Effective short-term forecasts of Saudi stock price trends using technical indicators and large-scale multivariate time series

ABSTRACT: 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 market’s hidden patterns with respect to time to enable proactive decision-making and better futuristic insights. Recurrent neural network-based methods have been a prime candidate for solving complex and nonlinear sequences, including the task of modeling multivariate time series forecasts. Due to the lack of comprehensive and reference work in short-term forecasts for the Saudi stock price and trends, this article introduces a comprehensive and accurate forecasting methodology tailored to the Saudi stock market. Two steps were configured to render effective short-term forecasts. First, a custom-built feature

SUBMITTER:  

PROVIDER: S-EPMC10280263 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature