Emerging market sovereign spreads,global financial conditions and U.S. macroeconomic news

We investigate the impact of global financial conditions, U.S. macroeconomic news and domestic fundamentals on the evolution of EMBI spreads for a panel of 18 emerging market (EM) countries using daily data. To this end, we consider not only the conventional panel cointegration procedures but also the recent common correlated effects method to tackle cross-section dependence that may stem from common global shocks such as contagion. The results suggest that the long-run evolution of EMBI spreads depends on global financial conditions, crises contagion and domestic fundamentals proxied by sovereign ratings. The results from panel equilibrium correction models suggest that EMBI spreads respond substantially also to U.S. macroeconomic news and changes in the Federal Reserve's target interest rates. The magnitude and the sign of the effect of the U.S. news, however, crucially depend on the state of the U.S. economy, such as the presence of inflation dominance.     

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.     

Impacts of China's crash on Asia-Pacific financial integration: Volatility interdependence,information transmission and market co-movement

This paper examines the price and volatility dynamics between China and major stock markets in the Asia-Pacific, investigating the effects of the Chinese stock market crash (2015–2016) for the first time. Employing the Bayesian VAR and BEKK GARCH, we observe that price and volatility spillover behaviours are different during the stable and stress periods. Particularly, price spillovers from China to other regional markets are more significant during a bullish period, showing that ‘good news’ emanating from China has strong impacts on its neighbours during better market condition. In the turbulent period, we observe strong shock spillover effects and enhanced volatility spillovers from China to most Asia-Pacific stock markets. This is because China, as an important trading partner and strategic financial centre shows to exert significant influence on the Asia-Pacific region through various economic channels. We also find that the Asia-Pacific stock markets spill over their shocks to China during the crisis, indicating that China is becoming more integrated with the regional financial markets.     

China's liberalizing stock market,crude oil,and safe-haven assets: A linkage study based on a novel multivariate wavelet-vine copula approach

China is the world's largest oil importer, and therefore the correlations between stock indices and highly volatile oil prices deserve close examination when investing in China's gradually liberalizing stock market. Another concern for international investors is whether safe-haven assets can reduce portfolio risks for investment in China. The paper makes two main contributions. First, we develop a novel method of examining a multivariate dependence structure by combining wavelet analysis with the vine copula model. Second, we apply the proposed methodology to study the correlations between China's liberalizing stock market, petroleum, and safe-haven assets at different frequencies. We find that the multidimensional dependence of these assets has been altered as a result of the 2008 global financial crisis. Moreover, the vine structures exhibit dependence patterns that vary over time horizons, indicating that the multidimensional dependence is sensitive to time scales.