Volatility Spillover between Gold Prices and the Indian Stock Market: Evidence from Time-Series Econometrics and Machine Learning
Affiliation
| DOI | https://doi.org/10.67313/stanzaleafbookchapter.2026.20 Registered |
| Published In | INSURING EMERGING RISKS ADDRESSING PANDEMICS CYBER ATTACKS AND POLITICAL ISSUES |
| Book Editors | Ramya A J. Deepak Kumar K.M. Anitha R. Srikala J. Chandhini |
| ISBN | 978-81-687720-2-1 |
| Pages | 127-136 |
| Publication Date | 17 July 2026 |
| Publisher | Stanzaleaf Publication |
Abstract
Gold is widely regarded as a safe-haven asset that helps hedge against stock market uncertainty,
particularly during periods of economic instability. This study examines the volatility spillover
between gold prices and the Indian stock market using daily data from January 2015 to December
2024. Time-series econometric techniques, including ADF, VAR, Granger causality, and GARCH
(1,1), are employed to analyze return dynamics and volatility transmission. Machine learning
models such as Random Forest, XGBoost, and LSTM are used to forecast market volatility and
compare predictive performance. The findings reveal significant volatility spillovers between gold
and equity markets, with LSTM providing the highest forecasting accuracy. The study offers useful
insights for investors, portfolio managers, and policymakers in improving diversification and risk
management strategies.
Keywords
Gold Prices, Indian Stock Market, Volatility Spillover, GARCH, Machine Learning, LSTM, Random Forest, Financial Markets