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Motivated by this, this paper presents an innovation model known as the uncertain autoregressive conditional heteroskedasticity model to capture the volatility of variance in financial time series, thereby enhancing the understanding of market dynamics and risk assessment. As a complement the modeling process, a potent method is proposed to test whether a time series has an uncertain autoregressive conditional heteroskedasticity effect. Furthermore, this paper delineates a comprehensive new prediction process tailored for time series that exhibit the uncertain autoregressive conditional heteroskedasticity effect. Finally, two real data examples are proposed to the practical application and efficacy of the proposed method.<\/jats:p>","DOI":"10.1142\/s175289092550014x","type":"journal-article","created":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T01:59:24Z","timestamp":1749002364000},"source":"Crossref","is-referenced-by-count":0,"title":["Uncertain Autoregressive Conditional Heteroskedasticity Model with Application in Financial Market"],"prefix":"10.1142","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-7368-4907","authenticated-orcid":false,"given":"Yujiao","family":"Han","sequence":"first","affiliation":[{"name":"School of Economics, Ocean University of China, Qingdao 266100, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5739-1610","authenticated-orcid":false,"given":"Yue","family":"Xin","sequence":"additional","affiliation":[{"name":"School of Economics, Ocean University of China, Qingdao 266100, P. R. 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