Stock market volatility may be a function of company, industry, or world over information made public. The present study has investigated the volatility of Indian banking sectoral indices with the general banking index for two shocking events: the Sub-prime crisis and COVID-19. A comparative analysis of both the shocks leading to these indices’ volatility has been conducted using symmetric and asymmetric models. This study’s findings show that these indices’ volatile behaviour has been strong enough to persist in the market with the leverage effect present during the sub-prime crisis. This effect disappeared for Nifty Bank Indices and Private Sector Bank Indices as compared to Public Sector Undertaking Bank Indices during COVID-19 (probably because the pandemic is not over yet). With GARCH and EGARCH models, the study suggests that the investors may use the diversification approach, in the long run, to safeguard their portfolio values to survive from global shocks.

The possibility of including financial instruments, such as equity, debt, derivative and market-based funds, in a portfolio varies with their market sensitivity. Cryptocurrency (crypto) has been of recent origin and interest to investors and policymakers. The study has attempted to explore opportunities for Indian and international investors in equity and crypto markets. Bivariate analysis between the crypto index and Indian market indices revealed few causal linkages between crypto and other indices. Standard VAR and Granger causality have been used for exploring the association between the variables. DCC-GARCH has been applied for checking further on volatility spillover and the relationship between indices. Granger results indicate the presence of linkages between crypto and energy, media, and oil & gas indices. However, spillover results have shown an absence of such linkages in the short run but a significant presence in the long run except for a few indices.

We examine the inter-relationship between India, the USA, Japan, China, France, Dubai and Germany using multivariate co-integration techniques. The study has investigated co-movements between these world indices from 2009 to 2018. During this period, it was found using Johansen co-integration that these indices were co-integrated in the long run. However, in the vector error correction model, long-run causality could not be found. Thereafter with Wald-χ2 diagnostics, it was found that short-run linkages existed among Indian and rest of the world markets in the study. Therefore, the seven indices may be concluded to have causal relationship in the short run and co-integrating association in the long run.

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