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On The Error Estimate for Cubature on Wiener Space

Published online by Cambridge University Press:  29 November 2013

Thomas Cass
Affiliation:
Department of Mathematics, Imperial College London, South Kensington Campus, London SW7 2AZ, UK, ([email protected])
Christian Litterer
Affiliation:
Department of Mathematics, Imperial College London, South Kensington Campus, London SW7 2AZ, UK, ([email protected])
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Abstract

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It was pointed out by Crisan and Ghazali that the error estimate for the cubature on Wiener space algorithm developed by Lyons and Victoir requires an additional assumption on the drift. In this paper we demonstrate that it is straightforward to adopt the analysis of Kusuoka to obtain a general estimate without an additional assumptions on the drift. In the process we slightly sharpen the bounds derived by Kusuoka.

Type
Research Article
Copyright
Copyright © Edinburgh Mathematical Society 2014 

References

1.Ben Arous, G., Flots et series de Taylor stochastiques, Prob. Theory Relat. Fields 81 (1989), 2977.Google Scholar
2.Crisan, D. and Ghazali, S., On the convergence rates of a general class of weak approximations of SDEs, Stochastic differential equations: theory and applications, pp. 221248 (World Scientific, 2007).Google Scholar
3.Crisan, D. and Manolarakis, K., Solving backward stochastic differential equations using the cubature method: application to nonlinear pricing, SIAM J. Fin. Math 3(1) (2012), 534571.CrossRefGoogle Scholar
4.Crisan, D. and Manolarakis, K., Second-order discretization of backward SDEs, preprint (arXiv 1012.5650v1 [math.PR]; 2010).Google Scholar
5.Kusuoka, S., Approximation of expectation of diffusion process and mathematical finance, Adv. Stud. Pure Math. 31 (2001), 147165.CrossRefGoogle Scholar
6.Kusuoka, S., Malliavin calculus revisited, J. Math. Sci. Univ. Tokyo 10 (2003), 261277.Google Scholar
7.Kusuoka, S., Approximation of expectation of diffusion processes based on Lie algebra and Malliavin calculus, Adv. Math. Econom. 6 (2004), 6983.CrossRefGoogle Scholar
8.Kusuoka, S. and Stroock, D., Application of the Malliavin calculus, III, J. Fac. Sci. Univ. Tokyo (1) A 34 (1987), 391442.Google Scholar
9.Litterer, C., The signature in numerical algorithms, DPhil Thesis, University of Oxford (2008).Google Scholar
10.Litterer, C. and Lyons, T., High-order recombination and an application to cubature on Wiener space, Annals Appl. Prob. 22(4) (2012), 13011327.Google Scholar
11.Lyons, T., The interpretation and solution of ordinary differential equations driven by rough signals, Proc. Symp. Pure Math. 57 (1995), 115128.CrossRefGoogle Scholar
12.Lyons, T. and Sidorova, N., On the radius of convergence of the logarithmic signature, Illinois J. Math. 50 (2006), 763790.CrossRefGoogle Scholar
13.Lyons, T. and Victoir, N., Cubature on Wiener space, Proc. R. Soc. Lond. A 460 (2004), 169198.Google Scholar
14.Ninomiya, S., A partial sampling method applied to the Kusuoka approximation, Monte Carlo Meth. Appl. 9(1) (2003), 2738.Google Scholar
15.Ninomiya, S. and Victoir, N., Weak approximation of stochastic differential equations and application to derivative pricing, Appl. Math. Fin. 15(2) (2008), 107121.Google Scholar
16.Reutenauer, C., Free Lie algebras, London Mathematical Society Monographs, Volume 7 (Oxford University Press, 1993).CrossRefGoogle Scholar
17.Teichmann, J., Calculating the Greeks by cubature formulae, Proc. R. Soc. Lond. A 462 (2006), 647670.Google Scholar