International Journal For Multidisciplinary Research

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Comparative Predictive Performance of GARCH, EGARCH and TGARCH Models for Retail Gold Prices in India – Evidences from Daily Retail Gold Price Data in India, 2014 - 2025

Author(s) Rajib Bhattacharya
Country India
Abstract This study models and forecasts the volatility dynamics of retail gold prices in India using three advanced econometric frameworks—GARCH, EGARCH, and TGARCH—to examine volatility persistence, asymmetry, and predictive accuracy. Using daily retail gold price data from 2014 to 2025, the paper investigates whether asymmetric extensions of the GARCH model better capture leverage effects and nonlinear responses to market shocks. The research employs Maximum Likelihood Estimation (MLE) for parameter estimation and applies rigorous diagnostic testing, including the Ljung–Box Q-statistic, ARCH–LM test, and Jarque–Bera test, to ensure model adequacy.
The empirical analysis reveals that while all three models effectively capture volatility clustering and persistence—a stylized fact of financial and commodity markets—the asymmetric models, EGARCH and TGARCH, exhibit superior forecasting performance. The EGARCH model achieves the lowest Mean Absolute Percentage Error (MAPE) of 4.66%, followed by TGARCH (4.69%) and standard GARCH (4.76%). This indicates that models incorporating asymmetric responses to positive and negative shocks provide more accurate and economically meaningful forecasts of volatility. The EGARCH model successfully accounts for the leverage effect, where negative news or price declines lead to disproportionately higher volatility compared to positive shocks.
The findings have substantial implications for investors, policymakers, and portfolio managers. Improved volatility forecasting enhances risk assessment, portfolio diversification, and derivative pricing strategies in volatile commodity markets. For policymakers, accurate volatility estimates support inflation management and monetary stability, as gold acts as both an investment hedge and a cultural asset in India.
Overall, the study reaffirms the empirical validity of asymmetry-based volatility models in explaining and forecasting gold price dynamics. It contributes to the econometric literature by demonstrating that asymmetric GARCH variants, particularly EGARCH, better reflect the complex behavioural and structural properties of the Indian retail gold market.
Keywords Volatility Modelling, GARCH, EGARCH, TGARCH, Gold Prices JEL Classification: C22, C58, E31, G10, Q02
Published In Volume 7, Issue 5, September-October 2025
Published On 2025-10-31
DOI https://doi.org/10.36948/ijfmr.2025.v07i05.59462
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