Robust Functional Data Analysis for Stochastic Evolution Equations in Infinite Dimensions
Fuente:
arXiv
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866916936350171136 |
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| author | Schroers, Dennis |
| author_facet | Schroers, Dennis |
| contents | We develop an asymptotic theory for the jump robust measurement of covariations in the context of stochastic evolution equation in infinite dimensions. Namely, we identify scaling limits for realized covariations of solution processes with the quadratic covariation of the latent random process that drives the evolution equation which is assumed to be a Hilbert space-valued semimartingale. We discuss applications to dynamically consistent and outlier-robust dimension reduction in the spirit of functional principal components and the estimation of infinite-dimensional stochastic volatility models. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_16286 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Robust Functional Data Analysis for Stochastic Evolution Equations in Infinite Dimensions Schroers, Dennis Methodology Mathematical Finance 62E20, 46N30, 60H15 We develop an asymptotic theory for the jump robust measurement of covariations in the context of stochastic evolution equation in infinite dimensions. Namely, we identify scaling limits for realized covariations of solution processes with the quadratic covariation of the latent random process that drives the evolution equation which is assumed to be a Hilbert space-valued semimartingale. We discuss applications to dynamically consistent and outlier-robust dimension reduction in the spirit of functional principal components and the estimation of infinite-dimensional stochastic volatility models. |
| title | Robust Functional Data Analysis for Stochastic Evolution Equations in Infinite Dimensions |
| topic | Methodology Mathematical Finance 62E20, 46N30, 60H15 |
| url | https://arxiv.org/abs/2401.16286 |