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- W3022746105 endingPage "106384" @default.
- W3022746105 startingPage "106384" @default.
- W3022746105 abstract "Computational intelligence in finance has been a very popular topic for both academia and financial industry in the last few decades. Numerous studies have been published resulting in various models. Meanwhile, within the Machine Learning (ML) field, Deep Learning (DL) started getting a lot of attention recently, mostly due to its outperformance over the classical models. Lots of different implementations of DL exist today, and the broad interest is continuing. Finance is one particular area where DL models started getting traction, however, the playfield is wide open, a lot of research opportunities still exist. In this paper, we tried to provide a state-of-the-art snapshot of the developed DL models for financial applications. We not only categorized the works according to their intended subfield in finance but also analyzed them based on their DL models. In addition, we also aimed at identifying possible future implementations and highlighted the pathway for the ongoing research within the field." @default.
- W3022746105 created "2020-05-13" @default.
- W3022746105 creator A5048947308 @default.
- W3022746105 creator A5050114655 @default.
- W3022746105 creator A5063733234 @default.
- W3022746105 date "2020-08-01" @default.
- W3022746105 modified "2023-10-14" @default.
- W3022746105 title "Deep learning for financial applications : A survey" @default.
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- W3022746105 doi "https://doi.org/10.1016/j.asoc.2020.106384" @default.
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