News-based intelligent prediction of financial markets using text mining and machine learning: A systematic literature review
Researchers and practitioners have attempted to predict the financial market by analyzing
textual (eg, news articles and social media) and numeric data (eg, hourly stock prices, and …
textual (eg, news articles and social media) and numeric data (eg, hourly stock prices, and …
Artificial intelligence applied to stock market trading: a review
The application of Artificial Intelligence (AI) to financial investment is a research area that
has attracted extensive research attention since the 1990s, when there was an accelerated …
has attracted extensive research attention since the 1990s, when there was an accelerated …
Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process
The stock market has performed one of the most important functions in a laissez-faire
economic system by gathering people, companies, and flows of money for several centuries …
economic system by gathering people, companies, and flows of money for several centuries …
Predicting stock market trends using machine learning and deep learning algorithms via continuous and binary data; a comparative analysis
The nature of stock market movement has always been ambiguous for investors because of
various influential factors. This study aims to significantly reduce the risk of trend prediction …
various influential factors. This study aims to significantly reduce the risk of trend prediction …
Stock price prediction using deep learning and frequency decomposition
Nonlinearity and high volatility of financial time series have made it difficult to predict stock
price. However, thanks to recent developments in deep learning and methods such as long …
price. However, thanks to recent developments in deep learning and methods such as long …
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 …
Prediction of stock market index based on ISSA-BP neural network
X Liu, J Guo, H Wang, F Zhang - Expert Systems with Applications, 2022 - Elsevier
Stock market index forecasting is a very tempting topic. Appropriate analysis of such a topic
will provide valuable insights for investors, traders and policymakers in the appealing stock …
will provide valuable insights for investors, traders and policymakers in the appealing stock …
Application of deep learning models for automated identification of Parkinson's disease: A review (2011–2021)
Parkinson's disease (PD) is the second most common neurodegenerative disorder affecting
over 6 million people globally. Although there are symptomatic treatments that can increase …
over 6 million people globally. Although there are symptomatic treatments that can increase …
Long-term wind power forecasting using tree-based learning algorithms
The intermittent and uncertain nature of wind places a premium on accurate wind power
forecasting for the reliable and efficient operation of power grids with large-scale wind power …
forecasting for the reliable and efficient operation of power grids with large-scale wind power …
Predicting shear wave velocity from conventional well logs with deep and hybrid machine learning algorithms
Shear wave velocity (VS) data from sedimentary rock sequences is a prerequisite for
implementing most mathematical models of petroleum engineering geomechanics …
implementing most mathematical models of petroleum engineering geomechanics …