Modelling dependence and systemic risk between oil prices and BSE sectoral indices using stochastic copula and CoVar, ΔCoVar and MES approaches

We investigate the dependency, risk spillovers, and systemic risk between the sectoral indices returns of the Bombay stock exchange (BSE) and oil prices using recently developed empirical techniques. The dependence is modelled using the time varying Stochastic Autoregressive Copulas (SCAR). Conditional value-at-risk (CoVaR), ΔCoVaR and marginal expected shortfall (MES) measures are used to examine the systemic risk. We find rotated Gumbel and normal copulas to be the best fitting in our analysis. Sectors such as energy, power, and industrial exhibit higher persistence in dependence structure compared to other sectors. Our results reveal that the underlying forces of the dependence between oil prices with other industries vary across time, albeit not so much during stable periods, but increase remarkably during turbulent times. All sectors are affected significantly by extreme oil price movements. The average short-run MES is highest for the metals, materials, and industrials sectors. The lowest average short-run MES values are observed for the fast-moving consumer goods, auto, and carbon sectors. Our risk analysis results reveal that Indian stock sectors are not resistant to oil shocks and there exists significant systemic risk between these markets and the crude oil market.