Disputas: Marcus Karl Viren Eriksson
M. Sc. Marcus Karl Viren Eriksson ved Matematisk institutt vil forsvare sin avhandling for graden ph.d.:
Valuation of Energy Derivatives: A Stochastic Control Approach
Marcus Karl Viren Eriksson
Tid og sted for prøveforelesning
Assistant Professor Tiziano Vargiolu, Dipartimento di Matematica, Università degli Studi di Padova
- Professor Jeannette Woerner, Technische Universität Dortmund, Lehrstuhl LSIV
- Professor Tom Lindstrøm, Matematisk institutt, Universitet i Oslo
Leder av disputas
Professor Bernt Øksendal, Matematisk institutt, Universitet i Oslo
- Professor Fred Espen Benth, Matematisk institutt, Universitet i Oslo
- Professor Ruediger Kiesel, Institute for Business and Economic Studies (IBES), University of Duisburg-Essen
- Førsteamanuensis Jukka Mikael Lempa, Institutt for økonomi og administrasjon, Høgskolen i Oslo og Akershus
Producers and traders in the electricity and related markets need hedging instruments to cover for low prices. Also, as electricity is non-storable and may have high uncertainty in the production, equally important is the volume risk. In this thesis we propose and investigate derivatives that are theoretically tractable, as well as practically reasonable to hedge for these predicaments that typically occure in the electricity market.
We provide valuation models for such hedging derivatives. The valuation models are formulated in terms of a stochastic control problem and solved via dynamic programming.
The underlying prices are allowed to have a non-Gaussian factor dynamics, which is supported by a large body of literature for e.g. electricity prices.
We construct and apply valuation models for swing options, tolling agreements and flexible-load contracts. Moreover, we also provide a valuation model to hedge for price levels and production rate in the Swedish-Norwegian green certificate market. In addition, we make an empirical investigation of green certificate prices.
Furthermore, we conduct a comparison between the BNS model and the Heston model as models for prices of emission allowances in the EU ETS market. This is based on an empirical analysis and the comparison is with respect to the capturing of distributional properties and autocorrelation structure.
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