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ANDROID APPLICATION FOR PRICING TWO-AND THREE-ASSET EQUITY-LINKED SECURITIES

  • JANG, HANBYEOL (DEPARTMENT OF FINANCIAL ENGINEERING, KOREA UNIVERSITY) ;
  • HAN, HYUNSOO (DEPARTMENT OF FINANCIAL ENGINEERING, KOREA UNIVERSITY) ;
  • PARK, HAYEON (DEPARTMENT OF FINANCIAL ENGINEERING, KOREA UNIVERSITY) ;
  • LEE, WONJIN (DEPARTMENT OF FINANCIAL ENGINEERING, KOREA UNIVERSITY) ;
  • LYU, JISANG (DEPARTMENT OF MATHEMATICS, KOREA UNIVERSITY) ;
  • PARK, JINTAE (DEPARTMENT OF MATHEMATICS, KOREA UNIVERSITY) ;
  • KIM, HYUNDONG (DEPARTMENT OF MATHEMATICS, KOREA UNIVERSITY) ;
  • LEE, CHAEYOUNG (DEPARTMENT OF MATHEMATICS, KOREA UNIVERSITY) ;
  • KIM, SANGKWON (DEPARTMENT OF MATHEMATICS, KOREA UNIVERSITY) ;
  • CHOI, YONGHO (DEPARTMENT OF MATHEMATICS AND BIG DATA, DAEGU UNIVERSITY) ;
  • KIM, JUNSEOK (DEPARTMENT OF MATHEMATICS, KOREA UNIVERSITY)
  • Received : 2019.09.05
  • Accepted : 2019.09.14
  • Published : 2019.09.25

Abstract

We extend the previous work [J. Korean Soc. Ind. Appl. Math. 21(3) 181] to two-and three-asset equity-linked securities (ELS). In the real finance market, two-or three-asset ELS is more popular than one-asset ELS. Therefore, we need to develop mobile platform for pricing the two-and three-asset ELS. The mobile implementation of the ELS pricing will be very useful in practice.

Keywords

References

  1. D. Gabor and S. Brooks, The digital revolution in financial inclusion: international development in the fintech era, New Polit. Econ., 22(4) (2017), 423-436. https://doi.org/10.1080/13563467.2017.1259298
  2. P. Gomber, J.A. Koch, and M. Siering, Digital Finance and FinTech: current research and future research directions, J. Bus. Econ., 87(5) (2017), 537-580.
  3. P. Gomber, R.J. Kauffman, C. Parker, and B.W. Weber, On the fintech revolution: interpreting the forces of innovation, disruption, and transformation in financial services, J. Manag. Inf. Syst., 35(1) (2018), 220-265.
  4. K. Gai, M. Qiu, and X. Sun, A survey on FinTech, J. Netw. Comp. Appl., 103 (2018), 262-273. https://doi.org/10.1016/j.jnca.2017.10.011
  5. W. Jian, J. Ban, J. Han, S. Lee, and D. Jeong, Mobile platform for pricing of Equity-Linked Securities, J. Korean Soc. Ind. Appl. Math., 21(3) (2017), 181-202. https://doi.org/10.12941/jksiam.2017.21.181
  6. S.G. Kou, A jump-diffusion model for option pricing, Manag. Sci., 48(8) (2002), 1086-1101. https://doi.org/10.1287/mnsc.48.8.1086.166
  7. J.D. Hamilton, A new approach to the economic analysis of nonstationary time series and the business cycle, Econometrica, 57(2) (1989), 357-384. https://doi.org/10.2307/1912559
  8. S.S. Clift and P.A. Forsyth, Numerical solution of two asset jump diffusion models for option valuation, Appl. Numer. Math., 58(6) (2008), 743-782. https://doi.org/10.1016/j.apnum.2007.02.005
  9. D.J. Duffy. Finite Difference methods in financial engineering: a Partial Differential Equation approach, John Wiley and Sons, 2013.
  10. A.Q.M. Khaliq, D.A. Voss, and K. Kazmi , Adaptive ${\theta}$-methods for pricing American options, J. Comput. Appl. Math., 222(1) (2008), 210-227. https://doi.org/10.1016/j.cam.2007.10.035
  11. Z. Cen, A. Le, and A. Xu, Finite difference scheme with a moving mesh for pricing Asian options, App.l Math. Comput., 219(16) (2013), 8667-8675. https://doi.org/10.1016/j.amc.2013.02.065
  12. D. Jeong, J. Kim, and I.S. Wee, An accurate and efficient numerical method for Black-Scholes equations, Commun. Korean Math. Soc., 24(4) (2009), 617-628. https://doi.org/10.4134/CKMS.2009.24.4.617
  13. S. Foulon, ADI finite difference schemes for option pricing in the Heston model with correlation, Int. J. Numer. Anal. Model., 7(2) (2010), 303-320.
  14. P. Glasserman, Monte Carlo methods in financial engineering. Springer Science & Business Media, 2013.
  15. P.P. Boyle, Options: A monte carlo approach, J. Fin. Econ., 4(3) (1977), 323-338. https://doi.org/10.1016/0304-405X(77)90005-8
  16. P. Boyle, M. Broadie, and P. Glasserman, Monte Carlo methods for security pricing, J. Econ. Dyn. Control, 21 (1997), 1267-1321. https://doi.org/10.1016/S0165-1889(97)00028-6
  17. C.P. Fries and M.S. Joshi. Conditional analytic Monte-Carlo pricing scheme of auto-callable products, Centre for Actuarial Studies, Department of Economics, University of Melbourne, 2008.
  18. J.E. Handschin, Monte Carlo techniques for prediction and filtering of non-linear stochastic processes, Automatica, 6(4) (1970), 555-563. https://doi.org/10.1016/0005-1098(70)90010-5
  19. H.L. Koh and S.Y. Teh, Learning Black Scholes option pricing the fun way via mobile apps, Proc. 2013 IEEE Int. Conf. Teaching, Assessm. Learn. Eng. (TALE), 192-195.
  20. J. Wang and C. Liu, Generating multivariate mixture of normal distributions using a modified Cholesky decomposition, Proc. 38th Conf. Winter Simul., 2006.

Cited by

  1. FAST ANDROID IMPLIMENTATION OF MONTE CARLO SIMULATION FOR PRICING EQUITY-LINKED SECURITIES vol.24, pp.1, 2019, https://doi.org/10.12941/jksiam.2020.24.079