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Applying model reference adaptive search to American-style option pricing
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Source Winter Simulation Conference archive
Proceedings of the 38th conference on Winter simulation table of contents
Monterey, California
SESSION: Risk analysis: pricing American options table of contents
Pages: 711 - 718  
Year of Publication: 2006
ISBN:1-4244-0501-7
Authors
Huiju Zhang  University of Maryland, College Park, MD
Michael C. Fu  University of Maryland, College Park, MD
Sponsors
IEICE ESS : Institute of Electronics, Information and Communication Engineers, Engineering Sciences Society
IIE : Institute of Industrial Engineers
ASA : American Statistical Association
IEEE-CS\DATC : The IEEE Computer Society
INFORMS-CS : Institute for Operations Research and the Management Sciences-College on Simulation
NIST : National Institute of Standards and Technology
SIGSIM: ACM Special Interest Group on Simulation and Modeling
(SCS) : The Society for Modeling and Simulation International
Publisher
Winter Simulation Conference 
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ABSTRACT

This paper considers the application of stochastic optimization methods to American-style option pricing. We apply a randomized optimization algorithm called Model Reference Adaptive Search (MRAS) to pricing American-style options by parameterizing the early exercise boundary. Numerical results are provided for pricing American-style call and put options written on underlying assets following geometric Brownian motion and Merton jump-diffusion processes. The results from the MRAS algorithm are also compared with the Cross-Entropy (CE) method.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
Broadie, M., and P. Glasserman. 1997. Pricing American-style securities using simulation. Journal of Economic Dynamics and Control 21: 1323--1352.
 
3
Broadie, M., and P. Glasserman. 2004. A stochastic mesh method for pricing high-dimensional American options. Journal of Computational Finance 7: 35--72.
 
4
Carriere, J. F. 1996. Valuation of the early-exercise price for derivative securities using simulations and splines. Insurance: Mathematics and Economics 19: 19--30.
 
5
 
6
Fu, M. C., and J. Q. Hu. 1995. Sensitivity analysis for Monte Carlo simulation of option pricing. Prob. in the Engineering and Information Sciences 9: 417--446.
 
7
 
8
Fu, M. C., S. B. Laprise, D. B. Madan, Y. Su, and R. Wu. 2001. Pricing American options: a comparison of Monte Carlo simulation approaches. Journal of Computational Finance 4: 39--88.
 
9
Fu, M. C., Hu, J., and S. I. Marcus. 2006. Model-based randomized methods for global optimization. Proc. of the 17th International Symposium on Mathematical Theory of Networks and Systems, CD-ROM.
 
10
Glover, F. W. 1990. Tabu search: a tutorial. Interfaces 20: 74--94.
 
11
Grant, D., G. Vora, and D. Weeks. 1996. Simulation and the early-exercise option problem. Journal of Financial Engineering 5: 211--227.
 
12
 
13
Hu, J., M. C. Fu, and S. I. Marcus. 2006. A model reference adaptive search algorithm for global optimization. Operations Research (to appear).
 
14
 
15
Kroese, D., R. Y. Rubinstein, and S. Porotsky. 2004. The cross-entropy method for continuous multi-extremal optimization. Submitted to Operations Research.
 
16
Laprise, S. B., M. C. Fu, S. I. Marcus, A. E. B. Lim, and H. Zhang. 2006. Pricing American-style derivatives with European call options. Management Science 52: 95--110.
 
17
Larranaga, P., R. Etxeberria, J. A. Lozano, B. Sierra, I. Inza, and J. Pena. 1999. A review of the cooperation between evolutionary computation and probabilistic graphical models. Proceedings of the Second Symposium on Artificial Intelligence. Adaptive Systems. CIMAF 99. Special Session on Distributions and Evolutionary Computation, 314--324.
 
18
 
19
Longstaff, F., and E. Schwartz. 2001. Valuing American options by simulation: a simple least-squares approach. The Review of Financial Studies 14: 113--148.
 
20
Merton, R. C. 1976. Option pricing when underlying stock returns are discontinuous. Journal of Financial Economics 3: 125--144.
 
21
 
22
Paul, T., and H. Iba. 2002. Linear and combinatorial optimizations by estimation of distribution algorithms. 9th MPS Symposium on Evolutionary Computation, IPSJ, Japan.
 
23
 
24
Spall, J. 1992. Multivariate stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Transaction on Automatic Control 37: 332--341.
 
25
 
26
Tilley, J. 1993. Valuating American options in a path simulation model. Transactions of the Society of Actuaries 45: 83--104.
Collaborative Colleagues:
Huiju Zhang: colleagues
Michael C. Fu: colleagues