Ai in finance: challenges, techniques, and opportunities

L Cao - ACM Computing Surveys (CSUR), 2022 - dl.acm.org
AI in finance refers to the applications of AI techniques in financial businesses. This area has
attracted attention for decades, with both classic and modern AI techniques applied to …

[HTML][HTML] How are reinforcement learning and deep learning algorithms used for big data based decision making in financial industries–A review and research agenda

V Singh, SS Chen, M Singhania, B Nanavati… - International Journal of …, 2022 - Elsevier
Data availability and accessibility have brought in unseen changes in the finance systems
and new theoretical and computational challenges. For example, in contrast to classical …

Machine learning-aided operations and communications of unmanned aerial vehicles: A contemporary survey

H Kurunathan, H Huang, K Li, W Ni… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Over the past decade, Unmanned Aerial Vehicles (UAVs) have provided pervasive, efficient,
and cost-effective solutions for data collection and communications. Their excellent mobility …

Data science in economics: comprehensive review of advanced machine learning and deep learning methods

S Nosratabadi, A Mosavi, P Duan, P Ghamisi, F Filip… - Mathematics, 2020 - mdpi.com
This paper provides a comprehensive state-of-the-art investigation of the recent advances in
data science in emerging economic applications. The analysis is performed on the novel …

An application of deep reinforcement learning to algorithmic trading

T Théate, D Ernst - Expert Systems with Applications, 2021 - Elsevier
This scientific research paper presents an innovative approach based on deep
reinforcement learning (DRL) to solve the algorithmic trading problem of determining the …

Machine learning for quantitative finance applications: A survey

F Rundo, F Trenta, AL Di Stallo, S Battiato - Applied Sciences, 2019 - mdpi.com
Featured Application The described approaches can be used in various applications in the
field of quantitative finance from HFT trading systems to financial portfolio allocation and …

A multi-layer and multi-ensemble stock trader using deep learning and deep reinforcement learning

S Carta, A Corriga, A Ferreira, AS Podda… - Applied …, 2021 - Springer
The adoption of computer-aided stock trading methods is gaining popularity in recent years,
mainly because of their ability to process efficiently past information through machine …

A systematic study on reinforcement learning based applications

K Sivamayil, E Rajasekar, B Aljafari, S Nikolovski… - Energies, 2023 - mdpi.com
We have analyzed 127 publications for this review paper, which discuss applications of
Reinforcement Learning (RL) in marketing, robotics, gaming, automated cars, natural …

Data science and AI in FinTech: An overview

L Cao, Q Yang, PS Yu - International Journal of Data Science and …, 2021 - Springer
Financial technology (FinTech) has been playing an increasingly critical role in driving
modern economies, society, technology, and many other areas. Smart FinTech is the new …

A multi-agent reinforcement learning framework for optimizing financial trading strategies based on timesnet

Y Huang, C Zhou, K Cui, X Lu - Expert Systems with Applications, 2024 - Elsevier
An increasing number of studies have shown the effectiveness of using deep reinforcement
learning to learn profitable trading strategies from financial market data. However, a single …