In this literature review, we investigate machine learning techniques that are applied for
stock market prediction. A focus area in this literature review is the stock markets …

The financial sector has greatly impacted the monetary well-being of consumers, traders,
and financial institutions. In the current era, artificial intelligence is redefining the limits of the …

In stock market forecasting, the identification of critical features that affect the performance of
machine learning (ML) models is crucial to achieve accurate stock price predictions. Several …

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 …

Many researchers attempt to accurately predict stock price trends using technologies such
as machine learning and deep learning to achieve high returns in the stock market …

It has been evidenced by numerous studies that irrational investor sentiment is one of the
critical factors leading to dramatic volatility in financial market prices. Therefore, how to …

Abstract Interferometric Synthetic Aperture Radar (InSAR) is a highly effective and widely
used approach for monitoring large-scale ground deformation. The precise and timely …

Stock market plays a vital role in a country's economy, serving as a platform for companies to
raise capital and enabling investors to share in their growth and success. The market is very …

Prediction with higher accuracy is vital for stock market prediction. Recently, considerable
amount of effort has been poured into employing machine learning (ML) techniques for …

The transformer architecture with its attention mechanism is the state-of-the-art deep
learning method for sequence learning tasks and has achieved superior results in many …