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Pricing European Options with Triangular Fuzzy Parameters: Assessing Alternative Triangular Approximations in the Spanish Stock Option Market

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Abstract

The aim of this paper is contributing from a practical and empirical perspective to option pricing under fuzziness. When we evaluate Black–Scholes option pricing formula with triangular fuzzy numbers, we obtain a non-triangular price that may be slightly difficult to use in practical applications. We improve the applicability of the fuzzy version of that formula by proposing and testing three triangular approximations when the subjacent asset price, its volatility and free interest rate are triangular fuzzy numbers. To check the goodness of these approximations, we firstly evaluate their closeness to the actual values of fuzzy Black and Scholes model. We find that the quality of those approximations depends on options maturity and moneyness grade and if we are pricing call or put options. We also assess the capability of those approximating methods to reflect satisfactorily real market prices and obtain good results. To develop all empirical applications, we use a sample of options on IBEX35 traded in the Spanish derivatives market on 3/1/2017.

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Notes

  1. Notice that since 2016, in Eurozone, interest rates have been negative in all short-term monetary markets due to the expansive monetary policy of the European Central Bank.

  2. In [22], it is developed a non-triangular approximating method for fuzzy option prices that also uses the Greeks. This paper proposes a flexible polynomial approximation to the fuzzy price of options, which is built up with the value of the extremes of the α-cuts in certain predefined knots and the value of the Greeks in these knots.

References

  1. Abbasbandy, S., Ahmady, E., Ahmady, N.: Triangular approximations of fuzzy numbers using α-weighted valuations. Soft. Comput. 14(1), 71–79 (2010)

    Article  MATH  Google Scholar 

  2. Anzilli, L., Facchinetti, G.: New definitions of mean value and variance of fuzzy numbers: an application to the pricing of life insurance policies and real options. Int. J. Approx. Reason. 91, 96–113 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  3. Ban, A.: Approximation of fuzzy numbers by trapezoidal fuzzy numbers preserving the expected interval. Fuzzy Sets Syst. 159(11), 1327–1344 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  4. Ban, A.I., Coroianu, L.: Nearest interval, triangular and trapezoidal approximation of a fuzzy number preserving ambiguity. Int. J. Approx. Reason. 53(5), 805–836 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  5. Black, F., Cox, J.C.: Valuing corporate securities: some effects of bond indenture provisions. J. Financ. 31(2), 351–367 (1976)

    Article  Google Scholar 

  6. Black, F., Scholes, M.: The pricing of options and corporate liabilities. J. Polit. Econ. 81(3), 637–654 (1973)

    Article  MathSciNet  MATH  Google Scholar 

  7. Brennan, M.J., Schwartz, E.S.: The pricing of equity-linked life insurance policies with an asset value guarantee. J. Financ. Econ. 3(3), 195–213 (1976)

    Article  Google Scholar 

  8. Buckley, J.J., Eslami, E.: Pricing options, forwards and futures using fuzzy set theory. In: Kahraman, C. (ed.) Fuzzy engineering economics with applications, pp. 339–357. Springer, Berlin, Heidelberg (2008)

    Chapter  Google Scholar 

  9. Buckley, J.J., Qu, Y.: On using α-cuts to evaluate fuzzy equations. Fuzzy Sets Syst. 38(3), 309–312 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  10. Buckley, J.J.: Fuzzy statistics: hypothesis testing. Soft. Comput. 9(7), 512–518 (2005)

    Article  MATH  Google Scholar 

  11. Capotorti, A., Figà-Talamanca, G.: On an implicit assessment of fuzzy volatility in the Black and Scholes environment. Fuzzy Sets Syst. 223, 59–71 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  12. Carlsson, C., Fullér, R.: A fuzzy approach to real option valuation. Fuzzy Sets Syst. 139(2), 297–312 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  13. Chrysafis, K.A., Papadopoulos, B.K.: On theoretical pricing of options with fuzzy estimators. J. Comput. Appl. Math. 223(2), 552–566 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  14. de Andrés-Sánchez, J., González-Vila, L.: The valuation of life contingencies: a symmetrical triangular fuzzy approximation. Insur. Math. Econ. 72, 83–94 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  15. de Andrés-Sánchez, J.: An empirical assestment of fuzzy Black and Scholes pricing option model in Spanish stock option market. J. Intell. Fuzzy Syst. 33(4), 2509–2521 (2017)

    Article  MATH  Google Scholar 

  16. Dubois, D., Prade, H.: Fuzzy numbers: an overview. In: Dubois, D., Prade, H., Yager, R.R. (eds.) Readings on Fuzzy Sets for Intelligent Systems, pp. 113–148. Morgan Kaufmann Publishers, San Mateo (1993)

    Google Scholar 

  17. Dumas, B., Fleming, J., Whaley, R.E.: Implied volatility functions: empirical tests. J. Financ. 53(6), 2059–2106 (1998)

    Article  Google Scholar 

  18. Figa-Talamanca, G., Guerra, M.L., Stefanini, L.: Market application of the fuzzy-stochastic approach in the heston option pricing model. Financ. a Uver 62(2), 162–179 (2012)

    Google Scholar 

  19. Grzegorzewski, P.: Fuzzy number approximation via shadowed sets. Inf. Sci. 225, 35–46 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  20. Grzegorzewski, P., Mrówka, E.: Trapezoidal approximations of fuzzy numbers. Fuzzy Sets Syst. 153(1), 115–135 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  21. Grzegorzewski, P., Mrówka, E.: Trapezoidal approximations of fuzzy numbers—revisited. Fuzzy Sets Syst. 158(7), 757–768 (2007)

    Article  MATH  Google Scholar 

  22. Grzegorzewski, P., Pasternak-Winiarska, K.: Natural trapezoidal approximations of fuzzy numbers. Fuzzy Sets Syst. 250, 90–109 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  23. Guerra, M.L., Sorini, L., Stefanini, L.: Option price sensitivities through fuzzy numbers. Comput. Math Appl. 61(3), 515–526 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  24. Heberle, J., Thomas, A.: Combining chain-ladder reserving with fuzzy numbers. Insur. Math. Econ. 55, 96–104 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  25. Heston, S.L.: A closed-form solution for options with stochastic volatility with applications to bond and currency options. Rev. Financ. Stud. 6(2), 327–343 (1993)

    Article  MATH  Google Scholar 

  26. Jiménez, M., Rivas, J.A.: Fuzzy number approximation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 6(01), 69–78 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  27. Kaufmann, A.: Fuzzy subsets applications in OR and management. In: Jones, A., Kaufmann, A., Zimmermann, H.J. (eds.) Fuzzy sets theory and applications, pp. 257–300. Springer, Netherlands. (1986)

    Chapter  Google Scholar 

  28. Liu, Y., Chen, X., Ralescu, D.A.: Uncertain currency model and currency option pricing. Int. J. Intell. Syst. 30(1), 40–51 (2015)

    Article  Google Scholar 

  29. MacBeth, J.D., Merville, L.J.: An empirical examination of the black–scholes call option pricing model. J. Financ. 34(5), 1173–1186 (1979)

    Article  Google Scholar 

  30. Merton, R.C.: Applications of option-pricing theory: twenty-five years later (digest summary). Am. Econ. Rev. 88(3), 323–349 (1998)

    Google Scholar 

  31. Muzzioli, S., De Baets, B.: A comparative assessment of different fuzzy regression methods for volatility forecasting. Fuzzy Optim. Decis. Mak. 12(4), 433–450 (2013)

    Article  MathSciNet  Google Scholar 

  32. Muzzioli, S., De Baets, B.: Fuzzy approaches to option price modeling. IEEE Trans. Fuzzy Syst. 25(2), 392–401 (2017)

    Article  Google Scholar 

  33. Muzzioli, S., Ruggieri, A., De Baets, B.: A comparison of fuzzy regression methods for the estimation of the implied volatility smile function. Fuzzy Sets Syst. 266, 131–143 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  34. Nowak, P., Pawłowski, M.: Option pricing with application of levy processes and the minimal variance equivalent martingale measure under uncertainty. IEEE Trans. Fuzzy Syst. 25(2), 402–416 (2017)

    Article  Google Scholar 

  35. Nowak, P., Romaniuk, M.: Computing option price for Levy process with fuzzy parameters. Eur. J. Oper. Res. 201(1), 206–210 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  36. Nowak, P., Romaniuk, M.: A fuzzy approach to option pricing in a Levy process setting. Int. J. Appl. Math. Comput. Sci. 23(3), 613–622 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  37. Nowak, P., Romaniuk, M.: Application of Levy processes and Esscher transformed martingale measures for option pricing in fuzzy framework. J. Comput. Appl. Math. 263, 129–151 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  38. Savic, D., Pedrycz, W.: Fuzzy linear regression models: construction and evaluation. In: Kacprzyk, J., Fedrizzi, M. (eds.) Fuzzy regression analysis, pp. 91–101. Physica Verlag, Heidelberg (1992)

    Google Scholar 

  39. Sfiris, D.S., Papadopoulos, B.K.: Non-asymptotic fuzzy estimators based on confidence intervals. Inf. Sci. 279, 446–459 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  40. Sun, Y., Kai, Y., Jichang, D.: Asian option pricing problems of uncertain mean-reverting stock model. Soft. Comput. (2017). https://doi.org/10.1007/s00500-017-2524-8

    Google Scholar 

  41. Terceño, A., De Andrés, J., Barberà, G., Lorenzana, T.: Using fuzzy set theory to analyze investments and select portfolios of tangible investments in uncertain environments. Int. J. Uncertain.Fuzziness Knowl. Based Syst. 11(03), 263–281 (2003)

    Article  MATH  Google Scholar 

  42. Thavaneswaran, A., Appadoo, S.S., Frank, J.: Binary option pricing using fuzzy numbers. Appl. Math. Lett. 26(1), 65–72 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  43. Trigeorgis, L.: Real options: managerial flexibility and strategy in resource allocation. MIT press, Boston (1996)

    Google Scholar 

  44. Wang, X., He, J.: A geometric Levy model for n-fold compound option pricing in a fuzzy framework. J. Comput. Appl. Math. 306, 248–264 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  45. Wang, X., He, J., Li, S.: Compound option pricing under fuzzy environment. J. Appl. Math. (2014). https://doi.org/10.1155/2014/875319

    MathSciNet  Google Scholar 

  46. Wu, H.C.: Pricing European options based on the fuzzy pattern of Black–Scholes formula. Comput. Oper. Res. 31(7), 1069–1081 (2004)

    Article  MATH  Google Scholar 

  47. Wu, H.C.: Using fuzzy sets theory and Black–Scholes formula to generate pricing boundaries of European options. Appl. Math. Comput. 185(1), 136–146 (2007)

    MathSciNet  MATH  Google Scholar 

  48. Xu, W., Xu, W., Li, H., Zhang, W.: A study of Greek letters of currency option under uncertainty environments. Math. Comput. Model. 51(5), 670–681 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  49. Yoshida, Y.: The valuation of European options in uncertain environment. Eur. J. Oper. Res. 145(1), 221–229 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  50. Zhang, L.H., Zhang, W.G., Xu, W.J., Xiao, W.L.: The double exponential jump diffusion model for pricing European options under fuzzy environments. Econ. Model. 29(3), 780–786 (2012)

    Article  Google Scholar 

  51. Zmeškal, Z.: Application of the fuzzy–stochastic methodology to appraising the firm value as a European call option. Eur. J. Oper. Res. 135(2), 303–310 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  52. Zmeškal, Z.: Generalised soft binomial American real option pricing model (fuzzy–stochastic approach). Eur. J. Oper. Res. 207(2), 1096–1103 (2010)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

The author thanks anonymous reviewers for their constructive comments and suggestions.

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Correspondence to Jorge de Andrés-Sánchez.

Appendix: Relative Deviations of Three Alternative Triangular Approximations to the Fuzzy Black and Scholes Formula

Appendix: Relative Deviations of Three Alternative Triangular Approximations to the Fuzzy Black and Scholes Formula

See Tables 9, 10, 11, 12, 13 and 14.

Table 9 \(\underline{wae} \left( {\alpha^{*} } \right)\) and \(\overline{wae} \left( {\alpha^{*} } \right)\) of TFNAs to call prices with expiration date 3/24/2017
Table 10 \(\underline{wae} \left( {\alpha^{*} } \right)\) and \(\overline{wae} \left( {\alpha^{*} } \right)\) of TFNAs to call prices with expiration date 4/21/2017
Table 11 \(\underline{wae} \left( {\alpha^{*} } \right)\) and \(\overline{wae} \left( {\alpha^{*} } \right)\) of TFNAs to call prices with expiration date 5/19/2017
Table 12 \(\underline{wae} \left( {\alpha^{*} } \right)\) and \(\overline{wae} \left( {\alpha^{*} } \right)\) of TFNAs to put prices with expiration date 3/24/2017
Table 13 \(\underline{wae} \left( {\alpha^{*} } \right)\) and \(\overline{wae} \left( {\alpha^{*} } \right)\) of TFNAs to put prices with expiration date 4/21/2017
Table 14 \(\underline{wae} \left( {\alpha^{*} } \right)\) and \(\overline{wae} \left( {\alpha^{*} } \right)\) of TFNAs to put prices with expiration date 5/19/2017

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de Andrés-Sánchez, J. Pricing European Options with Triangular Fuzzy Parameters: Assessing Alternative Triangular Approximations in the Spanish Stock Option Market. Int. J. Fuzzy Syst. 20, 1624–1643 (2018). https://doi.org/10.1007/s40815-018-0468-5

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