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Journal of Statistics and Management Systems

(Since 1998)
Open Access ·Peer-reviewed·ISSN (Online): 2169-0014·ISSN (Print): 0972-0510
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The Journal of Statistics and Management Systems (JSMS) is a world leading journal publishing high quality, rigorously peer-reviewed original research on theoretical and applied statistics and management systems since 1998. The scope is intentionally broad, but papers must make a novel contribution to the field to be considered for publication. Topics include, but are not limited to, the following: • Statistics • Applied Statistics • Industrial Statistics • Statistical Inference • Interdisciplinary role of Statistics • Actuarial Sciences • Decision Sciences • Managerial Aspects • Management Sciences • Management Information Systems

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Journal of Statistics and Management Systems
Open Access Research Article

Analyzing forecasting capabilities of GARCH models for stock prices in stochastic volatility contexts

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pp. 1065–1084Vol. 27Issue 5July 2024DOI: 10.47974/JSMS-1349XML
Received:
08 May 2024
Published Online:
05 Aug 2024
Article type:
Research Article
Language:
EN
Article no.:
JSMS-1349
Pages:
1065–1084

Abstract

Gold, a highly valued and sought-after asset, has long captured the interest of investors, financial analysts, and policymakers due to its historical significance. To predict future gold prices, this study uses the Generalised Autoregressive Conditional Heteroskedasticity (GARCH) model. The GARCH model is implemented in R Studio, and this study’s findings provide valuable insights for investors, equipping them with informed decision-making capabilities and robust risk management strategies. The precise gold price forecasting achieved through the GARCH method highlights its reliability in financial prediction. This research also adds to the body of knowledge already available on gold price forecasting and provides a basis for investigating alternative models and incorporating macroeconomic aspects to improve prediction accuracy. Three versions of GARCH model are compared namely: GJR-GARCH, EGARCH, and standard GARCH. The implications shows that EGARCH model showed promising results, there is scope for further research and validation. Continual refinement and testing of the model’s assumptions and parameters are essential to ensure its reliability and applicability in different market conditions.

Keywords

Gold priceGARCHEHARCH and GJR GARCH

Subject Classifications

68Q10

References

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