{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,12,22]],"date-time":"2022-12-22T06:04:17Z","timestamp":1671689057640},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643683683","type":"print"},{"value":"9781643683690","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,12,13]],"date-time":"2022-12-13T00:00:00Z","timestamp":1670889600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,12,13]]},"abstract":"<jats:p>With the rapid development of economy, investment has become a hot word. Many people hope to find an investment method to make profits. Many investment methods such as stocks, wealth management and funds have emerged. In the process of investment, forecasting the trend of investment products is one of the most important links. This paper analyzes the time series of APPLE, AMERICAN AIRLINES and AMD based on ARMA-GARCH model, and evaluates the model according to AIC, BIC, HQIC and other indicators to select the optimal model. The research results show that ARMA (3,2) \u2013 GARCH (1,1) model is applicable to APPLE stock logarithmic profit Prediction, ARMA (2,2) model is applicable to AMERICAN AIRLINES stock logarithmic profit prediction, and ARMA (2,2) \u2013 GARCH (1,1) is applicable to AMD stock logarithmic profit prediction.<\/jats:p>","DOI":"10.3233\/faia220575","type":"book-chapter","created":{"date-parts":[[2022,12,21]],"date-time":"2022-12-21T08:03:33Z","timestamp":1671609813000},"source":"Crossref","is-referenced-by-count":0,"title":["Prediction and Analysis of Stock Logarithmic Returns Based on ARMA-GARCH Model"],"prefix":"10.3233","author":[{"given":"Hao","family":"Qi","sequence":"first","affiliation":[{"name":"School of Mathematics and Big Data, Chongqing University of Arts and Sciences, China"}]},{"given":"Yuanshen","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Mathematics and Big Data, Chongqing University of Arts and Sciences, China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Proceedings of CECNet 2022"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA220575","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,21]],"date-time":"2022-12-21T08:03:34Z","timestamp":1671609814000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA220575"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,13]]},"ISBN":["9781643683683","9781643683690"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia220575","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,13]]}}}