Esra’a Alshabeeb, M. Aljabri, R. Mohammad, Fatemah S. Alqarqoosh, Aseel A. Alqahtani, Zainab T. Alibrahim, Najd Y. Alawad, Mashael A. Alzeer
{"title":"Intelligent Techniques for Predicting Stock Market Prices: A Critical Survey","authors":"Esra’a Alshabeeb, M. Aljabri, R. Mohammad, Fatemah S. Alqarqoosh, Aseel A. Alqahtani, Zainab T. Alibrahim, Najd Y. Alawad, Mashael A. Alzeer","doi":"10.1142/s021964922250099x","DOIUrl":null,"url":null,"abstract":"The stock market is an exciting field of interest to many people regardless of their occupational background. It is a market where individuals with adequate knowledge can join and earn an additional income. Nowadays, life expenses have increased. Hence, the number of people investing in stocks is increasing dramatically. Anyone may indeed start participating in the stock market at any time, yet it is not ensured that they will profit from this investment. The stock market is a risky field of investment, given that it is unknown whether the stock will rise or fall. Stock market prediction using Artificial Intelligence techniques is a possible way to help people anticipate stock market directions. Current research showed that many factors aid in changing the stock market value in general and specifically in the Saudi stock market. To our knowledge, most research studies only consider historical data in predicting stock market trends. However, this research aims to enhance the accuracy of the daily closing price for three Saudi stock market sectors by considering historical and sentimental data. Several intelligent algorithms are considered, and their performance indicators are discussed and contrasted against each other. This research concluded that more accurate stock market prediction models could be produced by employing historical and sentimental data.","PeriodicalId":127309,"journal":{"name":"J. Inf. Knowl. Manag.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Inf. Knowl. Manag.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s021964922250099x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The stock market is an exciting field of interest to many people regardless of their occupational background. It is a market where individuals with adequate knowledge can join and earn an additional income. Nowadays, life expenses have increased. Hence, the number of people investing in stocks is increasing dramatically. Anyone may indeed start participating in the stock market at any time, yet it is not ensured that they will profit from this investment. The stock market is a risky field of investment, given that it is unknown whether the stock will rise or fall. Stock market prediction using Artificial Intelligence techniques is a possible way to help people anticipate stock market directions. Current research showed that many factors aid in changing the stock market value in general and specifically in the Saudi stock market. To our knowledge, most research studies only consider historical data in predicting stock market trends. However, this research aims to enhance the accuracy of the daily closing price for three Saudi stock market sectors by considering historical and sentimental data. Several intelligent algorithms are considered, and their performance indicators are discussed and contrasted against each other. This research concluded that more accurate stock market prediction models could be produced by employing historical and sentimental data.