The stock market is characterized by extreme fluctuations, non-linearity, and shifts in internal
and external environmental variables. Artificial intelligence (AI) techniques can detect such …

In a business environment with strict competition among firms, accurate demand forecasting
is not straightforward. In this paper, a forecasting method is proposed, which has a strong …

Under the background of big data and Internet finance, quantitative investment is becoming
more and more critical, and the prediction of the stock price has become the focus of …

This work contributes to this ongoing debate on the nature and the characteristics of
propagation channels of crash events in international stock markets. Specifically, we …

` MACHINE LEARNING FOR STOCK MARKET FORECASTING: A REVIEW OF MODELS AND
ACCURACY Page 1 Finance & Accounting Research Journal, Volume 6, Issue 2, February 2024 …

Accurate prediction of the seawater intrusion extent is necessary for many applications, such
as groundwater management or protection of coastal aquifers from water quality …

An accurate forecasting model for the price volatility of minerals plays a vital role in future
investments and decisions for mining projects and related companies. In this paper, a hybrid …

Stock price prediction is a complex and difficult task due to the chaotic behavior and high
uncertainty in stock market prices. The design of a highly accurate, simple and intelligible …

In this paper, an application of the Bayesian classifier for short-term stock trend prediction is
presented. In order to use Bayesian classifier effectively, we transform the daily stock price …

This paper enters the ongoing volatility forecasting debate by examining the ability of a wide
range of Machine Learning methods (ML), and specifically Artificial Neural Network (ANN) …