Main Article Content

Abstract

An option is a financial instrument that investors often use for speculation or hedging purposes. Calculating the profit in the investment using options also considers its price, so the investor needs to know the proper value of the option's price or at least the range of these values. This paper aims to improve the Bino-Trinomial tree model for determining the price of a European call option with a volatility parameter in the form of a triangular Fuzzy number. The Bino-Trinomial tree model is a combination of the Binomial and Trinomial trees that aims to control the values of its branches. Due to the involvement of the Fuzzy number, the obtained value of the option price is in a range or interval, so the investor could use it appropriately in arranging investment strategies. In the proposed model, the Fuzzy volatility parameter is utilized to capture the uncertainty of the estimated volatility in the financial market which can fluctuate from time to time. This parameter is expected to provide reasonable ranges and appropriate Fuzzy membership functions for option pricing so that investors can expect different optimal values for different risk preferences. We also adjusted the formulation of the increase and decrease factors in the Fuzzy Binomial tree to model stock price movements. Using different values of the volatility's sensitivity level and the option period, the results of numerical simulations show that prices of European call options given by the market are always within the option price range of the proposed model's result. Likewise, the results of the defuzzification of options prices in our Fuzzy Bino-Trinomial tree model are not much different from the prices given by the market. This shows that the Fuzzy Bino-Trinomial tree model performs better in determining the price of European call options than the Fuzzy Binomial tree and Fuzzy Trinomial models.

Keywords

Fuzzy volatility option pricing Bino-Trinomial tree model Binomial tree model Trinomial tree model

Article Details

Author Biographies

Novriana Sumarti, Institut Teknologi Bandung

Profesor in Industrial and Financial Mathematics Research Group, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung 

Kuntjoro Adji Sidarto, Institut Teknologi Bandung

Industrial and Financial Mathematics Research Group, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung

How to Cite
Agustina, F., Sumarti, N., & Sidarto, . K. A. (2024). CONSTRUCTION OF THE BINO-TRINOMIAL METHOD USING THE FUZZY SET APPROACH FOR OPTION PRICING. Journal of the Indonesian Mathematical Society, 30(2), 179–204. https://doi.org/10.22342/jims.30.2.1775.179-204

References

  1. [Bank for International Settlements(2023)] Data Over-The-Counter (OTC) global, diperoleh melalui situs internet https://stats.bis.org/statx/srs/table/d5.1. Diunduh pada 25 Agustus 2023.
  2. Black, F., and Scholes, M., ”The Pricing of Options and Corporate Liabilities”, Journal of Political Economy, 81 (1973), 637–645.
  3. Cox, J.C., Ross, S.A., and Rubinstein, M., ”Option Pricing: A Simplified Approach”, Journal of Financial Economics, 7 (1979), 229–263.
  4. Boyle, P. P., ”A Lattice Framework for Option Pricing with Two State Variables”, The Journal of Financial and Quantitative Analysis, 23 (1988), 1-12.
  5. Kamrad, B. and Ritchken, P., ”Multinomial Approximating Models for Options with k State Variables”, Management Science, 37 (1991), 197-210.
  6. Leisen, D.P.J., and Reimer, M., ”Binomial Models for Option Valuation-Examining and Improving Convergence”, Applied Mathematical Finance, 3 (1996), 319-346.
  7. Tian, Y., ”A Flexible Binomial Option Pricing Model”, Journal of Futures Markets, 19 (1996), 817-843.
  8. P. Boyle and S. Lau, ”Bumping up against the Barrier with the Binomial Method”, Journal of Derivatives, 1 (1994), 6-14.
  9. Ritchken, P., ”On Pricing Barrier Options”, The Journal of Derivatives, 3 (1995), 19-28.
  10. Klassen, T., ”Simple, Fast and Flexible Pricing of Asian Options”, The Journal of Computational Finance, 4 (2001), 89-124.
  11. Costabile M., Massabo, I., and Russo, E., ”An Adjusted Binomial Model for Pricing Asian Options”, Review of Quantitative Finance and Accounting, 27 (2006), 285-296.
  12. T.-S. Dai and Y.-D. Lyuu, ”The Bino-Trinomial Tree: A Simple Model for Efficient and Accurate Option Pricing”, The Journal of Derivatives, 17 (2010), 7-24.
  13. Moon, K.Y. and Kim, H., ”An Improved Binomial Method for Pricing Asian Options”, Communications of the Korean Mathematical Society, 28 (2013), 397-406.
  14. Chendra, E., Sidarto, K.A., Syamsuddin, M., and Puspita, D., ”Pricing ’Partial-Average’ Asian Options with The Binomial Method”, Journal of Banking, Accounting and Finance, 10 (2019), 101-116.
  15. Jumana, S.S. and Hossain, A.B.M.S., ”An Improved Binomial Method for Pricing Asian Options”, GANIT: Journal of Bangladesh Mathematical Society, 41 (2019), 26-40.
  16. Wu H., ”Pricing European options based on the Fuzzy pattern of Black-Scholes formula”, Computers and Operations Research, 31 (2004), 1069-1081.
  17. Zadeh, L. A., ”Fuzzy sets”, Information and Control, 8 (1965), 338-353.
  18. Muzzioli, S. and Torricelli, C., ”A model for Pricing an Option with a Fuzzy Payoff”, Fuzzy Economic Review, 6 (2001), 49-87.
  19. Muzzioli, S. and Torricelli, C., ”A Multiperiod Binomial Model for Pricing Options in a Vague World”, Journal of Economic Dynamics and Control, 8 (2004), 861-887.
  20. Appadoo, S.S. and Thavaneswaran A., ”Recent Developments in Fuzzy Sets Approach in Option Pricing”, Journal of Mathematical Finance, 3 (2013), 312-322.
  21. Liu, S., Chen, Y. and Xu. N., ”Application of Fuzzy Theory to Binomial Option Pricing Model”, In Fuzzy Information and Engineering, 54 (2009), 63-70.
  22. Yu, S., Li., M., Huarng, K., Chen, T., and Chen, C., ”Model Construction of Option Pricing Based on Fuzzy Theory”, Journal of Marine Science and Technology, 19 (2011), 460-469.
  23. Yoshida, Y., ”A Discrete Time Model of American Put Option in an Uncertain Environment”, European Journal of Operational Research, 151 (2003), 153-166.
  24. Muzzioli, S. and Reynaerts, H., ”The Solution of Fuzzy Linear Systems by Nonlinear Programming: a Financial Application”, European Journal of Operational Research, 177 (2008), 1218-1231.
  25. W. Xu, G. Liu and X. Yu, ”A Binomial Tree Approach to Pricing Vulnerable Option in a Vague World,” International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 26 (2018), 143-162.
  26. Muzzioli, S. and De Baets, B., ”Fuzzy Approaches to Option Price Modeling”, IEEE Transactions on Fuzzy Systems, 25 (2017).
  27. Liao, S., Ho, S., ”Investment project valuation based on a fuzzy binomial approach”, Information Sciences, 180(11) (2010), 2124-2133.
  28. Sumarti,N. and Nadya, P. ”A Dynamic Portfolio of American Option Using Fuzzy Binomial Method”, Journal of Innovative Technology and Education, 3(1) (2016), 85-92.
  29. Agustina, F., Sidarto, K.A., and Sumarti, N. ”European Put Option Model Up-and-Out Constant Barrier and Exponential Barrier with Fuzzy Parameters”, accepted to the proceeding of 9th ICRIEMS (International Conference on Research, Implementation, and Education of Mathematics and Sciences), (2022).
  30. Zadeh, L. A., ”The Concept of Linguistic Variable and Its Application to Approximate Reasoning I, II and III”, Information Sciences, 8,9 (1975), 199–249, 301–57, 43–80.
  31. Wu, Hsien-Chung. ”Pricing European Options Based on The Fuzzy Pattern of Black–Scholes Formula”, Computers and Operations Research, 13 (2007), 1069-1081.
  32. Prasada, S. and Sinha S. ”A Unified Distance Approach for Ranking Fuzzy Numbers and Its Comparative Reviews”, Journal of the Indonesian Mathematical Society, 12(3) (2023), 341-371,
  33. Bodjanova S. ”Median Value and Median Interval of A Fuzzy Number”, Information Sciences, 172 (2005), 73–89.
  34. Josheski D. and Apostolov M., ”A Review of the Binomial and Trinomial Models for Option Pricing and their Convergence to the Black-Scholes Model Determined Option Prices”, Econometrics. Advances in Applied Data Analysis, Sciendo, 24 (2020), 53-85.
  35. Lee C.F., Tzeng G-H., and Wang S-Y., ”A Fuzzy Set Approach for Generalized CRR Model: An Empirical Analysis of S and P 500 Index Option”, Review of Quantitative Finance and Accounting, 25 (2005), 255-275.
  36. Yu, S. E. S., Huarng, K. H., Li, M. Y. L., and Chen, C. Y., “A Novel option pricing model via Fuzzy Binomial decision tree,” International Journal of Innovative Computing, Information and Control, 7 (2011), 709-718.
  37. Kellison, S. ”The Theory of Interest”, 3rd Ed., McGraw-Hill/Irwin, (February 7, 2008).
  38. Bertsimas D., Kogan L., and Lo A. W., ”Pricing and Hedging Derivative Securities in Incomplete Markets: An E-Aritrage Model”, NBER Working Paper No. w6250 (1997).
  39. Abdurakhman, Seno Saleh, S., Guritno, S., and Soejoeti, Z. ”Valueing Trinomial Option Pricing with Pseudoinverse Matrix”, Journal of the Indonesian Mathematical Society, 12 (2006).