Empirical Understanding of the Dynamic Interconnectedness Between ESG/Green Indices and Conventional Indices in the Indian Capital Markets

Vijeta Singh, Varsha Nerlekar () and Himanshu Pate
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Vijeta Singh: Dr. Vishwanath Karad MIT World Peace University
Varsha Nerlekar: Dr. Vishwanath Karad MIT World Peace University
Himanshu Pate: Credit Analyst

A chapter in Financial Markets, Climate Risk and Renewables, 2024, pp 47-72 from Springer

Abstract: Abstract India has committed to achieving sustainable development goals by 2030 and aims to achieve net zero emissions by 2070. This rise of ESG and green stocks/indices in the capital market that are new investment alternatives alongside conventional stocks/indices indicates the new investment opportunity alongside conventional indices that align with SDG goals by 2030. These indices have witnessed modest growth since their inception in the capital markets. There has been an increased inter-connectedness (movement in volatilities and returns) amongst various ESG/green indices with other indices components of the capital markets. Using the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) model, the study examines the volatility spillover amongst ESG/green indices and benchmark stock market indices in India. The study results conclude that MGARCH conditional correlations were positive and statistically significant for all indices reported. GARCH effects were consistent across all indices, and the Granger causality test results also established causality across the index used. Further, the study confirmed structural breaks during COVID-19, and ESG/green indices were not underperforming against the conventional index.

Keywords: ESG; Green; Volatility; Conditional correlation; Indices; MGARCH; Markets; G20; G23; G11; G12; E44; G01 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/978-981-97-6687-1_12

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