Return and volatility transmission between world oil prices and stock markets of the GCC countries

This paper investigates the return links and volatility transmission between oil and stock markets in the Gulf Cooperation Council (GCC) countries over the period 2005-2010. We employ a recent generalized VAR-GARCH approach which allows for transmissions in return and volatility. In addition, we analyze the optimal weights and hedge ratios for oil-stock portfolio holdings. On the whole, our results point to the existence of substantial return and volatility spillovers between world oil prices and GCC stock markets, and appear to be crucial for international portfolio management in the presence of oil price risk.     

Impact of macroeconomic factors and country risk ratings on GCC stock markets: evidence from a dynamic panel threshold model with regime switching

This study examines the non-linear relationship between stock markets in GCC countries and their country risk ratings as well as with major macroeconomic factors. Based on a dynamic panel threshold model with two and four regimes, the results provide evidence of short-term asymmetry between first-lagged GCC stock returns and the performance of GCC stock markets. In addition, only the financial risk (FR) rating has a significant positive effect on the performance of GCC stock markets according to the prevailing regimes for the GCC lagged returns and the Brent oil market. Among the macroeconomic factors, improvements in the global stock markets, the MSCI Global Islamic Index, and the oil price increased the performance of GCC stock markets, whereas increases in the gold price, the 3-month U.S. Treasury bill rate, and the U.S. Treasury bond rate reduced the performance of the GCC stock markets. These results have important implications for investors, policymakers, and portfolio managers.     

Volatility and dynamic conditional correlations of worldwide emerging and frontier markets

This study examines the relationship between time-varying correlations and conditional volatility among 32 worldwide emerging and frontier stock markets and the MSCI World stock market index from January 2000 to December 2012. Correlations are estimated in the standard and asymmetric dynamic conditional correlation model frameworks. The results can be summarized by three main findings: (1) asymmetry in volatility is not a common phenomenon in emerging and frontier markets; (2) asymmetry in correlations is found only with respect to the Hungarian stock market; and (3) the relationship between volatility and correlations is positive and significant in most countries. Thus, diversification benefits decrease during periods of higher volatility.     

Do oil producing countries offer international diversification benefits? Evidence from GCC countries

This paper provides evidence of the existence of diversification benefits in international stock markets when oil producing countries are included in a global portfolio. Moreover, it examines whether recent oil shocks and financial events have significant impact on the conditional correlations and diversification benefits. Using stock returns from developed, emerging, GCC countries and a global portfolio, the empirical findings show that while developed and emerging stock markets have experienced increased correlations over relatively long periods of time, the correlation in GCC stock markets remained low and constant offering high diversification benefits. Interestingly, the paper also finds that, during 2012–2014, the rising conditional correlation levels have reversed trends in developed and emerging markets alike offering more potential for international diversification. Our results are robust to model selection, data frequency, and innovations distribution.     

Responses of international stock markets to oil price surges: a regime-switching perspective

We propose an enhanced regime-switching model to investigate the relationships between oil price surges and stock market cycles in five oil-dependent countries. Our model accounts for the joint effects of the West Texas Intermediate (WTI) and Brent oil markets and simultaneously captures asymmetry, volatility persistence and regime shifts contained in the underlying financial data. We find that stock market returns strongly exhibit a regime-switching behaviour, but they react differently to the increases in the price of oil. More precisely, the conditional volatility of studied stock markets during the bear market phases is found to be less affected by oil price surges than during the bull market phases. Whether the effects of oil shocks are positive or negative depends greatly on the degree of reliance on imported oil, the share of the cost of oil in the national income and the degree of improvement in energy efficiency of a given country. Finally, the relatively opposite effects of the WTI and Brent oil markets suggest the potential of substitution between them as well as the necessity of a diversification strategy of oil supply sources.     

Can asymmetric conditional volatility imply asymmetric tail dependence?

In this article, we investigate two types of asymmetries, that is, the asymmetry of conditional volatility and the asymmetry of tail dependence in the crude oil markets. We employ the two different sample datasets in which each dataset covers the time period of stable and unstable oil prices, individually. A variety of different copulas and three asymmetric GARCH regression models are used in order to capture the two types of asymmetries. In particular, we extend the TBL-GARCH model proposed by Choi et al. (2012) to the asymmetric GARCH regression type model. The findings from the two different approaches are congruent, in that there is no asymmetry of tail dependence and no asymmetric conditional volatility in crude oil returns over the two different sample periods. Our study reconfirms the findings of Aboura and Wagner (2016) by showing that asymmetric conditional volatility relates to asymmetric tail dependence.     

Correlations and volatility spillovers across commodity and stock markets: Linking energies,food, and gold

This paper employs a VAR-GARCH model to investigate the return links and volatility transmission between the S&P 500 and commodity price indices for energy, food, gold and beverages over the turbulent period from 2000 to 2011. Understanding the price behavior of commodity prices and the volatility transmission mechanism between these markets and the stock exchanges are crucial for each participant, including governments, traders, portfolio managers, consumers, and producers. For return and volatility spillover, the results show significant transmission among the S&P 500 and commodity markets. The past shocks and volatility of the S&P 500 strongly influenced the oil and gold markets. This study finds that the highest conditional correlations are between the S&P 500 and gold index and the S&P 500 and WTI index. We also analyze the optimal weights and hedge ratios for commodities/S&P 500 portfolio holdings using the estimates for each index. Overall, our findings illustrate several important implications for portfolio hedgers for making optimal portfolio allocations, engaging in risk management and forecasting future volatility in equity and commodity markets.     

Oil price and Gulf Corporation Council stock indices: New evidence from time-varying copula models

Using a time-varying GJR copula approach, we determine the conditional dependence of the GCC stock indices on oil price between 2007 and 2016. We show how to improve the forecasting accuracy of the co-movement of energy and stock prices in an equally weighted portfolio. Contrary to prior findings, we demonstrate that due to the different co-movements across the GCC stock indices, portfolios of oil assets and several GCC stocks are less likely to be affected by systemic risk. The different co-movements across several stock indices over time provide different entry and exit points for stock investors. This approach is in line with the ‘buy low/sell high’ adage.     

Stock market comovements in Central Europe: Evidence from the asymmetric DCC model

We examine time-varying stock market comovements in Central Europe employing the asymmetric dynamic conditional correlation multivariate GARCH model. Using daily data from 2001 to 2011, we find that the correlations among stock markets in Central Europe and between Central Europe vis-à-vis the euro area are strong. The correlations increased over time, particularly after their EU entry and largely remained at these levels during the financial crisis. The stock markets exhibit asymmetry in the conditional variances and to a certain extent in the conditional correlations as well, pointing to the importance of applying a sufficiently flexible econometric framework. The conditional variances and correlations are positively related, suggesting that the diversification benefits decrease disproportionally during volatile periods.     

Stock markets in GCC countries and global factors: A further investigation

This paper investigates the long-run links between stock markets of the Gulf Cooperation Countries (GCC) and three global factors, including oil price, MSCI (Morgan Stanley Capital International) world index and US interest rate. Unlike previous empirical works, we employ econometric techniques that account for simultaneously the effects of heterogeneity, cross-country dependence and unknown regime-shifts in order to examine the sensitivity of GCC stock markets to movements of global factors. Our findings are of great interest since they show strong evidence of nonlinear long-run relationship between the variables of interest when there is dependence between countries, and indicate that the global factors have predictability effect on most GCC stock markets. We also stress the importance of including regime-shifts in the analysis that leads to more reliable conclusions than those obtained in the literature by neglecting structural breaks.     

Return and volatility transmission between oil prices and oil-exporting and oil-importing countries

This paper provides further evidence of the comovements and dynamic volatility spillovers between stock markets and oil prices for a sample of five oil-importing countries (USA, Italy, Germany, Netherland and France) and four oil-exporting countries (United Arab Emirates, Kuwait, Saudi Arabia and Venezuela). We make use of a multivariate GJR-DCC-GARCH approach developed by Glosten et al. (1993). The results show that: i) dynamic correlations do not differ for oil-importing and oil-exporting economies; ii) cross-market comovements as measured by conditional correlation coefficients increase positively in response to significant aggregate demand (precautionary demand) and oil price shocks due to global business cycle fluctuations or world turmoil; iii) oil prices exhibit positive correlation with stock markets; and iv) oil assets are not a good ‘safe haven’ for protection against stock market losses during periods of turmoil.     

Volatility Spillovers and Contagion from Mature to Emerging Stock Markets

This paper models volatility spillovers from mature to emerging stock markets, tests for changes in the transmission mechanism during turbulences in mature markets, and examines the implications for conditional correlations between mature and emerging market returns. Tri‐variate GARCH–BEKK models of returns in mature, regional emerging, and local emerging markets are estimated for 41 emerging market economies (EMEs). Wald tests suggest that mature market volatility affects conditional variances in many emerging markets. Moreover, spillover parameters change during turbulent episodes. In the majority of the sample EMEs, conditional correlations between local and mature markets increase during these episodes. While conditional variances in local markets rise as well, volatility in mature markets rises more, and this shift is the main factor behind the increase in conditional correlations. With few exceptions, conditional beta coefficients between mature and emerging markets tend to be unchanged or lower during turbulences.     

Modeling the Taiwan Stock Market and International Linkages

This paper analyzes the Taiwan stock market and examines its price and volatility linkages with those of the United States. In particular, it tests the hypothesis that the short-term volatility and price changes spill over from the developed markets, mainly the United States, to the emerging Taiwan stock market. The model and the test are built upon Engle's ARCH (autoregressive conditional heteroskedasticity) and Engle and Kroner's M-GARCH (multivariate generalized ARCH) models. The paper differs from previous studies on the Taiwan stock market in three respects. First, instead of using daily closing prices, it uses close-to-open and open-to-close returns to avoid the problem of overlapping samples. It carefully models the day-of-the-week effect in daily data to avoid misspecification of the model. Second, to circumvent the generated regressor problem arising from the two-step estimation procedure, it also employs the M-GARCH model where all parameters are estimated simultaneously. Third, the misspecification test is carried out on various kinds of asymmetric ARCH factors. A substantial volatility spillover effect is found from the US stock market to the Taiwan stock market, especially for the model using close-to-open returns. There is also evidence supporting a spillover effect in price changes. The findings can be explained by the recent gradual opening of the Taiwan stock market to foreign investors.     

Dynamic Relationships among GCC Stock Markets and Nymex Oil Futures

Daily relationships among stock markets of the Gulf Cooperation Council (GCC) members, excluding Qatar, form two equilibrium relationships with varying predictive power. The Saudi market leads, followed by Bahrain and United Arab Emirates. Kuwait, which is dominated by momentum traders, and Oman have the weakest links with the other GCC markets. Only the Saudi index can predict—and be predicted by—New York Mercantile Exchange oil futures prices. Therefore these markets are candidates for diversified regional portfolios at the country level. The trading day effect is weak for all GCC markets and oil futures prices but remains consistent with findings for the U.S. stock market. (JEL C22 , F3 , Q49 )     

Does crude oil move stock markets in Europe? A sector investigation

The aim of this article is to investigate the responses of European sector stock markets to oil price changes. We use linear and asymmetric models and study the association of oil and stock prices. Our findings suggest that the strength of this association varies greatly across sectors. Moreover, for some sectors we find strong evidence of asymmetry in the reaction of stock returns to changes in the price of oil.     

Extracting portfolio management strategies from volatility transmission models in regime-changing environments: Evidence from GCC and global markets

Unlike previous studies, this paper uses the Multi-Chain Markov Switching model (MCMS) to examine portfolio management strategies based on volatility transmission between six domestic stock markets of Gulf Arab states (GCC) and global markets (i.e., the U.S. S&P 500 index and oil prices) and compares the results with those of the VAR model. Our volatility approach is range-based and not return-based which is traditionally used in estimating the optimal hedge ratios and portfolio weights. The results demonstrate the relative hedging effectiveness of the MCMS model compared to the VAR. We also highlight the time and regime dependency of the optimal hedge ratios and the portfolio weights for each selected pair of the considered markets conditional on the regime of the same market and the regimes of the other market. Policy implications on portfolio strategies under different states are also discussed.     

Modelling the relationship between future energy intraday volatility and trading volume with wavelet

Although the energy and stock markets are both characterized by volatility and liquidity, and there has been substantial research to explore the relationship between volatility and trading volume (TV) in stock markets, few researchers have investigated this relationship in energy markets. Moreover, studies that have explored this association within energy markets did not describe its nature or impetus. To redress this oversight, we investigate this relationship using intraday data from the oil and gas markets – the most liquid energy markets in the world. In this way, the current article extends the previous studies through the use of a frequency approach to propose an original analysis of the relationship between volume and volatility. More specifically, we employ a continuous wavelet transform to identify the lead–lag phase between volatility and volume. This framework supplants usual time series modelling, as it uses a measure of coherence for different frequencies and time-scales to capture further changes and time variation in the volume–volatility relationship. Our results provide supportive evidence for the well-known positive relationship between realized volatility and TV, thereby supporting the mixture distribution hypothesis. In particular, our results show that volume causes volatility only during ‘turbulent times’, while volatility causes volume during ‘good times’. Furthermore, there is no relationship between volume and volatility in the long term, due to the absence of noise traders and liquidity traders in the long run. These findings are helpful for investors and policymakers as they contribute to better forecast the TV and price volatility during turbulent and calm periods and over several investment horizons.     

Volatility transmission between Islamic and conventional equity markets: evidence from causality-in-variance test

This study examines whether a volatility/risk transmission exists between the Dow Jones Islamic stock and three conventional stock markets for the United States, Europe and Asia during the pre- and the in- and post-2008 crisis periods. It also explores the volatility spillover dynamics between those markets and US Monetary policy, oil prices, global financial risk and uncertainty factors. The recently developed Hafner and Herwartz (2006)’s causality-in-variance test provides evidence of risk transfers between these seemingly different equity markets, indicating a contagion between them during the full sample and the subperiods. The volatility structure of these markets is dominated by short-run volatility in the first period and by high long-run volatility in the second period. The volatility impulse response analysis indicates a similar volatility transmission pattern although it is characterized by a more volatile and short-lived structure in the second period. It also appears that the Islamic equity market responds to shocks from the risk factors and not from the oil price and the US economic policy uncertainty index during both periods.     

The linkages,persistence, asymmetry in the volatility,the price discovery and efficiency,and the effect of the US subprime mortgage financial crisis on the spot and the futures market’s returns: the case of India

This article examines the effects of persistence, asymmetry and the US subprime mortgage crisis on the volatility of the returns and also the price discovery, efficiency and the linkages and causality between the spot and futures volatility by using various classes of the ARCH and GARCH models, and through the Granger’s causality. We have used two indices: one for spot and the other for futures, for the daily data from 12 June 2000 to 30 September 2013 from Nifty stock indices. We have then tested for ARCH effects, and subsequently employed various models of the ARCH and GARCH conditional volatility. The GARCH(1,1) model is found to be significant, and it implies that the returns are not autocorrelated and have ‘short memory’. It supports the hypothesis of the efficiency of the markets. The negative ‘news’ has more significant effect on volatility, corroborating the ‘leverage impact’ in finance on market volatility. We have also tested the volatility spillover effects. The two methods we employed support the spillover effects and the causality is bidirectional. We also have used the dummy variable for the US subprime mortgage financial crisis and found that they are statistically significant. Indian stock market is thus integrated to the world stock markets.     

Hedging and diversification across commodity assets

ABSTRACT

We investigate the conditional cross effects and volatility spillover between equity markets and commodity markets (oil and gold), Fama and French HML and SMB factors, volatility index (VIX) and bonds using different multivariate GARCH specifications considering the potential asymmetry and persistence behaviours. We analyse the dynamic conditional correlation between the US equity market and a set of commodity prices and risk factors to forecast the transmission of shock to the equity market firstly, and to determine and compare the optimal hedge ratios from the different models based on the hedging effectiveness of each model. Our findings suggest that all models confirm the significant returns and volatility spillovers. More importantly, we find that GO-GARCH is the best-fit model for modelling the joint dynamics of different financial variables. The results of the current study have implications for investors: (i) the equity market displays inverted dynamics with the volatility index suggesting strong evidence of diversification benefit; (ii) of the hedging assets gold appears the best hedge for the US equity market as it has a higher hedge effectiveness than oil and bonds over time; and (iii) despite these important results, a better hedge may be obtained by using well-selected firm sized and profitability-based portfolios.