Financial sentiment analysis: Techniques and applications

K Du, F **ng, R Mao, E Cambria - ACM Computing Surveys, 2024 - dl.acm.org
Financial Sentiment Analysis (FSA) is an important domain application of sentiment analysis
that has gained increasing attention in the past decade. FSA research falls into two main …

[HTML][HTML] Applying artificial intelligence in cryptocurrency markets: A survey

R Amirzadeh, A Nazari, D Thiruvady - Algorithms, 2022 - mdpi.com
The total capital in cryptocurrency markets is around two trillion dollars in 2022, which is
almost the same as Apple's market capitalisation at the same time. Increasingly …

Deep reinforcement learning for stock portfolio optimization by connecting with modern portfolio theory

J Jang, NY Seong - Expert Systems with Applications, 2023 - Elsevier
With artificial intelligence and data quality development, portfolio optimization has improved
rapidly. Traditionally, researchers in the financial market have utilized the modern portfolio …

[HTML][HTML] Multi-period portfolio optimization using a deep reinforcement learning hyper-heuristic approach

T Cui, N Du, X Yang, S Ding - Technological Forecasting and Social …, 2024 - Elsevier
Portfolio optimization concerns with periodically allocating the limited funds to invest in a
variety of potential assets in order to satisfy investors' appetites for risk and return goals …

Deeptrader: a deep reinforcement learning approach for risk-return balanced portfolio management with market conditions embedding

Z Wang, B Huang, S Tu, K Zhang, L Xu - Proceedings of the AAAI …, 2021 - ojs.aaai.org
Most existing reinforcement learning (RL)-based portfolio management models do not take
into account the market conditions, which limits their performance in risk-return balancing. In …

Reinforcement learning for quantitative trading

S Sun, R Wang, B An - ACM Transactions on Intelligent Systems and …, 2023 - dl.acm.org
Quantitative trading (QT), which refers to the usage of mathematical models and data-driven
techniques in analyzing the financial market, has been a popular topic in both academia and …

Multi-scale local cues and hierarchical attention-based LSTM for stock price trend prediction

X Teng, X Zhang, Z Luo - Neurocomputing, 2022 - Elsevier
Stock price trend prediction is to seek profit maximum of stock investment by estimating
future stock price tendency. Nevertheless, it is still a tough task due to noisy and non …

A multimodal foundation agent for financial trading: Tool-augmented, diversified, and generalist

W Zhang, L Zhao, H **a, S Sun, J Sun, M Qin… - Proceedings of the 30th …, 2024 - dl.acm.org
Financial trading is a crucial component of the markets, informed by a multimodal
information landscape encompassing news, prices, and Kline charts, and encompasses …

Stock movement prediction via gated recurrent unit network based on reinforcement learning with incorporated attention mechanisms

H Xu, L Chai, Z Luo, S Li - Neurocomputing, 2022 - Elsevier
The recent advances usually mine market information from the chaotic data to conduct a
stock movement prediction task. However, the current stock price movement prediction …

Crop: Certifying robust policies for reinforcement learning through functional smoothing

F Wu, L Li, Z Huang, Y Vorobeychik, D Zhao… - arxiv preprint arxiv …, 2021 - arxiv.org
As reinforcement learning (RL) has achieved great success and been even adopted in
safety-critical domains such as autonomous vehicles, a range of empirical studies have …