时间分数阶 CIR 模型下回望期权的定价问题
Pricing of Lookback Options under the Time-Fractional CIR Model
DOI: 10.12677/FIN.2024.144159, PDF, 下载: 10  浏览: 16  国家自然科学基金支持
作者: 杜云康, 许作良*:中国人民大学数学学院,北京
关键词: CIR 模型时间分数阶期权定价数值方法CIR Model Time-Fractional Option Pricing Numerical Methods
摘要: 本文主要研究了时间分数阶 CIR (Cox-Ingersoll-Ross) 模型下回望期权的定价问题。传统的 CIR 模型由于其对长期记忆效应的忽视,已无法充分描述金融市场中的一些复杂现象。因此,本 文引入了时间分数阶导数,以捕捉金融市场中更为复杂的动态特性。在研究过程中,本文首先利 用 It^o 引理和 ∆-对冲原理对时间分数阶 CIR 模型进行了数学推导,建立了回望期权定价的理论 框架。然后,本文在时间方向与空间方向上使用了有限差分方法对定价公式进行了数值离散处理。 最后,本文进行了数值实验,数值实验的结果验证了所提出方法的有效性。
Abstract: This paper primarily studies the pricing problem of lookback options under the time-fractional CIR (Cox-Ingersoll-Ross) model. The traditional CIR model, due to its neglect of long-term memory effects, can no longer fully describe some complex phenomena in financial markets. Therefore, this paper introduces the time-fractional derivative to capture more complex dynamic characteristics in financial markets. In the research process, this paper first uses Ito’s lemma and the Delta-hedging principle to mathematically derive the time-fractional CIR model, establishing the theoretical framework for lookback option pricing. Then, the paper uses the finite difference method in both the time and space directions to numerically discretize the pricing formula. Finally, numerical experiments are conducted, and the results of these ex- periments validate the effectiveness of the proposed method.
文章引用:杜云康, 许作良. 时间分数阶 CIR 模型下回望期权的定价问题[J]. 金融, 2024, 14(4): 1539-1551. https://doi.org/10.12677/FIN.2024.144159

参考文献

[1] Bachelier, L. (1900) Théorie de la spéculation. Annales Scientifiques de l’École Normale Supé rieure, 17, 21-86.
https://doi.org/10.24033/asens.476
[2] Samuelson, P.A. (2015) Rational Theory of Warrant Pricing. In: Grünbaum, F., van Moer- beke, P. and Moll, V., Eds., Henry P. McKean Jr. Selecta. Contemporary Mathematicians, Birkhäuser, 195-232.
https://doi.org/10.1007/978-3-319-22237-0_11
[3] Black, F. and Scholes, M. (1973) The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81, 637-654.
https://doi.org/10.1086/260062
[4] d’Halluin, Y., Forsyth, P.A. and Labahn, G. (2004) A Penalty Method for American Options with Jump Diffusion Processes. Numerische Mathematik, 97, 321-352.
https://doi.org/10.1007/s00211-003-0511-8
[5] Khabir, M.H.M. and Patidar, K.C. (2012) Spline Approximation Method to Solve an Option Pricing Problem. Journal of Difference Equations and Applications, 18, 1801-1816.
https://doi.org/10.1080/10236198.2011.596150
[6] Cox, J.C., Ingersoll, J.E. and Ross, S.A. (2005) A Theory of the Term Structure of Interest Rates. In: Bhattacharya, S. and Constantinides, G.M., Eds., Theory of Valuation, World Scientific, 129-164.
https://doi.org/10.1142/9789812701022_0005
[7] Vasicek, O. (1977) An Equilibrium Characterization of the Term Structure. Journal of Finan- cial Economics, 5, 177-188.
https://doi.org/10.1016/0304-405x(77)90016-2
[8] Cox, J.C. (1996) The Constant Elasticity of Variance Option Pricing Model. The Journal of Portfolio Management, 23, 15-17.
https://doi.org/10.3905/jpm.1996.015
[9] Park, J.J., Jang, H.J. and Jang, J. (2020) Pricing Arithmetic Asian Options under Jump Diffusion CIR Processes. Finance Research Letters, 34, Article 101269.
https://doi.org/10.1016/j.frl.2019.08.017
[10] Carr, P., Itkin, A. and Muravey, D. (2020) Semi-Closed Form Prices of Barrier Options in the Time-Dependent CEV and CIR Models. The Journal of Derivatives, 28, 26-50.
https://doi.org/10.3905/jod.2020.1.113
[11] Lv, G., Xu, P. and Zhang, Y. (2023) Pricing of Vulnerable Options Based on an Uncertain CIR Interest Rate Model. AIMS Mathematics, 8, 11113-11130.
https://doi.org/10.3934/math.2023563
[12] Goldman, M.B., Sosin, H.B. and Gatto, M.A. (1979) Path Dependent Options: “Buy at the Low, Sell at the High”. The Journal of Finance, 34, 1111-1127.
https://doi.org/10.1111/j.1540-6261.1979.tb00059.x
[13] 姜礼尚. 期权定价的数学模型和方法 [M]. 北京: 高等教育出版社, 2003.
[14] 袁国军, 杜雪樵. 跳 -扩散模型中回望期权的定价研究 [J]. 合肥工业大学学报 (自然科学版), 2006, 29(10): 1302-1305.
[15] 张艳秋, 杜雪樵. 随机利率下的回望期权的定价 [J]. 合肥工业大学学报 (自然科学版), 2007, 30(4): 515-517.
[16] 冯德育. 分数布朗运动条件下回望期权的定价研究 [J]. 北方工业大学学报, 2009, 21(1): 67-72.
[17] 黄东南, 周圣武. 基于跳扩散过程的回望期权定价的数值算法 [J]. 大学数学, 2019, 35(1): 14-19.
[18] 顾哲煜. 混合双分数布朗运动模型下回望期权定价 [J]. 淮海工学院学报 (自然科学版), 2019,28(1): 8-13.
[19] Cao, J. and Li, C. (2013) Finite Difference Scheme for the Time-Space Fractional Diffusion Equations. Open Physics, 11, 1440-1456.
https://doi.org/10.2478/s11534-013-0261-x
[20] Li, C., Chen, A. and Ye, J. (2011) Numerical Approaches to Fractional Calculus and Fractional Ordinary Differential Equation. Journal of Computational Physics, 230, 3352-3368.
https://doi.org/10.1016/j.jcp.2011.01.030
[21] Gao, G., Sun, Z. and Zhang, H. (2014) A New Fractional Numerical Differentiation Formula to Approximate the Caputo Fractional Derivative and Its Applications. Journal of Computational Physics, 259, 33-50.
https://doi.org/10.1016/j.jcp.2013.11.017
[22] Alikhanov, A.A. (2015) A New Difference Scheme for the Time Fractional Diffusion Equation. Journal of Computational Physics, 280, 424-438.
https://doi.org/10.1016/j.jcp.2014.09.031
[23] Cao, J.Y., Xu, C.J. and Wang, Z.Q. (2014) A High Order Finite Difference/Spectral Approximations to the Time Fractional Diffusion Equations. Advanced Materials Research, 875,781-785.
https://doi.org/10.4028/www.scientific.net/amr.875-877.781
[24] Cao, J., Li, C. and Chen, Y. (2015) High-Order Approximation to Caputo Derivatives and Caputo-Type Advection-Diffusion Equations (II). Fractional Calculus and Applied Analysis, 18, 735-761.
https://doi.org/10.1515/fca-2015-0045
[25] Mokhtari, R. and Mostajeran, F. (2019) A High Order Formula to Approximate the Caputo Fractional Derivative. Communications on Applied Mathematics and Computation, 2, 1-29.
https://doi.org/10.1007/s42967-019-00023-y
[26] Wyss, W. (2000) The Fractional Black-Scholes Equation. Fractional Calculus and Applied Analysis, 3, 51-61.
[27] Jumarie, G. (2008) Stock Exchange Fractional Dynamics Defined as Fractional Exponential Growth Driven by (Usual) Gaussian White Noise. Application to Fractional Black-Scholes Equations. Insurance: Mathematics and Economics, 42, 271-287.
https://doi.org/10.1016/j.insmatheco.2007.03.001
[28] Zhang, H., Liu, F., Turner, I. and Yang, Q. (2016) Numerical Solution of the Time Fractional Black-Scholes Model Governing European Options. Computers & Mathematics with Applica- tions, 71, 1772-1783.
https://doi.org/10.1016/j.camwa.2016.02.007
[29] Nourian, F., Lakestani, M., Sabermahani, S. and Ordokhani, Y. (2022) Touchard Wavelet Technique for Solving Time-Fractional Black-Scholes Model. Computational and Applied Math- ematics, 41, Article No. 150.
https://doi.org/10.1007/s40314-022-01853-y
[30] Taghipour, M. and Aminikhah, H. (2022) A Spectral Collocation Method Based on Fraction- al Pell Functions for Solving Time-Fractional Black-Scholes Option Pricing Model. Chaos, Solitons & Fractals, 163, Article 112571.
https://doi.org/10.1016/j.chaos.2022.112571