A new lattice-based scheme for swing option pricing under mean-reverting regime-switching jump–diffusion processes

Swing options are complex path-dependent contracts, granting their holders a prefixed number of transaction rights to buy/sell a variable amount of the underlying asset (e.g. energy commodities) subject to daily or periodic constraints. Stating the swing option price as the solution of a stochastic...

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Bibliographic Details
Published inJournal of computational and applied mathematics Vol. 383; p. 113132
Main Authors Ahmadi, Z., Hosseini, S.M., Bastani, A. Foroush
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.02.2021
Subjects
Dynamic programming
Electricity spot price
Least-squares Monte-Carlo (LSM)
Swing option
Trinomial tree method
Electricity spot price
Dynamic programming
Trinomial tree method
Swing option
Least-squares Monte-Carlo (LSM)
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Summary:Swing options are complex path-dependent contracts, granting their holders a prefixed number of transaction rights to buy/sell a variable amount of the underlying asset (e.g. energy commodities) subject to daily or periodic constraints. Stating the swing option price as the solution of a stochastic optimal control problem, we employ a dynamic programming formulation in which the underlying asset price is modeled by a mean-reverting regime-switching jump–diffusion process. We explore a newly devised lattice-based pricing framework to find the premium of swing options in a cost-effective and easily implementable manner. We compare the performance of the proposed tree building procedure with a simulation-based Least-Squares Monte-Carlo (LSM) approach.
ISSN:0377-0427
1879-1778
DOI:10.1016/j.cam.2020.113132