Abstract
In this paper, we consider two new stock models in which their differential equations are modeled by Liu process in uncertain environment. Firstly, we study the uncertain Schöbel–Zhu–Hull–White hybrid model and obtain its closed European call option pricing using Liu calculus. Also, we solve this model by Monte Carlo simulation to ensure the performance of Monte Carlo method. Our main purpose is to present a new model, uncertain Heston–CIR hybrid model, in which its uncertain differential equations cannot be solved and so we can calculate the option value via Monte Carlo simulation. Finally, some examples are stated for illustrating these models to obtain successful results and show the efficiency of Monte Carlo method.
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Black F, Scholes M (1973) The pricing of options and corporate liabilities. J Polit Econ 81:637–654
Chen X (2011) American option pricing formula for uncertain financial market. Int J Oper Res 8:27–32
Chen X, Liu B (2010) Existence and uniqueness theorem for uncertain differential equations. Fuzzy Optim Decis Mak 9:69–81
Chen X, Liu Y, Ralescu DA (2013) Uncertain stock model with periodic dividends. Fuzzy Optim Decis Mak 12:111–123
Christoffersen P, Heston S, Jacobs K (2009) The shape and term structure of the index option smirk: why multifactor stochastic volatility models work so well. Manag Sci 55:1914–1932
Fan Y, Zhang H (2014) The pricing of Asian options in uncertain volatility model. Math Probl Eng 2014:1–19
Francesco M, Foschi P, Pascucci A (2006) Analysis of an uncertain volatility model. J Appl Math Decis Sci 2006:1–17
Grzelak L, Oosterlee C (2011) On the Heston model with stochastic interest rate. SIAM J Financ Math 2:255–286
Haastrecht A, Lord R, Pelsser A, Schrager D (2009) Pricing long-maturity equity and FX derivatives with stochastic interest rates and stochastic volatility. Insur Math Econ 45:1–28
Heston S (1993) A closed-form solution for options with stochastic volatility with applications to bond and currency options. Rev Financ Stud 6:327–343
Hull J, White A (1990) Pricing interest-rate derivative securities. Rev Financ Stud 3:573–592
Hull J, White A (1993) One factor interest rate models and the valuation of interest rate derivative securities. J Financ Quant Anal 28(235):254
Liu B (2007) Uncertainty theory, 2nd edn. Springer, Berlin
Liu B (2008) Fuzzy process, hybrid process and uncertain process. J Uncertain Syst 2:3–16
Liu B (2009) Some research problems in uncertainty theory. J Uncertain Syst 3:3–10
Liu B (2010) Uncertainty theory: a branch of mathematics for modeling human uncertainty. Springer, Berlin
Liu Y, Ha M (2010) Expected value of function of uncertain variables. J Uncertain Syst 4:181–186
Peng J, Yao K (2010) A new option pricing model for stocks in uncertainty markets. Int J Oper Res 7:213–224
Schobel R, Zhu J (1999) Stochastic volatility with an ornstein uhlenbeck process: an extension. Eur Finance Rev 4:23–46
Stein JC, Stein EM (1991) Stock price distributions with stochastic volatility: an analytic approach. Rev Financ Stud 4:727–752
Vasicek OA (1977) An equilibrium characterization of the term structure. J Financ Econ 5:177–188
Yang X, Shen S (2015) Runge–Kutta method for solving uncertain differential equations. J Uncertain Anal Appl 3:1–12
Yao K, Chen X (2013) A numerical method for solving uncertain differential equations. J Intell Fuzzy Syst 25:825–832
Zhang K, Wang S (2009) A computational scheme for uncertain volatility model in option pricing. Appl Numer Math 59:1754–1767
Zhou Q, Li X (2019) Vulnerable options pricing under uncertain volatility model. J Inequal Appl 315:1–16
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Fathi-Vajargah, B., Mirzazadeh, M. & Ghasemalipour, S. An efficient Monte Carlo simulation for new uncertain Heston–CIR hybrid model. Soft Comput 25, 8539–8547 (2021). https://doi.org/10.1007/s00500-021-05702-8
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DOI: https://doi.org/10.1007/s00500-021-05702-8