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Error distributions for random grid approximations of multidimensional stochastic integrals

Carl Lindberg (Institutionen för matematiska vetenskaper, matematisk statistik) ; Holger Rootzén (Institutionen för matematiska vetenskaper, matematisk statistik)
The Annals of Applied Probability (1050-5164). Vol. 23 (2013), 2, p. 834-857.
[Artikel, refereegranskad vetenskaplig]

This paper proves joint convergence of the approximation error for several stochastic integrals with respect to local Brownian semimartingales, for nonequidistant and random grids. The conditions needed for convergence are that the Lebesgue integrals of the integrands tend uniformly to zero and that the squared variation and covariation processes converge. The paper also provides tools which simplify checking these conditions and which extend the range for the results. These results are used to prove an explicit limit theorem for random grid approximations of integrals based on solutions of multidimensional SDEs, and to find ways to "design" and optimize the distribution of the approximation error. As examples we briefly discuss strategies for discrete option hedging.

Nyckelord: Approximation error, random grid, joint weak convergence, multidimensional stochastic differential, differential-equations, weak-convergence, limit-theorems

Denna post skapades 2013-04-05. Senast ändrad 2016-08-22.
CPL Pubid: 175362


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Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, matematisk statistik (2005-2016)



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