Spreading the fear: The central role of CBOE VIX in global stock market uncertainty

Construction of efficient portfolios is reliant on understanding the correlation between assets. If correlations change markedly during times of economic turmoil then investors are exposed to greater risk at the most inopportune time. We examine the linkages between global stock markets using measures of market uncertainty (implied volatility). Using a sample of daily changes in G7 and BRIC implied volatility measures, over a 20-year sample period, we demonstrate that uncertainty in U.S. markets plays a pivotal role in global stock market uncertainty. “Fear is spread” across markets, as heightened uncertainty in U.S. markets is transmitted across global markets. Conversely, changes in global market uncertainty do not explain changes in U.S. market uncertainty. While there is a clear increase in connectedness during crisis periods, we observe a disparity in the way that inter-dependencies change during the two major economic crises in our sample period; the GFC (2007–2009) and COVID-pandemic (2020). The additional importance of US news largely drives our results during the GFC, while the effect is spread among several countries (particularly within European markets) during COVID.     

The effects of quantitative easing on the integration of UK capital markets

We examine the effects of quantitative easing (QE) on the volatility of and correlation between stocks, short-term bonds and long-term bonds in the UK. Using a multivariate dynamic conditional correlation generalised autoregressive conditional heteroscedasticity model, we find that volatility in each of the markets experiences a significant increase during the financial crisis that is reversed during the first phase of QE. We find limited effects of the specific occurrence or intensity of QE activity on either the volatility or correlations for these asset classes, but some evidence that volatility persistence experienced temporary shifts during the sample period. We find short-term variability in the correlations between the markets during the crisis and QE periods, but cannot reject the hypothesis that correlations were constant throughout the sample period.     

Volatility dependences of stock markets with structural breaks

We develop a Vector Heterogeneous Autoregression model with Continuous Volatility and Jumps (VHARCJ) where residuals follow a flexible dynamic heterogeneous covariance structure. We employ the Bayesian data augmentation approach to match the realised volatility series based on high-frequency data from six stock markets. The structural breaks in the covariance are captured by an exogenous stochastic component that follows a three-state Markov regime-switching process. We find that the stock markets have higher volatility dependence during turmoil periods and that breakdowns in volatility dependence can be attributed to the increase in market volatilities. We also find positive correlations between the Asian stock markets, the European stock market, and the UK stock market. The US stock market has positive correlations with all other markets for most of the sample periods, indicating the leading position of US stock market in the global stock markets. In addition, the proposed three-state VHARCJ model with Dynamic Conditional Correlation (DCC) and break structure under student-t distribution has a superior density forecast performance as compared to the competing models. The forecast models with structural breaks outperform those without structural breaks based on the log predicted likelihood, the log Bayesian factor, and the root mean square loss function.     

Spatial linkage of volatility spillovers and its explanation across G20 stock markets: A network framework

This paper empirically estimates the spatial correlation relationship of volatility spillovers and its influencing factors across G20 stock market. We apply GARCH-BEKK model to estimate volatility spillover and construct dynamic volatility networks. The connectedness analysis shows that the spatial linkage of volatility spillover is time varying and has obvious multiple superposition phenomena. As somewhat innovation results, we use the factor analysis method to obtain centrality comprehensive indicators that can clearly depict the risk contagion intensity and risk acceptance intensity. In general, the developed markets are more influential than the emerging markets during periods of turbulence, and the emerging markets are more sensitive to volatility shocks than developed markets during any period. Finally, this paper introduces quadratic assignment procedure (QAP) method to identify the major factors that influence the spatial linkage of volatility spillovers. Results show that geography influences the volatility spatial correlation differently across economic cycles, and the centrality structure factors have greater impact on the spatial correlation than the external economic factors. The QAP regression analysis shows that these influencing factors can explain about 50% of the spatial correlation variation of international financial markets' volatility spillovers.     

Volatility and correlation of Islamic and conventional indices during crises

We examine the correlation and volatility of Islamic indices and their conventional counterparts during the 2008–2009 Global Financial Crisis as well as the Covid-19 pandemic. We provide evidence that the volatility of Islamic indices is relatively lower than that of conventional peers during turmoil periods. Consistent with the decoupling hypothesis, our results indicate that the volatility of Islamic and the volatility of conventional indices tend to move in tandem in tranquil times but diverge in times of crises. Our results also indicate that the correlation between Islamic and conventional indices is a priced risk factor for Islamic index returns.     

On financial contagion and implied market volatility

This paper investigates volatility contagion across U.S. and European stock markets during the Global Financial Crisis (GFC) and the Eurozone Sovereign Debt Crisis (ESDC). Using a sample of international implied volatility indices on daily changes, I explore asymmetric conditional correlation dynamics across stable and crisis periods and across the different phases of both crises. Empirical evidence indicates the existence of contagion in cross-market volatilities. A different pattern of infection is observed across the phases, since the early phase of the GFC and the late period of escalation of the Euro crisis are the most contagious periods. This implies that the initial signal of the two crises has been differently recognized by implied volatility markets. The results provide important implications for the effectiveness of international portfolio diversification and volatility hedging during periods of negative shocks.     

Dependences and volatility spillovers between the oil and stock markets: New evidence from the copula and VAR-BEKK-GARCH models

This paper examines the dynamic relationship between the oil market and stock markets from two perspectives: dependence between the crude oil market (WTI) and stock markets of the US and China, and volatility spillovers between them during 1991–2016. We further analyze structural breaks of market dependences and consider the extent of their influence on such relationships. Our vine-copula results show that the dependences between the three paired markets, WTI-US, WTI-China and US-China, vary dynamically across the six identified structural break periods. In particular, the dependence between WTI-US is stronger and more volatile than that between WTI-China during most of the periods. The dependence between US-China remains at a lower level in the earlier periods, but increases in the final period. Our VAR-BEKK-GARCH results demonstrate distinctive volatility spillovers across these periods, with varying directionality, in response to the structural changes. Overall, our results indicate that the oil market stimulates rapid and continual fluctuations in market dependences, which become manifest most acutely in the aftermath of the Financial Crisis of 2007–08, demonstrating the increasing interdependence between the oil and stock markets. Further, the growing influence of China on the dynamics of these relationships, in the period following the Great Recession, presents evidence that it begins to assume an increasingly important role in global economic recovery.     

Volatility Reversion and Correlation Structure of Returns in Major International Stock Markets

This paper investigates the stochastic behavior of weekly stock market returns in the U.S., Japan, and the U.K. during the period 1984 to 1994. The analysis is carried out using an augmented version of Bollerslev's [7] multivariate GARCH model with structural dummies to test for differences in the mean, volatility, and covariance structure of returns during the pre- and post-October 1987 crash periods. In addition, the paper explores the issue of the volatility reversion and time-varying behavior of correlation structure of returns in these markets. Mean-spillovers exist from the U.S. and Japan to the U.K. The magnitude of these spillovers is, however, low. Volatility spillovers exist from the U.S. and, to a lesser extent, from Japan to the U.K. Mean returns in all three markets and volatility in Japan and the U.K. are the same during the two periods, while volatility in the U.S. is lower during the post-crash period. With the exception of the correlation of returns between Japan and the U.K., which has doubled since the October 1987 crash, the remaining correlations are statistically similar during the two periods. Simulations performed indicate that volatility is reverting in the sense that, when it departs from its long-run equilibrium level, it tends to revert back to that level.     

Economic evaluation of asymmetric and price range information in gold and general financial markets

Gold is widely perceived as a good diversification or safe haven tool for general financial markets, especially in market turmoil. To fully understand the potential, this study constructs an asymmetric multivariate range-based volatility model to investigate the dependence and volatility structures of gold, stock, and bond markets and further to compare the difference between the financial crisis and post-financial crisis periods. We find a striking explanatory ability to volatility structures provided by the price range information and significant evidence of asymmetric dependence across gold, stock, and bond markets. We implement an asset-allocation strategy incorporating asymmetric dependence and price range information to explore their economic importance. The out-of-sample results show that between 35 and 517 basis points and between 90 and 1111 basis points are earned annually when acknowledging asymmetric dependence and price range information, respectively. These economic benefits are inversely related to the level of investors’ risk aversion and are particularly significant in the period of the global financial crisis.     

Exchange rate volatility across financial crises

This paper studies the impact of global financial turmoil on the exchange rate policies in emerging countries. Spillovers from advanced financial markets to currencies in emerging countries are likely to be exacerbated during crisis periods. To test this hypothesis, we assess the exchange rate policies by currencies’ volatility and investigate their relationship to a global financial stress indicator, measured by the volatility on global markets. We introduce the possibility of nonlinearities by running smooth transition regressions over a sample of 21 emerging countries from January 1994 to September 2009. The results confirm that exchange rate volatility does increase more than proportionally with the global financial stress, for most countries in the sample. We also evidence regional contagion effects spreading from one emerging currency to other currencies in the neighboring area.     

On emerging stock market contagion: The Baltic region

This study provides new evidence on emerging stock market contagion during the Global Financial crisis (GFC) and the Euro zone Sovereign Debt Crisis (ESDC). Focusing on the three emerging Baltic markets and developed European markets, proxied by the EUROSTOXX50 stock index, we explore asymmetric dynamic conditional correlation dynamics across stable and crisis periods. Empirical evidence indicates a diverse contagion pattern for the Baltic region across the two crises. Latvia and Lithuania were contagious during the GFC, while they were insulated from the adverse effects of the ESDC. On the other hand, Estonia decoupled from the negative consequences during the global turmoil period, but recoupled during the ESDC. The results could be attributed to financial and macroeconomic characteristics of the Baltic countries before and after the turmoil periods and the introduction time of the Euro as a national currency.     

Volatility transmission patterns and terrorist attacks

The objective of this study is to analyse volatility transmission between the US and Eurozone stock markets considering the financial market responses to the September 11, March 11 and July 7 terrorist attacks. In order to do this, we use a multivariate GARCH model and take into account the asymmetric volatility phenomenon, the non-synchronous trading problem and the turmoil periods themselves. Moreover, a graphical analysis of the Asymmetric Volatility Impulse-Response Functions (AVIRF) is introduced, which takes into consideration the financial market responses to the terrorist attacks. Results suggest that there is bidirectional and asymmetric volatility transmission and show the different impacts that terrorist attacks had on both markets.     

Volatility spillover in the foreign exchange market: the Indian experience

We find evidence of significant volatility co-movements and/or spillover from different financial markets to the forex market in India. Among a large number of variables examined, volatility spillovers from domestic stock, government securities, overnight index swap, Ted spread and international crude oil markets to the foreign exchange market are found to be significant. There is evidence of asymmetric reactions in the forex market volatility. Comparisons between pre-crisis and post-crisis volatility indicate that the reform measures and changes in financial markets microstructure during the crisis period had significant impact on volatility spillover. During the post-crisis period, the lagged volatility component that represents persistent or fundamental changes had significant spillover effect on forex volatility, rather than the temporary shocks component. There is evidence of a decline in the asymmetric response in the forex volatility during the post-crisis period in India.     

The information in the Mexican term structure of interest rates: capital market implications

This paper employs the term structure approach to examine Mexican security markets during the recent period of political and economic turmoil. We investigate the characteristics of these markets and the forecast applicability of the pure expectations hypothesis to interest rates in Mexico. We find that both forward rates and spot rate spreads are found to have significant forecasting ability for future spot rates for Mexico. Both forecasting approaches suggest greater predictive ability during the period of higher interest rates and general economic volatility (1995–1996) than the more stable economic environment of the early 1990s (1991–1994).     

Pricing volatility of stock returns with volatile and persistent components

This paper introduces a two-component volatility model based on first moments of both components to describe the dynamics of speculative return volatility. The two components capture the volatile and the persistent part of volatility, respectively. The model is applied to 10 Asia-Pacific stock markets. Their in-mean effects on returns are tested. The empirical results show that the persistent component is much more important for the volatility dynamic process than is the volatile component. However, the volatile component is found to be a significant pricing factor of asset returns for most markets. A positive or risk-premium effect exists between the return and the volatile component, yet the persistent component is not significantly priced for the return dynamic process.

Is volatility clustering of asset returns asymmetric?

Volatility clustering is a well-known stylized feature of financial asset returns. This paper investigates asymmetric pattern in volatility clustering by employing a univariate copula approach of Chen and Fan (2006). Using daily realized kernel volatilities constructed from high frequency data from stock and foreign exchange markets, we find evidence that volatility clustering is highly nonlinear and strongly asymmetric in that clusters of high volatility occur more often than clusters of low volatility. To the best of our knowledge, this paper is the first one to address and uncover this phenomenon. In particular, the asymmetry in volatility clustering is found to be more pronounced in the stock markets than in the foreign exchange markets. Further, the volatility clusters are shown to remain persistent for over a month and asymmetric across different time periods. Our findings have important implications for risk management. A simulation study indicates that models which accommodate asymmetric volatility clustering can significantly improve the out-of-sample forecasts of Value-at-Risk.     

Herding and excessive risk in the American stock market: A sectoral analysis

This paper aims to test whether herding behavior is a driving force of excessive market volatility and increasing bubbles in the US stock market at a sectoral level. Trading volume turnover and investors’ sentiment are ubiquitous factors besides market return to fuel herding movement in most sectors. Our sample covers all listed companies in the American stock market over four major turmoil periods. Granger causality test shows that herding is a vital ingredient to increasing bubbles in some sectors, but not all. Moreover, herding and trading volume have an inhibiting effect on both overall and in-sector market volatility in large markets, as opposed to concentrated markets commonly studied in the literature.     

The Dynamic Relation Between Returns and Idiosyncratic Volatility

We claim that regressing excess returns on one-lagged volatility provides only a limited picture of the dynamic effect of idiosyncratic risk, which tends to be persistent over time. By correcting for the serial correlation in idiosyncratic volatility, we find that idiosyncratic volatility has a significant positive effect. This finding seems robusrt for various firm size portfolios, sample periods, and measures of idiosyncratic risk. Our findings suggest stock markets mis-price idiosyncratic risk. There may be some measurement problems with idiosyncratic risk. There may be some measurement problems with idiosyncratic risk that could be related to nondiversifiable risk.     

Is the realized volatility good for option pricing during the recent financial crisis?

The contributions of this paper are threefold. The first contribution is the proposed logarithmic HAR (log-HAR) option-pricing model, which is more convenient compared with other option pricing models associated with realized volatility in terms of simpler estimation procedure. The second contribution is the test of the empirical implications of heterogeneous autoregressive model of the realized volatility (HAR)-type models in the S&P 500 index options market with comparison of the non-linear asymmetric GARCH option-pricing model, which is the best model in pricing options among generalized autoregressive conditional heteroskedastic-type models. The third contribution is the empirical analysis based on options traded from July 3, 2007 to December 31, 2008, a period covering a recent financial crisis. Overall, the HAR-type models successfully predict out-of-sample option prices because they are based on realized volatilities, which are closer to the expected volatility in financial markets. However, mixed results exist between the log-HAR and the heterogeneous auto-regressive gamma models in pricing options because the former is better than the latter in times of turmoil, whereas it is worse during the rather stable periods.     

Emerging Bond Market Volatility and Country Spreads

Using JPMorgan's emerging market bond index, this paper analyzes how increases in country credit spreads can persist in emerging bond markets. The results of T-GARCH regressions show that, during financial crisis periods, emerging countries' credit spreads may increase persistently as a result of interaction between changes in spreads and volatilities, making emerging bond markets more turbulent. The results suggest that emerging countries should endeavor to develop a stabilization mechanism by enhancing information efficiency in bond markets. In particular, because Asian countries have experienced persistent, overreactive volatility, this paper implies that Asian countries should work together more closely during financial crisis periods.