferential statistics and introductory econometric methods illustrated in Brooks (2019).
This module aims to introduce EViews, so participants do not need to possess any previous knowledge of the software.
SESSION I: MODELS FOR ENERGY PRICES
Analysis of energy prices time series:
Stationarity
Autocorrelation
Conditional heteroscedasticity
Fat tails
Univariate time series models for forecasting energy prices (ARMA, ARIMA, ARFIMA, SARIMA);
Vector autoregressive (VAR) models for forecasting energy prices and for understanding interdependences between energy markets.
SESSION II: MODELS FOR ENERGY PRICES VOLATILITY
ARCH, GARCH, GARCH-in-mean and IGARCH models for energy prices volatility. Inverse leverage effect in energy markets. Estimating asymmetric GARCH models (SAARCH, EGARCH, GJR, TGARCH, APARCH)
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 REFERENCES
Introductory Econometrics for Finance. Brooks, C., (2019). Cambridge University Press, 4th edition.
Due to the current COVID-19 situation, the 2021 edition of this Training Course will also be offered ONLINE.
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.
Full-time Students*: € 355.00
University: € 505.00
Commercial: € 675.00
*To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year.
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.
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.
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.
Individuals interested in attending the training course should contact TStat Training to ask for a registration form. The completed application should then be returned to TStat by 2nd April 2021.
ONLINE FORMAT
The modelling and forecasting of energy prices and volatility has become of utmost importance in the current turbulent times. The statistical features 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.
The objective of TStat’s “Forecasting Energy Prices and Volatility with EViews” course is to provide participants with the specific analytical tools to undertake a rigorous and in- depth analysis of prices in international energy markets. 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.