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 …

Artificial intelligence (AI)-based models have emerged as powerful tools in financial markets,
capable of reducing investment risks and aiding in selecting highly profitable stocks by …

In a multi-objective setting, a portfolio manager's highly consequential decisions can benefit
from assessing alternative forecasting models of stock index movement. The present …

The case of features selection plays an important role in fine-tuning the prediction capacity
of machine learning models. This paper reviews the different scenarios with three sets of …

Many studies have been proposed to prove that technical analysis can help investors make
trading decisions. The moving average (MA) is a widely used technical indicator that plays …

Cryptocurrency has become a popular trading asset due to its security, anonymity, and
decentralization. However, predicting the direction of the financial market can be …

Forecasting the stock market trend and movement is a challenging task due to multiple
factors, including the stock's natural volatility and nonlinearity. It concerns discovering the …

This paper presents a method for creating Forex market predictive models using multi-agent
and fuzzy systems, which have the objective of simulating the interactions that provoke …

Computational intelligence and machine learning techniques have been widely considered
for a variety of domains, including financial and data analysis applications. Stock market …

In this study, we propose a predictive model TabLSTM that combines machine learning
methods such as TabNet and Long Short-Term Memory Neural Network (LSTM) with a …