Feature selection for stock price prediction: a critical review. (27th October 2022)

• Record Type: Journal Article
• Authors: Kumari, Binita; Patnaik, Srikanta; Swarnkar, Tripti
• Is Part Of: International journal of intelligent enterprise. Volume 10:Number 1(2023)
• Page Start: 48
• Page End: 72
• Publication Date: 2022-10-27
• Subjects: features -- feature selection -- stock price prediction; Organizational learning -- Periodicals; Knowledge management -- Periodicals; Business intelligence -- Periodicals; Business enterprises -- Design -- Periodicals; Organizational effectiveness -- Periodicals; 658.005
• Languages: English
• ISSNs: 1745-3232

Abstract

Stock price prediction has drawn huge attention due to its impact on economic stability. Accurate stock price prediction is highly essential to reduce the risk associated with it so as to decide good investment strategies. There are various factors influencing the prediction of stock indices namely gross margin, exchange rate, inflation rate, relative index and so on. Feature selection plays a vital role in effective and accurate prediction of stock indices. This paper aims to provide a clear review of widely used features affecting the stock price fluctuations, feature selection techniques and prediction models from the recent literature. The study also highlights the future directions in this domain focusing the enhancement of the prediction performance.