A numerical scheme for pricing American options with transaction costs under a jump diffusion process

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October 2017, 13(4): 1793-1813. doi: 10.3934/jimo.2017019

A numerical scheme for pricing American options with transaction costs under a jump diffusion process

Donny Citra Lesmana ^1, and Song Wang ^2,

1.	Department of Mathematics, Bogor Agricultural University, Kampus IPB Darmaga, Bogor, Jawa Barat 16680, Indonesia
2.	Department of of Mathematics & Statistics, Curtin University, GPO Box U1987, WA 6845, Australia

Received April 2016 Revised July 2016 Published December 2016

In this paper we develop a numerical method for a nonlinear partial integro-differential complementarity problem arising from pricing American options with transaction costs when the underlying assets follow a jump diffusion process. We first approximate the complementarity problem by a nonlinear partial integro-differential equation (PIDE) using a penalty approach. The PIDE is then discretized by a combination of a spatial upwind finite differencing and a fully implicit time stepping scheme. We prove that the coefficient matrix of the system from this scheme is an M-matrix and that the approximate solution converges to the viscosity solution to the PIDE by showing that the scheme is consistent, monotone, and unconditionally stable. We also propose a Newton's iterative method coupled with a Fast Fourier Transform for the computation of the discretized integral term for solving the fully discretized system. Numerical results will be presented to demonstrate the convergence rates and usefulness of this method.

Keywords: American option pricing, nonlinear partial integro-differential equation, nonlinear complementarity problem, upwind finite difference, penalty method, convergence.

Mathematics Subject Classification: Primary: 65K15, 65M06; Secondary: 91G60.

Citation: Donny Citra Lesmana, Song Wang. A numerical scheme for pricing American options with transaction costs under a jump diffusion process. Journal of Industrial & Management Optimization, 2017, 13 (4) : 1793-1813. doi: 10.3934/jimo.2017019

References:

[1]	A. Almendral and C. W. Oosterlee, Numerical valuation of options with jumps in the underlying, Appl. Math. Comput., 53 (2005), 1-18. doi: 10.1016/j.apnum.2004.08.037. Google Scholar
[2]	A. Anderson and J. Andresen, Jump diffusion process: volatility smile fitting and numerical methods for option pricing, Rev. Derivat. Res., 4 (2000), 231-262. Google Scholar
[3]	J. Ankudinova and M. Ehrhardt, On the numerical solution of nonlinear Black-Scholes equations, Computers and Mathematics with Applications, 56 (2008), 799-812. doi: 10.1016/j.camwa.2008.02.005. Google Scholar
[4]	C. G. Averbuj, Nonlinear differential evolution equation arising in option pricing when including transaction costs: a viscosity solution approach, R. Bras. Eco. de Emp., 12 (2012), 81-90. Google Scholar
[5]	G. Barles, Convergence of numerical schemes for degenerate parabolic equations arising in finance theory, in: L. C. G. Rogers, D. Talay (Eds), Numerical Methods in Finance, Cambridge University Press, Cambridge, (1997), 1-21. Google Scholar
[6]	F. Black and M. Scholes, The pricing of options and corporate liabilities, The Journal of Political Economy, 81 (1973), 637-654. doi: 10.1086/260062. Google Scholar
[7]	W. Chen and S. Wang, A penalty method for a fractional order parabolic variational inequality governing American put option valuation, Computers & Mathematics with Applications, 67 (2014), 77-90. doi: 10.1016/j.camwa.2013.10.007. Google Scholar
[8]	W. Chen and S. Wang, A finite difference method for pricing European and American options under a geometric Levy process, Journal of Industrial and Management Optimization, 11 (2015), 241-264. doi: 10.3934/jimo.2015.11.241. Google Scholar
[9]	R. Company, L. Jodar and J. R. Pintos, A numerical method for European option pricing with transaction costs nonlinear equation, Mathematics and Computer Modelling, 50 (2009), 910-920. doi: 10.1016/j.mcm.2009.05.019. Google Scholar
[10]	R. Cont and P. Tankov, Financial Modelling with Jump Processes, Chapman and Hall/CRC, Boca Raton, FL, 2004.
[11]	R. Cont and E. Voltchkova, A finite difference scheme for option pricing in jump diffusion and exponential lěvy models, SIAM J. Numer. Anal., 43 (2005), 1596-1626. doi: 10.1137/S0036142903436186. Google Scholar
[12]	B. Dupire, Pricing with a smile, Risk, 7 (1994), 18-20. Google Scholar
[13]	B. D. üring, M. Fournier and A. J. üngel, High order compact finite difference schemes for a nonlinear Black-Scholes equation, International Journal of Theoretical and Applied Finance, 6 (2003), 767-789. Google Scholar
[14]	Y. d'Halluin, P. A. Forsyth and K. R. Vetzal, Robust numerical methods for contingent claims under jump diffusion processes, IMA J. Numer. Anal., 25 (2005), 87-112. doi: 10.1093/imanum/drh011. Google Scholar
[15]	P. Heider, Numerical methods for nonlinear Black-Scholes equations, Applied Mathematical Finance, 17 (2010), 59-81. doi: 10.1080/13504860903075670. Google Scholar
[16]	S. L. Heston, A closed-form solution for options with stochastic volatility with application to bond and currency options, Rev. Financial Stud., 6 (1993), 327-343. doi: 10.1093/rfs/6.2.327. Google Scholar
[17]	C. Huang and S. Wang, A power penalty approach to a nonlinear complementary problem, Operations Research Letters, 38 (2010), 72-76. doi: 10.1016/j.orl.2009.09.009. Google Scholar
[18]	C. Huang and S. Wang, A penalty method for a mixed nonlinear complementarity problem, Nonlinear Analysis TMA, 75 (2012), 588-597. doi: 10.1016/j.na.2011.08.061. Google Scholar
[19]	C. S. Huang, C. H. Hung and S. Wang, A fitted finite volume method for the valuation of options on assets with stochastic volatilities, Computing, 77 (2006), 297-320. doi: 10.1007/s00607-006-0164-4. Google Scholar
[20]	J. Hull, Options, Futures, and Other Derivatives, Prentice-Hall, Englewood Cliffs, 2005.
[21]	J. Hull and A. White, The pricing of options on assets with stochastic volatilities, J. Finance, 42 (1987), 281-300. doi: 10.1111/j.1540-6261.1987.tb02568.x. Google Scholar
[22]	H. E. Leland, Option pricing and replication with transaction costs, Journal of Finance, 40 (1985), 1283-1301. Google Scholar
[23]	D.C. Lesmana and S. Wang, An upwind finite difference method for a nonlinear Black-Scholes equation governing European option valuation, Applied Mathematics and Computation, 219 (2013), 8818-8828. doi: 10.1016/j.amc.2012.12.077. Google Scholar
[24]	D. C. Lesmana and S. Wang, Penalty approach to a nonlinear obstacle problem governing American put option valuation under transaction costs, Applied Mathematics and Computation, 251 (2015), 318-330. doi: 10.1016/j.amc.2014.11.060. Google Scholar
[25]	W. Li and S. Wang, Pricing American options under proportional transaction costs using a penalty approach and a finite difference scheme, Journal of Industrial and Management Optimization, 9 (2013), 365-389. doi: 10.3934/jimo.2013.9.365. Google Scholar
[26]	C. Van Loan, Computational Frameworks for the Fast Fourier Transform, Frontier in applied mathematics, Vol. 10.SIAM, Philadelphia, PA, 1992. doi: 10.1137/1.9781611970999. Google Scholar
[27]	R. C. Merton, Option pricing when underlying stock returns are discontinuous, J. Financial Econ., 3 (1976), 125-144. doi: 10.1016/0304-405X(76)90022-2. Google Scholar
[28]	A. Mocioalca, Jump diffusion options with transaction costs, Rev. Roumaine Math. Pures Appl., 52 (2007), 349-366. Google Scholar
[29]	R. S. Varga, Matrix Iterative Analysis, Prentice-Hall, Engelwood Cliffs, NJ, 1962.
[30]	S. Wang, A penalty method for a finite-dimensional obstacle problem with derivative constraints, Optimization Letters, 8 (2014), 1799-1811. doi: 10.1007/s11590-013-0651-4. Google Scholar
[31]	S. Wang, A penalty approach to a discretized double obstacle problem with derivative constraints, Journal of Global Optimization, 62 (2015), 775-790. doi: 10.1007/s10898-014-0262-3. Google Scholar
[32]	S. Wang and X. Q. Yang, A power penalty method for linear complementarity problems, Operations Research Letters, 36 (2008), 211-214. doi: 10.1016/j.orl.2007.06.006. Google Scholar
[33]	S. Wang and X. Q. Yang, A power penalty method for a bounded nonlinear complementarity problem, Optimization, 64 (2015), 2377-2394. doi: 10.1080/02331934.2014.967236. Google Scholar
[34]	S. Wang, X. Q. Yang and K. L. Teo, Power penalty method for a linear complementarity problem arising from American option valuation, Journal of Optimization Theory & Applications, 129 (2006), 227-254. doi: 10.1007/s10957-006-9062-3. Google Scholar
[35]	S. Wang, S. Zhang and Z. Fang, A superconvergent fitted finite volume method for Black-Scholes equations governing European and American option valuation, Numerical Methods for Partial Differential Equations, 31 (2015), 1190-1208. doi: 10.1002/num.21941. Google Scholar
[36]	Y.-P. Wang and S.-L. Tao, Application of regularization technique to variational adjoint method: A case for nonlinear convection-diffusion problem, Applied Mathematics and Computation, 218 (2011), 4475-4482. doi: 10.1016/j.amc.2011.10.028. Google Scholar
[37]	P. Wilmott, J. Dewynne and S. Howison, Option Pricing: Mathematical Models and Computation, Oxford Financial Press, Oxford, 1993.
[38]	D. M. Young, Iterative Solution of Large Linear Systems, Academic Press, 1971.
[39]	K. Zhang and S. Wang, Pricing options under jump diffusion processes with fitted finite volume method, Applied Mathematics & Computation, 201 (2008), 398-413. doi: 10.1016/j.amc.2007.12.043. Google Scholar
[40]	K. Zhang and S. Wang, A computational scheme for options under jump diffusion processes, International Journals of Numerical Analysis and Modeling, 6 (2009), 110-123. Google Scholar
[41]	K. Zhang and S. Wang, Pricing American bond options using a penalty method, Automatica, 48 (2012), 472-479. doi: 10.1016/j.automatica.2012.01.009. Google Scholar
[42]	X. L. Zhang, Numerical analysis of American option pricing in a jump diffusion model, Math. Oper. Res., 22 (1997), 668-690. doi: 10.1287/moor.22.3.668. Google Scholar
[43]	Y. Y. Zhou, S. Wang and X. Q. Yang, A penalty approximation method for a semilinear parabolic double obstacle problem, Journal of Global Optimization, 60 (2014), 531-550. doi: 10.1007/s10898-013-0122-6. Google Scholar

show all references

References:

[1]	A. Almendral and C. W. Oosterlee, Numerical valuation of options with jumps in the underlying, Appl. Math. Comput., 53 (2005), 1-18. doi: 10.1016/j.apnum.2004.08.037. Google Scholar
[2]	A. Anderson and J. Andresen, Jump diffusion process: volatility smile fitting and numerical methods for option pricing, Rev. Derivat. Res., 4 (2000), 231-262. Google Scholar
[3]	J. Ankudinova and M. Ehrhardt, On the numerical solution of nonlinear Black-Scholes equations, Computers and Mathematics with Applications, 56 (2008), 799-812. doi: 10.1016/j.camwa.2008.02.005. Google Scholar
[4]	C. G. Averbuj, Nonlinear differential evolution equation arising in option pricing when including transaction costs: a viscosity solution approach, R. Bras. Eco. de Emp., 12 (2012), 81-90. Google Scholar
[5]	G. Barles, Convergence of numerical schemes for degenerate parabolic equations arising in finance theory, in: L. C. G. Rogers, D. Talay (Eds), Numerical Methods in Finance, Cambridge University Press, Cambridge, (1997), 1-21. Google Scholar
[6]	F. Black and M. Scholes, The pricing of options and corporate liabilities, The Journal of Political Economy, 81 (1973), 637-654. doi: 10.1086/260062. Google Scholar
[7]	W. Chen and S. Wang, A penalty method for a fractional order parabolic variational inequality governing American put option valuation, Computers & Mathematics with Applications, 67 (2014), 77-90. doi: 10.1016/j.camwa.2013.10.007. Google Scholar
[8]	W. Chen and S. Wang, A finite difference method for pricing European and American options under a geometric Levy process, Journal of Industrial and Management Optimization, 11 (2015), 241-264. doi: 10.3934/jimo.2015.11.241. Google Scholar
[9]	R. Company, L. Jodar and J. R. Pintos, A numerical method for European option pricing with transaction costs nonlinear equation, Mathematics and Computer Modelling, 50 (2009), 910-920. doi: 10.1016/j.mcm.2009.05.019. Google Scholar
[10]	R. Cont and P. Tankov, Financial Modelling with Jump Processes, Chapman and Hall/CRC, Boca Raton, FL, 2004.
[11]	R. Cont and E. Voltchkova, A finite difference scheme for option pricing in jump diffusion and exponential lěvy models, SIAM J. Numer. Anal., 43 (2005), 1596-1626. doi: 10.1137/S0036142903436186. Google Scholar
[12]	B. Dupire, Pricing with a smile, Risk, 7 (1994), 18-20. Google Scholar
[13]	B. D. üring, M. Fournier and A. J. üngel, High order compact finite difference schemes for a nonlinear Black-Scholes equation, International Journal of Theoretical and Applied Finance, 6 (2003), 767-789. Google Scholar
[14]	Y. d'Halluin, P. A. Forsyth and K. R. Vetzal, Robust numerical methods for contingent claims under jump diffusion processes, IMA J. Numer. Anal., 25 (2005), 87-112. doi: 10.1093/imanum/drh011. Google Scholar
[15]	P. Heider, Numerical methods for nonlinear Black-Scholes equations, Applied Mathematical Finance, 17 (2010), 59-81. doi: 10.1080/13504860903075670. Google Scholar
[16]	S. L. Heston, A closed-form solution for options with stochastic volatility with application to bond and currency options, Rev. Financial Stud., 6 (1993), 327-343. doi: 10.1093/rfs/6.2.327. Google Scholar
[17]	C. Huang and S. Wang, A power penalty approach to a nonlinear complementary problem, Operations Research Letters, 38 (2010), 72-76. doi: 10.1016/j.orl.2009.09.009. Google Scholar
[18]	C. Huang and S. Wang, A penalty method for a mixed nonlinear complementarity problem, Nonlinear Analysis TMA, 75 (2012), 588-597. doi: 10.1016/j.na.2011.08.061. Google Scholar
[19]	C. S. Huang, C. H. Hung and S. Wang, A fitted finite volume method for the valuation of options on assets with stochastic volatilities, Computing, 77 (2006), 297-320. doi: 10.1007/s00607-006-0164-4. Google Scholar
[20]	J. Hull, Options, Futures, and Other Derivatives, Prentice-Hall, Englewood Cliffs, 2005.
[21]	J. Hull and A. White, The pricing of options on assets with stochastic volatilities, J. Finance, 42 (1987), 281-300. doi: 10.1111/j.1540-6261.1987.tb02568.x. Google Scholar
[22]	H. E. Leland, Option pricing and replication with transaction costs, Journal of Finance, 40 (1985), 1283-1301. Google Scholar
[23]	D.C. Lesmana and S. Wang, An upwind finite difference method for a nonlinear Black-Scholes equation governing European option valuation, Applied Mathematics and Computation, 219 (2013), 8818-8828. doi: 10.1016/j.amc.2012.12.077. Google Scholar
[24]	D. C. Lesmana and S. Wang, Penalty approach to a nonlinear obstacle problem governing American put option valuation under transaction costs, Applied Mathematics and Computation, 251 (2015), 318-330. doi: 10.1016/j.amc.2014.11.060. Google Scholar
[25]	W. Li and S. Wang, Pricing American options under proportional transaction costs using a penalty approach and a finite difference scheme, Journal of Industrial and Management Optimization, 9 (2013), 365-389. doi: 10.3934/jimo.2013.9.365. Google Scholar
[26]	C. Van Loan, Computational Frameworks for the Fast Fourier Transform, Frontier in applied mathematics, Vol. 10.SIAM, Philadelphia, PA, 1992. doi: 10.1137/1.9781611970999. Google Scholar
[27]	R. C. Merton, Option pricing when underlying stock returns are discontinuous, J. Financial Econ., 3 (1976), 125-144. doi: 10.1016/0304-405X(76)90022-2. Google Scholar
[28]	A. Mocioalca, Jump diffusion options with transaction costs, Rev. Roumaine Math. Pures Appl., 52 (2007), 349-366. Google Scholar
[29]	R. S. Varga, Matrix Iterative Analysis, Prentice-Hall, Engelwood Cliffs, NJ, 1962.
[30]	S. Wang, A penalty method for a finite-dimensional obstacle problem with derivative constraints, Optimization Letters, 8 (2014), 1799-1811. doi: 10.1007/s11590-013-0651-4. Google Scholar
[31]	S. Wang, A penalty approach to a discretized double obstacle problem with derivative constraints, Journal of Global Optimization, 62 (2015), 775-790. doi: 10.1007/s10898-014-0262-3. Google Scholar
[32]	S. Wang and X. Q. Yang, A power penalty method for linear complementarity problems, Operations Research Letters, 36 (2008), 211-214. doi: 10.1016/j.orl.2007.06.006. Google Scholar
[33]	S. Wang and X. Q. Yang, A power penalty method for a bounded nonlinear complementarity problem, Optimization, 64 (2015), 2377-2394. doi: 10.1080/02331934.2014.967236. Google Scholar
[34]	S. Wang, X. Q. Yang and K. L. Teo, Power penalty method for a linear complementarity problem arising from American option valuation, Journal of Optimization Theory & Applications, 129 (2006), 227-254. doi: 10.1007/s10957-006-9062-3. Google Scholar
[35]	S. Wang, S. Zhang and Z. Fang, A superconvergent fitted finite volume method for Black-Scholes equations governing European and American option valuation, Numerical Methods for Partial Differential Equations, 31 (2015), 1190-1208. doi: 10.1002/num.21941. Google Scholar
[36]	Y.-P. Wang and S.-L. Tao, Application of regularization technique to variational adjoint method: A case for nonlinear convection-diffusion problem, Applied Mathematics and Computation, 218 (2011), 4475-4482. doi: 10.1016/j.amc.2011.10.028. Google Scholar
[37]	P. Wilmott, J. Dewynne and S. Howison, Option Pricing: Mathematical Models and Computation, Oxford Financial Press, Oxford, 1993.
[38]	D. M. Young, Iterative Solution of Large Linear Systems, Academic Press, 1971.
[39]	K. Zhang and S. Wang, Pricing options under jump diffusion processes with fitted finite volume method, Applied Mathematics & Computation, 201 (2008), 398-413. doi: 10.1016/j.amc.2007.12.043. Google Scholar
[40]	K. Zhang and S. Wang, A computational scheme for options under jump diffusion processes, International Journals of Numerical Analysis and Modeling, 6 (2009), 110-123. Google Scholar
[41]	K. Zhang and S. Wang, Pricing American bond options using a penalty method, Automatica, 48 (2012), 472-479. doi: 10.1016/j.automatica.2012.01.009. Google Scholar
[42]	X. L. Zhang, Numerical analysis of American option pricing in a jump diffusion model, Math. Oper. Res., 22 (1997), 668-690. doi: 10.1287/moor.22.3.668. Google Scholar
[43]	Y. Y. Zhou, S. Wang and X. Q. Yang, A penalty approximation method for a semilinear parabolic double obstacle problem, Journal of Global Optimization, 60 (2014), 531-550. doi: 10.1007/s10898-013-0122-6. Google Scholar

Figure 6.1. Prices of the European call and put options with $a=0.01$ and $b=0.07$

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Figure 6.2. Prices of the European call and put option for different values of the transaction cost parameter

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Figure 6.3. Computed American and European put option prices

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Figure 6.4. Computed American put option prices for different values of the transaction cost parameter

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Table 6.1. Computed rates of convergence for the call option with $a = 0.01$ and $b=0.07$

$M$	$N$	$\\|\cdot\\|_{h,2}$	Ratio$(\\|\cdot\\|_{h,2})$
21	11	0.215680
41	21	0.116543	1.85
81	41	0.061550	1.89
161	81	0.031986	1.92
321	161	0.016228	1.97
641	321	0.007861	2.06
1281	641	0.003457	2.27
2561	1281	0.001170	2.96

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$M$	$N$	$\\|\cdot\\|_{h,2}$	Ratio$(\\|\cdot\\|_{h,2})$
21	11	0.215680
41	21	0.116543	1.85
81	41	0.061550	1.89
161	81	0.031986	1.92
321	161	0.016228	1.97
641	321	0.007861	2.06
1281	641	0.003457	2.27
2561	1281	0.001170	2.96

Table 6.2. Computed rates of convergence for the put option with $a = 0.01$ and $b=0.07$

$M$	$N$	$\\|\cdot\\|_{h,2}$	Ratio$(\\|\cdot\\|_{h,2})$
21	11	0.454596
41	21	0.438884	1.04
81	41	0.390547	1.12
161	81	0.327934	1.19
321	161	0.259319	1.26
641	321	0.189478	1.37
1281	641	0.121703	1.56
2561	1281	0.058168	2.09

Table Options

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$M$	$N$	$\\|\cdot\\|_{h,2}$	Ratio$(\\|\cdot\\|_{h,2})$
21	11	0.454596
41	21	0.438884	1.04
81	41	0.390547	1.12
161	81	0.327934	1.19
321	161	0.259319	1.26
641	321	0.189478	1.37
1281	641	0.121703	1.56
2561	1281	0.058168	2.09

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