An Empirical Comparative Analysis of the Gold Market Dynamics of the Indian and U.S. Commodity Markets

Swaty Sharma, Munish Gupta, Simon Grima () and Kiran Sood
Additional contact information
Swaty Sharma: Mittal School of Business, Lovely Professional University, Jalandhar-Delhi G.T. Road, Phagwara 144411, Punjab, India
Munish Gupta: University School of Business, Chandigarh University, NH-95/NH-5, Chandigarh-Ludhiana Highway, Gharuan, Mohali 140413, Punjab, India
Simon Grima: Department of Insurance and Risk Management, Faculty of Economics, Management and Accountancy, University of Malta, MSD 2080 Msida, Malta
Kiran Sood: Chitkara Business School, Chitkara University, Chandigarh-Patiala National Highway (NH-64/NH-7), Jhansla Village, Rajpura Tehsil, Patiala District, Chandigarh 140401, Punjab, India

JRFM, 2025, vol. 18, issue 10, 1-18

Abstract: This study examines the dynamic relationship between the gold markets of India and the United States from 2005 to 2025. Recognising gold’s role as a hedge and safe-haven during market uncertainty, we employ the Autoregressive Distributed Lag (ARDL) model to assess long-term co-integration and apply the Toda–Yamamoto causality test to evaluate directional influences. Additionally, the Generalised Autoregressive Conditional Heteroskedasticity (GARCH) (1, 1) model is applied to examine volatility spillovers. Results reveal no long-term co-integration between the two markets, suggesting they function independently over time. However, unidirectional causality is observed from the U.S. to the Indian gold market, and the GARCH model confirms bidirectional volatility transmission, indicating interconnected short-run dynamics. These findings imply that gold market shocks in one country may affect short-term pricing in the other, but not long-term trends. From a portfolio diversification and risk management perspective, investors may benefit from allocating assets across both markets. This study contributes a novel empirical framework by integrating ARDL, Toda–Yamamoto Granger causality, and GARCH(1, 1) models over a two-decade period (2005–2025), incorporating post-COVID market dynamics. The combination of these methods, applied to both an emerging (India) and developed (U.S.) economy, provides a comprehensive understanding of gold market interdependence. In doing this, the paper offers valuable insights into causality, volatility transmission, and diversification potential. The econometric rigour of the study is enhanced through residual diagnostic tests, including tests of normality, autocorrelation, and other heteroscedasticity tests, as well as VAR stability tests. These ensure strong inference and model validity; more specifically, they are pertinent to the analysis of financial time series.

Keywords: gold; ARDL; Toda–Yamamoto; Granger causality; GARCH(1, 1); integration (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1911-8074/18/10/543/pdf (application/pdf)
https://www.mdpi.com/1911-8074/18/10/543/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jjrfmx:v:18:y:2025:i:10:p:543-:d:1758200

Access Statistics for this article

JRFM is currently edited by Ms. Chelthy Cheng

More articles in JRFM from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().