We introduce a comprehensive analysis of several approaches used in stock price
forecasting, including statistical, machine learning, and deep learning models. The …

Stock price prediction remains a complex challenge in financial markets. This study
introduces a novel Long Short-Term Memory (LSTM) model optimized by Sand Cat Swarm …

The Indian stock market is an emerging market that has outperformed other significant
markets like the US, UK, and Japan, providing a return of 19 percent, the highest in the …

The research community's treatise on computational economics and financial models has
promising interest for the exploration and exploitation of artificial intelligence (AI)-based …

Purpose Integrating artificial intelligence and quantitative investment has given birth to
various agricultural futures price prediction models suitable for nonlinear and non-stationary …

Accurate carbon price prediction can help save energy and reduce emissions worldwide.
Thus, this paper proposes a model that combines swarm intelligence algorithms with deep …

Research has substantiated that the presence of outliers in data usually introduces
additional errors and biases, which typically leads to a degradation in the precision of …

The prediction of the stock market offers information for the business to increase the profit in
the share market. The prediction of a stock's price is a challenging task because of the non …

To overcome the limitations of single-type intelligent optimization algorithms prone to
becoming stuck in local optima for complex problems, a hybrid intelligent optimization …

In the world of finance, every investment is intended to maximize profits and minimize
related risks. Financial market predictions have been a challenging task for researchers due …