در اثر نوسانات قیمت نفت در بازارهای سرمایه اروپا: لبریز نوسانات و اثر مصون سازی

The objective of this paper is to investigate the volatility spillovers between oil and stock markets in Europe. As not all industries are expected to be equally affected by oil price changes, we conduct our study at both the aggregate as well as sector levels. Empirically, we make use of a recently developed VAR–GARCH approach which allows for transmissions in volatilities. In addition, we analyze the optimal weights and hedge ratios for oil–stock portfolio holdings based on our results. On the whole, our findings show significant volatility spillovers between oil price and sector stock returns, and suggest that a better understanding of those links is crucial for portfolio management in the presence of oil price risk.

The analysis of the relationships between oil price shocks and stock markets has recently received much attention from finance practitioners and researchers. The primary economic rationale is the potential impacts of oil price changes on stock prices through their effects on corporate cash-flows and earnings, particularly being forced by the context of spectacular oil price fluctuations over the last years. The extent to which stock markets are affected by oil prices can be explained by referring to the theory of equity valuation where stock price is obtained by simply discounting all expected future cash-flows at the investors' required rate of return. Since corporate cash-flows and discount rate reflect economic conditions (inflation, interest rates, production costs, income, economic growth, and market confidence, etc.) which can be influenced by oil shocks (Apergis and Miller, 2009; Park and Ratti, 2008), stock prices may react significantly to patterns in oil price changes. This present study contributes to the extant literature by investigating the links between oil prices and stock markets in Europe. Unlike previous papers, which focus essentially on the impacts of oil price movements on stock returns using global or country market indices (Basher and Sadorsky, 2006; Fayyad and Daly, 2011; Papapetrou, 2001; Sadorsky, 1999), we use the European equity sector indices to examine the volatility transmission between oil and stock prices. The use of equity sector indices is, in our opinions, advantageous because market aggregation may mask the characteristics, not necessarily uniform, of various sectors. Sector sensitivities to changes in oil price volatility can be asymmetric. Some sectors may be more severely affected by this volatility than the others, depending on whether oil and oil-related products are an input or an output for the industry as well as on the indirect effect of oil prices on the industry, on the degree of competition and concentration in the industry, and on the capacity of the industry to transfer oil price shocks to its consumers. Further, the results of studies based on national stock market index such as Park and Ratti (2008) are likely to reflect considerable differences in industrial structure from one European market to another. Large European markets such as France and Germany are more diversified, whereas small markets such as Switzerland usually concentrate on a few industries. From a portfolio management point of view, identifying the heterogeneity of sector sensitivities to oil implies that there are sectors which can still provide a channel for international diversification during the periods of large swings in oil prices. Our analysis is also motivated by the lack of related attempts in the previous literature, while a better understanding of volatility transmission between oil and stock markets is important for building accurate asset pricing models, generating accurate forecasts of the volatility of both markets, and evaluating the oil risk exposure via value-at-risk calculation. Moreover, empirical insights from such study are equally crucial for hedging strategies and derivatives management. To achieve the objectives of our study, we make use of a recent multivariate econometric technique, vector autoregressive — generalized autoregressive conditional heteroskedasticity model (VAR–GARCH), introduced by Ling and McAleer (2003). One of the main advantages of this model is that it allows us to investigate the shock transmission, the dynamics of conditional volatility, and the volatility spillovers between series. It also provides meaningful estimates of the unknown parameters with less computational complication than several other multivariate specifications, such as the full-factor multivariate GARCH model (Hammoudeh et al., 2009). Furthermore, we are able to employ our empirical findings to compute the optimal weights of an oil–stock portfolio and optimal hedge ratios, as well as to analyze hedging effectiveness. This modeling framework has, to the best of our knowledge, never been employed to study the volatility transmission between oil prices and stock markets. The remainder of the article is organized as follows. Section 2 discusses the findings of selected previous works on the links between oil price and stock markets. Our empirical methodology is introduced in Section 3. Section 4 presents the data and reports their statistical properties. Section 5 discusses the obtained results. Section 6 provides summary conclusions.

This paper investigates the volatility transmission between oil and stock markets in Europe. Since all the industries may not be equally dependent on oil, we address this research question by using both the European global market index and seven stock sector indices. Our empirical framework is based on the recent VAR–GARCH model of Ling and McAleer (2003), which enables the analysis of spillover effects in both returns and conditional volatility. The results of this model are then used to construct portfolio designs and to calculate the optimal hedge ratios for oil–stock portfolio holdings. Globally, our results show the existence of significant volatility transmission between oil and stock markets in Europe, with the spillover effects being more apparent from oil to stock markets. It is however important to underline that the observed spillover effects come entirely from spillovers of shocks, and that spillovers of volatilities are all insignificant. In addition, a close inspection of the estimated coefficients in the conditional variance equations of each pair of markets indicates that the intensity of volatility interactions varies from one sector to another. The above results obviously prompt to examine the optimal portfolio holdings, and the calculated optimal weights and hedge ratios suggest that making oil assets part of a well-diversified portfolio of sector stocks improves its overall risk-adjusted performance and that it permits to hedge the oil price risk more effectively. Note finally that the average optimal weights and hedging effectiveness differ considerably across sectors.