Stock market prediction has been a classical yet challenging problem, with the attention from
both economists and computer scientists. With the purpose of building an effective prediction …

How can we efficiently correlate multiple stocks for accurate stock movement prediction?
Stock movement prediction has received growing interest in data mining and machine …

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 …

News dissemination in social media causes fluctuations in financial markets.(Scope) Recent
advanced methods in deep learning-based natural language processing have shown …

Stock movement forecasting is usually formalized as a sequence prediction task based on
time series data. Recently, more and more deep learning models are used to fit the dynamic …

Stock trend prediction is a challenging task due to the non-stationary dynamics and complex
market dependencies. Existing methods usually regard each stock as isolated for prediction …

Using machine learning coupled with stock price data to predict stock price trends has
attracted increasing attention from data mining and machine learning communities. An …

Using sentiment information in the analysis of financial markets has attracted much attention.
Natural language processing methods can be used to extract market sentiment information …

Stock movements prediction is a highly challenging study for research and industry. Using
social media for stock movements prediction is an effective but difficult task. However, the …

Stock Movement Prediction (SMP) aims at predicting listed companies' stock future price
trend, which is a challenging task due to the volatile nature of financial markets. Recent …