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Pricing of financial derivatives based on the Tsallis statistical theory

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  • Zhao, Pan
  • Pan, Jian
  • Yue, Qin
  • Zhang, Jinbo

Abstract

Asset return distributions usually have peaks, fat tails and skewed tails, because of the impact of extreme events outside financial markets. The Tsallis distribution has the peak and fat-tail characteristic, and the asymmetric jump process can fit the skewed tail of returns. Therefore, to accurately describe asset returns, we propose a price model by the use of the Tsallis distribution and a Poisson jump process, which can characterize the long-term memory and the skewness of asset returns. Moreover, using the stochastic differential theory and the martingale method, we obtain an explicit solution for pricing European options.

Suggested Citation

  • Zhao, Pan & Pan, Jian & Yue, Qin & Zhang, Jinbo, 2021. "Pricing of financial derivatives based on the Tsallis statistical theory," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
  • Handle: RePEc:eee:chsofr:v:142:y:2021:i:c:s0960077920308559
    DOI: 10.1016/j.chaos.2020.110463
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    1. S. G. Kou, 2002. "A Jump-Diffusion Model for Option Pricing," Management Science, INFORMS, vol. 48(8), pages 1086-1101, August.
    2. Ning Cai & S. G. Kou, 2011. "Option Pricing Under a Mixed-Exponential Jump Diffusion Model," Management Science, INFORMS, vol. 57(11), pages 2067-2081, November.
    3. Bryan Kelly & Hao Jiang, 2014. "Editor's Choice Tail Risk and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 27(10), pages 2841-2871.
    4. Chen, Joseph & Hong, Harrison & Stein, Jeremy C., 2001. "Forecasting crashes: trading volume, past returns, and conditional skewness in stock prices," Journal of Financial Economics, Elsevier, vol. 61(3), pages 345-381, September.
    5. Kaizoji, Taisei, 2006. "An interacting-agent model of financial markets from the viewpoint of nonextensive statistical mechanics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 109-113.
    6. Charan Raj Chimrani & Farhan Ahmed & Vinesh Kumar Panjwani, 2018. "Modeling Sectoral Stock Indexes Volatility: Empirical Evidence from Pakistan Stock Exchange," International Journal of Economics and Financial Issues, Econjournals, vol. 8(2), pages 319-324.
    7. Harvey, Campbell R. & Siddique, Akhtar, 1999. "Autoregressive Conditional Skewness," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(4), pages 465-487, December.
    8. Philippe Jorion, 1988. "On Jump Processes in the Foreign Exchange and Stock Markets," The Review of Financial Studies, Society for Financial Studies, vol. 1(4), pages 427-445.
    9. Christian Conrad & Karin Loch, 2015. "Anticipating Long‐Term Stock Market Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1090-1114, November.
    10. R. F. Engle & A. J. Patton, 2001. "What good is a volatility model?," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 237-245.
    11. Constantino Tsallis & Celia Anteneodo & Lisa Borland & Roberto Osorio, 2003. "Nonextensive statistical mechanics and economics," Papers cond-mat/0301307, arXiv.org.
    12. Kleinert, H. & Korbel, J., 2016. "Option pricing beyond Black–Scholes based on double-fractional diffusion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 200-214.
    13. Lisa Borland, 2002. "A theory of non-Gaussian option pricing," Quantitative Finance, Taylor & Francis Journals, vol. 2(6), pages 415-431.
    14. R. David Mclean & Jeffrey Pontiff, 2016. "Does Academic Research Destroy Stock Return Predictability?," Journal of Finance, American Finance Association, vol. 71(1), pages 5-32, February.
    15. Ma, Chao & Ma, Qinghua & Yao, Haixiang & Hou, Tiancheng, 2018. "An accurate European option pricing model under Fractional Stable Process based on Feynman Path Integral," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 87-117.
    16. Borland, Lisa, 2016. "Exploring the dynamics of financial markets: from stock prices to strategy returns," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 59-74.
    17. Kozaki, M. & Sato, A.-H., 2008. "Application of the Beck model to stock markets: Value-at-Risk and portfolio risk assessment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(5), pages 1225-1246.
    18. Lisa Borland, 2002. "A Theory of Non_Gaussian Option Pricing," Papers cond-mat/0205078, arXiv.org, revised Dec 2002.
    19. M. Beben & A. Orłowski, 2001. "Correlations in financial time series: established versus emerging markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 20(4), pages 527-530, April.
    20. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    21. Prakasa Rao, B.L.S., 2016. "Pricing geometric Asian power options under mixed fractional Brownian motion environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 446(C), pages 92-99.
    22. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    23. Michel Vellekoop & Hans Nieuwenhuis, 2007. "On option pricing models in the presence of heavy tails," Quantitative Finance, Taylor & Francis Journals, vol. 7(5), pages 563-573.
    24. Rak, R. & Drożdż, S. & Kwapień, J., 2007. "Nonextensive statistical features of the Polish stock market fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(1), pages 315-324.
    25. Karipova, Gulnur & Magdziarz, Marcin, 2017. "Pricing of basket options in subdiffusive fractional Black–Scholes model," Chaos, Solitons & Fractals, Elsevier, vol. 102(C), pages 245-253.
    26. S. M.D. Queirós & L. G. Moyano & J. de Souza & C. Tsallis, 2007. "A nonextensive approach to the dynamics of financial observables," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 55(2), pages 161-167, January.
    27. Conrad, Christian & Loch, Karin & Rittler, Daniel, 2014. "On the macroeconomic determinants of long-term volatilities and correlations in U.S. stock and crude oil markets," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 26-40.
    28. Tsallis, Constantino & Anteneodo, Celia & Borland, Lisa & Osorio, Roberto, 2003. "Nonextensive statistical mechanics and economics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 89-100.
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    Cited by:

    1. Tsallis, Constantino & Borges, Ernesto P., 2021. "Comment on “Pricing of financial derivatives based on the Tsallis statistical theory” by Zhao, Pan, Yue and Zhang," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    2. A. Gómez-Águila & J. E. Trinidad-Segovia & M. A. Sánchez-Granero, 2022. "Improvement in Hurst exponent estimation and its application to financial markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.

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