A Note on the Conditions for COS Convergence
Fuente:
arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866912743302365184 |
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| author | Wang, Qinling Shen, Xiaoyu Fang, Fang |
| author_facet | Wang, Qinling Shen, Xiaoyu Fang, Fang |
| contents | We study the truncation error of the COS method and give simple, verifiable conditions that guarantee convergence. In one dimension, COS is admissible when the density belongs to both L1 and L2 and has a finite weighted L2 moment of order strictly greater than one. We extend the result to multiple dimensions by requiring the moment order to exceed the dimension. These conditions enlarge the class of densities covered by previous analyses and include heavy-tailed distributions such as Student t with small degrees of freedom. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_02745 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Note on the Conditions for COS Convergence Wang, Qinling Shen, Xiaoyu Fang, Fang Computational Finance Numerical Analysis Probability We study the truncation error of the COS method and give simple, verifiable conditions that guarantee convergence. In one dimension, COS is admissible when the density belongs to both L1 and L2 and has a finite weighted L2 moment of order strictly greater than one. We extend the result to multiple dimensions by requiring the moment order to exceed the dimension. These conditions enlarge the class of densities covered by previous analyses and include heavy-tailed distributions such as Student t with small degrees of freedom. |
| title | A Note on the Conditions for COS Convergence |
| topic | Computational Finance Numerical Analysis Probability |
| url | https://arxiv.org/abs/2512.02745 |