Aarhus University Seal / Aarhus Universitets segl

Multivariate continuous-time modeling of wind indexes and hedging of wind risk

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

  • Fred E. Benth, University of Oslo
  • ,
  • Troels S. Christensen, Aalborg Universitet, Centrica Energy Trading
  • ,
  • Victor Rohde

With the introduction of the exchange-traded German wind power futures, opportunities for German wind power producers to hedge their volumetric risk are present. We propose two continuous-time multivariate models for wind power utilization at different wind sites, and discuss the properties and estimation procedures for the models. Applying the models to wind index data for wind sites in Germany and the underlying wind index of exchange-traded wind power futures contracts, the estimation results of both models suggest that they capture key statistical features of the data. We show how these models can be used to find optimal hedging strategies using exchange-traded wind power futures for the owner of a portfolio of so-called tailor-made wind power futures. Both in-sample and out-of-sample hedging scenarios are considered, and, in both cases, significant variance reductions are achieved. Additionally, the risk premium of the German wind power futures is analysed, leading to an indication of the risk premium of tailor-made wind power futures.

TidsskriftQuantitative Finance
Sider (fra-til)165-183
Antal sider19
StatusUdgivet - jan. 2021

Bibliografisk note

Funding Information:
Troels S?nderby Christensen is supported by the Innovation Fund Denmark under Grant 5189-00117B. Victor Rohde is supported by the Danish Council for Independent Research under Grant DFF-4002-00003. We are grateful for the careful reading and comments from two referees.

Publisher Copyright:
© 2020 Informa UK Limited, trading as Taylor & Francis Group.

Copyright 2020 Elsevier B.V., All rights reserved.

Se relationer på Aarhus Universitet Citationsformater

ID: 213699918