2015
DOI: 10.2139/ssrn.2553047
|View full text |Cite
|
Sign up to set email alerts
|

Multilevel Dimension Reduction Monte-Carlo Simulation for High-Dimensional Stochastic Models in Finance

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2015
2015
2017
2017

Publication Types

Select...
3

Relationship

2
1

Authors

Journals

citations
Cited by 3 publications
(1 citation statement)
references
References 7 publications
0
1
0
Order By: Relevance
“…We emphasize that the drMC framework could be easily combined with other efficient variance reduction techniques applied to the factor we condition on, to further significantly increase the efficiency of the method. In particular, we highlight potential applications of the drMC method when combined with the multilevel MC method developed by Giles (2008), due to the dimension reduction feature (e.g., see Dang, Xu, and Wu 2015c). Results in Dang (2017) show that the multilevel technique can be easily combined with the drMC method to efficiently tackle high-dimensional jump-diffusion models using Milstein schemes.…”
Section: Resultsmentioning
confidence: 92%
“…We emphasize that the drMC framework could be easily combined with other efficient variance reduction techniques applied to the factor we condition on, to further significantly increase the efficiency of the method. In particular, we highlight potential applications of the drMC method when combined with the multilevel MC method developed by Giles (2008), due to the dimension reduction feature (e.g., see Dang, Xu, and Wu 2015c). Results in Dang (2017) show that the multilevel technique can be easily combined with the drMC method to efficiently tackle high-dimensional jump-diffusion models using Milstein schemes.…”
Section: Resultsmentioning
confidence: 92%