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 Journal of Statistics and Management Systems cover
Hybrid ·Peer-reviewed·ISSN (Online): 2169-0014·ISSN (Print): 0972-0510

Monthly Journal: Publishes peer-reviewed aticles on theoretical and applied statistics and management systems, expoloring industrial statistics, actuarial and decision sciences.

Issues up to 2022 co-published with and available at:Taylor & Francis Online
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Open Access Research Article

Implementing LSTM models for forecasting gold prices and analyzing volatility

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pp. 1085–1094Vol. 27Issue 5July 2024DOI: 10.47974/JSMS-1350XML
Received:
09 May 2024
Published Online:
05 Aug 2024
Article type:
Research Article
Language:
EN
Article no.:
JSMS-1350
Pages:
1085–1094

Abstract

Stochastic volatility analysis is a sophisticated method for forecasting gold prices, accounting for the fact that volatility which is the degree of variation in gold prices is not constant over time but rather fluctuates unpredictably. This approach can be particularly effective because gold prices are often subject to sudden and unpredictable changes due to various economic, political, and market factors. Different statistical and machine learning models are available to predict the Gold price such as ARIMA, GARCH, SVM, Random Forest, GRU and CNN. In this paper LSTM model is implemented to forecast the Gold Price on the basis of 10 years of data from January 2013 to July 2023. Ater the implementation the value of Mean Absolute Error obtained is 1775.6294. In the future, this model can be extended to different versions of LSTM.

Keywords

Subject Classifications

68T05

References

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