Exact Sampling for Multivariate Diffusions

Add to your list(s) Download to your calendar using vCal

• Jose Blanchet (Columbia University; Stanford University)
• Friday 07 July 2017, 11:00-11:45
• Seminar Room 1, Newton Institute.

If you have a question about this talk, please contact INI IT.

SINW01 - Scalable statistical inference

We provide the first generic exact simulation algorithm for multivariate diffusions. Current exact sampling algorithms for diffusions require the existence of a transformation which can be used to reduce the sampling problem to the case of a constant diffusion matrix and a drift which is the gradient of some function. Such transformation, called Lamperti transformation, can be applied in general only in one dimension. So, completely different ideas are required for exact sampling of generic multivariate diffusions. The development of these ideas is the main contribution of this paper. Our strategy combines techniques borrowed from the theory of rough paths, on one hand, and multilevel Monte Carlo on the other. (Joint work with Fan Zhang.)

This talk is part of the Isaac Newton Institute Seminar Series series.

This talk is included in these lists:

• All CMS events
• Featured lists
• INI info aggregator
• Isaac Newton Institute Seminar Series
• School of Physical Sciences
• Seminar Room 1, Newton Institute
• bld31

Note that ex-directory lists are not shown.