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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...
Autores principales: | Song, Zitao, Wang, Yining, Qian, Pin, Song, Sifan, Coenen, Frans, Jiang, Zhengyong, Su, Jionglong |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
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 |
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