Methods for Gold Price Prediction Regarding Pandemics and News
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Abstract
Abstract :
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..
Description
Supervisor : Dr. Amina BELALIA / Co-Supervisor : Dr. Badia KLOUCHE
