Quantitative Analysis of Crude Oil Market and Industrial Fluctuation in India

Abstract

This paper investigates the quantitative analysis of crude oil market and industrial fluctuation in India in the context of automobile, financial Service, energy, metal, and commodities sectors in order to study the optimal portfolio construction and to estimate risk minimizing hedge ratios. We compare bivariate generalized autoregressive conditional heteroskedasticity models as a conditional mean equation and the vector autoregressive moving average GARCH model as a conditional variance equation with the error terms following the Student's t distribution so as to identify the model that would be appropriate for optimal portfolio construction and to estimate risk minimizing hedge ratios. Our findings indicate that the DCC-BVGARCH model outperforms other models and we find evidence of return and volatility spillover effects from the crude oil market to the Indian industrial sectors. In addition, we find that the conditional correlations between the crude oil market and the Indian industrial sectors change dynamically over time and that they reach their highest values during the period of the global financial crisis (2008-2009). We also estimate risk minimizing hedge ratios and oil-stock optimal portfolio holdings based on the results of econometric models.