Correlations and volatility spillovers between oil, natural gas, and stock prices in India

This study investigates the extent of time-varying volatility and correlations between crude oil, natural gas, and stock prices in India using various multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) models with and without asymmetry. Our empirical results reveal that...

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Bibliographic Details
Published in:Resources policy 2019-08, Vol.62, p.282-291
Main Authors: Kumar, Satish, Pradhan, Ashis Kumar, Tiwari, Aviral Kumar, Kang, Sang Hoon
Format: Article
Language:English
Subjects:
Asymmetry
Autoregressive models
Commodities
Commodity futures
Correlation analysis
Crude oil
Diversification
Economic forecasting
Economic models
Empirical analysis
Energy
Forecasting
Futures
Hedging
Indian energy futures
Investors
Markets
Natural gas
Optimal portfolio weight
Petroleum
Prices
Securities markets
Stochastic models
Stock exchanges
Stock prices
Stocks
Time-varying hedge ratio
Trading
VARMA-DCC-GARCH
Volatility
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Summary:This study investigates the extent of time-varying volatility and correlations between crude oil, natural gas, and stock prices in India using various multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) models with and without asymmetry. Our empirical results reveal that there is no long-run cointegration between crude oil, natural gas, and stock prices in India. We find that the VARMA-DCC-GARCH model is more efficient compared to the CCC model with asymmetry in estimating time-varying correlations. We also analyze optimal portfolio weights and hedging ratios through pair trading between stocks and energy commodity futures. Our results have several implications for portfolio investors dealing with the Indian stock market and energy commodity futures for forecasting potential market risk exposure and determining the existence of portfolio diversification benefits. •This study investigates the extent of time-varying volatility and correlations between crude oil, natural gas, and stock prices in India.•We use various multivariate GARCH models with asymmetry and without asymmetry.•The VARMA-DCC-GARCH model is more efficient compared to the CCC model with asymmetry in estimating time-varying correlations.•We also analyze optimal portfolio weights and hedge ratios.
ISSN:0301-4207
1873-7641
DOI:10.1016/j.resourpol.2019.04.004