Beyond Black-Scholes: Evidence of Systematic Mispricing in the Indian Options Market and the Case for a Behavioral Pricing Model

Authors

  • Isha Tewari Author
  • L. K. Singh Professor, Department of Management Studies, Bhimtal, Kumaun University, Nainital, Uttarakhand, India Author

DOI:

https://doi.org/10.66635/9xbvc809

Keywords:

Black-Scholes model, Option mispricing, Moneyness, Probability weighting, Indian derivatives market

Abstract

This study examines whether Black-Scholes option prices deviate systematically from observed market prices in the Indian equity derivatives market, and whether the pattern of deviation supports a behavioral interpretation. Black-Scholes theoretical prices were computed for 69,372 call-option observations across 47 Nifty-50 constituent stocks between January 2023 and December 2024. Pricing errors were tested company-wise and in aggregate using paired-sample and one-sample t-tests, and compared across moneyness categories using the Friedman test with Kendall’s coefficient of concordance. Because pricing errors are strongly serially correlated, all inference is reported both naively and with Newey-West HAC standard errors, cluster-level aggregation and false discovery rate control, with effect sizes accompanying every test. Black-Scholes prices differ significantly from market prices, with a median absolute error of 18.9 percent of premium, although the effect size is small. The direction of deviation is not stable: market prices were below the model prices in 2023 and above them in 2024, and the sign tracks the annual volatility input rather than investor behavior, so no behavioral reading of the direction is defensible. The robust finding concerns magnitude. Using moneyness reconstructed from contemporaneous strike-to-spot ratios, median absolute percentage error is 4.6 percent for in-the-money contracts, 21.5 percent for at-the-money contracts and 70.1 percent for out-of-the-money contracts. Every one of the 47 companies displays this ordering, and it holds within each year of the sample separately. Relative mispricing therefore concentrates in the segment whose value depends entirely on small-probability outcomes, which points toward probability weighting rather than loss aversion as the mechanism most likely to carry explanatory power in this market. The study further documents that where volatility is estimated annually rather than implied from contract prices, the direction of measured mispricing follows that input, a result bearing on how existing Indian evidence on the sign of Black-Scholes error should be interpreted.

 

References

1.Abbink, K., & Rockenbach, B. (2006). Option pricing by students and professional traders: A behavioural investigation. Managerial and Decision Economics, 27(6), 497–510.

2.Baele, L., Driessen, J., Ebert, S., Londono, J. M., & Spalt, O. G. (2019). Cumulative prospect theory, option returns, and the variance premium. The Review of Financial Studies, 32(9), 3667–3723.

3.Barberis, N., Huang, M., & Santos, T. (2001). Prospect theory and asset prices. Quarterly Journal of Economics, 116(1), 1–53. https://doi.org/10.1162/003355301556310

4.Bates, D. S. (1996). Jumps and stochastic volatility: Exchange rate processes implicit in Deutsche Mark options. The Review of Financial Studies, 9(1), 69–107. https://doi.org/10.1093/rfs/9.1.69

5.Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B, 57(1), 289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x

6.Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81(3), 637–654. https://doi.org/10.1086/260062

7.Breuer, W., & Perst, A. (2005). Retail banking and behavioral financial engineering (Working Paper Bfw39V5/04). RWTH Aachen.

8.Chauhan, A., & Gor, R. (2021). Comparison of three option pricing models for Indian options market. International Journal of Engineering Science Technologies, 5(4), 54–64.

9.Coelho, F. R., & Reddy, Y. V. (2017). Applicability of Black-Scholes and Black’s option pricing models in Indian derivatives market. IUP Journal of Financial Risk Management, 14(2).

10.Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.

11.Corrado, C. J., & Su, T. (1996). Skewness and kurtosis in S&P 500 index returns implied by option prices. Journal of Financial Research, 19(2), 175–192. https://doi.org/10.1111/j.1475-6803.1996.tb00592.x

12.Dumas, B., Fleming, J., & Whaley, R. E. (1998). Implied volatility functions: Empirical tests. The Journal of Finance, 53(6), 2059–2106. https://doi.org/10.1111/0022-1082.00083

13.Friedman, M. (1937). The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American Statistical Association, 32(200), 675–701. https://doi.org/10.1080/01621459.1937.10503522

14.Heston, S. L. (1993). A closed-form solution for options with stochastic volatility with applications to bond and currency options. The Review of Financial Studies, 6(2), 327–343. https://doi.org/10.1093/rfs/6.2.327

15.Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 6(2), 65–70.

16.Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291. https://doi.org/10.2307/1914185

17.Kendall, M. G., & Babington Smith, B. (1939). The problem of m rankings. The Annals of Mathematical Statistics, 10(3), 275–287. https://doi.org/10.1214/aoms/1177732186

18.MathWorks. (2023). MATLAB (Version R2023a) [Computer software]. The MathWorks Inc. https://www.mathworks.com

19.Mayhew, S. (1995). Implied volatility. Financial Analysts Journal, 51(4), 8–20. https://doi.org/10.2469/faj.v51.n4.1916

20.Merton, R. C. (1973). Theory of rational option pricing. Bell Journal of Economics and Management Science, 4(1), 141–183. https://doi.org/10.2307/3003143

21.Mitra, S. K. (2008). Valuation of Nifty options using Black's option pricing formula. ICFAI Journal of Derivatives Markets, 5(1).

22.Nardon, M., & Pianca, P. (2019). European option pricing under cumulative prospect theory with constant relative sensitivity probability weighting functions. Computational Management Science, 16(1), 249–274.

23.Newey, W. K., & West, K. D. (1987). A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55(3), 703–708. https://doi.org/10.2307/1913610

24.Omberg, E. (1991). On the theory of perfect hedging. Advances in Futures and Options Research, 5, 1–29.

25.Securities and Exchange Board of India. (2023, January 25). Analysis of profit and loss of individual traders dealing in equity F&O segment [Study]. https://www.sebi.gov.in/sebi_data/attachdocs/jan-2023/1674645296493.pdf

26.Securities and Exchange Board of India. (2024a, September 23). Updated SEBI study reveals 93% of individual traders incurred losses in equity F&O between FY22 and FY24 [Press release]. https://www.sebi.gov.in/media-and-notifications/press-releases/sep-2024/updated-sebi-study-reveals-93-of-individual-traders-incurred-losses-in-equity-fando-between-fy22-and-fy24-aggregate-losses-exceed-1-8-lakh-crores-over-three-years_86906.html

27.Securities and Exchange Board of India. (2024b, October 1). Measures to strengthen equity index derivatives framework for increased investor protection and market stability [Circular]. https://www.sebi.gov.in/legal/circulars/oct-2024/measures-to-strengthen-equity-index-derivatives-framework-for-increased-investor-protection-and-market-stability_87208.html

28.Securities and Exchange Board of India. (2025, July 7). Study on profitability of individual traders in the equity derivatives segment, FY25 [Report].

29.Securities and Exchange Board of India. (2026a, August 20). Study: Profitability of individual traders in the equity derivatives segment (FY25–FY26). Department of Economic and Policy Analysis. https://www.sebi.gov.in/reports-and-statistics/research/aug-2026/study-profitability-of-individual-traders-in-the-equity-derivatives-segment-fy25-fy26-_103835.html

30.Securities and Exchange Board of India. (2026b, August). Trading behaviour of individual traders in the equity derivatives segment: A study of trading strategies, capital employed, persistence and behavioural patterns among individual traders in EDS (FY25–FY26). Department of Economic and Policy Analysis. https://www.sebi.gov.in/reports-and-statistics/research/aug-2026/study-trading-behaviour-of-individual-traders-in-the-equity-derivatives-segment-fy25-fy26-_103836.html

31.Shefrin, H., & Statman, M. (1993). Behavioral aspects of the design and marketing of financial products. Financial Management, 22(2), 123–134. https://doi.org/10.2307/3665864

32.Siddiqi, H. (2015). Anchoring heuristic in option pricing (MPRA Paper No. 63218). Munich Personal RePEc Archive, University Library of Munich.

33.Siddiqi, H. (2019). Anchoring-adjusted option pricing models. Journal of Behavioral Finance, 20(2), 139–153. https://doi.org/10.1080/15427560.2018.1492922

34.Singh, V. K. (2013). Empirical performance of option pricing models: Evidence from India. International Journal of Economics and Finance, 5(2), 141–149. https://doi.org/10.5539/ijef.v5n2p141

35.Singh, V. K., & Kumar, P. (2024). Effectiveness of deterministic option pricing models: New evidence from Nifty and Bank Nifty index options. Journal of Asset Management, 25(2), 172–189. https://doi.org/10.1057/s41260-024-00348-1

36.Srivastava, A., & Shastri, M. (2018). A study of relevance of Black-Scholes model on option prices of Indian stock market. International Journal of Governance and Financial Intermediation, 1(1), 82–104.

37.Swapna, H. R., & Reddy, M. V. (2020). Pricing of options in Indian derivative market: An empirical analysis. International Journal of Control and Automation, 13(2s), 36–50.

38.Sun, Y., & Peng, W. (2024). Behavioral option pricing under prospect theory framework and Heston model. Journal of Guangdong University of Technology, 41(1), 127–134. https://doi.org/10.12052/gdutxb.220185

39.Thaler, R. (1980). Toward a positive theory of consumer choice. Journal of Economic Behavior & Organization, 1(1), 39–60. https://doi.org/10.1016/0167-2681(80)90051-7

40.Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5(4), 297–323. https://doi.org/10.1007/BF00122574

41.Varma, J. R. (2002). Mispricing of volatility in the Indian index options market (Working Paper No. 2002-04-01). Indian Institute of Management Ahmedabad.

42.Wolff, C., Lehnert, T., & Versluis, C. (2009). A cumulative prospect theory approach to option pricing (Working Paper No. 09-03). Luxembourg School of Finance, University of Luxembourg.

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Published

2026-09-21

How to Cite

Beyond Black-Scholes: Evidence of Systematic Mispricing in the Indian Options Market and the Case for a Behavioral Pricing Model. (2026). Journal of Asia Entrepreneurship and Sustainability, 22(9), 17-30. https://doi.org/10.66635/9xbvc809