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This study aims to investigate the existence of bubbles and their contagion effect in crude oil and stock markets of oil-exporting countries Gulf Cooperation Council (GCC) from 2016 to 2021.

The authors use Generalized Sup augmented Dickey–Fuller (GSADF) and Backward Sup augmented Dickey–Fuller (BSADF) to significantly identify multiple bubbles stock and oil markets with precise dates. Furthermore, the authors check the contagion effect of bubbles between crude oil and GCC stock markets based on the time-varying Granger causality test.

First, the authors find empirical evidence of downwards bubbles in crude oil prices and in all GCC stock indexes (except the Saudi stock index) during the corona virus disease 2019 (COVID-19) outbreak. Second, the authors do not detect empirical evidence of bubble transmission between crude oil markets and GCC stock markets (except with the Dubai Financial Market index).

The findings of this study would illuminate policymakers not to limit the factors of systematic financial crises in oil-exporting countries to crude oil and to consider factors such as monetary policy and economic diversification measures. This study has also crucial implications for investors. In fact, investors should not ignore the responses of the stock markets to oil price shocks that are heterogeneous across countries when looking for investment opportunities in the GCC region.

The study justifies the changing nature of the bubble contagion effect through the novel implementation of the time-varying Granger causality test to detect whether bubble contagion exists between oil and GCC stock markets and if that does, in which direction.

This study aims to examine the links between oil price shocks and Gulf Cooperation Council (GCC) stock markets from February 2004 to December 2019. Knowledge of such links is important to both investors and policymakers in understanding the transmission of shocks across markets.

The authors use the Ready (2018) oil price decomposition method and the quantile regression approach to conduct the analysis.

Initial results show a positive oil price change increases stock returns, while greater volatility decreases returns. The oil shock decomposition results reveal a significant positive impact of supply-side shocks on stocks. This contrasts with the literature that argues demand-side shocks are more important. While factors such as liquidity and the lack of hedging instruments can increase the vulnerability of GCC equities to oil price shocks, the result reflects the unique economic structure of the GCC bloc, notably, marked by dependency on oil revenues. In analysing quantile-based results, oil supply shocks mainly exhibit lower-tail dependence, while the authors do uncover some evidence of demand-side shocks affecting mid and upper-tail dependence.

Acknowledging the presence of endogeneity in the relation between oil and economic activity, to the best of the authors’ knowledge, this study is the first to combine the oil price decompositions of Ready (2018) with a quantile regression framework in the GCC context. The results reveal notable difference to those previously reported in the literature.

This paper aims to employ GARCH-class models (GARCH, IGARCH and CGARCH) to estimate the volatility persistence on crude oil, US, Gulf Corporation Council (GCC), Brazil, Russia, India and China (BRIC) stock markets. Also, the paper investigates the volatility spillover and the dynamic conditional correlation between crude oil, US stock index and stock indices of GCC and BRIC countries. The results prove a high degree of volatility persistence in the crude oil and stock markets. Based on the BEKK-GARCH and DCC-GARCH results, the paper finds strong evidence of the contagion effect of the oil shock and US financial crisis of 2008 on GCC and BRIC stock markets.

In the beginning, the paper uses univariate GARCH models to estimate the volatility persistence of the oil market, US stock market, and GCC and BRIC stock markets. Then, the paper uses a trivariate BEKK-GARCH model of Malik and Hammoudeh to examine the volatility spillover between oil market, US stock market and stock markets for GCC and BRIC countries. Finally, the paper analyses the dynamic conditional correlation between US market and each stock market of GCC and BRIC countries using the DCC-GARCH model. Also, the paper estimates the dynamic conditional correlation between oil market and all stock markets.

The results indicate the contagion effect of the oil shock and US financial crisis of 2008 on the GCC stock markets which are among the most important oil-exporting countries and also on BRIC stock markets which are among the emergent countries which are characterized by high economic growth level.

The contribution of this paper is to investigate the existence of contagion effect between oil market, US stock market and two panels of emerging stock markets which have different economic characteristics, the GCC and BRIC countries, during the oil shock and US financial crisis period of 2008-2009.

This paper aims to investigate the transmission of international oil prices to the stock market indices of the Gulf Cooperation Council (GCC) countries over the weekly period from April 07, 2004, to August 15, 2018.

The authors use the augmented Dickey–Fuller (ADF) unit root test to check the order of integration of data series. Afterward, the authors use the ordinary least square method to determine the spillover of international oil prices to the stock markets of GCC countries while accounting for the time-varying volatility of oil and stock market returns through the generalized autoregressive conditional heteroskedasticity. Then, the Johansen (1991) cointegration test is used to determine the long-run equilibrium relationship. Finally, the Granger (1969) causality test is used to determine the short-run causal effects between oil and the stock markets returns of GCC countries.

The findings indicate that the stock markets of GCC countries are efficient and respond significantly to international oil prices and evidence of high volatility associated with oil returns.

Investors and portfolio managers should consider the association between international oil prices and GCC stock returns when allocating their funds for diversification strategy. Moreover, policymakers should better understand the behavior of local stock markets.

This study aims to investigate the nature and degree of US economic policy uncertainty spillover on the stock markets of a group of non-conventional economies like the Gulf Cooperation Council (GCC) countries, where a risk-sharing-based financial system is prominent and foreign investment, risk-free interest, derivatives, etc. are not as widespread as in the western economies.

the monthly data of 1992–2018, linear and nonlinear structural vector autoregression (VAR) model, and an impulse response-based test to explore the nature and degree of US economic policy uncertainty spillover on the stock markets of the GCC countries.

This study finds that an unexpected increase in the US economic policy uncertainty significantly decreases the stock market index of all the GCC countries. This study also gets this relationship symmetric, meaning that the GCC stock market indices decrease and increase by the same amount when the US economic policy uncertainty increases and decreases, respectively.

This study investigates the characteristics of economic policy uncertainty spillover from the biggest economy of the world to the stock markets of the GCC region, which is new to the literature. The study results provide the first evidence that a risk-sharing based financial system does not necessarily protect the stock market from US uncertainty shock. However, the abundance of local investors, risk-sharing investment activities, the absence of derivatives, etc. may be responsible for the symmetric behavior of a stock market.

This study aims to investigate the transmission of shock between the oil market and the Islamic and conventional stock markets of the Gulf Cooperation Council (GCC) countries during the oil shocks of 2008 and 2014.

This study uses two models. First, the dynamic conditional correlation–generalized autoregressive conditionally heteroskedastic model has been used to capture the fundamental contagion effects between the oil market and the Islamic and conventional stock markets during the tranquil and turmoil-crisis periods of 2008-2014. Second, the filter of Kalman has been used to capture the effects of pure contagion between the oil market and the GCC Islamic and conventional stock markets. The authors analyze the dynamic correlation between forecasting errors of oil returns and stock returns of GCC Islamic and GCC conventional indices.

The main findings of this investigation are: first, the estimation of the dynamic conditional correlation– generalized autoregressive conditionally heteroskedastic model for oil market and the Islamic and conventional stock markets proves that the Islamic and conventional stock markets and oil market displayed a significant increase in the dynamic correlation during the turmoil period, from mid-2008 and mid-2014. This proves the existence of contagion between the markets studied. Second, the authors analyze the dynamic correlation between forecasting errors of oil returns and stock returns of GCC Islamic and GCC conventional indices. They show a strong increase in the correlation coefficients between the oil market and the conventional GCC stock markets, and between the conventional and Islamic GCC stock markets during the oil crisis of 2014. However, there is no change in regime in the figure of the correlation coefficient between the oil market and the GCC Islamic stock markets during the 2008 financial crisis. This pure contagion is mainly attributed to the herding bias in 2014 oil crisis.

This study contributes to identifying the contribution of herding bias on the volatility transmission between the oil markets, and the GCC Islamic and conventional stock market, especially during two controversial shocks: the 2008 oil-price increase and the 2014 oil drop.

This study aims to examine the spillover effects of the mean and volatility between oil prices and stock indices of six Gulf Cooperation Council (GCC) countries (UAE, Kuwait, Saudi Arabia, Qatar, Oman and Bahrain).

Over the period 2008–2019, a bivariate VARMA-GARCH-ADCC model was combined with the maximal overlap discrete wavelet transform technique filter to shed light on a wide range of possible spillover effects in the mean and variances of level prices at various time horizons.

The authors find that the spillover effects between oil prices and the GCC stock markets are time-varying and spread across various time horizons. Besides, oil prices and stock market indices are directly impacted by their own shocks and variations and indirectly influenced by other price volatilities and wavelet scales. The linkages in volatility spillovers between oil prices and the GCC stock markets occur in the short-term, midterm and long-term horizons. More specifically, the results also show that the asymmetric estimates are statistically significant for the associations between oil prices and each stock market in the GCC countries. This implies that negative shocks play a more vital role than positive shocks in driving the dynamic condition correlations between oil and stock markets under study.

The significant interrelatedness between oil prices and each stock market in the GCC countries has important implications for investors, portfolio managers, and other market participants. They can use the findings of this research to create the best oil-GCC stock portfolios and predict more precisely the volatility spillover patterns in constructing their hedging strategies.

In several ways, this study differs from previous research. First, while previous empirical studies of the dynamic link between oil prices and stock markets have focused primarily on developed or emerging markets, the focus of this is on six GCC countries. Second, the linkage between oil prices and stock markets is typically studied at the original data level in the time domain in relevant literature, while frequency information is overlooked. Therefore, the current study examines this relationship from a multiscale perspective. Third, in this paper, to capture a wide range of possible spillover effects in the mean and variance of level prices at multiple wavelet scales, the authors use a VARMA-GARCH-ADCC model in conjunction with wavelet multiresolution analysis. Additionally, this article also applies wavelet hedge ratio and wavelet hedge portfolio analysis at various time horizons.

This study aims to investigate the reaction (in terms of returns and volatility) of Gulf Cooperation Council (GCC) country-wise stock markets (both conventional and Islamic) in response to the surge of COVID-19 cases, with special reference to the announcement of financial stimulus packages in each country and the recent global oil price plunge. Further, the study also examines the impact of COVID-19 cases on the stock market returns of each GCC country and the continuous dynamics of correlation between COVID-19 cases and GCC stock markets.

This study uses an exponential generalized auto regressive conditional heteroskedasticity model and continuous wavelet coherence to estimate the stock market volatility and co-movement between COVID-19 cases and stock returns.

Empirical findings indicate an adverse reaction (negative returns and high volatility) during the period examined, with the stimulus package resulting in a positive transformation of returns in each country-level stock market as well as the regional stock index. Further, no evidence of an adverse effect of the oil price plunge is identified. All findings are identical between both conventional and Islamic stock indices.

While ample research has been conducted on the impact and dynamics of the pandemic on stock markets, little has addressed the areas of financial stimulus packages and the oil price plunge. The findings of this study show that further research needs to be conducted to elucidate the ways in which effective financial stimulus packages can be formulated in the GCC region to mitigate the adverse effects of COVID-19 for economies without causing major financial deficits, as well as to find strategies to diversify economies away from the oil curse.

This study aims to uncover the main predictors of financial distress in the Gulf Cooperation Council (GCC) countries using a wide range of global factors and asset classes.

This study uses novel approaches that take into account extreme events as well as the nonlinear behavior of time series over various time intervals (i.e. short, medium and long term) and during boom and bust episodes. This study primarily uses the conditional value at risk (CoVaR), the quantile multivariate causality test and the partial wavelet coherence method. The data collection period ranges from March 2014 to September 2022.

US T-bills and gold are the primary factors that can increase financial stability in the GCC region, according to VaRs and CoVaRs. More proof of the predictive value of the oil, gold and wheat markets, as well as geopolitical tensions, uncertainty over US policy and volatility in the oil and US equities markets, is provided by the multivariate causality test. When low extreme quantiles or cross extreme quantiles are taken into account, these results are substantial and sturdy. Lastly, after adjusting for the effect of crude oil prices, this study’s wavelet coherence results indicate diminished long-run connections between the GCC stock market and the chosen global determinants.

Despite the implications of the author’s research for decision makers, there are some limitations mainly related to the selection of Morgan Stanley Capital International (MSCI) GCC ex-Saudi Arabia. Considering the economic importance of the Kingdom of Saudi Arabia (KSA) in the region, the author believes that it would be better to include this country in the data to obtain more robust results. In addition, there is evidence in the literature of the existence of heterogeneous responses to global shocks; some markets are more vulnerable than others. This is another limitation of this study, as this study considers the GCC as a bloc rather than each country individually. These limitations could open up further research opportunities.

These findings are important for investors seeking to manage their portfolios under extreme market conditions. They are also important for government policies aimed at mitigating the impact of external shocks.

This paper investigates the impact of financial stress on the dynamic connectedness and hedging for oil market and stock-bond markets of the Gulf Cooperation Council (GCC).

This study uses the wavelet coherence model to examine the interactions between financial stress, oil and GCC stock and bond markets. Second, the authors apply the time–frequency connectedness developed by Barunik and Krehlik (2018) so as to identify the direction and scale connectedness among these markets. Third, the authors examine the optimal weights, hedge ratio and hedging effectiveness for oil and financial markets based on constant conditional correlation (CCC), dynamic conditional correlation (DCC) and Baba-Engle-Kraft-Kroner (BEKK)-GARCH models.

The authors have found that the correlation between the oil and stock-bond markets tends to be stable in nonshock periods, but it evolves during oil and financial shocks at lower frequencies. Moreover, the authors find that the oil market and financial stress are the main transmitters of risks. The connectedness is mainly driven by the long term, demonstrating that the markets rapidly process the financial stress spillover effect, and the shock is transmitted over the long run. Optimal weights show different patterns for each negative and positive case of the financial stress index. In the negative (positive) financial stress case, investors should have more oil (stocks) than stocks (oil) in their portfolio in order to minimize risk.

This study has gone some way toward enhancing one’s understanding of the time–frequency connectedness between the financial stress, oil and GCC stock-bond markets. Second, it identifies the impact of financial stress into hedging strategies offering important insights for investors aiming at managing and reducing portfolio risk.