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International Journal of Neutrosophic Science

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Online: 2690-6805 Print: 2692-6148
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International Journal of Neutrosophic Science
Full Length Article

Volume 27Issue 2PP: 287-296 • 2026

An Empirical Evaluation of the Stock Market Using Fuzzy Variant Black and Scholes Model Involving Central Fuzzy Measures

K. Meenakshi 1* ,
Pavithra S. 1 ,
S. Sathish 1 ,
Prabakaran N. 2
1School of Engineering, Presidency University, Bengaluru, Karnataka, India
2School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India
* Corresponding Author.
Received: February 08, 2025 Revised: May 28, 2025 Accepted: July 09, 2025

Abstract

This article defines the central tendency fuzzy measures, which include the weighted fuzzy possiblistic mean and the fuzzy probability mean involving octagonal fuzzy numbers. The same is supported by a fuzzy variant of the Black-Scholes option model, in which uncertain pricing parameters such as volatility, interest rate, and stock price are described using octagonal fuzzy numbers.

Keywords

Weighted fuzzy possiblistic mean Interval-valued fuzzy expectation Octagonal fuzzy numbers Black-Scholes variant fuzzy option model

References

[1] Andres-Sanchez, J. D., An Empirical Assessment of Fuzzy Black and Scholes Pricing Option Model in Spanish Stock Option Market. Journal of Intelligent and Fuzzy Systems 33, (2017) 2509-2521.DOI:

 

[2] C. Carlsson, R. Fuller, On possibilistic mean and variance of fuzzy numbers, Fuzzy Sets and Systems122, (2001), 315–326.

 

[3] Cheng-Few Lee, Gwo-Hshiung Tzeng, Shin-Yun Wang, A new application of fuzzy set theory to the Black–Scholes option pricing model, Expert Systems with Applications Vol. 29, 2 (2005) 330-342.

 

[4] U. Cherubini, Fuzzy measures and asset prices: Accounting for information ambiguity, Applied Mathematical Finance 4, (1997), 135-149.

 

[5] Konstantinos A. Chrysafis, Basil K. Papadopoulos, On theoretical pricing of options with fuzzy estimators, Journal of Computational and Applied Mathematics 223(2), (2009), 552-566.

 

[6] F. Black, M. Scholes, The pricing of options and corporate liabilities, Journal of Political Economy 81, (1973), 637–659.

 

[7] K.R. French, Stock returns and the weekend effect, Journal of Financial Economics 8, (1980), 55–69.

 

[8] R. Fuller, P. Majlender, On weighted possibilistic mean and variance of fuzzy numbers, Fuzzy Sets and Systems 136, (2003), 363–374.

 

[9] H. Ghaziri, S. Elfakhani, J. Assi, Neural networks approach to pricing options, Neural Network World10, C(2000), 271–277..

 

[10] M.L. Guerra, L. Sorini, L. Stefanini, Option price sensitivities through fuzzy numbers, Computers and Mathematics with Applications 61(3), (2011), 515–526.

 

[11] S. Heilpern, The expected value of a fuzzy number, Fuzzy Sets and Systems 47, (1992), 81–86.

 

[12] S.L. Heston, A closed-form solution for options with stochastic volatility with applications to bond and currency options, Review of financial studies 6(2), (1993), 327–343.

 

[13] M. Jimenez and J.A. Rivas, Fuzzy number approximation, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 6(01), (1998), 69–78.

 

[14] J.D. MacBeth and L.J. Merville, An empirical examination of the Black-Scholes call option pricing model The Journal of Finance 34(5), (1979), 1173–1186.

 

[15] L. Maciel, F. Gomide, and R. Ballini, Evolving fuzzy- GARCH pproach for financial volatility modeling and forecasting, Computational Economics 48(3), (2016), 379–398.

 

[16] Malini, S. SU, Felbin C. Kennedy, An approach for solving fuzzy transportation problem using octagonal fuzzy numbers, Applied Mathematical Sciences 54, (2013), 2661-2673.

 

[17] Maria Letizia Guerra, Laerte Sorini, Luciano Stefanini, Option price sensitivities through fuzzy numbers, Computers and Mathematics with Applications Volume 61, Issue 3, (2011), 515-526.

 

[18] S. Mixon, The implied volatility term structure of stock index options, Journal of Empirical Finance14(3), (2007), 333–354.

 

[19] S. Muzzioli and B. De Baets, Fuzzy approaches to option price modeling, IEEE Transactions on Fuzzy Systems 25(2), (2017), 392–401.

 

[20] H.T. Nguyen, A note on the extension principle for fuzzy sets, Journal of Mathematical Analysis and Applications 64, (1978), 369–380.

 

[21] P. Nowak and M. Romaniuk, A fuzzy approach to option pricing in a Levy process setting, International Journal of Applied Mathematics and Computer Science 23(3), (2013), 613–622.

 

[22] M.R. Simonelli, Fuzziness in valuing financial instruments by certainty equivalents, European Journal of Operational Research, 135, (2001) 296–302.

 

[23] A. Thavanaeswaran, J. Singh, S.S. Appadoo, Option pricing for some volatility models, The Journal of Risk Finance 7 (2006) 425–445.

 

[24] A. Thavaneswaran, S.S. Appadoo, A. Paseka, Weighted possibilistic moments of fuzzy numbers with applications to GARCH modeling and option pricing, Mathematical and Computer Modelling 49 (1–2), (2009), 352–368.

 

 [25] K. Thiagarajah, S.S. Appadoo, A. Thavaneswaran, Option valuation model with adaptive fuzzy numbers, Computers and Mathematics with Applications Vol. 53, 5 (2007), 831–841.

 

[26] K. Thiagarajah, A. Thavanaeswaran, Fuzzy random coefficient volatility models with financial applications, Journal of Risk Finance 7 (2006), 503–524.

 

[27] N.N. Trenev, A refinement of the Black-Scholes formula of pricing options, Cybernetics and Systems Analysis 37, (2001), 911-917.

 

[28] H.C. Wu, Using fuzzy sets theory and Black–Scholes formula to generate pricing boundaries of European options, Applied Mathematics and Computation 185, (2007), 136–146.

 

[29] Y. Yoshida, The valuation of European options in uncertain environment, European Journal of Operational Research 145, (2003), 221–229.

 

[30] Z. Zmeskal, Applications of the fuzzy-stochastic methodology to appraising the firm value as a European call option, European Journal of Operational Research 135, (2001), 303-310.

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Meenakshi, K., S., Pavithra, Sathish, S., N., Prabakaran. "An Empirical Evaluation of the Stock Market Using Fuzzy Variant Black and Scholes Model Involving Central Fuzzy Measures." International Journal of Neutrosophic Science, vol. Volume 27, no. Issue 2, 2026, pp. 287-296. DOI: https://doi.org/10.54216/IJNS.270224
Meenakshi, K., S., P., Sathish, S., N., P. (2026). An Empirical Evaluation of the Stock Market Using Fuzzy Variant Black and Scholes Model Involving Central Fuzzy Measures. International Journal of Neutrosophic Science, Volume 27(Issue 2), 287-296. DOI: https://doi.org/10.54216/IJNS.270224
Meenakshi, K., S., Pavithra, Sathish, S., N., Prabakaran. "An Empirical Evaluation of the Stock Market Using Fuzzy Variant Black and Scholes Model Involving Central Fuzzy Measures." International Journal of Neutrosophic Science Volume 27, no. Issue 2 (2026): 287-296. DOI: https://doi.org/10.54216/IJNS.270224
Meenakshi, K., S., P., Sathish, S., N., P. (2026) 'An Empirical Evaluation of the Stock Market Using Fuzzy Variant Black and Scholes Model Involving Central Fuzzy Measures', International Journal of Neutrosophic Science, Volume 27(Issue 2), pp. 287-296. DOI: https://doi.org/10.54216/IJNS.270224
Meenakshi K, S. P, Sathish S, N. P. An Empirical Evaluation of the Stock Market Using Fuzzy Variant Black and Scholes Model Involving Central Fuzzy Measures. International Journal of Neutrosophic Science. 2026;Volume 27(Issue 2):287-296. DOI: https://doi.org/10.54216/IJNS.270224
K. Meenakshi, P. S., S. Sathish, P. N., "An Empirical Evaluation of the Stock Market Using Fuzzy Variant Black and Scholes Model Involving Central Fuzzy Measures," International Journal of Neutrosophic Science, vol. Volume 27, no. Issue 2, pp. 287-296, 2026. DOI: https://doi.org/10.54216/IJNS.270224
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