Location of Repository

Spatial Risk Premium on Weather Derivatives and Hedging Weather Exposure in Electricity

By Wolfgang Karl Härdle and Maria Osipenko

Abstract

Due to dependency of energy demand on temperature, weather derivatives enable the effective hedging of temperature related fluctuations. However, temperature varies in space and time and therefore the contingent weather derivatives also vary. The spatial derivative price distribution involves a risk premium. We examine functional principal components of temperature variation for this spatial risk premium. We employ a pricing model for temperature derivatives based on dynamics modelled via a vectorial Ornstein-Uhlenbeck process with seasonal variation. We use an analytical expression for the risk premia depending on variation curves of temperature in the measurement period. The dependence is exploited by a functional principal component analysis of the curves. We compute risk premia on cumulative average temperature futures for locations traded on CME and fit to it a geographically weighted regression on functional principal component scores. It allows us to predict risk premia for nontraded locations and to adopt, on this basis, a hedging strategy, which we illustrate in the example of Leipzig

Topics: risk premium, weather derivatives, Ornstein-Uhlenbeck process, functional principal components, geographically weighted regression, 330 Wirtschaft, ddc:330
Publisher: Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
Year: 2011
OAI identifier: oai:edoc.hu-berlin.de:18452/4955
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://dx.doi.org/10.18452/430... (external link)
  • http://edoc.hu-berlin.de/18452... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.