[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 …
and new theoretical and computational challenges. For example, in contrast to classical …
An overview of machine learning, deep learning, and reinforcement learning-based techniques in quantitative finance: recent progress and challenges
Forecasting the behavior of the stock market is a classic but difficult topic, one that has
attracted the interest of both economists and computer scientists. Over the course of the last …
attracted the interest of both economists and computer scientists. Over the course of the last …
[HTML][HTML] Stock price prediction with optimized deep LSTM network with artificial rabbits optimization algorithm
B Gülmez - Expert Systems with Applications, 2023 - Elsevier
The stock market is a financial market where shares of publicly listed corporations are
purchased and sold. It is an indicator of a country's economic health, reflecting the …
purchased and sold. It is an indicator of a country's economic health, reflecting the …
Three and a half decades of artificial intelligence in banking, financial services, and insurance: A systematic evolutionary review
H Herrmann, B Masawi - Strategic Change, 2022 - Wiley Online Library
The banking, financial services, and insurance (BFSI) sector is one of the earliest and most
prominent adopters of artificial intelligence (AI). However, academic research substantially …
prominent adopters of artificial intelligence (AI). However, academic research substantially …
A review on big data based on deep neural network approaches
Big data analytics has become a significant trend for many businesses as a result of the
daily acquisition of enormous volumes of data. This information has been gathered because …
daily acquisition of enormous volumes of data. This information has been gathered because …
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 …
learning to learn profitable trading strategies from financial market data. However, a single …
Genetic algorithm-based hyperparameter optimization of deep learning models for PM2.5 time-series prediction
C Erden - International Journal of Environmental Science and …, 2023 - Springer
Since air pollution negatively affects human health and causes serious diseases, accurate
air pollution prediction is essential regarding environmental sustainability. Although …
air pollution prediction is essential regarding environmental sustainability. Although …
Quantum machine learning on near-term quantum devices: Current state of supervised and unsupervised techniques for real-world applications
The past decade has witnessed significant advancements in quantum hardware,
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …
Stock market prediction via deep learning techniques: A survey
Existing surveys on stock market prediction often focus on traditional machine learning
methods instead of deep learning methods. This motivates us to provide a structured and …
methods instead of deep learning methods. This motivates us to provide a structured and …
A novel deep reinforcement learning framework with BiLSTM-Attention networks for algorithmic trading
Y Huang, X Wan, L Zhang, X Lu - Expert Systems with Applications, 2024 - Elsevier
The financial market, as a complex nonlinear dynamic system frequently influenced by
various factors, such as international investment capital, is very challenging to build trading …
various factors, such as international investment capital, is very challenging to build trading …