Skip navigation
Please use this identifier to cite or link to this item: https://repository.esi-sba.dz/jspui/handle/123456789/481
Full metadata record
DC FieldValueLanguage
dc.contributor.authorBELAMBRI, SAmy-
dc.date.accessioned2023-10-15T08:29:41Z-
dc.date.available2023-10-15T08:29:41Z-
dc.date.issued2023-
dc.identifier.urihttps://repository.esi-sba.dz/jspui/handle/123456789/481-
dc.descriptionSupervisor : Dr. Badia KLOUCHE / Co-Supervisor : Dr. Amina BELALIAen_US
dc.description.abstractAbstract : Predicting the stock market, and especially the price of gold, is a hard job that involves economics, computer science, and a number of outside factors. It is a well-known subset of artificial intelligence for researchers in finance. It gets a lot of attention in school and the finance industry because it has so many uses and has a big effect. Researchers in machine learning have made a lot of models and released a lot of studies in this field, most of which are about predicting financial time series. In the past few years, deep learning models have become strong tools that work better than traditional machine learning methods. Building on this progress, the goal of this project is to use deep learning techniques to make a complete model for predicting the price of gold and then compare its accuracy to that of more standard forecasts methods. The project’s goal is to make correct predictions about the price of gold by taking into account things like historical data, market emotion, and outside events like pandemics, wars, and news. To do this, methods for machine learning and deep learning will be used to look at past data on gold prices and find patterns and trends. Also, a sentiment study will be done to find out how the market feels and how outside factors affect gold rates. By taking these things into account, a whole-person method to predicting the price of gold is created. The answer that is put into place will use the latest web technologies to build an easyto- use tool for getting to and seeing the gold price forecasts. This tool will give users useful information and help them make smart investment choices based on predicted gold prices and research of public opinion, pandemics, wars, and news. In short, the goal of this project is to use machine learning, deep learning, emotion analysis, and a number of outside factors to make an accurate and complete model for predicting stock market gold rates. By looking at past data, market mood, and outside events, the goal is to give buyers useful information and help them make better decisions.en_US
dc.language.isoenen_US
dc.subjectDeep Learningen_US
dc.subjectMachine Learningen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectStock Marketen_US
dc.subjectGold Priceen_US
dc.subjectNewsen_US
dc.subjectCovid 19en_US
dc.subjectTradingen_US
dc.subjectTime Seriesen_US
dc.subjectTechnical Analysisen_US
dc.subjectFinancial Forecastingen_US
dc.subjectLSTMen_US
dc.subjectCNNen_US
dc.subjectBiLSTMen_US
dc.subjectPAXGUSDTen_US
dc.subjectBerten_US
dc.subjectTextBloben_US
dc.subjectDjangoen_US
dc.subjectSentiment Analysisen_US
dc.subjectNestJsen_US
dc.subjectFlutteren_US
dc.titleEnhancing gold price forecasting using deep learning technique insights from pandemics and news data.en_US
dc.typeThesisen_US
Appears in Collections:Ingénieur

Files in This Item:
File Description SizeFormat 
PFE-1-1.pdf53,96 kBAdobe PDFView/Open
Show simple item record


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.