Analyzing the causality and dependence between energy price and G7 stock markets

Abstract

This study aims to investigate the causality and dependence structure of energy shocks and G7 stock markets. The positive and negative shocks of energy prices are quantified, and Granger causality-based Vector autoregressive and Copula approaches are employed to measure the causality and contagion effect, respectively, between the positive and negative energy shocks and G7 stock markets’ volatilities. Besides, this study uses a smooth dynamic Copula model to describe the nonlinear and asymmetric dependency structure and obtains a lower tail coefficient, which can fully describe the risk of contagion effects. Compared with previous studies, the use of tail coefficients to measure the risk spread of energy prices impacting the G7 stock markets is also an innovative method of this study.

Briefly, the purposes of this study are as follows: 1) to measure the dependence between coal, oil, natural gas, and the stock markets of G7 countries. 2) to test the causality between the coal, oil, natural gas shocks, and G7’s stock market volatilities. 3) to investigate the "risk contagion" mechanism of coal, oil, natural gas, and G7 stock markets by investigating the tail dependencies of variables. In this study, the weekly data of WTI crude oil price, Rotterdam coal price and world natural gas price from August 2006 to December 2020 will be selected as well as the comprehensive stock price indices of G7 countries, which are the US S&P 500 Index and the Nikkei 225 index, the German DAX30 index, the French CAC40 index, the British FTSE100 index, the Italian FTSE MIB index, and the Canadian Toronto S&P_TSX composite index. In this way, we will study the causal and interdependent relationship between changes in international energy prices and the stock markets of G7 countries.

In addition, the nonlinear link between energy and stock markets is of concern and this motivates us to propose a Smooth Transition Dynamic Copula that allows for the structural change in time-varying dependence between energy shocks and G7 markets’ volatilities. Several Copula families are also considered, and the best-fit Copula model is used to explain the correlation and risk contagion effect. The findings of the study show that there is weak evidence that the Granger causality between G7 stock markets' volatilities and energies shocks (except the Japanese stock market with energies shocks and the Canadian stock market with oil negative shocks). In addition, the oil market cannot be used as a safe haven for the U.S. and U.K. stock markets, the coal market cannot be a safe haven for the Italian stock market, and the natural gas market can become a safe haven for the stock markets of G7 countries. Finally, there is evidence of tail dependence between the G7 stock market and the negative oil shock, indicating that there is a risk contagion effect between oil and the G7 stock markets.