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Dissertation/Thesis Abstract

Pricing of swing options: A Monte Carlo simulation approach
by Leow, Kai-Siong, Ph.D., Kent State University, 2013, 117; 3618875
Abstract (Summary)

We study the problem of pricing swing options, a class of multiple early exercise options that are traded in energy market, particularly in the electricity and natural gas markets. These contracts permit the option holder to periodically exercise the right to trade a variable amount of energy with a counterparty, subject to local volumetric constraints. In addition, the total amount of energy traded from settlement to expiration with the counterparty is restricted by a global volumetric constraint. Violation of this global volumetric constraint is allowed but would lead to penalty settled at expiration.

The pricing problem is formulated as a stochastic optimal control problem in discrete time and state space. We present a stochastic dynamic programming algorithm which is based on piecewise linear concave approximation of value functions. This algorithm yields the value of the swing option under the assumption that the optimal exercise policy is applied by the option holder. We present a proof of an almost sure convergence that the algorithm generates the optimal exercise strategy as the number of iterations approaches to infinity. Finally, we provide a numerical example for pricing a natural gas swing call option.

Indexing (document details)
Advisor: Mocioalca, Oana
School: Kent State University
Department: Mathematical Science
School Location: United States -- Ohio
Source: DAI-B 75/08(E), Dissertation Abstracts International
Subjects: Applied Mathematics, Economic theory, Energy
Keywords: Energy derivatives, Simulation, Stochastic dynamic programming, Swing options
Publication Number: 3618875
ISBN: 978-1-303-87406-2
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