Equity market contagion during the global financial crisis: Evidence from the world's eight largest economies

The global financial crisis (2007–2009) saw sharp declines in stock markets around the world, affecting both advanced and emerging markets. In this paper we test for the existence of equity market contagion originating from the US to advanced and emerging markets during the crisis period. Using a latent factor model, we provide strong evidence of contagion effects in both advanced and emerging equity markets. In the aggregate equity market indices, contagion from the US explains a large portion of the variance in stock returns in both advanced and emerging markets. However, in the financial sector indices we find less evidence of contagion than in the aggregate indices, and this is particularly the case for the advanced markets. The results suggest that contagion effects are not strongly related to high levels of global integration.     

COVID-19 and asymmetric volatility spillovers across global stock markets

In this study, I improve the assessment of asymmetry in volatility spillovers, and define six asymmetric spillover indexes. Employing Diebold-Yilmaz spillover index, network analysis, and my developed asymmetric spillover index, this study investigates the time-varying volatility spillovers and asymmetry in spillovers across stock markets of the U.S., Japan, Germany, the U.K., France, Italy, Canada, China, India, and Brazil based on high-frequency data from June 1, 2009, to August 28, 2020. I find that the global markets are well connected, and volatility spillovers across global stock markets are time-varying, crisis-sensitive, and asymmetric. Developed markets are the main risk transmitters, and emerging markets are the main risk receivers. Downside risk dominates financial contagion effects, and a great deal of downside risk spilled over from stock markets of risk transmitters into the global markets. Moreover, during the coronavirus recession, the total degree of volatility spillover is staying at an extremely high level, and emerging markets are the main risk receivers in the 2020 stock markets crash.     

Better to give than to receive: Predictive directional measurement of volatility spillovers

Using a generalized vector autoregressive framework in which forecast-error variance decompositions are invariant to the variable ordering, we propose measures of both the total and directional volatility spillovers. We use our methods to characterize daily volatility spillovers across US stock, bond, foreign exchange and commodities markets, from January 1999 to January 2010. We show that despite significant volatility fluctuations in all four markets during the sample, cross-market volatility spillovers were quite limited until the global financial crisis, which began in 2007. As the crisis intensified, so too did the volatility spillovers, with particularly important spillovers from the stock market to other markets taking place after the collapse of the Lehman Brothers in September 2008.     

The impact of VIX on China’s financial market: A new perspective based on high-dimensional and time-varying methods

Based on the new perspective of high-dimensional and time-varying methods, this paper analyzes the contagion effects of US financial market volatility on China’s nine financial sub-markets. The results show evidence of non-linear Granger causality from the US financial volatility (VIX) to the China’s financial markets. Increased US financial volatility has a negative next-day impact on the stock, bond, fund, interest rate, foreign exchange, industrial product and agricultural product markets, and a positive next-day impact on the gold and real estate markets. US financial volatility has the greatest impact on industrial product market, following by stock, agricultural product, fund, real estate, bond, gold, foreign exchange, and interest rates. Major risk events such as the global financial crisis can cause an enhanced contagion effect of US financial volatility to China's financial markets. This paper supports the achievements of China's actions to prevent and resolve major financial risks in the period of the COVID-19 epidemic.     

Spatial spillover effects and risk contagion around G20 stock markets based on volatility network

Employing the spatial econometric model as well as the complex network theory, this study investigates the spatial spillovers of volatility among G20 stock markets and explores the influential factors of financial risk. To achieve this objective, we use GARCH-BEKK model to construct the volatility network of G20 stock markets, and calculate the Bonacich centrality to capture the most active and influential nodes. Finally, we innovatively use the volatility network matrix as spatial weight matrix and establish spatial Durbin model to measure the direct and spatial spillover effects. We highlight several key observations: there are significant spatial spillover effects in global stock markets; volatility spillover network exists aggregation effects, hierarchical structure and dynamic evolution features; the risk contagion capability of traditional financial power countries falls, while that of “financial small countries” rises; stock market volatility, government debt and inflation are positively correlated with systemic risk, while current account and macroeconomic performance are negatively correlated; the indirect spillover effects of all explanatory variables on systemic risk are greater than the direct spillover effects.     

Volatility contagion: A range-based volatility approach

This article proposes a new approach to evaluate volatility contagion in financial markets. A time-varying logarithmic conditional autoregressive range model with the lognormal distribution (TVLCARR) is proposed to capture the possible smooth transition in the range process. Additionally, a smooth transition copula function is employed to detect the volatility contagion between financial markets. The approach proposed is applied to the stock markets of the G7 countries to investigate the volatility contagion due to the subprime mortgage crisis. Empirical evidence shows that volatility is contagious from the US market to several markets examined.     

Multiscale financial risk contagion between international stock markets: Evidence from EMD-Copula-CoVaR analysis

Considering the frequency domain and nonlinear characteristics of financial risks, we measure the multiscale financial risk contagion by constructing EMD-Copula-CoVaR models. Using a sample composed of nine international stock markets from January 4, 1999, to May 13, 2021, the empirical study reveals that: (1) EMD-Copula-CoVaR models can effectively measure the multiscale financial risk contagion, and the financial risk contagion is significant at all time scales; (2) The high-frequency component is the major contributor of financial risk contagion; meanwhile, the low-frequency component is the smallest among all time scale components; (3) The risk export of the US financial market to other markets, except the UK under the original and medium-frequency component, is higher than that it receives; and (4) Even though the magnitude of overall financial risk contagion is similar for the COVID-19 pandemic, Subprime Crises, 9/11 terrorist attack and other crises, the relative importance of different frequency components is heterogeneous. Therefore, the countermeasures of risk contagion should be designed according to its multiscale characteristics.     

Network VAR models to measure financial contagion

Financial contagion among countries can arise from different channels, the most important of which are financial markets and bank lending. The paper aims to build an econometric network approach to understand the extent to which contagion spillovers (from one country to another) aris from financial markets, from bank lending, or from both. To achieve this aim we consider a model specification strategy which combines Vector Autoregressive models with network models. The paper contributes to the contagion literature with a model that can consider bank exposures and financial market prices, jointly and not only separately. From an empirical viewpoint, our results show that both bilateral exposures and market prices act as contagion channels in the transmission of shocks arising from a country to other countries.     

Modelling contagion of financial crises

Inspired by the empirical findings, we include international traders to capture linkage between markets and propose a two-market heterogeneous agents model to simulate financial crisis with contagion effect. This paper manages to calibrate sudden crash behavior of US and UK stock markets during “Black Monday” of 1987 besides smooth crisis and disturbing crisis categorized in literature. It is implied that financial crisis and its contagion could be endogenous, which supports a scenario of over-valuation causing a financial crisis. In addition, the model shows that financial system could be fragile in which small shock(s) hitting individual market’s fundamental could cause financial crisis spreading to the other market. This also supports a scenario of external shock triggering a financial crisis. Lastly, to demonstrate the relevance of our model to financial markets, we manage to match typical stylized facts, especially cross-correlation which is exclusive to a multiple-market case.     

Risk spillovers and hedge strategies between global crude oil markets and stock markets: Do regime switching processes combining long memory and asymmetry matter?

This paper investigates risk spillovers and hedge strategies between global crude oil markets and stock markets. In the paper, we propose a multivariate long memory and asymmetry GARCH framework that integrates state-dependent regime switching in the mean process with multivariate long memory and asymmetry GARCH in the variance process. Our results first show that there are linear risk spillovers running from the US stock markets to the WTI oil market in the short term. However, the linear risk spillover effect running from the oil market to the US stock market can only exist in the long term. In addition, there is a bidirectional linear risk spillover effect between the European stock markets and the Brent oil market in the short and long terms. Furthermore, there is no linear risk spillover effect between the Dubai oil market and the Chinese stock market. Second, the nonlinear risk spillovers running from the WTI oil market to the US stock market can be found in the tranquil regime. Moreover, there is also a nonlinear risk spillover effect running from the European stock markets to the Brent oil market in the tranquil regime. In addition, the nonlinear risk spillover effect running from the Brent oil markets to the European stock market can be found in the crisis regime. Furthermore, there is bidirectional nonlinear Granger causality between the Dubai crude oil market and the Chinese stock market in the tranquil regime. Finally, dynamic hedge effectiveness shows that the regime switching process combined with long memory and asymmetry behavior seems to be a plausible and feasible way to conduct hedge strategies between the global crude oil markets and stock markets.     

Multiscale features of extreme risk spillover networks among global stock markets

This paper studies the multiscale features of extreme risk spillover among global stock markets over various time–frequency horizons. We propose multiscale risk spillover indexes based on GARCH-EVT-VaR, maximal overlap discrete wavelet transform method, and forecast-error-variance decompositions. We further construct multiscale risk spillover networks to visualize risk spillovers at different scales. Our findings show that the US and the UK are detected as the centers of risk spillovers, while Asian stock markets are mainly at the edge of the risk spillover network. The topological properties are unevenly spread over each time scale. The network tends to be closer not only at the short-term scale but also during the financial crisis. For individual features, the US and the UK are super-spreaders of risk spillover at each time scale, while most developing markets mainly act as absorbers. The role of European stock markets is complex at different scales.     

Dynamic volatility spillovers between industries in the US stock market: Evidence from the COVID-19 pandemic and Black Monday

We examine the volatility spillovers among various industries during the COVID-19 pandemic period. We measure volatility spillovers by defining the volatility of each sector in the S&P 500 index and implement a static and rolling-window analysis following the Diebold and Yilmaz (2012) approach. We find that the pandemic enhanced volatility spillovers, which reveals the financial contagion effects on the US stock market. Second, there were sudden, large changes in the dynamic volatility spillovers on Black Monday (March 9, 2020), much of it due to the energy sector shock. These findings have important implications for portfolio managers and policymakers.     

Financial contagion vulnerability and resistance: A comparison of European stock markets

This paper investigates contagion to European stock markets associated with seven big financial shocks between 1997 and 2002. We apply methods using heteroscedasticity-adjusted correlation coefficients to discriminate between contagion, interdependence and breaks in stock markets relationships. The analysis focuses on a comparison between developed Western European markets and emerging stock markets in Central and Eastern Europe. We find modest evidence of significant instabilities in cross-market linkages after the crises. The Central and Eastern European stock markets are not more vulnerable to contagion than Western European markets.     

Global and regional integration of the Middle East and North African (MENA) stock markets

We investigate financial integration of MENA region to facilitate a more in-depth exploration of the structure of interdependence and transmission mechanism of stock returns and volatility between MENA and world stock markets. The EGARCH-M models with a generalized error distribution are employed to consider both leverage effect of negative shocks and leptokurtosis prevalent in the MENA stock markets. The estimation results of multivariate AR-GARCH models indicate that there are large and predominantly positive volatility spillovers and volatility persistence in conditional volatility between MENA and world stock markets. Own-volatility spillovers are generally higher than cross-volatility spillovers for all the markets.     

Region-wide connectedness of Asian equity and currency markets

This study systemically analyzes the dynamics of interdependence between the Asian equity and currency markets. The novelty of our study is that unlike other studies that explore either co-movements among equity markets or co-movements among currency markets, we pay particular attention to the interdependence between the two in terms of both return and volatility connectedness. We find that the contribution of crossspillovers between the Asian equities and currencies is substantial for the region-wide connectedness of both the returns and volatilities. We also find that the short-term spillovers are far more important for the return spillovers, while the long-term spillovers are far more important for the volatility spillovers, presumably reflecting the long-lasting effects of volatility shocks. All the results consistently underline the pivotal role of cross-interdependence between equity and currency markets, both as channels for integrating Asian financial markets and as sources of financial contagion across these markets. Our findings will provide useful guidance for portfolio risk management to adopt better hedging strategies for foreign exchange risks involved in the international investment of Asian equities.     

Contagion between real estate and financial markets: A Bayesian quantile-on-quantile approach

We study contagion between Real Estate Investment Trusts (REITs) and the equity market in the U.S. over four sub-samples covering January, 2003 to December, 2017, by using Bayesian nonparametric quantile-on-quantile (QQ) regressions with heteroskedasticity. We find that the spillovers from the REITs on to the equity market has varied over time and quantiles defining the states of these two markets across the four sub-samples, thus providing evidence of shift-contagion. Further, contagion from REITs upon the stock market went up during the global financial crisis particularly, and also over the period corresponding to the European sovereign debt crisis, relative to the pre-crisis period. Our main findings are robust to alternative model specifications of the benchmark Bayesian QQ model, especially when we control for omitted variable bias using the heteroskedastic error structure. Our results have important implications for various agents in the economy namely, academics, investors and policymakers.     

What drives herding in oil-rich,developing stock markets? Relative roles of own volatility and global factors

The main goal of this paper is to formally establish the volatility-herding link in the developing stock markets of the oil-rich GCC countries by examining how market volatility affects herd behavior after controlling for global factors. Using a regime-switching, smooth transition regression model (STR), we find significant evidence of herding in all Gulf Arab stock markets, with the market volatility being the more paramount factor governing the switches between the extreme states of non-herding and herding. The global variables comprised of the U.S. stock market performance, the price of oil and the US interest rate as well as the risk indexes including the CBOE Volatility Index (VIX) and the St. Louis Fed's Financial Stress Index (FSI) are found to be significant factors governing the transition to herding states. The findings stress the effect of contagion in financial markets, despite the restrictions established by the GCC policymakers in order to protect their markets.     

Risk spillover analysis across worldwide ESG stock markets: New evidence from the frequency-domain

With the increasing global awareness of green environmental protection, the international environmental, social, and governance (ESG) stock markets are developing rapidly together with rising risk linkages across worldwide markets. Therefore, this study explores the risk spillover characteristics of international ESG stock markets in the time and frequency domains and constructs a risk linkage network to further explore the risk contagion mechanism. The results show that in most cases, the developed North American market is the core of outward risk spillover in international ESG stock markets. The entire system presents a small-world structure, and the internal regions display different risk spillover characteristics. Moreover, international ESG markets generally have strong time–frequency spillover and medium-frequency (a month to a year) spillover. In contrast, the high- (a day to a month) and low-frequency (more than one year) spillovers are located at relatively low levels, but they will rise significantly under sudden financial events. The empirical results expand the ESG stock market's theoretical framework and provide a reference for investors and market regulators to reduce the investment risk of ESG.     

Interest rate risk propagation: Evidence from the credit crunch

During the 2007–2009 financial crisis, US subprime mortgage risk exposures led to severe liquidity problems in several other foreign markets. Such risk contagion was caused by enormous changes in interest rates. Although risk contagion has been investigated by several literatures, the magnitude of propagated interest rate risk around global financial markets remains unexplored. Therefore, this study quantifies the degree to which the increased credit risk within the US financial system propagated to the European markets’ liquidity risks. Specifically, using a conditional value-at-risk (CoVaR) model, we quantitatively measure interest rate risk of a European country, by looking at the upside risk in distribution of changes in interest rate. And such propagation risk measure considers additional value-at-risk conditional on the interest rate movements in the US. The results show significantly positive differences between European country's value-at-risk conditional on the US financial markets being in a normal or distressed state. This propagating effect increased from 2007, and was particularly pronounced in the 2008–2009. In addition, the interest rate risk contagion is especially severe for some countries in the Euro regions with greater sovereign debt problems. Hence our result foretells the deterioration of the European sovereign debt crisis which started to unfold in 2010. Our work supplements the literature by successfully quantifying the magnitude of additional interest rate risk conditional on risk exposure from external sectors.