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A SEMI-ANALYTICAL PRICING FORMULA FOR EUROPEAN OPTIONS UNDER THE ROUGH HESTON-CIR MODEL

Published online by Cambridge University Press:  06 March 2020

XIN-JIANG HE
Affiliation:
School of Mathematics and Applied Statistics, University of Wollongong, NSW 2522, Australia email xinjiang@uow.edu.au
SHA LIN*
Affiliation:
School of Finance, Zhejiang Gongshang University, Hangzhou, Zhejiang Province, China email linsha@mail.zjgsu.edu.cn
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Abstract

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We combine the rough Heston model and the CIR (Cox–Ingersoll–Ross) interest rate together to form a rough Heston-CIR model, so that both the rough behaviour of the volatility and the stochastic nature of the interest rate can be captured. Despite the convoluted structure and non-Markovian property of this model, it still admits a semi-analytical pricing formula for European options, the implementation of which involves solving a fractional Riccati equation. The rough Heston-CIR model is more general, taking both the rough Heston model and the Heston-CIR model as special cases. The influence of rough volatility and stochastic interest rate is shown to be significant through numerical experiments.

Type
Research Article
Copyright
© 2020 Australian Mathematical Society

References

Abi Jaber, E., Larsson, M. and Pulido, S., “Affine Volterra processes”, Ann. Appl. Probab. 29 (2019) 31553200; doi:10.1214/19-AAP1477.CrossRefGoogle Scholar
Abudy, M. and Izhakian, Y., “Pricing stock options with stochastic interest rate”, NYU working paper 2451/30272; https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1944450.Google Scholar
Alòs, E., Mazet, O. and Nualart, D., “Stochastic calculus with respect to fractional Brownian motion with Hurst parameter less than 1/2”, Stochastic Process. Appl. 86 (2000) 121139; doi:10.1016/S0304-4149(99)00089-7.CrossRefGoogle Scholar
Bakshi, G., Cao, C. and Chen, Z., “Empirical performance of alternative option pricing models”, J. Finance 52 (1997) 20032049; doi:10.1111/j.1540-6261.1997.tb02749.x.CrossRefGoogle Scholar
Bakshi, G., Ju, N. and Ou-Yang, H., “Estimation of continuous-time models with an application to equity volatility dynamics”, J. Financ. Econ. 82 (2006) 227249; doi:10.1016/j.jfineco.2005.09.005.CrossRefGoogle Scholar
Black, F. and Scholes, M., “The pricing of options and corporate liabilities”, J. Polit. Econ. 81 (1973) 637654; doi:10.1086/260062.CrossRefGoogle Scholar
Bracewell, R. N., The Fourier transform and its applications (McGraw-Hill, New York, 1986); ISBN-10: 0070664544.Google Scholar
Brigo, D. and Mercurio, F., Interest rate models – theory and practice: with smile, inflation and credit, 2nd ed. (Springer, Berlin–Heidelberg, 2007); ISBN: 978-3-540-22149-4.Google Scholar
Diethelm, K., Ford, N. J. and Freed, A. D., “A predictor–corrector approach for the numerical solution of fractional differential equations”, Nonlinear Dynam. 29 (2002) 322; doi:10.1023/A:1016592219341.CrossRefGoogle Scholar
Diethelm, K., Ford, N. J. and Freed, A. D., “Detailed error analysis for a fractional Adams method”, Numer. Algorithms 36 (2004) 3152; doi:10.1023/B:NUMA.0000027736.85078.be.CrossRefGoogle Scholar
Dumas, B., Fleming, J. and Whaley, R. E., “Implied volatility functions: empirical tests”, J. Finance 53 (1998) 20592106; doi:10.1111/0022-1082.00083.CrossRefGoogle Scholar
Elliott, R. J. and Lian, G.-H., “Pricing variance and volatility swaps in a stochastic volatility model with regime switching: discrete observations case”, Quant. Finance 13 (2013) 687698; doi:10.1080/14697688.2012.676208.CrossRefGoogle Scholar
Euch, O. E. and Rosenbaum, M., “Perfect hedging in rough Heston models”, Ann. Appl. Probab. 28 (2018) 38133856; doi:10.1214/18-AAP1408.CrossRefGoogle Scholar
Euch, O. E. and Rosenbaum, M., “The characteristic function of rough Heston models”, Math. Finance 29 (2019) 338; doi:10.1111/mafi.12173.CrossRefGoogle Scholar
Fang, F. and Oosterlee, C. W., “A Fourier-based valuation method for Bermudan and barrier options under Heston’s model”, SIAM J. Financial Math. 2 (2011) 439463; doi:10.1137/100794158.CrossRefGoogle Scholar
Forde, M. and Jacquier, A., “Robust approximations for pricing Asian options and volatility swaps under stochastic volatility”, Appl. Math. Finance 17 (2010) 241259; doi:10.1080/13504860903335348.CrossRefGoogle Scholar
Gatheral, J., Jaisson, T. and Rosenbaum, M., “Volatility is rough”, Quant. Finance 18 (2018) 933949; doi:10.1080/14697688.2017.1393551.CrossRefGoogle Scholar
Grzelak, L. A. and Oosterlee, C. W., “On the Heston model with stochastic interest rates”, SIAM J. Financial Math. 2 (2011) 255286; doi:10.1137/090756119.CrossRefGoogle Scholar
Grzelak, L. A., Oosterlee, C. W. and Van Weeren, S., “Extension of stochastic volatility equity models with the Hull–White interest rate process”, Quant. Finance 12 (2012) 89105; doi:10.1080/14697680903170809.CrossRefGoogle Scholar
He, X.-J. and Zhu, S.-P., “An analytical approximation formula for European option pricing under a new stochastic volatility model with regime-switching”, J. Econom. Dynam. Control 71 (2016) 7785; doi:10.1016/j.jedc.2016.08.002.CrossRefGoogle Scholar
He, X.-J. and Zhu, S.-P., “Pricing European options with stochastic volatility under the minimal entropy martingale measure”, European J. Appl. Math. 27 (2016) 233247; doi:10.1017/S0956792515000510.CrossRefGoogle Scholar
He, X.-J. and Zhu, S.-P., “A closed-form pricing formula for European options under the Heston model with stochastic interest rate”, J. Comput. Appl. Math. 335 (2018) 323333; doi:10.1016/j.cam.2017.12.011.CrossRefGoogle Scholar
Heston, S. L., “A closed-form solution for options with stochastic volatility with applications to bond and currency options”, Rev. Financ. Stud. 6 (1993) 327343; doi:10.1093/rfs/6.2.327.CrossRefGoogle Scholar
Hull, J. and White, A., “The pricing of options on assets with stochastic volatilities”, J. Finance 42 (1987) 281300; doi:10.1111/j.1540-6261.1987.tb02568.x.CrossRefGoogle Scholar
Johnson, H., “Option pricing when the variance rate is changing”, working paper, University of California, Los Angeles.Google Scholar
Johnson, H. and Shanno, D., “Option pricing when the variance is changing”, J. Financ. Quant. Anal. 22 (1987) 143151; doi:10.2307/2330709.CrossRefGoogle Scholar
Moral, P. D., “Feynman–Kac formulae”, in: Feynman–Kac formulae: genealogical and interacting particle systems with applications, probability and its applications, A Series of the Applied Probability Trust (Springer, New York, 2004); doi:10.1007/978-1-4684-9393-1_2.CrossRefGoogle Scholar
Rindell, K., “Pricing of index options when interest rates are stochastic: an empirical test”, J. Bank. Finance 19 (1995) 785802; doi:10.1016/0378-4266(94)00087-J.CrossRefGoogle Scholar
Scott, L. O., “Option pricing when the variance changes randomly: theory, estimation, and an application”, J. Financ. Quant. Anal. 22 (1987) 419438; doi:10.2307/2330793.CrossRefGoogle Scholar
Stein, E. M. and Stein, J. C., “Stock price distributions with stochastic volatility: an analytic approach”, Rev. Financ. Stud. 4 (1991) 727752; doi:10.1093/rfs/4.4.727.CrossRefGoogle Scholar
Vellekoop, M. and Nieuwenhuis, H., “A tree-based method to price American options in the Heston model”, J. Comput. Finance 13 (2009) 121; doi:10.21314/JCF.2009.197.CrossRefGoogle Scholar
Wiggins, J. B., “Option values under stochastic volatility: theory and empirical estimates”, J. Financ. Econ. 19 (1987) 351372; doi:10.1016/0304-405X(87)90009-2.CrossRefGoogle Scholar