The Linkage Between The World Oil Price And Chinese Energy-Rrelated Stock Price: Implications For Risk Management

With the rapidly rising oil import dependence, energy security has become one of the top concerns for the Chinese government in recent years. In order to implement the government’s policy strategies of national energy security, Chinese energy companies (including fossil fuel companies and new energy companies) undoubtedly play a crucial role. However, to acquire capitals for further development, they have to depend on one of the most important financing channels, the stock market. In the last decades, the number and market capitalization of listed Chinese energy firms expanded quickly; the energy stock price changes have not only been the concern of enegy companies, but also have attracted much attention from other stock investors. In order to hedge energy stock price risks, it is quite necessary for investors to consider the key risk factor of energy stock investment, the oil price. This risk factor is expected to impose a larger effect on Chinese energy stock prices in future.In spite that many of the current studies have regarded oil price as the key risk factor of energy stock prices and investigated the relationship between oil prices and energy stock prices so far, few of them focus on the case of China. In very recent years, with the non-negligible high volatilities of world oil prices and the increasingly significant financial attribute of the world oil market, stock investors are not only interested in the effect of oil price shocks on stock returns, but also in their volatility link, even in their extreme dependence and the corresponding risk management strategies. To the best of our knowledge, studies about oil price-energy stock price volatility linkage and extreme dependence are still lacking, so are the risk management strategies. To fill in the research gap, this paper aims to describe the dependence between the world oil price and Chinese energy stock price comprehensively and accurately; in addition, based on the market dependence and conditional volatilities of the asset returns, several portfolios are established and evaluated.The concrete contents are as follows:(1) The return and volatility spillover effect between the world oil price and Chinese energy stock price. This paper employs the asymmetric bivariate BEKK model to capture return and volatility spillovers between the world oil price and Chinese energy stock price, in particular, it used the news impact surfaces to vividly present the market volatility spillovers; it also conducted the sub-sample (periods of turmoil and tranquility) and sub-energy sector (fossil fuel industry:oil & gas and coal sector; new energy industry:solar and wind energy sector) analysis so as to provide more empirical evidences on the linkage of the world oil price and Chinese energy stock price;(2) The conditional dependence between the world oil price and Chinese energy stock price. This paper firstly uses AR(1)-GJR(1,1)-skewed-t to model the marginal distributions of asset returns and then applies four dynamic copulas, including dynamic Gaussian Copula, dynamic Student-t Copula, dynamic Gumbel Copula and dynamic Rotated Gumbel Copulas in modeling the conditional dependence between the world oil price and Chinese energy stock price. The Log-likelihood and AIC are the two criterions for choosing the optimal copula function. The dynamic linear and nonlinear dependence coefficients are obtained from the optimal copulas. To further investigate the market conditional dependence, the sub-sample (periods of turmoil and tranquility) and sub-energy sector (fossil fuel industry: oil & gas and coal sector; new energy industry:solar and wind energy sector) analysis are conducted as well;(3) The risk management of Chinese energy stock investment using the world oil futures. Based on the conditional dependence between the world oil price and Chinese energy stock prices obtained from the optimal copula and the conditional volatilities of asset returns, time-varying optimal portfolio weights and hedging ratios are calculated, then optimally-weighted portfolio and hedged portfolio are established; meanwhile, for further comparison, the equally-weighted portfolio and hedged portfolio with OLS static hedging ratio are considered as well. To examine whether these four portfolios could improve the risk-return of Chinese energy stock investment, this paper evaluated these portfolios from three respects including the risk-adjusted returns, hedging effectiveness and downside risk gains. The sub-sample (periods of turmoil and tranquility) and sub-energy sector (fossil fuel industry:oil & gas and coal sector; new energy industry:solar and wind energy sector) analysis are further conducted to prove the empirical results are robust.This paper finds that the return and volatility spillovers from the world oil price to Chinese energy stock price are significant (compared with positive lagged world oil price returns, the negative lagged returns cause larger changes in Chinese current energy stock returns; and the own variance asymmetry is found both in the world oil market and Chinese fossil fuel stock market); the average dependence between the world oil price and Chinese fossil fuel stock price is higher than that of the world oil price and Chinese new energy stock price while Chinese new energy stock price is more vulnerable to the extreme changes of the world oil price; based on the world oil price — Chinese energy stock price dependence, the optimally weighted portfolio is found to be the best risk management strategy, which can most significantly improve the risk-return of Chinese energy stock investment and reduce its extreme downside risks, however, based on the VaR-based investor loss function, this strategy is doubted for not statistically significantly reducing the extreme risks of Chinese energy stock investment. The results of sub-sample and sub-sector analysis are consistent with those of the full-sample and aggregate energy industry analysis in most cases.The results in this paper could not only provide empirical evidences for Chinese energy stock investors to understand and predict crude oil price risks and then manage energy stock investment risks, they also have potential implications for Chinese energy policy making.