Deep Learning for Financial Applications : A Survey

By A. Ozbayoglu, M. Ugur Gudelek, Omer Berat Sezer. 2020

513 citations recorded by the source corpus.

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, as of today. 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.

Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Management Science and Operations Research, Time-Series & Forecasting

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Omer Berat Sezer
2. M. Ugur Gudelek
3. A. Ozbayoglu
4. Longbing Cao

In Electrical and Electronic Engineering

1. Longbing Cao
2. A. Ozbayoglu
3. M. Ugur Gudelek
4. Omer Berat Sezer
5. Weiwei Jiang

In Management Science and Operations Research

1. M. Ugur Gudelek
2. Omer Berat Sezer
3. A. Ozbayoglu
4. Longbing Cao
5. Weiwei Jiang

In Time-Series & Forecasting

1. M. Ugur Gudelek
2. Longbing Cao
3. Omer Berat Sezer
4. A. Ozbayoglu
5. Weiwei Jiang

Citations in the corpus

• Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019, background): “, interested readers can check the recent survey paper [1].”
• Data-centric Artificial Intelligence: A Survey (2023, unknown): “The past decade has witnessed dramatic progress in Artificial Intelligence (AI), which has made a profound impact in almost every domain, such as natural language processing [47], computer vision [236], recommender system [285], healthcare [161], biology [249], finance [175], and so forth.”
• AI in Finance: Challenges, Techniques, and Opportunities (2021, background): “Such modern AI technologies play increasingly critical roles in deeply understanding, modeling, analyzing, predicting, optimizing and managing complex EcoFin problems and systems [7, 42, 46, 68, 70, 73, 89, 94, 96, 112, 120, 123, 135, 138, 162].”