Oil price and stock market co-movement: What can we learn from time-scale approaches?

This paper study the relationship between oil and stock markets in G7 countries, by distinguishing between interactions based on fundamentals (long-term interdependence: high memory impact) and contagion (short-term interaction: transitory contamination). To do this, we propose in the first time two complementary frequency approaches based: the evolutionary co-spectral analysis and the wavelet approach allowing a time-varying measure of the dynamic correlation between the oil and stock markets over time and across time horizons. We find that interdependence between oil price and the stock market is more pronounced in the short and medium terms than in the long term. In addition, we prove that stock markets are more sensitive to oil shocks originating from demand shocks. These findings provide important policy implications for both policymakers, in terms of taking relevant actions regarding oil shocks originating from the demand side, and investors, in terms of a policy of diversification that depends on horizons.     

Time-varying impacts of demand and supply oil shocks on correlations between crude oil prices and stock markets indices

This paper investigates the time-varying impacts of demand and supply oil shocks on correlations between changes in crude oil prices and stock markets returns. The findings, obtained by means of a DCC-GARCH from June 2006 to June 2016, indicate that demand shocks positively affected the correlations between crude oil prices and stock market returns from late 2007 to mid-2008, during the apex of the financial markets volatility; from early 2009 to mid-2013, during global economy recovery from the financial crisis; and after 2015, when uncertainties about the Chinese growth and the US economy upturning arose. The dynamic conditional correlation, obtained after the removal of demand shocks effects, presented an average value of 0.13 when all economy sectors were considered and of 0.03 when the energy sector returns were excluded from the stock index. These correlations, still positive on average, suggest that exogenous supply oil shocks had little impact on US mainly enterprises cash flows over the last 10 years. Exceptions are the periods from 2006 to financial crisis and from 2014 until April 2016, when significant and unpredicted changes in oil market happened, considerably affecting the value of the main US companies.     

Oil price shocks and American depositary receipt stock returns

In this paper we examine the impact of oil price shocks on twelve countries American Depositary Receipt (ADR) returns using monthly data from 1999.01 to 2014.12. The results show that oil price shocks have a positive and statistically significant impact on ADR return in all twelve countries. These results are robust to the inclusion of other explanatory variables such as oil price volatility and the spillover of the United States stock market. Further analysis shows that this effect is stronger in the post financial crisis time period compared to the pre-financial crisis time period.     

Financial Crisis and Intertemporal Linkages Across the ASEAN-5 Stock Markets

The stock indices of five ASEAN countries, namely, Singapore, Malaysia, Indonesia, Thailand and the Philippines have experienced a structural change after mid-1997 due to the Asian financial crisis, and another shift slightly more than a year later when the markets rebounded. Contemporaneous correlation in stock returns is the strongest and Indonesia leads the movements of the other indices during the crisis. The relative influence of foreign shocks is much more felt during the crisis, as seen in the stronger and longer horizon of responses of all the markets. The stock indices are cointegrated before, but not during the crisis. Price feedbacks between the larger markets of Singapore, Malaysia and Indonesia that existed before the crisis disappear once the crisis is over. Short-run linkages of Malaysia with the other markets have weakened after the crisis. With an increase in the degree of exogeneity of its stock market, contemporaneous co-movements with the other markets have reduced and the causal relationships no longer exist.JEL Classification: G15, F30An earlier draft of this paper was presented at the 11th Annual Conference on Pacific Basin Finance, Economics & Accounting held in Taipei. This paper benefited from the discussions at the conference. We are grateful to two anonymous referees for helpful comments and suggestions which led to further improvement of the paper.     

Crude oil shocks and African stock markets

In this paper, we investigate the impact of crude oil shocks on selected African stock markets using a Structural Vector Autoregressive model and a two-state regime smooth transition regression framework on monthly data from January 2000 to July 2018. The study is timely given the fast-growing energy sector and stock markets in Africa as well as the place of Africa in international trade. Selected markets are classified into oil-exporting (Nigeria, Tunisia, and Egypt) and oil-importing (Botswana, South Africa, Kenya, and Mauritius). The key findings are as follows: global demand shock does not really matter in oil-importing countries; there is little evidence that oil supply shock affects the real stock return for oil-exporting and oil-importing countries; oil-specific shock is significant for most countries investigated; negative price shocks have more impact than positive price shocks. The findings from this study have important implications for investors whose portfolios may comprise of assets from African stock markets and crude oil. Given the importance of oil in the global market, one would typically avoid equities that suffer from its shock. This study provides the indicators to inform that decision.     

Multivariate FIAPARCH modelling of financial markets with dynamic correlations in times of crisis

This paper applies the vector AR-DCC-FIAPARCH model to eight national stock market indices' daily returns from 1988 to 2010, taking into account the structural breaks of each time series linked to the Asian and the recent Global financial crisis. We find significant cross effects, as well as long range volatility dependence, asymmetric volatility response to positive and negative shocks, and the power of returns that best fits the volatility pattern. One of the main findings of the model analysis is the higher dynamic correlations of the stock markets after a crisis event, which means increased contagion effects between the markets. The fact that during the crisis the conditional correlations remain on a high level indicates a continuous herding behaviour during these periods of increased market volatility. Finally, during the recent Global financial crisis the correlations remain on a much higher level than during the Asian financial crisis.     

Oil prices and economic policy uncertainty: Evidence from global,oil importers,and exporters’ perspective

Containing various information, economic policy uncertainty reflects significant rises and declines when facing shocks like financial crisis, oil-price change, and other specific economic or policy events. This paper empirically studies the interaction between oil prices and the newly formulated economic policy uncertainty indices using a time-varying parameter vector autoregression framework. Generally, the results of this study suggest that economic policy uncertainty reveals fluctuating responses to oil price shocks, while the oil price has a negative response to the uncertainty. The findings also reveal that the economic policy uncertainty indices for oil-importers and oil-exporters respond to oil price shocks differently. The oil price shock has a larger fluctuation to the economic policy uncertainty of oil-exporters than that of importers. Moreover, for the oil-exporters, the negative response to the oil price shock is greater than that of the oil-importing countries. This paper also discusses the impact of asymmetric shocks of oil price on economic policy uncertainty. In particular, after two financial crises, positive shocks decrease the uncertainty and vice versa. These findings are robustly verified.     

Oil Price and Stock Market Synchronization in Gulf Cooperation Council Countries

Knowing that the Gulf Cooperation Council (GCC) economies are dichotomous in nature, and growth in the non-oil sector is tributary to the oil sector, we document the extent of synchronization between crude oil prices and stock markets for each of the GCC markets and for the GCC as an economic bloc. We use both the bivariate and multivariate nonparametric synchronicity measures proposed by Mink et al. (2007) to assess that linkage. We find a low to mild (mild to strong) degree of synchronization between oil price and stock market returns (volatilities). In a very few instances, we find very strong (above 80 percent) associations between these variables. These results hold irrespective of whether we assume that stock market participants form adaptive or rational expectations about the price of oil. Dynamic factor results confirm that shocks to volatility are more important than shocks to oil price returns for the GCC stock markets.     

Black swan events and safe havens: The role of gold in globally integrated emerging markets

There is evidence to suggest that gold acts as both a hedge and a safe haven for equity markets over recent years, and particularly during crises periods. Our work extends the recent literature on hedging and diversification roles of gold by analyzing its interaction with the stock markets of the leading emerging economies, the BRICS. While they generally exhibit a high growth rate, these economies still experience a pronounced vulnerability to external shocks, particularly to commodity price fluctuations. Using a multi-scale wavelet approach and a GARCH-based copula methodology, we mainly show evidence of: (i) the time-scale co-evolvement patterns between BRICS stock markets and gold market, with some profound regions of concentrated extreme variations; and (ii) a strong time-varying asymmetric dependence structure between those markets. These findings are essential for risk diversification and portfolio hedging strategies among the investigated markets.     

Contagion in financial markets after September 11: myth or reality?

Major global events can lead to a change in the cross‐country correlation of assets. Using stock prices from 25 economies, we test whether the terrorist attack in the United States on September 11, 2001, resulted in a contagion—an increase in correlation across global financial markets. Unlike prior works on contagion, we model the intrinsic heteroskedasticity. Our results indicate that international stock markets, particularly in Europe, responded more closely to U.S. stock market shocks in the three to six months after the crisis than before. Our evidence suggests that the benefits of international diversification in times of crisis are substantially diminished.     

Modeling systemic risk and dependence structure between oil and stock markets using a variational mode decomposition-based copula method

This study combines the variational mode decomposition (VMD) method and static and time-varying symmetric and asymmetric copula functions to examine the dependence structure between crude oil prices and major regional developed stock markets (S&P500, stoxx600, DJPI and TSX indexes) during bear, normal and bull markets under different investment horizons. Furthermore, it analyzes the upside and downside short- and long-run risk spillovers between oil and stock markets by quantifying three market risk measures, namely the value at risk (VaR), conditional VaR (CoVaR) and the delta CoVaR (∆CoVaR). The results show that there is a tail dependence between oil and all stock markets for the raw return series. By considering time horizons, we show that there is an average dependence between the considered markets for the short-run horizons. However, the tail dependence is also found for the long-run horizons between the oil and stock markets, with the exception of the S&P500 index which exhibits average dependence with the oil market. Moreover, we find strong evidence of up and down risk asymmetric spillovers from oil to stock markets and vice versa in the short-and long run horizons. Finally, the market risk spillovers are asymmetric over the time and investment horizons.     

On the volatility spillover between lslamic and conventional stock markets: A quantile regression analysis

This paper aims at analyzing the degree and structure of interdependencies in terms of volatility (transmission, contagion) between Islamic and conventional stock markets on calm periods and at times of financial fragility and crisis. We focused on the recent financial instability periods and used the Quantile Regression-based GARCH model. Main results lead to very interesting conclusions. First, it has been found that Islamic stock markets are not totally immune to the global financial crisis. Second, a very strong interdependence is sensed from the conventional to the Islamic stock markets, especially, from the conventional developed markets to the Islamic Emerging and Arab markets and to the Islamic developed markets. Finally, it has been proved that the interdependencies from conventional to Islamic markets are propagated between Islamic markets. Our findings suggest that the Islamic finance industry does not seem able to provide cushion against economic and financial shocks that affect conventional markets.     

Studying the properties of the Bitcoin as a diversifying and hedging asset through a copula analysis: Constant and time-varying

In this study, we analyze the properties of Bitcoin as a diversifier asset and hedge asset against the movement of international market stock indices: S&P500 (US), STOXX50 (EU), NIKKEI (Japan), CSI300 (Shanghai), and HSI (Hong Kong). For this, we use several copula models: Gaussian, Student-t, Clayton, Gumbel, and Frank. The analysis period runs from August 18, 2011 to June 31, 2019. We found that the Gaussian and Student-t copulas are best at fitting the structure dependence between markets. Also, these copulas suggest that under normal market conditions, Bitcoin might act as a hedge asset against the stock price movements of all international markets analyzed. However, the dependence on the Shanghai and Hong Kong markets was somewhat higher. Also, under extreme market conditions, the role of Bitcoin might change from hedge to diversifier. In a time-varying copula analysis, given by the Student-t copula, we found that even under normal market conditions, for some markets, the role of Bitcoin as a hedge asset might fail on a high number of days.     

Equity market integration in emerging Balkan markets

This paper examines long-run relationships among five Balkan emerging stock markets (Turkey, Romania, Bulgaria, Croatia, Serbia), the United States and three developed European markets (UK, Germany, Greece), during the period 2000-2009. Conventional, regime-switching cointegration tests and Monte Carlo simulation provide evidence in favour of a long-run cointegrating relationship between the Balkan emerging markets within the region and globally. Moreover, we apply the Asymmetric Generalized Dynamic Conditional Correlation (AG-DCC) multivariate GARCH model of Cappiello et al. (2006), in order to capture the impact of the 2007-2009 financial crisis on the time-varying correlation dynamics among the developed and the Balkan stock markets. Results show that stock market dependence is heightened, supporting the herding behaviour during the 2008 stock market crash period. Our findings have important implications for international portfolio diversification and the effectiveness of domestic policies, as these emerging markets are exposed to external shocks.     

The dynamic dependence between stock markets in the greater China economic area: a study based on extreme values and copulas

This study employs the dynamic copula method and extreme value theory to investigate the dependence structure between pairs of greater China economic area (GCEA) stock markets consisting of Shanghai (SHSE), Shenzhen (SZSE), Hong Kong (HKSE), and Taiwan (TWSE) stock exchanges from July 2000 to June 2017. We also examine the impact of financial crisis on the dependence structure by considering the global financial crisis and the Chinese stock market crash (2015–2016). Many studies have shown that the benefits of portfolio diversification across the stock markets in the same region could be diminishing. However, it is interesting to see that the diversification benefits appear to be viable for investing in some GCEA pairs of stock markets (SHSE–TWSE and SZSE–HKSE).     

Stock–bond dependence and flight to/from quality

This paper investigates the stock–bond dependence structure using a dependence-switching copula model. The model allows stock–bond dependence to switch between positive dependence regimes (contagions or crashes of the two markets during downturns or booms in both markets during upturns) and negative dependence regimes (flight-to-quality from stock markets to bond markets or flight-from-quality from bond markets to stock markets). Using data from four developed markets including the US, Canada, Germany, and France for the period between January 1985 and August 2022, we find that the within-country stock–bond (extreme) dependence could be both positive and negative. In the positive dependence regimes, the stock–bond dependence is asymmetric with stronger left tail dependence than the right tail dependence, giving evidence of a higher likelihood of joint stock–bond market crashes or contagions during market downturns than the collective stock–bond market booms. Under the negative dependence regimes, we find both flight-from-quality and flight-to-quality, with flight-to-quality being more dominant in the North American markets while flight-from-quality is more prominent in the European markets. Further, the dependence switches between positive and negative regimes over time. Moreover, the dependence is mainly in the positive regimes before 2000 while mostly in the negative regimes after that, indicating contagions mostly before 2000 and flights afterwards. Further, the dependence switches between positive and negative regimes around financial crises and the COVID-19 pandemic. These results greatly enrich the findings in the existing literature on the co-movements of stock–bond markets and are important for risk management and asset pricing.     

How do oil supply and demand shocks affect Asian stock markets?

This paper examines how oil market shocks affect Asian stock prices using the structural vector autoregression (VAR) approach. Global oil supply and demand shocks are disentangled using sign restrictions and elasticity bounds. Oil price increases are bad news only if the source is from oil-market-specific demand shifts. Northeast Asian stock markets are more resilient as investors’ expectation of continued economic growth outweighs the adverse effect of higher oil prices. Increased global economic activity also stimulates stock prices. Global oil shocks are more important in explaining variability in Asian stock returns compared with the United States, suggesting different dynamics in Asia.     

Financial crisis and stock market efficiency: Empirical evidence from Asian countries

This paper empirically investigates the effects of the 1997 financial crisis on the efficiency of eight Asian stock markets, applying the rolling bicorrelation test statistics for the three sub-periods of pre-crisis, crisis, and post-crisis. On a country-by-country basis, the results demonstrate that the crisis adversely affected the efficiency of most Asian stock markets, with Hong Kong being the hardest hit, followed by the Philippines, Malaysia, Singapore, Thailand and Korea. However, most of these markets recovered in the post-crisis period in terms of improved market efficiency. Given that the evidence of nonlinear serial dependencies indicates equilibrium deviation resulted from external shocks, the present findings of higher inefficiency during the crisis are not surprising as in the chaotic financial environment at that time, investors would overreact not only to local news, but also to news originating in the other markets, especially when the news events were adverse.     

Re-examination of international bond market dependence: Evidence from a pair copula approach

The finance literature provides substantial evidence on the dependence between international bond markets across developed and emerging countries. Early works in this area were based on linear models and multivariate GARCH models. However, based on the limitations of these models this paper re-examines the non-linearity, multivariate and tail dependence structure between government bond markets of the US, UK, Japan, Germany, Canada, France, Italy, Australia and the Eurozone, from January 1970 to February 2019 using ARMA-GARCH based pair- copula models. We find that the bond markets in our sample tend to have both upper tail dependence in terms of positive shocks and lower tail dependence in terms of negative shocks. The estimated C-vine shows Eurozone has the highest average dependency. The D-vine, with optimal chain dependency structure shows the best order of connectedness to be the UK, the USA, Italy, Japan, Eurozone, France, Canada, Germany and Australia. The R-vine copula results underline the complex dynamics of bond market relations existing between the selected economies. The estimated R-vine shows Eurozone, Germany and Australia are the most inter-connected nodes. The multivariate distribution structure (interdependency) of bond markets for all countries were modelled with the C-vine, D-vine and R-vine copulas. In this application, the R-vine copula allows for detailed modelling of all bond markets and hence provides a more accurate goodness of fit and mean square error for the interdependency between all markets. In light of the changing volatility in bond markets, we conduct additional tests using time-varying copulas and find that the dependence structure among the bond markets examined is time-varying with the dynamic dependence parameter plots revealing that the nature of the dependence structure is intense during crisis periods.     

Global financial crisis and emerging stock market contagion: A volatility impulse response function approach

By employing the volatility impulse response (VIRF) approach, this paper presents a general framework for addressing the extent of contagion effects between the BRICSs’ and U.S. stock markets and how the BRICSs’ stock markets have been influenced in the context of the 2007–2009 global financial crisis. Our empirical results show during the period of 2007–2009 global financial crisis, there are significant contagion effects from the U.S. to the BRICSs’ stock markets. Yet, the degree of stock market reactions to such shocks differs from one market to another, depending on the level of integration with the international economy. Besides, the strengthened degree of stock market integration among the U.S. and BRICS has adverse effect such that if the 2007–2009 global financial crisis occurs today it may result in heavier impact on stock market volatility nowadays compared to the crisis-era.