Summer School "Modelling and Forecasting Energy Markets - 6th Edition

Summer School "Modelling and Forecasting Energy Markets - 6th Edition

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Start Date

End Date

Application Deadline

Type

Summer schools

Reference Number

I-SS12

Certifications & Titles

Certificate of participation

Study Options

Full Time

Fees

Regular fees: 1250 - 3250 EUR

Comment:

Kindly note:

The Residential Summer School fee amounts to:

  • Full-time Students*: € 1250.00
  • Full-time PhD Students: € 1920.00
  • Academic: € 2200.00
  • Commercial: € 3250.00
  1. *To be eligible for full-time student prices, participants MUST provide proof of their full-time student status for the current academic year. Our standard policy is to provide all full-time students, be they Undergraduates or Masters students, access to our student registration rates. Part-time master and doctoral students on the other hand, who are also currently employed will however, be assigned the standard academic registration fee. Residential costs for full-time students are completely covered TStat Training through our Investing in Young Researchers Programme. Participation is however restricted to a maximum of 3 students.
  2. Fees are subject to VAT (applied at the current Italian rate of 22%). However, under current EU fiscal regulations, VAT will not be applied to companies, institutions or universities, providing a valid tax registration number.
  3. Please note that a non-refundable deposit of €100.00 for students and €250.00 for Academic 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.
  4. Course fee covers: teaching materials (copies of lecture slides, databases and routines used developed specifically for the summer school); a temporary software licence for use throughout the sessions, valid for 30 days from the first day of the course; half board accommodation (breakfast, lunch and coffee breaks), a single room at CISL Studium Center or equivalent (for 5 nights).

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.

Individuals interested in attending this summer school must return their completed registration forms by e-mail training@tstat.eu to TStat by 10th August 2022.

 

Funding Options

Students have access to discounted courses fees

In the last two decades energy markets operators have witnessed significant structural changes that have had a profound impact on how prices are determined in the market. Market liberalization, the adoption of energy efficiency regulation, increased production from renewable energy sources and climate change have contributed to making both demand and supply less predictable and prices more volatile.

The accurate modelling and forecasting of demand and prices has therefore become of utmost importance to energy producers, commodity traders and financial analysts focusing on the energy sector. Moreover, the statistical characteristics 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. TStat’s “Modelling and Forecasting Energy Markets” School  provides participants with the analytical tool set necessary to undertake a rigorous and in-depth analysis of both demand and prices in international energy markets.

Program:

The program covers a wide range of econometric methods currently available to researchers and practitioners, such as: i) univariate and multivariate time series models for forecasting prices and demand; ii) univariate and multivariate GARCH models for forecasting price volatility and iii) cointegration models and panel data models for assessing the sensitivity of energy demand to price, income and climate variables and for constructing long-run policy scenarios.

  • Day 1: Energy Data Analysis
  • Day 2: Times Series Models
  • Day 3: Volatility Models
  • Day 4: Cointegration Models
  • Day 5: Panel Data Models

Click here for a more detailed scientific program.

Prerequisites:

A knowledge of intermediate statistics and econometrics, such as that of Wooldridge, J.M. (2019) and/or Brooks, C. (2019), is required. In particular, participants MUST be familiar with linear regression analysis, inference, regression misspecification issues and the time series concepts of autocorrelation, stationarity and volatility.

During the Summer School, participants will be introduced to the econometric/statistical software Stata. Attendees do NOT however, require any previous knowledge of the software.

Target Audience:

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/researchers 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 Leaders:

Dr Elisabetta PELLINI, Centre for Econometric Analysis, The Business School (formerly Cass), City, University of London (UK)

Professor Giovanni URGA, Centre for Econometric Analysis, The Business School (formerly Cass), City, University of London (UK) 

Course Structure:

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 econometric software. 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 2022 edition also includes an extended Case Study Group session during which participants will either work in small groups on a short applied case study or on a presentation of their own research work. Course leaders will discuss with participants the appropriateness of the methods adopted in their case study and the interpretation of the results obtained and will also provide feedback and guidance on possible future developments of individual research agendas.

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Attendance

On-Site

Posted on

Start Date

End Date

Application Deadline

Type

Summer schools

Reference Number

I-SS12

Certifications & Titles

Certificate of participation

Study Options

Full Time

Fees

Regular fees: 1250 - 3250 EUR

Comment:

Kindly note:

The Residential Summer School fee amounts to:

  • Full-time Students*: € 1250.00
  • Full-time PhD Students: € 1920.00
  • Academic: € 2200.00
  • Commercial: € 3250.00
  1. *To be eligible for full-time student prices, participants MUST provide proof of their full-time student status for the current academic year. Our standard policy is to provide all full-time students, be they Undergraduates or Masters students, access to our student registration rates. Part-time master and doctoral students on the other hand, who are also currently employed will however, be assigned the standard academic registration fee. Residential costs for full-time students are completely covered TStat Training through our Investing in Young Researchers Programme. Participation is however restricted to a maximum of 3 students.
  2. Fees are subject to VAT (applied at the current Italian rate of 22%). However, under current EU fiscal regulations, VAT will not be applied to companies, institutions or universities, providing a valid tax registration number.
  3. Please note that a non-refundable deposit of €100.00 for students and €250.00 for Academic 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.
  4. Course fee covers: teaching materials (copies of lecture slides, databases and routines used developed specifically for the summer school); a temporary software licence for use throughout the sessions, valid for 30 days from the first day of the course; half board accommodation (breakfast, lunch and coffee breaks), a single room at CISL Studium Center or equivalent (for 5 nights).

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.

Individuals interested in attending this summer school must return their completed registration forms by e-mail training@tstat.eu to TStat by 10th August 2022.

 

Funding Options

Students have access to discounted courses fees

Via%20Della%20Piazzola%2C%2071%2C%20Florence%2C%20Italy

Via Della Piazzola, 71

50123 Florence , Italy