Numerical methods for backward Markov chain driven Black-Scholes option pricing

Chi Yan Au , Eric S. Fung , Leevan Ling

Front. Math. China ›› 2010, Vol. 6 ›› Issue (1) : 17 -33.

PDF (484KB)
Front. Math. China ›› 2010, Vol. 6 ›› Issue (1) : 17 -33. DOI: 10.1007/s11464-010-0089-2
Research Article
RESEARCH ARTICLE

Numerical methods for backward Markov chain driven Black-Scholes option pricing

Author information +
History +
PDF (484KB)

Abstract

The drift, the risk-free interest rate, and the volatility change over time horizon in realistic financial world. These frustrations break the necessary assumptions in the Black-Scholes model (BSM) in which all parameters are assumed to be constant. To better model the real markets, a modified BSM is proposed for numerically evaluating options price-changeable parameters are allowed through the backward Markov regime switching. The method of fundamental solutions (MFS) is applied to solve the modified model and price a given option. A series of numerical simulations are provided to illustrate the effect of the changing market on option pricing.

Keywords

backward Markov regime switching / method of fundamental solutions (MFS) / free boundary problem / American option / European option

Cite this article

Download citation ▾
Chi Yan Au, Eric S. Fung, Leevan Ling. Numerical methods for backward Markov chain driven Black-Scholes option pricing. Front. Math. China, 2010, 6(1): 17-33 DOI:10.1007/s11464-010-0089-2

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Beichelt F. E., Fatti L. P. Stochastic Processes and Their Applications, 2002, Boca Raton: CRC Press.

[2]

Berman A., Plemmons R. Nonnegative Matrices in the Mathematical Sciences, 1979, New York: Academic Press.

[3]

Black F., Scholes M. The pricing of options and corporate liabilities. J Polit Econ, 1973, 81, 637-654

[4]

Chen C. S., Fan C. M., Monroe J. The method of fundamental solutions for solving convection-diffusion equations with variable coefficients. Advances in Applied Mathematics and Mechanics, 2009, 1, 215-230

[5]

Chen C. S., Golberg M. A., Hon Y. C. The method of fundamental solutions and quasi-Monte Carlo method for diffusion equations. International Journal for Numerical Methods in Engineering, 1998, 43 8 1421-1435

[6]

Chen C S, Hon Y C, Schaback R. Scientific Computing with Radial Basis Functions. 2009

[7]

Ching W K, Siu T K, Li L M. Pricing exotic options under a higher-order hidden Markov model. Applied Mathematics and Decision Science, 2007, (18014): 15

[8]

Ding J., Tian H. Y., Chen C. S. The recursive formulation of particular solutions for some elliptic PDEs with polynomial source functions. Communications in Computational Physics, 2009, 5, 942-958

[9]

Duan J. C., Popova I., Ritchken P. Option pricing under regime switching. Quantitative Finance, 2002, 2, 116-132

[10]

Golberg M. A. The method of fundamental solutions for Poisson’s equation. Engineering Analysis with Boundary Elements, 1995, 16 3 205-213

[11]

Hillier F. S., Lieberman G. J. Introduction to Operations Research, 2001, New York: McGraw-Hill.

[12]

Hon Y. C. A quasi-radial basis functions method for American options pricing. Computer Mathematics and its Applications, 2002, 43 3–5 513-524

[13]

Hon Y. C., Mao X. Z. A Radial Basis Function Method For Solving Options Pricing Model. Financial Engineering, 1999, 8 1 31-49

[14]

Hull J. C. Options, Futures, and Other Derivatives, 2006, 6th ed., Englewod Cliffs: Prentice Hall.

[15]

Karageorghis A., Lesnic D. The Method of Fundamental Solutions for Steady-State Heat Conduction in Nonlinear Materials. Communications in Computational Physics, 2008, 4, 911-928

[16]

Lin J., Liang Jin. Pricing of perpetual American and Bermudan options by binomial tree method. Front Math China, 2007, 2 2 243-256

[17]

Ling L., Schaback R. Stable and convergent unsymmetric meshless collocation methods. SIAM Journal on Numerical Analysis, 2008, 46, 1097-1115

[18]

Meyer A. L., Drombosky T. W., Ling L. Applicability of the method of fundamental solutions. Engineering Analysis with Boundary Elements, 2009, 33, 637-643

[19]

Press W. H., Flannery B. P., Teukolsky S. A., Vetterling W. T., Chipperfield J. R. Numerical Recipes in FORTRAN: The Art of Scientific Computing, 1992, Cambridge: Cambridge University Press.

[20]

Siu T. K., Ching W. K., Fung E. S., Ng M. K. Extracting information from spot interest rates and credit ratings using double higher-order hidden Markov models. Computational Economics, 2005, 26 3–4 251-284

[21]

Siu T K, Ching W K, Fung E S, Ng M K. Option valuation under multivariate Markov chain model via Esscher transform. International Journal of Theoretical and Applied Finance, 2006 (submission)

[22]

Siu T K, Ching W K, Fung E S, Ng M K, Li X. A higher-order Markov-switching model for risk measurement. International Journal of Computer and Mathematics with Applications, 2007, (58): 1–10

[23]

Svishchuk A. V., Zhuravitskyj D. G., Kalemanova A. V. Analog of the Black-Scholes formula for option pricing under conditions of (B,S,X)-incomplete market of securities with jumps. Ukr Math J, 2000, 52 3 489-497

[24]

Tsai C. C., Young D. L., Chiang J. H., Lo D. C. The method of fundamental solutions for solving options pricing models. Applied Mathematics and Computation, 2006, 181 1 390-401

[25]

Wei T., Hon Y. C., Ling L. Method of fundamental solutions with regularization techniques for Cauchy problems of elliptic operators. Engineering Analysis with Boundary Elements, 2007, 31 4 373-385

[26]

Wilmott P., Howison S., Dewynne J. The Mathematics of Financial Derivatives, 1995, Cambridge: Cambridge University Press.

[27]

Wu L., Kwok Y. K. A front-fixing finite difference method for the valuation of American options. Journal of Financial Engineering, 1997, 6, 83-97

[28]

Young D. L., Tsai C. C., Murugesan K., Fan C. M., Chen C. W. Time-dependent fundamental solutions for homogeneous diffusion problems. Engineering Analysis with Boundary Elements, 2004, 28 12 1463-1473

AI Summary AI Mindmap
PDF (484KB)

790

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/