New optimal adaptive stepsize algorithm for solving black-scholes equation

Document Type : Research Paper

Authors

Department of Mathematics and Computer Science, Lorestan University, Khorramabad, Lorestan 44316-68151, Iran.

Abstract

In this paper, a new algorithm is designed based on a state feedback global error control system, Laplace trans form, order reduction method, and k-step numerical integration methods to numerically solve the Black-Scholes equation. For this purpose, the Black-Scholes equation is converted into a first-order system of ordinary differ ential equations by using the Laplace transform and order reduction method. Also, a new robust linear optimal adaptive global error control dynamic for designing an adaptive time variant step size sequence is modeled and a corresponding optimal control law based on robust and optimal eigenvalue assignment is designed. The proposed optimal control law guarantees the absolute stability of the implemented k-step numerical integrator methods.  Finally, the transformed approximate solution of the Black-Scholes equation has been obtained using the Stefhest inverse Laplace transformation algorithm. The simulation examples show that the optimal control of global error under a given tolerance level, the guarantee of absolute stability, and the best approximation of sensitivity analysis indexes for the proposed approximate solution of the Black-Scholes equation is among the important advantages of the proposed method.

Keywords

Main Subjects


  • [1] F. B. Agusto, Optimal isolation control strategies and cost-effectiveness analysis of a two-strain avian influenza model, Biosystems, 113(3) (2013), 155–164.
  • [2] A. Ayalew, Y. Molla, T. Tilahun, and T. Tesfa, Mathematical Model and Analysis on the Impacts of Vaccination and Treatment in the Control of the COVID-19 Pandemic with Optimal Control, Journal of Applied Mathematics, 2023 (2023).
  • [3] Y. Bai, L. Yao, T. Wei, F. Tian, D. Y. Jin, L. Chen, and M. Wang, Presumed asymptomatic carrier transmission of COVID-19, JAMA, 323(14) (2020), 1406-1407.
  • [4] A. Babaei, H. Jafari, S. Banihashemi, and M. Ahmadi, Mathematical analysis of a stochastic model for the spread of Coronavirus, Chaos, Solitons & Fractals, 145 (2021), 110788.
  • [5] G. Birkhoff and G. C. Rota, Ordinary Differential Equations, Blaisdell Pub. Co., Waltham, Mass, (1969).
  • [6] S. Biswas, A. Subramanian, I. M. ELMojtaba, J. Chattopadhyay, and R. R. Sarkar, Optimal combinations of control strategies and cost-effective analysis for visceral leishmaniasis disease transmission, PLoS One, 12(2) (2017), e0172465.
  • [7] S. P. Brand, R. Aziza, I. K. Kombe, C. N. Agoti, J. Hilton, K. S. Rock, and E. W. Barasa, Forecasting the scale of the COVID-19 epidemic in Kenya, MedRxiv, 2020(04) (2020).
  • [8] K. M. Bubar, K. Reinholt, S. M. Kissler, M. Lipsitch, S. Cobey, Y. H. Grad, and D. B. Larremore, Model-informed COVID-19 vaccine prioritization strategies by age and serostatus, Science, 391(6352) (2021), 916-921.
  • [9] B. Buonomo, D. Lacitignola, and C. Vargas-De-Le´on, Qualitative analysis and optimal control of an epidemic model with vaccination and treatment, Mathematics and Computers in Simulation, 100 (2014), 88-102.
  • [10] C. Connelly, Epidemiology Through the Lens of Differential Equations, (2023).
  • [11] K. Dehingia, A. A. Mohsen, S. A. Alharbi, R. D. Alsemiry, and S. Rezapour, Dynamical behavior of a fractional order model for within-host SARS-CoV-2, Mathematics, 10(13) (2022), 2344.
  • [12] C. T. Deressa, Y. O. Mussa, and G. F. Duressa, Optimal control and sensitivity analysis for transmission dynamics of Coronavirus, Results in Physics, 19 (2020), 103942.
  • [13] M. L. Diagne, H. Rwezaura, S. Y. Tchoumi, and J. M. Tchuenche, A mathematical model of COVID-19 with vaccination and treatment, Computational and Mathematical Methods in Medicine, 2021 (2021).
  • [14] O. Diekmann, J. A. P. Heesterbeek, and J. A. J. Metz, On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations, Journal of Mathematical Biology, 28 (1990), 395-392.
  • [15] K. Dietz, The estimation of the basic reproduction number for infectious diseases, Statistical Methods in Medical Research, 2 (1993), 23–41.
  • [16] K. D. Elgert, Immunology: understanding the immune system, John Wiley & Sons, (2009).
  • [17] L. X. Feng, S. L. Jing, S. K. Hu, D. F. Wang, and H. F. Huo, Modelling the effects of media coverage and quarantine on the COVID-19 infections in the UK, Math. Biosci. Eng., 17(4) (2020), 3918-3939.
  • [18] M. Fudolig and R. Howard, The local stability of a modified multi-strain SIR model for emerging viral strains, PLoS One, 15(12) (2020), e0243408.
  • [19] Y. Gu, S. Ullah, M. A. Khan, M. Y. Alshahrani, M. Abohassan, and M. B. Riaz, Mathematical modeling and stability analysis of COVID-19 with quarantine and isolation, Results in Physics, 34 (2022), 105284.
  • [20] S. D. Gupta, R. Jain, and S. Bhatnagar, COVID-19 pandemic in Rajasthan: Mathematical modelling and social distancing, Journal of Health Management, 22(2) (2020), 129-139.
  • [21] E. Hansen and T. Day, Optimal control of epidemics with limited resources, Journal of Mathematical Biology, 62 (2011), 423-451.
  • [22] D. La Torre, D. Liuzzi, T. Malik, O. Sharomi, and R. Zaki, Dynamics and optimal control for a spatially-structured environmental-economic model, Electronic Journal of Differential Equations, 2015, 1-15.
  • [23] S. Lenhart and J. T. Workman, Optimal control applied to biological models, Chapman and Hall/CRC, 2007.
  • [24] Q. Li, X. Guan, P. Wu, X. Wang, L. Zhou, Y. Tong, ..., and Z. Feng, Early transmission dynamics in Wuhan, China, of novel coronavirus–infected pneumonia, New England Journal of Medicine, 392(13) (2020), 1199-1207.
  • [25] E. T. Lofgren, M. E. Halloran, C. M. Rivers, J. M. Drake, T. C. Porco, B. Lewis, ..., and S. Eubank, Mathematical models: A key tool for outbreak response, Proceedings of the National Academy of Sciences, 111(51) (2014), 1809518096.
  • [26] S. Mwalili, M. Kimathi, V. Ojiambo, D. Gathungu, and R. Mbogo, SEIR model for COVID-19 dynamics incorporating the environment and social distancing, BMC Research Notes, 13(1) (2020), 1-5.
  • [27] H. J. Namawejje, L. S. Luboobi, D. Kuznetsov, and E. Wobudeya, Modeling optimal control of rotavirus disease with different control strategies, Journal of Mathematical and Computational Science, 4(5) (2014), 892.
  • [28] E. G. Nepomuceno, M. L. Peixoto, M. J. Lacerda, A. S. Campanharo, R. H. Takahashi, and L. A. Aguirre, Application of optimal control of infectious diseases in a model-free scenario, SN Computer Science, 2(5) (2021), 405.
  • [29] G. Oliveira, Refined compartmental models, asymptomatic carriers and COVID-19, arXiv preprint, arXiv:2004.14780, (2020).
  • [30] B. Pantha, F. B. Agusto, and I. M. Elmojtaba, Optimal control applied to a visceral leishmaniasis model, (2020).
  • [31] C. A. Pearson, F. Bozzani, S. R. Procter, N. G. Davies, M. Huda, H. T. Jensen, and R. M. Eggo, Health impact and cost-effectiveness of COVID-19 vaccination in Sindh Province Pakistan, medRxiv, (2021).
  • [32] Z. H. Shen, Y. M. Chu, M. A. Khan, S. Muhammad, O. A. Al-Hartomy, and M. Higazy, Mathematical modeling and optimal control of the COVID-19 dynamics, Results in Physics, 31 (2021), 105028.
  • [33] B. Tang, X. Wang, Q. Li, N. L. Bragazzi, S. Tang, Y. Xiao, and J. Wu, Estimation of the transmission risk of the 2019-nCoV and its implication for public health interventions, Journal of Clinical Medicine, 9(2) (2020), 462.
  • [34] P. Van Den Driessche and J. Watmough, Further notes on the basic reproduction number, Mathematical Epidemiology, (2008), 159-178.
  • [35] H. M. Wanjala, M. O. Okongo, and J. O. Ochwach, Impact of Media Awareness and Use of Face-Masks on Infectious Respiratory Disease, Pan-American Journal of Mathematics, 2 (2023), 15.
  • [36] H. M. Wanjala, M. Okongo, and J. Ochwach, Mathematical Model of the Impact of Home-Based Care on Contagious Respiratory Illness Under Optimal Conditions, Jambura Journal of Biomathematics (JJBM), 5(2) (2024), 83-94.
  • [37] I. M. Wangari, S. Sewe, G. Kimathi, M. Wainaina, V. Kitetu, and W. Kaluki, Mathematical modelling of COVID19 transmission in Kenya: a model with reinfection transmission mechanism, Computational and Mathematical Methods in Medicine, 2021 (2021).
  • [38] L. Yao, T. Wei, F. Tian, D. Y. Jin, L. Chen, and M. Wang, Presumed asymptomatic carrier transmission of COVID-19, JAMA, 323(14) (2020), 1406-1407.
  • [39] X. M. Zhang and Q. L. Han, New Lyapunov-Krasovskii functionals for global asymptotic stability of delayed neural networks, IEEE Transactions on Neural Networks, 20(3) (2009), 533-539.