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Modelling spikes and pricing swing options in electricity markets

[Zeitschriftenartikel]

Hambly, Ben
Howison, Sam
Kluge, Tino

Abstract

Most electricity markets exhibit high volatilities and occasional distinctive price spikes, which result in demand for derivative products which protect the holder against high prices. In this paper we examine a simple spot price model that is the exponential of the sum of an Ornstein-Uhlenbeck and... mehr

Most electricity markets exhibit high volatilities and occasional distinctive price spikes, which result in demand for derivative products which protect the holder against high prices. In this paper we examine a simple spot price model that is the exponential of the sum of an Ornstein-Uhlenbeck and an independent mean reverting pure jump process. We derive the moment generating function as well as various approximations to the probability density function of the logarithm of the spot price process at maturity $T$. Hence we are able to calibrate the model to the observed forward curve and present semi-analytic formulae for premia of path-independent options as well as approximations to call and put options on forward contracts with and without a delivery period. In order to price path-dependent options with multiple exercise rights like swing contracts a grid method is utilised which in turn uses approximations to the conditional density of the spot process.... weniger

Klassifikation
Wirtschaftsstatistik, Ökonometrie, Wirtschaftsinformatik
Wirtschaftssektoren

Methode
Theorieanwendung

Freie Schlagwörter
Energy derivatives; Financial mathematics; Stochastic jumps; Numerical methods for option pricing; Continuous time models; Derivative pricing models

Sprache Dokument
Englisch

Publikationsjahr
2009

Seitenangabe
S. 937-949

Zeitschriftentitel
Quantitative Finance, 9 (2009) 8

DOI
https://doi.org/10.1080/14697680802596856

Status
Postprint; begutachtet (peer reviewed)

Lizenz
PEER Licence Agreement (applicable only to documents from PEER project)


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© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.