Approximation of the Fractional SDEs with Stochastic Forcing

被引:0
作者
Kubilius, Kestutis [1 ]
机构
[1] Vilnius Univ, Fac Math & Informat, Akademijos G 4, LT-03225 Vilnius, Lithuania
关键词
stochastic differential equations; stochastic forcing; fractional Brownian motion; implicit Euler scheme; implicit Milstein scheme; p-variation; Pearson model; DIFFERENTIAL-EQUATIONS DRIVEN; EULER APPROXIMATION; BROWNIAN-MOTION; CONVERGENCE; SCHEMES; UNIQUENESS; EXISTENCE; MEMORY;
D O I
10.3390/math12243875
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Using the implicit Euler and Milstein approximation schemes, the conditions for the pathwise convergence rate of these approximations to the solution of the fractional SDEs with stochastic forcing are found.
引用
收藏
页数:22
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  • [1] Falkowski A., Slominski L., Sweeping processes with stochastic perturbations generated by a fractional Brownian motion, arXiv, (2015)
  • [2] Falkowski A., Slominski L., Mean reflected stochastic differential equations with two constraints, Stoch. Process. Appl, 141, pp. 172-196, (2021)
  • [3] Kubilius K., Medziunas A., A class of the fractional stochastic differential equations with a soft wall, Fractal Fract, 7, (2023)
  • [4] Kubilius K., Fractional SDEs with stochastic forcing: Existence, uniqueness, and approximation, Nonlinear Anal. Model. Control, 28, pp. 1196-1225, (2023)
  • [5] Bollerslev T., Mikkelsen H.O., Modeling and pricing long memory in stock market volatility, J. Econom, 73, pp. 151-184, (1996)
  • [6] Di Nunno G., Kubilius K., Mishura Y., Yurchenko-Tytarenko A., From Constant to Rough: A Survey of Continuous Volatility Modeling, Mathematics, 11, (2023)
  • [7] Fischer T., Krauss C., Deep learning with long short-term memory networks for financial market predictions, Eur. J. Oper. Res, 270, pp. 654-669, (2018)
  • [8] Kubilius K., The implicit Euler scheme for FSDEs with stochastic forcing: Existence and uniqueness of the solution, Mathematics, 12, (2024)
  • [9] Jamshidi N., Kamrani M., Convergence of a numerical scheme associated to stochastic differential equations with fractional Brownian motion, Appl. Numer. Math, 167, pp. 108-118, (2021)
  • [10] Hong J., Huang C., Wang X., Optimal rate of convergence for two classes of schemes to stochastic differential equations driven by fractional Brownian motions, IMA J. Numer. Anal, 41, pp. 1608-1638, (2021)