Florence, Italy

Modelling and Forecasting Energy Markets

when 7 September 2020 - 11 September 2020
language English
duration 1 week

In the last two decades, the deregulation of energy markets and the increasing adoption of renewable energy have resulted in significant volatility of both energy price and demand worldwide. The modelling and forecasting of energy demand and price has therefore become of utmost importance, not only to energy producers themselves, but also to commodity traders and financial analysts focusing on the energy sector. 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 and modelling of energy data somewhat challenging.

The objective of TStat’s “Modelling and Forecasting Energy Markets” Summer School is therefore to provide participants with the specific analytical tools to undertake a rigorous and in-depth analysis of both prices and demand 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 demand and ii) univariate and multivariate GARCH models for the estimation and forecast of price volatility and risk management in energy markets.

Following TStat’s training philosophy, the teaching style features both theoretical sessions, where participants are given the intuition behind the choice of a specific technique, and several practical sessions using Stata. In this manner, the 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.

The Summer School opens with a one-day full-immersion module on energy data analysis with the statistical software Stata, which aims at developing the necessary practical skills to actively participate in the applied sessions during the course of the week.

The 2020 edition also includes an extended Case Study Group session during which participants will either work in small groups on a short applied case study analysis or on a presentation of their own research work using the techniques illustrated during the course of the week. Course leaders will discuss with participants the appropriateness of the methodologies adopted in their case study, the interpretation of the results obtained and also to indicate potential problems to be aware of given the characteristics of the underlying data, as well as providing feedback and guidance on possible future developments of individual research agendas.

At the end of the school participants are expected to be in a position to autonomously conduct energy markets analysis, with the aid of the Stata routines developed specifically for the Summer School. In particular, participants will be able to evaluate which econometric method is more appropriate to the analysis in hand and will be able to test the appropriateness of their estimated model and the robustness of the results obtained.

Course leader

Dr Elisabetta PELLINI, Centre for Econometric Analysis, Cass Business School, London (UK)

Professor Giovanni URGA, Centre for Econometric Analysis, Cass Business School, London (UK) and Bergamo University (Italy)

Target group

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.

Course aim

The objective of TStat’s “Modelling and Forecasting Energy Markets” Summer School is therefore to provide participants with the specific analytical tools to undertake a rigorous and in-depth analysis of both prices and demand 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 demand and ii) univariate and multivariate GARCH models for the estimation and forecast of price volatility and risk management in energy markets.

Fee info

EUR 0: The Summer School fee amounts to:

Students*: € 1250.00
Academic: € 2200.00
Non-Profit/Public Research Centres: € 2725.00
Commercial: € 3250.00

*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.

Please note that a non-refundable deposit of €100.00 for students and €200.00 for Academic, Non-Profit/Public Research Centres and Commercial participants, is required to secure a place and is payable upon registration. The number of participants is limited to 15. Places will be allocated on a first come, first serve basis.

Course fee covers: teaching materials (copies of lecture slides, databases and Stata routines used during the school); a temporary licence of Stata valid for 30 days from the beginning of the school; half board accommodation (breakfast, lunch and coffee breaks) in a single room at CISL Studium Center or equivalent (5 nights). Participants requiring accommodation the night of the final day of the school, are requested to contact us as soon as possible.

To maximize the usefulness of this summer school, we strongly recommend that participants bring their own laptops with them, to enable them to actively participate in the empirical sessions.