30 January

Energy Risk Modelling 2024

Event is now fully booked! This two-day in-depth workshop is dedicated for risk management professionals, analysts and traders wanting to gain insights into risk modelling of energy markets.

The workshop is now fully booked. The next edition of Energy Risk Modelling will be organised 4-5 June 2024.

Learn how to measure and model risk in energy portfolios

More volatile energy markets, combined with complex trading and hedging portfolios have increased the need for measuring risk of individual contracts and whole portfolios, as well as at corporate level (Enterprise risk management). Furthermore, understanding the dynamics and determinants of volatility, correlation and risk (value at risk and expected shortfall) in energy markets is essential.

For questions, please contact

morten.hegna@montelgroup.com

Click here to add to clipboard

+47 917 57 662

Click here to add to clipboard

Day 1: Energy Risk Modelling

Risk and return characteristics of energy spot futures markets

Excel data add in from Montel
Cases from European energy futures and spot markets (Nordic, German, and more)

Risk measures:

Volatility and Correlation
Value at Risk (VaR)
Expected Tail Loss (ETL)

Risk factor models for electricity spot markets

How to model spot price and spot price distributions. How fundamentals like fuel prices, forecast of demand and supply, wind and solar influence the price formation. How the sensitivities to fundamentals changes over time and over the levels of electricity prices. How to model and predict the price distribution. Methods applied: Static regression analysis, Rolling regression analysis, Quantile regression.

Case study: The German electricity spot market

Modeling volatility and correlation in energy markets

Moving average models for volatility and correlation
GARCH models
Models based on intradaily data
Models based on implied volatility

Case study: Natural Gas, Crude Oil, Coal, Co2, and electricity markets

Day 2: Energy Risk Modelling

Statistical trading models for energy futures

Trend strategies involving one energy commodity
Spread trading strategies between energy markets (calendar spread and cross commodity spreads)
Measuring performance and risk in trading positions

Case studies recent trading losses in oil, natural gas and electricity futures and option markets. (China Aviation Oil, Amaranth, Bank of Montreal, Einar Aas, Optionsellers.Com)

Risk models for energy commodity portfolios:

Risk Metrics
Filtered Historical Simulation
Cornish Fisher Models
Models based on Student-T distributions
Models based on Extreme Value Theory
Quantile Regression
Stress testing and scenario analysis
Model risk
Backtesting VaR
Backtesting of Expected Shortfall

Case study: Natural Gas, Crude Oil, Coal, Co2, and electricity markets

Modelling joint wind and price risk with copulas

Pitfalls of correlations
Introduction to copulas
Capturing different marginal distributions, assymetric tail behaviour and complex non-linear features with copulas Calibration of data with copulas
Simulation and cash flow at risk analysis using copulas

Case study: Danish wind production and prices

Speakers

Professor Sjur Westgaard

MSC AND PHD OF INDUSTRIAL ECONOMICS FROM NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY AND A MSC OF FINANCE FROM NORWEGIAN SCHOOL OF BUSINESS AND ECONOMICS

Professor Westgaard has previously worked as an investment portfolio manager for an insurance company, a project manager for a consultant company and as a credit analyst for an international bank. Currently he is professor at the Norwegian University of Science and Technology and an Adjunct Professor at the Innland University – Center for Business Analytics. His teaching involves business economics, corporate finance, derivatives and real options, empirical finance and financial risk management.

He also have bachelor, master and PhD courses on economic and financial forecasting. He is one of the founders and editors of Journal of Commodity Markets. He is also an associate editor of Journal of Energy Markets. His main research interest include financial risk forecasting. He has recently also been a project manager for two energy research projects involving the research council of Norway, power companies, and academic institutions in Europe.