Mathematics – Numerical Analysis
Scientific paper
2006-09-06
Mathematics
Numerical Analysis
27 pages
Scientific paper
This work develops Monte Carlo Euler adaptive time stepping methods for the weak approximation problem of jump diffusion driven stochastic differential equations. The main result is the derivation of a new expansion for the omputational error, with computable leading order term in a posteriori form, based on stochastic flows and discrete dual backward problems which extends the results in [STZ]. These expansions lead to efficient and accurate computation of error estimates. Adaptive algorithms for either stochastic time steps or quasi-deterministic time steps are described. Numerical examples show the performance of the proposed error approximation and of the described adaptive time-stepping methods.
Mordecki Ernesto
Szepessy Andras
Tempone Raul
Zouraris Georgios E.
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