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Pricing of Swing Options in a Mean Reverting Model with Jumps

Pricing of Swing Options in a Mean Reverting Model with Jumps We investigate the pricing of swing options in a model where the logarithm of the spot price is the sum of a deterministic seasonal trend and an Ornstein–Uhlenbeck process driven by a jump diffusion. First we calibrate the model to Nord Pool electricity market data. Second, the existence of an optimal exercise strategy is proved, and we present a numerical algorithm for computation of the swing option prices. It involves dynamic programming and the solution of multiple parabolic partial integro‐differential equations by finite differences. Numerical results show that adding jumps to a diffusion may result in 2–35% higher swing option prices, depending on the moneyness and timing flexibility of the option. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Mathematical Finance Taylor & Francis

Pricing of Swing Options in a Mean Reverting Model with Jumps

Kjaer, Mats
Applied Mathematical Finance , Volume 15 (5-6): 24 – Dec 1, 2008
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Pricing of Swing Options in a Mean Reverting Model with Jumps

Abstract

We investigate the pricing of swing options in a model where the logarithm of the spot price is the sum of a deterministic seasonal trend and an Ornstein–Uhlenbeck process driven by a jump diffusion. First we calibrate the model to Nord Pool electricity market data. Second, the existence of an optimal exercise strategy is proved, and we present a numerical algorithm for computation of the swing option prices. It involves dynamic programming and the solution of multiple parabolic...
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Publisher
Taylor & Francis
Copyright
Copyright Taylor & Francis Group, LLC
ISSN
1466-4313
eISSN
1350-486X
DOI
10.1080/13504860802170556
Publisher site
See Article on Publisher Site

Abstract

We investigate the pricing of swing options in a model where the logarithm of the spot price is the sum of a deterministic seasonal trend and an Ornstein–Uhlenbeck process driven by a jump diffusion. First we calibrate the model to Nord Pool electricity market data. Second, the existence of an optimal exercise strategy is proved, and we present a numerical algorithm for computation of the swing option prices. It involves dynamic programming and the solution of multiple parabolic partial integro‐differential equations by finite differences. Numerical results show that adding jumps to a diffusion may result in 2–35% higher swing option prices, depending on the moneyness and timing flexibility of the option.

Journal

Applied Mathematical Finance – Taylor & Francis

Published: Dec 1, 2008

Keywords: Energy derivatives; swing options; jump diffusions; parabolic PIDEs; finite differences

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