DETERMINING THE VALUE OF DOUBLE BARRIER OPTION USING STANDARD MONTE CARLO, ANTITHETIC VARIATE, AND CONTROL VARIATE METHODS

  • Romaito Br Silalahi Department of Mathematics, Faculty of Mathematics and Natural Science, IPB University, Indonesia
  • Donny Citra Lesmana Department of Mathematics, Faculty of Mathematics and Natural Science, IPB University, Indonesia
  • Retno Budiarti Department of Mathematics, Faculty of Mathematics and Natural Science, IPB University, Indonesia
Keywords: Pricing Barrier Option, Double Barrier, Antithetic Variates, Control Variates, Standard Monte Carlo

Abstract

In this paper, we applied the standard Monte Carlo, antithetic variate, and control variates methods to value the double barrier knock-in option price. The underlying asset used in the calculation of double barrier knock-in option is the share of ANTM from April 1, 2019 until March 1, 2022. The value of the double barrier knock-in option is simulated using standard Monte Carlo, antithetic variate, and control variates methods. The results showed that all the methods converge to the exact solution, with the control variate method to be the fastest. Standard Monte Carlo method has the least computational time, followed by control variate and antithetic variate method. Compared to the other methods, control variate is the most effective and efficient in determining the value of double barrier knock-in option, based on the option value, relative error and computational time. Antithetic variate method converges faster to the exact solution compared to standard Monte Carlo. However it has the longest computation time compared to the other methods.

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References

KSEI, “Statistik Pasar Modal Indonesia Agustus 2021,” Kustodian Sent. Efek Indones., pp. 1–6, 2021, [Online]. Available: https://www.ksei.co.id/files/Statistik_Publik_Januari_2021.pdf [Accessed: Feb. 14, 2022].

J. C. Hull, “‘Options, Futures, and Other Derivatives,’” in AMBER – ABBS Management Business and Entrepreneurship Review, vol. 7, no. 1, 2015, p. 70.

C. Albanese and G. Campolieti, Advanced Derivatives Pricing and Risk Management. USA: Elsevier Inc., 2016.

M. Rezaei, A. R. Yazdanian, A. Ashrafi, and S. M. Mahmoudi, “Numerical pricing based on fractional Black–Scholes equation with time-dependent parameters under the CEV model: Double barrier options,” Comput. Math. with Appl., vol. 90, pp. 104–111, May 2021, doi: 10.1016/j.camwa.2021.02.021.

H. Wang, J. Zhang, and K. Zhou, “On pricing of vulnerable barrier options and vulnerable double barrier options,” Financ. Res. Lett., vol. 44, Jan. 2022, doi: 10.1016/j.frl.2021.102100.

T. Guillaume, “Step double barrier options,” J. Deriv., vol. 18, no. 1, pp. 59–79, 2010, doi: 10.3905/jod.2010.18.1.059.

M. Milev and A. Tagliani, “Numerical valuation of discrete double barrier options,” J. Comput. Appl. Math., vol. 233, no. 10, pp. 2468–2480, 2010, doi: 10.1016/j.cam.2009.10.029.

J. Cai, A. Tagliani, X. Liu, A. Sachdeva, and K. Yi, “Pricing barrier options using PDEs in C++ Pricing JSE Exot ic Can-Do Opt ions: Mont e Carlo Simulat ion Ant onie Kot zé Efficient implicit scheme wit h posit ivit y preserving and smoot hing propert ies PRICING BARRIER OPTIONS USING PDES IN C++ A PREPRINT,” 2020.

P. Boyle, M. Broadie, and P. Glasserman, “Boyle Broadie Glasserman Monte Carlo Methods for security pricing.pdf,” vol. 21, no. 8–9, pp. 1267–1321, 1997, doi: doi.org/10.1016/S0165-1889(97)00028-6.

K. Nouri and B. Abbasi, “Implementation of the modified Monte Carlo simulation for evaluate the barrier option prices,” J. Taibah Univ. Sci., vol. 11, no. 2, pp. 233–240, Mar. 2017, doi: 10.1016/j.jtusci.2015.02.010.

B. Wang and L. Wang, “Pricing Barrier Options using Monte Carlo Methods,” 2011.

P. Glasserman, Monte Carlo Methods in Financial Engineering, no. April. New York: Springer, 2003. doi: 10.10071978-0-387-21617-1.

D. M. Putri and L. H. Hasibuan, “Penerapan Gerak Brown Geometrik Pada Data Saham PT. ANTM,” vol. 2, 2020, doi: https://doi.org/10.15548/map.v2i2.2258.

H. Alzubaidi, “Efficient Monte Carlo algorithm using antithetic variate and brownian bridge techniques for pricing the barrier options with rebate payments,” J. Math. Stat., vol. 12, no. 1, pp. 1–11, 2016, doi: 10.3844/jmssp.2016.1.11.

I. F. Maulida, Metode Monte Carlo control variate dalam penentuan nilai opsi double barrier [Thesis]. Universitas Islam Negeri Maulana Malik Ibrahim, 2020.

D. Sayekti, Perbandingan metode Monte Carlo standar, antithetic variate dan control variate pada penentuan harga opsi barrier [Thesis]. Universitas Sanata Dharma, 2010. [Online]. Available: http://repository.usd.ac.id/27090/2/063114017_Full.pdf

Published
2023-06-11
How to Cite
[1]
R. Silalahi, D. Lesmana, and R. Budiarti, “DETERMINING THE VALUE OF DOUBLE BARRIER OPTION USING STANDARD MONTE CARLO, ANTITHETIC VARIATE, AND CONTROL VARIATE METHODS”, BAREKENG: J. Math. & App., vol. 17, no. 2, pp. 1017-1026, Jun. 2023.