March  2021, 26(3): 1405-1446. doi: 10.3934/dcdsb.2020167

On Milstein-type scheme for SDE driven by Lévy noise with super-linear coefficients

Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India, 247 667

* Corresponding author: C. Kumar (chaman.kumar@ma.iitr.ac.in)

Received  July 2019 Revised  December 2019 Published  May 2020

Fund Project: The author is supported by Professional Development Allowance (PDA) and Faculty Initiation Grant provided by the Indian Institute of Technology Roorkee

A new explicit Milstein-type scheme for SDE driven by Lévy noise is proposed where both drift and diffusion coefficients are allowed to grow super-linearly. The strong rate of convergence (in $ \mathcal{L}^2 $-sense) is shown to be arbitrarily close to one which is consistent with the corresponding result on the classical Milstein scheme obtained for coefficients satisfying global Lipschitz conditions.

Citation: Chaman Kumar. On Milstein-type scheme for SDE driven by Lévy noise with super-linear coefficients. Discrete & Continuous Dynamical Systems - B, 2021, 26 (3) : 1405-1446. doi: 10.3934/dcdsb.2020167
References:
[1]

W.-J. BeynE. Isaak and R. Kruse, Stochastic C-stability and B-consistency of explicit and implicit Milstein-type schemes, Journal of Scientific Computing, 70 (2017), 1042-1077.  doi: 10.1007/s10915-016-0290-x.  Google Scholar

[2]

K. DareiotisC. Kumar and S. Sabanis, On tamed Euler approximations of SDEs driven by Lévy noise with application to delay equations, SIAM Journal on Numerical Analysis, 54 (2016), 1840-1872.  doi: 10.1137/151004872.  Google Scholar

[3]

D. Fudenberg and C. Harris, Evolutionary dynamics with aggregate shocks, Journal of Economic Theory, 57 (1992), 420-441.  doi: 10.1016/0022-0531(92)90044-I.  Google Scholar

[4]

F. B. Hanson, Applied Stochastic Processes and Control for Jump-Diffusions: Modeling, Analysis and Computation, Advances in Design and Control, 13. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA, 2007. doi: 10.1137/1.9780898718638.  Google Scholar

[5]

F. B. Hanson and H. C. Tuckwell, Population growth with randomly distributed jumps, Journal of Mathematical Biology, 36 (1997), 169-187.  doi: 10.1007/s002850050096.  Google Scholar

[6]

M. Hutzenthaler and A. Jentzen, Numerical approximations of stochastic differential equations with non-globally Lipschitz continuous coefficients, Memoirs of the American Mathematical Society, 236 (2015). doi: 10.1090/memo/1112.  Google Scholar

[7]

M. HutzenthalerA. Jentzen and P. E. Kloeden, Strong and weak divergence in finite time of Euler's method for stochastic differential equations with non-globally Lipschitz continuous coefficients, Proc. R. Soc. Lond. Ser. A Math. Phys. Eng. Sci., 467 (2011), 1563-1576.  doi: 10.1098/rspa.2010.0348.  Google Scholar

[8]

M. HutzenthalerA. Jentzen and P. E. Kloeden, Strong convergence of an explicit numerical method for SDEs with nonglobally Lipschitz continuous coefficients, Annals of Applied Probability, 22 (2012), 1611-1641.  doi: 10.1214/11-AAP803.  Google Scholar

[9]

C. Kumar and S. Sabanis, On explicit approximations for Lévy driven SDEs with super-linear diffusion coefficients, Electronic Journal of Probability, 22 (2017), Paper No. 73, 19 pp. doi: 10.1214/17-EJP89.  Google Scholar

[10]

C. Kumar and S. Sabanis, On tamed Milstein scheme of SDEs driven by Lévy noise, Discrete and Continuous Dynamical Systems-Series B, 22 (2017), 421-463.  doi: 10.3934/dcdsb.2017020.  Google Scholar

[11]

C. Kumar and S. Sabanis, On Milstein approximations with varying coefficients: The case of super-linear diffusion coefficients, BIT Numerical Mathematics, 59 (2019), 929-968.  doi: 10.1007/s10543-019-00756-5.  Google Scholar

[12]

E. Platen and N. Bruti-Liberati, Numerical Solution of Stochastic Differential Equations with Jumps in Finance, Stochastic Modelling and Applied Probability, 64. Springer-Verlag, Berlin, 2010. doi: 10.1007/978-3-642-13694-8.  Google Scholar

[13]

S. Sabanis, A note on tamed Euler approximations, Electronic Communications in Probability, 18 (2013), 10 pp. doi: 10.1214/ECP.v18-2824.  Google Scholar

[14]

S. Sabanis, Euler approximations with varying coefficients: The case of superlinearly growing diffusion coefficients, Annals of Applied Probability, 26 (2016), 2083-2105.  doi: 10.1214/15-AAP1140.  Google Scholar

[15]

S. Sabanis and Y. Zhang, On explicit order 1.5 approximations with varying coefficients: The case of super-linear diffusion coefficients, Journal of Complexity, 50 (2019), 84-115.  doi: 10.1016/j.jco.2018.09.004.  Google Scholar

[16]

R. Situ, Theory of Stochastic Differential Equations with Jumps and Applications: Mathematical and Analytic Techniques with Applications to Engineering, Springer, New York, 2005.  Google Scholar

[17]

M. V. Tretyakov and Z. Zhang, A fundamental mean-square convergence theorem for SDEs with locally Lipschitz coefficients and its applications, SIAM Journal on Numerical Analysis, 51 (2013), 3135-3162.  doi: 10.1137/120902318.  Google Scholar

[18]

X. J. Wang and S. Q. Gan, The tamed Milstein method for commutative stochastic differential equations with non-globally Lipschitz continuous coefficients, Journal of Difference Equations and Applications, 19 (2013), 466-490.  doi: 10.1080/10236198.2012.656617.  Google Scholar

[19]

Z. Q. Zhang and H. P. Ma, Order-preserving strong schemes for SDEs with locally Lipschitz coefficients, Applied Numerical Mathematics, 112 (2017), 1-16.  doi: 10.1016/j.apnum.2016.09.013.  Google Scholar

show all references

References:
[1]

W.-J. BeynE. Isaak and R. Kruse, Stochastic C-stability and B-consistency of explicit and implicit Milstein-type schemes, Journal of Scientific Computing, 70 (2017), 1042-1077.  doi: 10.1007/s10915-016-0290-x.  Google Scholar

[2]

K. DareiotisC. Kumar and S. Sabanis, On tamed Euler approximations of SDEs driven by Lévy noise with application to delay equations, SIAM Journal on Numerical Analysis, 54 (2016), 1840-1872.  doi: 10.1137/151004872.  Google Scholar

[3]

D. Fudenberg and C. Harris, Evolutionary dynamics with aggregate shocks, Journal of Economic Theory, 57 (1992), 420-441.  doi: 10.1016/0022-0531(92)90044-I.  Google Scholar

[4]

F. B. Hanson, Applied Stochastic Processes and Control for Jump-Diffusions: Modeling, Analysis and Computation, Advances in Design and Control, 13. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA, 2007. doi: 10.1137/1.9780898718638.  Google Scholar

[5]

F. B. Hanson and H. C. Tuckwell, Population growth with randomly distributed jumps, Journal of Mathematical Biology, 36 (1997), 169-187.  doi: 10.1007/s002850050096.  Google Scholar

[6]

M. Hutzenthaler and A. Jentzen, Numerical approximations of stochastic differential equations with non-globally Lipschitz continuous coefficients, Memoirs of the American Mathematical Society, 236 (2015). doi: 10.1090/memo/1112.  Google Scholar

[7]

M. HutzenthalerA. Jentzen and P. E. Kloeden, Strong and weak divergence in finite time of Euler's method for stochastic differential equations with non-globally Lipschitz continuous coefficients, Proc. R. Soc. Lond. Ser. A Math. Phys. Eng. Sci., 467 (2011), 1563-1576.  doi: 10.1098/rspa.2010.0348.  Google Scholar

[8]

M. HutzenthalerA. Jentzen and P. E. Kloeden, Strong convergence of an explicit numerical method for SDEs with nonglobally Lipschitz continuous coefficients, Annals of Applied Probability, 22 (2012), 1611-1641.  doi: 10.1214/11-AAP803.  Google Scholar

[9]

C. Kumar and S. Sabanis, On explicit approximations for Lévy driven SDEs with super-linear diffusion coefficients, Electronic Journal of Probability, 22 (2017), Paper No. 73, 19 pp. doi: 10.1214/17-EJP89.  Google Scholar

[10]

C. Kumar and S. Sabanis, On tamed Milstein scheme of SDEs driven by Lévy noise, Discrete and Continuous Dynamical Systems-Series B, 22 (2017), 421-463.  doi: 10.3934/dcdsb.2017020.  Google Scholar

[11]

C. Kumar and S. Sabanis, On Milstein approximations with varying coefficients: The case of super-linear diffusion coefficients, BIT Numerical Mathematics, 59 (2019), 929-968.  doi: 10.1007/s10543-019-00756-5.  Google Scholar

[12]

E. Platen and N. Bruti-Liberati, Numerical Solution of Stochastic Differential Equations with Jumps in Finance, Stochastic Modelling and Applied Probability, 64. Springer-Verlag, Berlin, 2010. doi: 10.1007/978-3-642-13694-8.  Google Scholar

[13]

S. Sabanis, A note on tamed Euler approximations, Electronic Communications in Probability, 18 (2013), 10 pp. doi: 10.1214/ECP.v18-2824.  Google Scholar

[14]

S. Sabanis, Euler approximations with varying coefficients: The case of superlinearly growing diffusion coefficients, Annals of Applied Probability, 26 (2016), 2083-2105.  doi: 10.1214/15-AAP1140.  Google Scholar

[15]

S. Sabanis and Y. Zhang, On explicit order 1.5 approximations with varying coefficients: The case of super-linear diffusion coefficients, Journal of Complexity, 50 (2019), 84-115.  doi: 10.1016/j.jco.2018.09.004.  Google Scholar

[16]

R. Situ, Theory of Stochastic Differential Equations with Jumps and Applications: Mathematical and Analytic Techniques with Applications to Engineering, Springer, New York, 2005.  Google Scholar

[17]

M. V. Tretyakov and Z. Zhang, A fundamental mean-square convergence theorem for SDEs with locally Lipschitz coefficients and its applications, SIAM Journal on Numerical Analysis, 51 (2013), 3135-3162.  doi: 10.1137/120902318.  Google Scholar

[18]

X. J. Wang and S. Q. Gan, The tamed Milstein method for commutative stochastic differential equations with non-globally Lipschitz continuous coefficients, Journal of Difference Equations and Applications, 19 (2013), 466-490.  doi: 10.1080/10236198.2012.656617.  Google Scholar

[19]

Z. Q. Zhang and H. P. Ma, Order-preserving strong schemes for SDEs with locally Lipschitz coefficients, Applied Numerical Mathematics, 112 (2017), 1-16.  doi: 10.1016/j.apnum.2016.09.013.  Google Scholar

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