Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-23T18:20:34.140Z Has data issue: false hasContentIssue false

An Euler–Poisson scheme for Lévy driven stochastic differential equations

Published online by Cambridge University Press:  24 March 2016

A. E. Kyprianou
Affiliation:
Department of Mathematical Sciences, University of Bath, Claverton Down, Bath BA2 7AY, UK.
R. Scheichl
Affiliation:
Department of Mathematical Sciences, University of Bath, Claverton Down, Bath BA2 7AY, UK.

Abstract

We describe an Euler scheme to approximate solutions of Lévy driven stochastic differential equations (SDEs) where the grid points are given by the arrival times of a Poisson process and thus are random. This result extends the previous work of Ferreiro-Castilla et al. (2014). We provide a complete numerical analysis of the algorithm to approximate the terminal value of the SDE and prove that the mean-square error converges with rate O(n-1/2). The only requirement of the methodology is to have exact samples from the resolvent of the Lévy process driving the SDE. Classical examples, such as stable processes, subclasses of spectrally one-sided Lévy processes, and new families, such as meromorphic Lévy processes (Kuznetsov et al. (2012), are examples for which our algorithm provides an interesting alternative to existing methods, due to its straightforward implementation and its robustness with respect to the jump structure of the driving Lévy process.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1]Abramowitz, M. and Stegun, I. A. (1964). Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. U.S. Government Printing Office, Washington, DC. Google Scholar
[2]Asmussen, S. and Rosiński, J. (2001). Approximations of small jumps of Lévy processes with a view towards simulation. J. Appl. Prob. 38, 482493. CrossRefGoogle Scholar
[3]Baran, M. (2009). Approximation for solutions of Lévy-type stochastic differential equations. Stoch. Anal. Appl. 27, 924961. CrossRefGoogle Scholar
[4]Carr, P. (1998). Randomization and the American put. Rev. Fin. Studies 11, 597626. CrossRefGoogle Scholar
[5]Chan, T. (1999). Pricing contingent claims on stocks driven by Lévy processes. Ann. Appl. Prob. 9, 504528. CrossRefGoogle Scholar
[6]Cont, R. and Tankov, P. (2004). Financial Modelling with Jump Processes. Chapman & Hall/CRC, Boca Raton, FL. Google Scholar
[7]Dereich, S. (2011). Multilevel Monte Carlo algorithms for Lévy-driven SDEs with Gaussian correction. Ann. Appl. Prob. 21, 283311. CrossRefGoogle Scholar
[8]Dereich, S. and Heidenreich, F. (2011). A multilevel Monte Carlo algorithm for Lévy-driven stochastic differential equations. Stoch. Process. Appl. 121, 15651587. CrossRefGoogle Scholar
[9]Doob, J. L. (1953). Stochastic Processes. John Wiley, New York. Google Scholar
[10]Ferreiro-Castilla, A. and Schoutens, W. (2012). The β-Meixner model. J. Comput. Appl. Math. 236, 24662476. CrossRefGoogle Scholar
[11]Ferreiro-Castilla, A., Kyprianou, A. E., Scheichl, R. and Suryanarayana, G. (2014). Multilevel Monte Carlo simulation for Lévy processes based on the Wiener–Hopf factorization. Stoch. Process. Appl. 124, 9851010. CrossRefGoogle Scholar
[12]Fisher, R. A. (1929). Tests of significance in harmonic analysis. Proc. R. Soc. London A 125, 5459. Google Scholar
[13]Gīhman, Ĭ. Ī. and Skorohod, A. V. (1972). Stochastic Differential Equations. Springer, New York. CrossRefGoogle Scholar
[14]Jacod, J., Kurtz, T. G., Méléard, S. and Protter, P. (2005). The approximate Euler method for Lévy driven stochastic differential equations. Ann. Inst. H. Poincaré Prob. Statist. 41, 523558. CrossRefGoogle Scholar
[15]Kloeden, P. E. and Platen, E. (1992). Numerical Solution of Stochastic Differential Equations. Springer, Berlin. CrossRefGoogle Scholar
[16]Kohatsu-Higa, A., Ortiz-Latorre, S. and Tankov, P. (2014). Optimal simulation scheme for Lévy driven stochastic differential equations. Math. Comput. 83, 22932324. CrossRefGoogle Scholar
[17]Kuznetsov, A. (2010). Wiener–Hopf factorization and distribution of extrema for a family of Lévy processes. Ann. Appl. Prob. 20, 18011830. CrossRefGoogle Scholar
[18]Kuznetsov, A., Kyprianou, A. E. and Pardo, J. C. (2012). Meromorphic Lévy processes and their fluctuation identities. Ann. Appl. Prob. 22, 11011135. CrossRefGoogle Scholar
[19]Kuznetsov, A., Kyprianou, A. E., Pardo, J. C. and van Schaik, K. (2011). A Wiener–Hopf Monte Carlo simulation technique for Lévy processes. Ann. Appl. Prob. 21, 21712190. CrossRefGoogle Scholar
[20]Matache, A.-M., Nitsche, P.-A. and Schwab, C. (2005). Wavelet Galerkin pricing of American options on Lévy driven assets. Quant. Finance 5, 403424. CrossRefGoogle Scholar
[21]Mauldon, J. G. (1951). Random division of an interval. Proc. Camb. Philos. Soc. 47, 331336. CrossRefGoogle Scholar
[22]Protter, P. E. (2005). Stochastic Integration and Differential Equations, 2nd edn. Springer, Berlin. CrossRefGoogle Scholar
[23]Protter, P. and Talay, D. (1997). The Euler scheme for Lévy driven stochastic differential equations. Ann. Prob. 25, 393423. CrossRefGoogle Scholar
[24]Rubenthaler, S. (2003). Numerical simulation of the solution of a stochastic differential equation driven by a Lévy process. Stoch. Process. Appl. 103, 311349. CrossRefGoogle Scholar
[25]Schoutens, W. and Van Damme, G. (2011). The β-variance gamma model. Rev. Deriv. Res. 14, 263282. CrossRefGoogle Scholar
[26]Situ, R. (2005). Theory of Stochastic Differential Equations with Jumps and Applications. Springer, New York. Google Scholar
[27]Sobczyk, K. (1991). Stochastic Differential Equations: With Applications to Physics and Engineering. Kluwer, Dordrecht. CrossRefGoogle Scholar