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A Multilevel Monte Carlo Method for the Valuation of Swing Options
Author(s) -
Hakimeh Ghodssi-Ghassemabadi,
Gholam Hossein Yari
Publication year - 2021
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2021/8407324
Subject(s) - swing , monte carlo method , valuation (finance) , monte carlo methods for option pricing , computer science , valuation of options , quasi monte carlo method , mathematical optimization , hybrid monte carlo , econometrics , markov chain monte carlo , mathematics , economics , accounting , statistics , engineering , mechanical engineering
In this study, we propose a novel approach for the valuation of swing options. Swing options are a kind of American options with multiple exercise rights traded in energy markets. Longstaff and Schwartz have suggested a regression-based Monte Carlo method known as the least-squares Monte Carlo (LSMC) method to value American options. In this work, first we introduce the LSMC method for the pricing of swing options. Then, to achieve a desired accuracy for the price estimation, we combine the idea of LSMC with multilevel Monte Carlo (MLMC) method. Finally, to illustrate the proper behavior of this combination, we conduct numerical results based on the Black–Scholes model. Numerical results illustrate the efficiency of the proposed approach.

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