This study presents a comprehensive bibliometric analysis of 132 articles from the Scopus database, specifically examining the forecasting of gold prices.
Authors
Sarveshwar Kumar Inani, Assistant Professor, Jindal Global Business School, O.P. Jindal, Global University, Sonipat, Haryana, India.
Gaurav Kabra, Associate Professor, Jindal Global Business School, O.P. Jindal, Global University, Sonipat, Haryana, India.
Arun Balodi, Electronics and Communication, Engineering Department, Atria Institute of Technology, Bengaluru, Karnataka, India.
Vaishali Pagaria, Academic Consultant, Southern New Hampshire University, Manchester, New Hampshire, United States (USA).
Summary
This study presents a comprehensive bibliometric analysis of 132 articles from the Scopus database, specifically examining the forecasting of gold prices. It explores publication trends, prominent journals, influential authors, institutions, and countries in the field.
The findings provide valuable insights into the evolution and trends within this domain, guiding researchers in identifying reputable journals for publication. Future research can focus on developing advanced neural network models to accurately capture complex patterns in gold price forecasting, including new architectures, optimization techniques, and additional variables.
Integrating sentiment analysis techniques, such as natural language processing and social media analysis, can enhance the incorporation of emotions and market sentiments.
Published in: 2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology (ICSEIET)
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