Transformer architectures are highly expressive because they use self-attention
mechanisms to encode long-range dependencies in the input sequences. In this paper, we …

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 …

Multivariate Time Series (MTS) forecasting plays a vital role in a wide range of applications.
Recently, Spatial-Temporal Graph Neural Networks (STGNNs) have become increasingly …

Leading graph ordinary differential equation (ODE) models have offered generalized
strategies to model interacting multi-agent dynamical systems in a data-driven approach …

Recently, large language models (LLMs) like ChatGPT have demonstrated remarkable
performance across a variety of natural language processing tasks. However, their …

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 …

Given historical stock prices and sparse tweets, how can we accurately predict stock price
movement? Many market analysts strive to use a large amount of information for stock price …

This survey presents an in-depth review of the transformative role of Natural Language
Processing (NLP) in finance, highlighting its impact on ten major financial applications:(1) …

Portfolio management is a fundamental problem in finance. It involves periodic reallocations
of assets to maximize the expected returns within an appropriate level of risk exposure …

With the continuing active research on deep learning, research on stock price prediction
using deep learning has been actively conducted in the financial industry. This paper …