An Empirical Investigation of the Volatility Dynamics of SENSEX and GREENEX Using the GARCH Model

Purpose: This study aims to analyse the volatility dynamics of two key Indian stock market indices—SENSEX and GREENEX—by employing GARCH-type models. The objective is to compare the volatility behaviour between the traditional market index (SENSEX) and the sustainability-focused index (GREENEX), thereby providing insights into the risk–return profiles of conventional versus green investments in the Indian financial market. Design/Methodology: The research utilises the GARCH (1,1), EGARCH (1,1) and TGARCH (1,1) models to assess the volatility patterns of the SENSEX and GREENEX indices over a period spanning January 2013 to December 2023. Stationarity of the time series is verified using the augmented Dickey–Fuller (ADF) test. The GARCH models are then applied to capture volatility persistence, clustering effects and asymmetric responses to both positive and negative market shocks for each index. Findings: The results demonstrate significant volatility clustering and persistence in both indices, with the GARCH (1,1) model indicating that volatility shocks in SENSEX and GREENEX tend to persist over time. The EGARCH model highlights asymmetries in volatility, particularly for GREENEX, where negative shocks have a larger impact on future volatility compared to positive shocks. The TGARCH model confirms the presence of leverage effects, with SENSEX exhibiting a more pronounced reaction to negative shocks. Overall, GREENEX shows relatively lower downside risk, making it a potentially more stable option compared to SENSEX. Research Limitations: Additionally, the analysis could be expanded by including macroeconomic variables such as inflation, interest rates and oil prices. Future studies might also apply advanced volatility models such as FIGARCH or DCC-GARCH for robustness. While SENSEX and GREENEX were chosen to represent traditional and sustainable finance, other indices and macroeconomic variables were not included, potentially limiting the scope. Additionally, factors such as liquidity, investor behaviour and the impact of extraordinary events like COVID-19 were not explicitly addressed, which may influence volatility patterns. Value: This study offers valuable insights into the volatility characteristics of both traditional and green investments in India. By comparing the volatility behaviour of SENSEX and GREENEX, it enlightens investors, policymakers and researchers about the risk dynamics of sustainable investments. The outcomes provide practical implications for portfolio management, investment strategies and risk assessment, highlighting the growing importance of green finance in the Indian market.

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Publication Details

Journal
Asia-Pacific Journal of Management Research and Innovation
Published
2025-12-01
DOI
https://doi.org/10.1177/2319510x251408575
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
0.00
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article

An Empirical Investigation of the Volatility Dynamics of SENSEX and GREENEX Using the GARCH Model

Sana Beg, Vardah Saghir, Saba Abid
Asia-Pacific Journal of Management Research and Innovation
Market Dynamics and Volatility
article

An Empirical Investigation of the Volatility Dynamics of SENSEX and GREENEX Using the GARCH Model

Sana Beg, Vardah Saghir, Saba Abid
article en

Abstract

Purpose: This study aims to analyse the volatility dynamics of two key Indian stock market indices—SENSEX and GREENEX—by employing GARCH-type models. The objective is to compare the volatility behaviour between the traditional market index (SENSEX) and the sustainability-focused index (GREENEX), thereby providing insights into the risk–return profiles of conventional versus green investments in the Indian financial market. Design/Methodology: The research utilises the GARCH (1,1), EGARCH (1,1) and TGARCH (1,1) models to assess the volatility patterns of the SENSEX and GREENEX indices over a period spanning January 2013 to December 2023. Stationarity of the time series is verified using the augmented Dickey–Fuller (ADF) test. The GARCH models are then applied to capture volatility persistence, clustering effects and asymmetric responses to both positive and negative market shocks for each index. Findings: The results demonstrate significant volatility clustering and persistence in both indices, with the GARCH (1,1) model indicating that volatility shocks in SENSEX and GREENEX tend to persist over time. The EGARCH model highlights asymmetries in volatility, particularly for GREENEX, where negative shocks have a larger impact on future volatility compared to positive shocks. The TGARCH model confirms the presence of leverage effects, with SENSEX exhibiting a more pronounced reaction to negative shocks. Overall, GREENEX shows relatively lower downside risk, making it a potentially more stable option compared to SENSEX. Research Limitations: Additionally, the analysis could be expanded by including macroeconomic variables such as inflation, interest rates and oil prices. Future studies might also apply advanced volatility models such as FIGARCH or DCC-GARCH for robustness. While SENSEX and GREENEX were chosen to represent traditional and sustainable finance, other indices and macroeconomic variables were not included, potentially limiting the scope. Additionally, factors such as liquidity, investor behaviour and the impact of extraordinary events like COVID-19 were not explicitly addressed, which may influence volatility patterns. Value: This study offers valuable insights into the volatility characteristics of both traditional and green investments in India. By comparing the volatility behaviour of SENSEX and GREENEX, it enlightens investors, policymakers and researchers about the risk dynamics of sustainable investments. The outcomes provide practical implications for portfolio management, investment strategies and risk assessment, highlighting the growing importance of green finance in the Indian market.

Asia-Pacific Journal of Management Research and InnovationVol. 21(4)
Jamia Hamdard (IN)
Openalex Percentile: Top 17%
Market Dynamics and Volatility
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