Saved in:
| Main Author: | |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.02085 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866909011601784832 |
|---|---|
| author | Aldridge, Irene |
| author_facet | Aldridge, Irene |
| contents | This paper proposes an eigenvalue-based small-sample approximation of the celebrated Markov Chain Monte Carlo that delivers an invariant steady-state distribution that is consistent with traditional Monte Carlo methods. The proposed eigenvalue-based methodology reduces the number of paths required for Monte Carlo from as many as 1,000,000 to as few as 10 (depending on the simulation time horizon $T$), and delivers comparable, distributionally robust results, as measured by the Wasserstein distance. The proposed methodology also produces a significant variance reduction in the steady-state distribution. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_02085 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Fast Monte-Carlo Aldridge, Irene Econometrics Data Structures and Algorithms Statistics Theory Pricing of Securities Risk Management I.6 This paper proposes an eigenvalue-based small-sample approximation of the celebrated Markov Chain Monte Carlo that delivers an invariant steady-state distribution that is consistent with traditional Monte Carlo methods. The proposed eigenvalue-based methodology reduces the number of paths required for Monte Carlo from as many as 1,000,000 to as few as 10 (depending on the simulation time horizon $T$), and delivers comparable, distributionally robust results, as measured by the Wasserstein distance. The proposed methodology also produces a significant variance reduction in the steady-state distribution. |
| title | Fast Monte-Carlo |
| topic | Econometrics Data Structures and Algorithms Statistics Theory Pricing of Securities Risk Management I.6 |
| url | https://arxiv.org/abs/2605.02085 |