About the project
With renewable sources of energy becoming more dominant in the production of power, the energy markets will become (even) more dependent on variations in weather. In this project we will model and analyse weather risk in energy markets, and investigate how actors on the market can manage this risk. We focus on two power markets, namely NordPool and EEX, and investigate how weather factors like temperature, precipitation and wind impact prices. We want to quantify this using stochastic models which are tractable for further analysis. The challenge is to develop models which appropriately include the relationships between weather factors and prices. Another challenge that we aim at solving is to correctly model the dependencies between different energy markets that are connected, through weather factors on one had, but also through interconnectors and fuels on the other. We focus on multivariate stochastic models for the market price dynamics, and sought to include related markets like the ones for emissions and temperatures. As an application of our advanced multivariate price models, we will analyse risk management using derivatives. Such derivatives include plain vanilla options on energy, temperature and emissions, but also more exotic spread and quanto options. The latter two classes of derivatives depend on the covariation between two or more prices and risk factors. Questions like pricing and hedging of these contracts will be investigated.
The outcomes of this project will make the foundation for the power industry to face the risk challenges from a growing impact of weather coming from renewable energy like for example wind power and trading with emission permits. This is important aspects for energy markets in transition from coal and gas fueled power production towards more "green" generation of electricity.
Objectives
- Identify and develop sophisticated stochastic models for the impact of weather risk factors to energy prices
- Analyse risk management for such models, using exotic derivatives on energy and emissions and temperature
- create multivariate models taking dependencies across weather factors, and across markets using random fields and stochastic processes
- develop and analyse spatio-temporal models for temperature, wind and rainfall
- price and hedge exotic energy-related derivatives like spreads and quanto options, and analyse the dependency towards risk factors
- develop numerical methods for practical simulation of prices/strategies/risks
- develop calibration and estimation tools for the models
Outcomes
Background
Professor Ole Barndorff-Nielsen at the University of Århus in Denmark and professor Rudiger Kiesel at University of Duisburg-Essen in Germany are active scientific collaborators in the project. MAWREM runs from January 2012 until December 2015. It will finance one PhD and one post doc position, both full time, as well as hosting workshops and intensive courses for both academia and industry. The project will be based on theory for stochastic processes, stochastic analysis, mathematical finance and statistics.
Financing
RENERGI, Norwegian Research Council. Total budget approx. 6 mill NOK.