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pro vyhledávání: '"Remlinger, Carl"'
Driven by the good results obtained in computer vision, deep generative methods for time series have been the subject of particular attention in recent years, particularly from the financial industry. In this article, we focus on commodity markets an
Externí odkaz:
http://arxiv.org/abs/2205.13942
Autor:
Mari, Alessandro, Remlinger, Carl, Castello, Roberto, Obozinski, Guillaume, Quarteroni, Silvia, Heymann, Fabian, Galus, Matthias
Publikováno v:
In Applied Energy 1 January 2025 377 Part C
Machine learning algorithms dedicated to financial time series forecasting have gained a lot of interest. But choosing between several algorithms can be challenging, as their estimation accuracy may be unstable over time. Online aggregation of expert
Externí odkaz:
http://arxiv.org/abs/2111.15365
We introduce three new generative models for time series that are based on Euler discretization of Stochastic Differential Equations (SDEs) and Wasserstein metrics. Two of these methods rely on the adaptation of generative adversarial networks (GANs)
Externí odkaz:
http://arxiv.org/abs/2102.05313
Reinforcement learning algorithms describe how an agent can learn an optimal action policy in a sequential decision process, through repeated experience. In a given environment, the agent policy provides him some running and terminal rewards. As in o
Externí odkaz:
http://arxiv.org/abs/2003.10014
Publikováno v:
In The Journal of Finance and Data Science November 2023 9
Autor:
Boursin, Nicolas1 (AUTHOR) nicolas.boursin@ensta-paris.fr, Remlinger, Carl2,3 (AUTHOR), Mikael, Joseph3 (AUTHOR) nicolas.boursin@ensta-paris.fr
Publikováno v:
Risks. Jan2023, Vol. 11 Issue 1, p7. 18p.
Akademický článek
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Publikováno v:
SSRN Electronic Journal.
Machine learning algorithms dedicated to financial time series forecasting have gained a lot of interest. But choosing between several algorithms can be challenging, as their estimation accuracy may be unstable over time. Online aggregation of expert
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::57c848522e1facb02a7b7fe09a96face
https://doi.org/10.2139/ssrn.4083389
https://doi.org/10.2139/ssrn.4083389
Akademický článek
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