Abstract

The intention of the research is to examine the volatility dynamics of sustainability indices in India, namely the BSE 100 ESG Index, BSE GREENEX and BSE CARBONEX. Taking day-to-day closing price data from January 2018 to August 2024, the study analysed volatility patterns using econometric models from the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) family. The study focused on finding volatility clustering, persistence and asymmetric volatility effects using GARCH (1, 1), EGARCH (1, 1) and EGARCH (1, 1) models. The results of the GARCH (1,1) model confirm the existence of significant volatility clustering and high volatility persistence in all three sustainability indices. The EGARCH (1,1) model’s negative and significant leverage parameter (γ) shows that negative market news has a greater effect on volatility than good news of the same size. The existence of asymmetric volatility and leverage effects in the sustainability indices is further supported by the TGARCH (1,1) model implying that negative information or adverse market events generate higher volatility compared to positive news. It is concluded that ESG index outperformed better than other two indices revealing substantial volatility clustering, high persistence of shock and leverage effects during the sample period.

Keywords: GARCH Family Models, Leverage Effect, Market Return, Volatility Clustering