Translating financial integration into correlation risk: A weekly reporting's viewpoint for the volatility behavior of stock markets

We apply the multivariate extension of GARCH-type models in order to assess the systematic and systemic risks as well as the joint volatility behaviors of the U.S. and three European financial markets (Andersen et al., 2010). Therefore, we can appraise the co-movements of the four previous financial markets as well as the joint behavior of their respective volatilities (i.e. systemic risk). Moreover, the resulting conditional variance and covariance metrics allow for handling volatility spillovers (i.e. contagion risk in terms of transmitting volatility shocks from one market place to another market place). Indeed, results highlight the unprecedented high systemic risk levels (i.e. joint increased volatility levels) as well as a high contagion risk (i.e. volatility spillover) during the subprime mortgage market crisis. The transmission process of volatility shocks reveals to be simultaneous across financial markets due to a strong arbitrage activity and electronic trading practices among others. Most importantly, the estimated conditional correlations exhibit an upward sloping trend, which underlines an increase in the correlation risk between financial markets in the late nineties or early 2000. Thus, our major findings are twofold. First, we characterize the dynamic correlation risk across financial markets. Second, we also confirm the increasing and nonlinear trend in the correlation risk, which we are able to quantify.     

FINANCIAL CRISES AND INTERNATIONAL STOCK MARKET VOLATILITY TRANSMISSION

This paper examines the interplay between stock market returns and their volatility, focusing on the Asian and global financial crises of 1997–98 and 2008–09 for Australia, Singapore, the UK, and the US. We use a multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model and weekly data (January 1992–June 2009). Based on the results obtained from the mean return equations, we could not find any significant impact on returns arising from the Asian crisis and more recent global financial crises across these four markets. However, both crises significantly increased the stock return volatilities across all of the four markets. Not surprisingly, it is also found that the US stock market is the most crucial market impacting on the volatilities of smaller economies such as Australia. Our results provide evidence of own and cross ARCH and GARCH effects among all four markets, suggesting the existence of significant volatility and cross volatility spillovers across all four markets. A high degree of time‐varying co‐volatility among these markets indicates that investors will be highly unlikely to benefit from diversifying their financial portfolio by acquiring stocks within these four countries only.     

Co-movements of Shanghai and New York stock prices by time-varying regressions

We use time-varying regression to model the relationship between returns in the Shanghai and New York stock markets, with possible inclusion of lagged returns. The parameters of the regressions reveal that the effect of current stock return of New York on Shanghai steadily increases after the 1997 Asian financial crisis and turns significantly and persistently positive after 2002 when China entered WTO. The effect of current return of Shanghai on New York also becomes significantly positive and increasing after 2002. The upward trend has been interrupted during the recent global financial crisis, but reaches the level of about 0.4–0.5 in 2010 for both markets. Our results show that China’s stock market has become more and more integrated to the world market in the past twenty years with interruptions occurring during the recent global economic downturn.     

Analysing dynamic linkages and hedging strategies between Islamic and conventional sector equity indexes

This study analyses the dynamic spillovers across 10 Dow Jones Islamic and conventional sector index pairs. Using various multivariate GARCH models, the results show significant time-varying conditional correlations for all the pairs. Moreover, there is evidence that the conditional correlations for all the sector pairs, except those of the Telecommunication and Utilities sectors, increase after the onset of the global financial crisis (GFC), suggesting non-subsiding risks, contagion effects and gradual greater financial linkages. The Islamic sectors’ risk exposure can be effectively hedged over time in diversified portfolios containing conventional sector stocks. These results provide several practical implications for portfolio managers and policymakers in regard to optimal asset allocations, portfolio risk management and the diversification benefits among these markets.     

Spillovers from the USA to stock markets in Asia: a quantile regression approach

This article analyses return spillovers from the USA to stock markets in Asia by means of quantile regressions. Traditional studies consider spillovers as effects of the conditional means of foreign returns onto the conditional means of chronologically succeeding domestic markets’ returns. We, by contrast, study the full range of quantiles of the conditional distribution of the domestic markets’ returns. This enables us to document the detailed structure of spillovers across return quantiles. Generally, we find spillovers from the USA to Asia to be negative. Specifically, however, we reveal an asymmetric structure of spillovers with an increasing negative magnitude from lower to upper return quantiles. Theoretically, this pattern is consistent with an asymmetric overreaction of traders in Asia to news from the US market. Extensions from the baseline model further suggest the presence of contagion throughout the financial crisis of 2007–2008 as well as of calm-down effects over weekends.     

Predictability of equity returns during a financial crisis

An occurrence of a market crash or a financial crisis has long been considered a cause of market inefficiency. An inefficient market commonly implies return predictability and the existence of profitable opportunities for traders and speculators. Technical analysis has been a popular tool to identify predictable patterns in asset prices. The usefulness of a large universe of technical trading rules popularized in the existing literature on technical analysis is tested when they are applied to a set of equity markets that are generally considered developed and efficient during the two most recent periods of major financial turmoil: the 1997 Asian financial crisis and the 2008 global financial crisis. Three major statistical deficiencies that existing studies on return predictability are commonly criticized for – data snooping bias, nonsynchronicity bias and transaction costs – have been incorporated in the analysis. Technical trading rules are largely unable to yield abnormal excess returns over the passive benchmark after data snooping bias, nonsynchronous pricing and transaction costs are accounted for. Chaotic price movements typical for a volatile market during a financial crisis are likely to have an adverse effect on the performance of active trend chasing trading strategies.     

Dynamic correlation and equicorrelation analysis of global financial turmoil: evidence from emerging East Asian stock markets

This study investigates the dynamic conditional correlations (DCCs) between eight emerging East Asian stock markets and the US stock market and analyses the dynamic equicorrelation among these nine stock markets. We find a significant increase in the conditional correlations and equicorrelation in the first phase of the global financial crisis. We refer to this finding as contagion from the US stock market to the emerging East Asian markets. We also find an additional significant process of increasing correlations and equicorrelation (herding) in the second phase of the global financial crisis. Further, we employ two new models, namely DCCX-MGARCH (a DCC Multivariate GARCH model with exogenous variables) and DECOX-MGARCH (a dynamic equicorrelation multivariate GARCH model with exogenous variables), to identify the channels of contagion. We find that an increase in the VIX Index increases the conditional correlations and equicorrelation, while increases in TED spreads decrease the conditional correlations of six emerging East Asian countries with the USA. We compare the accuracy of the conditional correlation estimates of the DCC and DCCX models (or DECO and DECOX models) by constructing a loss function. We find that the DCCX (DECOX) model provides more accurate conditional correlation estimates than the DCC (DECO) model by extracting additional information from exogenous variables.     

Asymmetric spillover effects between the Shanghai and Hong Kong stock markets: evidence from quantile lagged regression

This article surveys the asymmetric spillover effects between the mainland China-based Shanghai Composite Index (SCI) and the Hong Kong based Hang Seng Index (HSI) using a quantile lagged regression model. Compared to previous studies, this article, based on data before and after the 2008 global financial crisis, presents a more detailed analysis, as we investigate the spillovers in terms of returns, volatilities and exchange rates between the renminbi (RMB) and the Hong Kong dollar (HKD) throughout the entire conditional return distribution, including the central quantiles, which are closely related to the normal circumstances, and the extreme quantiles, which correspond to the bear and bull markets. First, we find that the return spillovers from its lagged returns or from the other index not only vary across time but also depend on stock state. Second, while return volatility may boost the stock market in a bull market, it accelerates the decline in a bear market. Third, the depreciation of the RMB relative to the HKD does not significantly affect current returns for the HSI, while it negatively affects current returns for the SCI in a bad state after the crisis. The findings presented in this article will facilitate investors’ understanding of the two stock markets.     

Spillover effects of the 2008 financial crisis on NIE stock markets

This article estimates dynamic conditional correlations of stock returns across countries by using DCC–GARCH model and analyse spillover effects of the 2008 financial crisis on the NIE’s stock markets. The results show that there is no regime shift in mean equation of the correlation coefficient during the financial crisis. It may imply there are no mean spillover effects of the US financial crisis on the NIE’s stock markets. However, there are volatility spillover effects of the financial crisis sparked in 2008 from the US to the NIE’s markets.     

Assessing downside and upside risk spillovers across conventional and socially responsible stock markets

Since the aftermath of the recent global financial crisis, socially responsible (SR) investments have become an alternative form of conventional finance, giving rise to further systemic risk between conventional and SR stock markets. In this paper, we assess this risk transmission using Value at Risk (VaR) modeling for the US, Europe and the Asia-Pacific region, over the period covering January 2004–December 2016. We find that socially responsible stock markets exhibit less risk than do conventional markets in terms of the risk hedging properties induced by the SR screening. Second, contributions to systemic risk vary across market phases and return distribution levels, with a larger contribution and spillover effect during the recent global financial crisis. For example, at the downside of the distribution (CoVaR at 5%), the conventional European index shows the highest contribution to the world market’s systemic risk, while the US stock market shows the highest contribution at the upside of the distribution (CoVaR at 95%). This finding is justified by the difference in the risk aversion of investors that varies with the market state as well as the disparities in the development of SR markets.     

Cumulant instrument estimators for hedge fund return models with errors in variables

We revisit the factors incorporated in asset pricing models following the recent developments in financial markets – i.e., the rise of shadow banking and the change in the transmission channel of monetary policy. We propose two versions of the Fung and Hsieh (2004) hedge fund return model, especially an augmented market model which accounts for the new dynamics of financial markets and the procyclicality of hedge fund returns. We run these models with an innovative Hausman procedure, tackling the measurement errors embedded in the models factor loadings. Our empirical method also allows for confronting the drawbacks of the instruments used to estimate hedge fund asset pricing models.     

Bull or bear markets: A wavelet dynamic correlation perspective

In this paper, we contribute to the literature on the international stock market co-movements and contagion, especially during the recent subprime crisis, by researching the interconnections between international stock markets in time-frequency domain.Our innovative approach consists on carrying out a wavelet decomposition of return time series before investigating the correlation dynamics across stock markets during the recent financial crisis. It thus enables us to show how the contagion dynamics between international stock market returns are changing across time scales corresponding to investors with heterogeneous time horizons. Moreover, our results reveal that the contagion dynamics depends on the bull or bear periods of stock markets, on stock markets maturity, and on regional aspects. Therefore, all these finding should be considered from an international portfolio diversification perspective.     

Tail dependence analysis of stock markets using extreme value theory

Financial risk modelling frequently uses the assumption of a normal distribution when considering the return series which is inefficient if the data is not normally distributed or if it exhibits extreme tails. Estimation of tail dependence between financial assets plays a vital role in various aspects of financial risk modelling including portfolio theory and hedging amongst applications. Extreme Value Theory (EVT) provides well established methods for considering univariate and multivariate tail distributions which are useful for forecasting financial risk or modelling the tail dependence of risky assets. The empirical analysis in this article uses nonparametric measures based on bivariate EVT to investigate asymptotic dependence and estimate the degree of tail dependence of the ASX-All Ordinaries daily returns with four other international markets, viz., the S&P-500, Nikkei-225, DAX-30 and Heng-Seng for both extreme right and left tails of the return distribution. It is investigated whether the asymptotic dependence between these markets is related to the heteroscedasticity present in the logarithmic return series using GARCH filters. The empirical evidence shows that the asymptotic extreme tail dependence between stock markets does not necessarily exist and rather can be associated with the heteroscedasticity present in the financial time series of the various stock markets.     

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.     

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.     

On the relationship between energy returns and trading volume: a multifractal analysis

Forecasting and modelling commodities price movements and the activity of energy markets are of real interest to investors and policymakers, especially during turbulent times. This study investigates the volume–returns relationship for two major energy markets (oil and gas) during the recent global financial crisis. Unlike previous studies, we examine this relationship by applying an original fractal approach to intraday data, which has the advantage of accounting for further non-normality, nonstationarity, and fat-tailedness properties. Our study provides two interesting findings. First, we find a significant multifractal relationship between returns and volume in both markets and across all timescales, suggesting nonlinearity in the cross-correlation between returns and volume and rejecting the efficiency assumption. Second, the measure of multifractality in this relationship shows that the magnitude of the fluctuations during bearish and bullish trends affects the volume–return relationship differently, and that the oil market exhibits higher volatility than does the gas market.     

Optimal and investable portfolios: An empirical analysis with scenario optimization algorithms under crisis market prospects

This paper develops scenario optimization algorithms for the assessment of investable financial portfolios under crisis market outlooks. To this end, this research study examines from portfolio managers' standpoint the performance of optimum and investable portfolios subject to applying meaningful financial and operational constraints as a result of a financial turmoil. Specifically, the paper tests a number of alternative scenarios considering both long-only and long and short-sales positions subject to minimizing the Liquidity-Adjusted Value-at-Risk (LVaR) and various financial and operational constraints such as target expected return, portfolio trading volume, close-out periods and portfolio weights. Robust optimization algorithms to set coherent asset allocations for investment management industries in emerging markets and particularly in Gulf Cooperation Council (GCC) financial markets are developed. The results show that the obtained investable portfolios lie off the efficient frontier, but that long-only portfolios appear to lie much closer to the frontier than portfolios including both long and short-sales positions. The proposed optimization algorithms can be useful in developing enterprise-wide portfolio management models in light of the aftermaths of the most-recent financial crisis. The developed methodology and risk optimization algorithms can aid in advancing portfolio management practices in emerging markets and predominantly in the wake of the latest credit crunch.     

Behavioral Factors in Equity Allocation Decisions: A Large-Scale Experimental Study With Context

Traditional models of rational behavior struggle to explain how individuals allocate their money over a variety of financial instruments, including annuities, the stock market, and risk-free bonds. This study uses a large and diverse data set from an investment experiment that is rich in context and captures some important features of actual financial decision making. The focus of the article is to build on the literature documenting behavioral explanations for investment choices by studying the equity allocation decision across different financial tools. The authors find evidence that risk aversion, inertia, and excessive extrapolation are associated with investment behavior even when it is clear that return rates are independent across decision-making periods. Further, subjects have an asymmetric response to positive versus negative returns. In addition to having a novel experimental design, the authors also examine behavior before and after the recent financial crisis. The authors find that the financial crisis indirectly affects the first-stage annuity take-up rate in the experiments vis-à-vis a higher average level of risk aversion after the start of the crisis.     

Spillover Effects of the 2008 Financial Crisis in Latin America Stock Markets

This paper examines the transmission of the 2008 US financial crisis to four Latin American stock markets using daily stock returns from 2006 to 2010, analyzing before, during and after the 2008 financial crisis. The empirical evidence presents a financial contagion by showing persistently higher and more volatile pair-wise conditional correlations during the crisis period. This indicates there are structural changes in mean and volatility of the correlation coefficients due to the 2008 financial crisis in Latin American markets. The results here could be useful in international portfolio diversification decision-making in Latin American region. In addition, the predicting the volatility in different markets could be a useful input for reducing financial instability in crisis episodes to policy makers.     

Student-t distribution based VAR-MGARCH: an application of the DCC model on international portfolio risk management

Significant second-moment transmission effects and obvious time-varying patterns of correlation coefficients among major equity and currency markets in the US, Japan and the UK are found to exist. Such observations inspire the time-varying setting of dynamic conditional correlation coefficients in MGARCH models. On the other hand, the multivariate Student-t distribution is suitable for analysing the visible leptokurtosis that is common in financial markets. Both are important for international portfolio risk management. Thus, a comparison on the hedging efficiency of hypothetical portfolios consisting of stock and currency future positions is conducted in order to justify the multivariate Student-t distribution based on the DCC-MGARCH model.