From deterministic to stochastic: an interpretable stochastic model-free reinforcement learning framework for portfolio optimization

As a fundamental problem in algorithmic trading, portfolio optimization aims to maximize the cumulative return by continuously investing in various financial derivatives within a given time period. Recent years have witnessed the transformation from traditional machine learning trading algorithms to...

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Detalles Bibliográficos
Autores principales: Song, Zitao, Wang, Yining, Qian, Pin, Song, Sifan, Coenen, Frans, Jiang, Zhengyong, Su, Jionglong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9651127/
https://www.ncbi.nlm.nih.gov/pubmed/36405345
http://dx.doi.org/10.1007/s10489-022-04217-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9651127/
https://www.ncbi.nlm.nih.gov/pubmed/36405345
http://dx.doi.org/10.1007/s10489-022-04217-5

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