Proceedings of the 3rd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2024)

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Exploring the Landscape of Financial Deep Learning: Models, Applications and Future Directions

Authors
Qin Wang1, Mary Jane C. Samonte2, *
1School of Information Technology, Mapua University, Xi’an Siyuan University, Manila, Philippines
2School of Information Technology, Mapua University, Manila, Philippines
*Corresponding author. Email: mjcsamonte@mapua.edu.ph
Corresponding Author
Mary Jane C. Samonte
Available Online 7 May 2024.
DOI
10.2991/978-94-6463-419-8_23How to use a DOI?
Keywords
Deep learning; The financial sector; Neural network; Text analysis; Risk assessment; Portfolio management
Abstract

With the rapid development of artificial intelligence and financial technology, the application of machine learning, especially deep learning, in the financial field has aroused strong research interest. In order to explore the application field of financial deep learning, the literature of financial deep learning in the past ten years is summarized, and the model introduction and application field are respectively summarized. The results show that the models commonly used in financial deep learning include convolutional neural networks, recurrent neural networks and long short-term memory neural networks, and they have a wide range of applications in financial text analysis, financial risk assessment and anomaly detection, and portfolio management. In the future, new text mining and natural language processing techniques can be applied to the field of behavioral finance for more in-depth research, while more possibilities for applying deep learning to emerging financial areas such as cryptocurrencies and blockchain can also be explored.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 3rd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2024)
Series
Atlantis Highlights in Computer Sciences
Publication Date
7 May 2024
ISBN
10.2991/978-94-6463-419-8_23
ISSN
2589-4900
DOI
10.2991/978-94-6463-419-8_23How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Qin Wang
AU  - Mary Jane C. Samonte
PY  - 2024
DA  - 2024/05/07
TI  - Exploring the Landscape of Financial Deep Learning: Models, Applications and Future Directions
BT  - Proceedings of the 3rd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2024)
PB  - Atlantis Press
SP  - 180
EP  - 187
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-419-8_23
DO  - 10.2991/978-94-6463-419-8_23
ID  - Wang2024
ER  -