How can the dual martingale help solving the primal optimal stopping problem?
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2026
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| _version_ | 1866910017895006208 |
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| author | Alfonsi, Aurélien Kebaier, Ahmed Lelong, Jérôme |
| author_facet | Alfonsi, Aurélien Kebaier, Ahmed Lelong, Jérôme |
| contents | Motivated by recent results on the dual formulation of optimal stopping problems, we investigate in this short paper how the knowledge of an approximating dual martingale can improve the efficiency of primal methods. In particular, we show on numerical examples that accurate approximations of a dual martingale efficiently reduce the variance for the primal optimal stopping problem. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_09950 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | How can the dual martingale help solving the primal optimal stopping problem? Alfonsi, Aurélien Kebaier, Ahmed Lelong, Jérôme Computational Finance Probability 62L15, 60G40, 91G20, 65C05 Motivated by recent results on the dual formulation of optimal stopping problems, we investigate in this short paper how the knowledge of an approximating dual martingale can improve the efficiency of primal methods. In particular, we show on numerical examples that accurate approximations of a dual martingale efficiently reduce the variance for the primal optimal stopping problem. |
| title | How can the dual martingale help solving the primal optimal stopping problem? |
| topic | Computational Finance Probability 62L15, 60G40, 91G20, 65C05 |
| url | https://arxiv.org/abs/2602.09950 |