A Diffusion Bridge Sampler for Drift- and Diffusion Dominated Models
(2018) 10th Bachelier world congress- Abstract
- We introduce an adaptive algorithm for sampling multivariate diffusion bridges that performs well for both diffusion and drift dominated models.
The algorithm combines the residual bridge sampler with adaptive MCMC, allowing the algorithm to make online improvements upon the ordinary residual bridge algorithm.
The simulation study show that the proposed bridge sampler is performing at least as good as the residual bridge sampler on a diffusion dominated problem, and substantially better on a drift dominated problem.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/0541dfb3-554c-4664-854a-34ab6a8a6fc4
- author
- Lindström, Erik LU and Damberg, Daniel
- organization
- publishing date
- 2018-07-16
- type
- Contribution to conference
- publication status
- in press
- subject
- conference name
- 10th Bachelier world congress
- conference location
- Dublin, Ireland
- conference dates
- 2018-07-16 - 2018-07-20
- language
- English
- LU publication?
- yes
- id
- 0541dfb3-554c-4664-854a-34ab6a8a6fc4
- date added to LUP
- 2018-04-05 14:51:26
- date last changed
- 2018-11-21 21:39:05
@misc{0541dfb3-554c-4664-854a-34ab6a8a6fc4, abstract = {{We introduce an adaptive algorithm for sampling multivariate diffusion bridges that performs well for both diffusion and drift dominated models.<br/>The algorithm combines the residual bridge sampler with adaptive MCMC, allowing the algorithm to make online improvements upon the ordinary residual bridge algorithm.<br/>The simulation study show that the proposed bridge sampler is performing at least as good as the residual bridge sampler on a diffusion dominated problem, and substantially better on a drift dominated problem.<br/>}}, author = {{Lindström, Erik and Damberg, Daniel}}, language = {{eng}}, month = {{07}}, title = {{A Diffusion Bridge Sampler for Drift- and Diffusion Dominated Models}}, year = {{2018}}, }