scholarly journals A Multilevel Monte Carlo Method for the Valuation of Swing Options

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Hakimeh Ghodssi-Ghassemabadi ◽  
Gholam Hossein Yari

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.

AIP Advances ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 095013
Author(s):  
Jin Su ◽  
Cuihong Hou ◽  
Yingcang Ma ◽  
Yaowu Wang

2004 ◽  
Vol 07 (05) ◽  
pp. 591-614 ◽  
Author(s):  
G. N. MILSTEIN ◽  
O. REIß ◽  
J. SCHOENMAKERS

We introduce a new Monte Carlo method for constructing the exercise boundary of an American option in a generalized Black–Scholes framework. Based on a known exercise boundary, it is shown how to price and hedge the American option by Monte Carlo simulation of suitable probabilistic representations in connection with the respective parabolic boundary value problem. The method presented is supported by numerical experiments.


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