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Methods for Gold Price Prediction Regarding Pandemics and News

dc.contributor.authorBELAMBRI, SAmy
dc.date.accessioned2023-10-15T08:24:25Z
dc.date.available2023-10-15T08:24:25Z
dc.date.issued2023
dc.descriptionSupervisor : Dr. Amina BELALIA / Co-Supervisor : Dr. Badia KLOUCHEen_US
dc.description.abstractAbstract : Forecasting the price of gold on the stock market is a difficult assignment that can have substantial repercussions for investors and experts of financial markets. The accuracy and efficiency of financial time series forecasting has seen a revolutionary change in recent years as a result of the incorporation of machine learning (ML), deep learning (DL), sentiment analysis, and a wide range of other elements. This research seeks to give a thorough and state-of-the-art examination of stock market price predictions by combining a variety of methodologies. These methodologies include ML and DL approaches, sentiment analysis, and external events such as pandemics, conflicts, and news..en_US
dc.identifier.urihttps://repository.esi-sba.dz/jspui/handle/123456789/480
dc.language.isoenen_US
dc.subjectDeep Learningen_US
dc.subjectMachine Learningen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectTime Seriesen_US
dc.subjectTechnical Analysisen_US
dc.subjectFinancial Forecastingen_US
dc.subjectLSTMen_US
dc.subjectBiLSTMen_US
dc.subjectCNNen_US
dc.subjectStock Marketen_US
dc.subjectGold Priceen_US
dc.subjectSentiment Analysisen_US
dc.titleMethods for Gold Price Prediction Regarding Pandemics and Newsen_US
dc.typeThesisen_US

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