سرریزهای نوسانات بین قیمت نفت و بازده بخش سهام: مفاهیم برای مدیریت پرتفولیو
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|21966||2011||19 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of International Money and Finance, Volume 30, Issue 7, November 2011, Pages 1387–1405
In this article we take a recent generalized VAR-GARCH approach to examine the extent of volatility transmission between oil and stock markets in Europe and the United States at the sector-level. The empirical model is advantageous in that it typically allows simultaneous shock transmission in the conditional returns and volatilities. Insofar as volatility transmission across oil and stock sector markets is a crucial element for portfolio designs and risk management, we also analyze the optimal weights and hedge ratios for oil-stock portfolio holdings with respect to the results. Our findings point to the existence of significant volatility spillover between oil and sector stock returns. However, the spillover is usually unidirectional from oil markets to stock markets in Europe, but bidirectional in the United States. Our back-testing procedures, finally, suggest that taking the cross-market volatility spillovers estimated from the VAR-GARCH models often leads to diversification benefits and hedging effectiveness better than those of commonly used multivariate volatility models such as the CCC-GARCH of Bollerslev (1990), the diagonal BEKK-GARCH of Engle and Kroner (1995) and the DCC-GARCH of Engle (2002).
It is common in theory that stock prices are equal to the sum of discounted values of expected future cash flows at different investment horizons. Market participants must therefore identify the factors affecting these discounted cash flows to support their decision making. In view of the crucial role of oil in the global economy and its spectacular price fluctuations in recent years, it is naturally opportune to ask questions about the impact of the price of oil on stock prices. Research in the energy finance literature has documented several channels through which oil shocks are transmitted to stock markets, but the most important one may be the financial link between oil prices, corporate cash flows, and the discount rate used in stock-valuation models. We can see easily that the latter two factors depend on economic conditions (changes in the consumer price index, interest rates, industrial production costs, economic growth rates, investor and consumer confidence, and so on) that are significantly influenced by changes in the price of oil (Jones and Kaul, 1996, Sadorsky, 1999, Park and Ratti, 2008 and Apergis and Miller, 2009). It is thus obvious that a change in oil prices of either sign (positive or negative) may move stock prices. Although understanding the causal relationships between oil price changes on stock markets is crucial for energy policy planning, portfolio diversification and energy risk management, and other such issues, it is only recently that these relationships have been examined1 Moreover, the focus was essentially on broad market indices (national and/or regional stock market indices). One of the earliest pieces, done by Kling (1985), studies oil shocks and US stock market behavior, and shows that stock market returns are negatively associated with the rise of crude oil prices. Jones and Kaul (1996) use a standard present value model to examine the response of four developed stock markets (Canada, Japan, the United Kingdom, and the United States) to oil shocks and find that changes in stock returns can be partially accounted for by the effect of oil price movements on current and future cash flows. Subsequent studies including, for example, those by Huang et al., 1996, Sadorsky, 1999 and Park and Ratti, 2008, and Apergis and Miller (2009) rely on such methods as vector autoregressive models, international multifactor asset pricing models, cointegration tests, and vector error-correction models and reach similar conclusions. As to emerging stock markets, several papers have shown that changes in the price of oil have significant effects on stock returns over both the short and the long-term (Papapetrou, 2001, Basher and Sadorsky, 2006 and Narayan and Narayan, 2010). But it must be emphasized that both the magnitude and sign of the effects differ from one market to another, depending on whether the market is more dependent on petroleum-related products or less so. Some studies have examined the extent of oil price impacts on stock prices from a sector-by-sector perspective. For instance, Sadorsky (2001) and Boyer and Filion (2007) show that the stock returns of Canadian Oil & Gas companies are positively related to oil price increases. El-Sharif et al. (2005) obtain similar findings for Oil & Gas returns in the United Kingdom, whereas non-Oil & Gas sectors are weakly linked to oil price changes. Nandha and Faff (2008) study the short-term relationship between oil prices and thirty-five global industries covered by Datastream International and show that the rise of oil prices has a negative impact on all industries but not Oil & Gas. The work of Nandha and Brooks (2009) focuses on the reaction of the transport sector to oil prices in thirty-eight countries around the world and shows that oil prices do play a role in determining the transport sector returns in developed countries. For the Asian and Latin American countries in their sample, however, there appears to be no such evidence. In a more recent attempt, Arouri and Nguyen (2010) shift attention to short-term links between oil and stock prices in the aggregate as well as sector-by-sector in Europe. Their findings, obtained through various econometric techniques, suggest that the sensitivity of sector stock returns to oil price changes differs greatly from one sector of activity to another. More interestingly, their out-of-sample analysis shows that there are substantial diversification benefits to adding the oil asset to a diversified portfolio of stocks, as doing so significantly improves the portfolio’s risk-return characteristics. This finding is consistent with those of several other papers, for which using futures contracts on traded commodities as part of existing portfolios of stocks improves overall returns ( Satyanarayan and Varangis, 1996 and Geman and Kharoubi, 2008). As we can see, almost all of the abovementioned papers look at price spillover in oil and stock markets, whereas little has been done on possible volatility spillover. Using different specifications of Engle and Kroner (1995)’s multivariate BEKK-GARCH models, some very recent papers document significant volatility spillover between oil and stock markets (Agren, 2006, Malik and Hammoudeh, 2007, Malik and Ewing, 2009 and Tansuchat et al., 2009). For example, Malik and Hammoudeh (2007) show that Gulf equity markets are sensitive to volatility from the oil markets, while stock market volatility spills over into the oil markets only in Saudi Arabia. For their part, Malik and Ewing (2009) investigate volatility spillover between oil prices and five US equity sector indices (Financials, Industrials, Consumer Services, Health Care, and Technology) and conclude in favor of significant transmission of return and volatility shocks. In firm-level analysis, Tansuchat et al. (2009) find no volatility spillover between WTI (West Texas Intermediate) crude oil futures returns and the stock returns of ten worldwide oil companies. Our study extends the research into volatility spillover between oil and stock markets. Specifically, we look at Europe and the United States over the period from 1998 to 2009 and do a thorough analysis of how shocks and volatility are transmitted from oil markets to the stock market sectors and from the stock markets to the oil markets. There are several reasons for this particular study. First, most previous work focuses on the oil-stock return links and often neglects the volatility spillover between these two markets, even though understanding volatility transmission mechanisms provides insight into means of building accurate stock-valuation models and accurate forecasts of the volatility of both markets. The information contained in empirical results also provides empirical bases from which to address issues regarding hedging strategies, optimal portfolio allocation, and derivatives management in the presence of energy risk. Second, our review of the literature indicates that little attention has been paid to the interaction of the volatility of oil prices and stock market sectors. Indeed, some sectors may be more severely affected by oil price volatility than others, depending on whether oil and oil-related products are an input or an output for the industry, 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 customers. The industry breakdown is even more important in that it would make it possible to counter biases inherent to the use of aggregate market indices that may mask the characteristics, not necessarily uniform, of several sectors. Here, the results of such studies based on national stock market indices as that of Park and Ratti (2008) may reflect differences in industrial structure from one country to another. Third, unlike previous studies that mostly report either country-specific or industry-specific results for oil-stock sector relationships, our research considers both the European and US industrial sectors. By doing so we are able to compare the volatility transmission mechanisms between two of the most influential trading blocs in the global economy as well as to compare our results with previous findings on this matter. Finally, we also examine the transmission of volatility between oil prices and aggregate stock market indices to perform a robustness check on our sector-level results. At the empirical stage, we employ a multivariate vector autoregressive-generalized autoregressive conditional heteroscedasticity (VAR-GARCH) model recently developed by Ling and McAleer (2003). This model offers the possibility to explore the conditional volatility dynamics of the series considered as well as the conditional cross effects and volatility spillover between series. It also provides meaningful estimates of the model’s parameters with fewer computational complications than several other multivariate GARCH specifications, such as the full-factor GARCH model. Furthermore, the findings can be used to analyze the diversification and hedging effectiveness across oil asset and sector equity. Some papers have taken the VAR-GARCH approach to investigate volatility spillover and hedging strategies among Gulf Arab equity sectors (Hammoudeh et al., 2009), between previous metals and exchange rates (Hammoudeh et al., 2010), and between crude oil spot and futures returns of the Brent and WTI oil price benchmarks (Chang et al., in press). On the whole, we find evidence of significant volatility cross effects between oil and equity sector indices in Europe and the United States over the study period. Past oil shocks are found to play a crucial role in explaining the time-dynamics of conditional volatility of sector returns and should thus be accounted for when making volatility forecasts of future stock returns. On the other hand, portfolio analysis suggests that adding the oil asset to a well-diversified portfolio of European and US stocks improves its risk-adjusted performance and that oil risk exposures can be effectively hedged in portfolios of sector stocks over time. In addition, we show that among the models considered, the VAR-GARCH is the best model for optimal portfolio designs and hedging effectiveness. But there are several differences between Europe and the United States. First, for Europe, transmission of volatility is greater from oil to stocks than from stocks to oil, whereas for the United States it seems to be bidirectional. Second, the oil risk premium appears not to be relevant to international asset pricing models for European stocks as past values of oil price volatility do not significantly affect stock market volatility, whereas it is for the Automobile and Parts, Basic Materials, and Utilities sectors in the United States. The remainder of the article is structured as follows. Section 2 introduces our empirical methodology. Section 3 presents the sample, data sources, and some preliminary analysis. Section 4 reports and discusses the empirical findings. Section 5 makes concluding remarks.
نتیجه گیری انگلیسی
The main purpose of this article was to examine the extent of volatility transmission, portfolio designs, and hedging effectiveness in oil and stock markets in Europe and the United States from a sector perspective. The rationale for doing so is that market-wide indices such as the DJ Stoxx Europe 600 and S&P 500 may mask the industry-specific characteristics, and different industries may react differently to oil shocks as well. Moreover, with respect to portfolio management, studies focusing on sector sensitivities to oil price shocks are of particular interest since they offer insight into sectors that still provide valuable opportunities for international diversification during large swings in oil prices. Taking the recent VAR-GARCH modeling approach, which permits volatility spillover, we find significant volatility interaction in oil and stock market sectors, although, for Europe, the transmission of volatility is much more apparent from oil to stocks than from stocks to oil. In the US, there is evidence to support the hypothesis of bidirectional volatility spillover. Empirical results also point out to the heterogeneous intensity of volatility cross effects across the seven stock sectors. Finally, our examination of optimal weights and hedge ratios suggests that optimal portfolios in both Europe and the US should have stocks outweigh oil assets and that the stock investment risk can be hedged with relatively low hedging costs by taking a short position in the oil futures markets. In particular, we show that optimally hedged oil-stock portfolios outperform traditional portfolios of stocks regardless of bivariate volatility model, and that our benchmark VAR-GARCH model is the best one when diversification and hedging effectiveness are analyzed. On the whole, oil assets can be considered a dynamic and valuable asset class that helps improve the risk-adjusted performance of a well-diversified portfolio of sector stocks and serves to hedge oil risk more effectively.