Liquidity in Asian markets: Intensity of Regional and global linkages

This study investigates cross-market linkages and the intensity of liquidity spillovers across nine Asian markets and five developed markets during 2006 to 2016. Further, the study examines the contagion caused by recent global financial crisis and its impact on the market liquidity. The direction and intensity of spillovers has been measured using forecast error variance decomposition method as suggested by Diebold and Yilmaz (2012). Among the developed markets, the United States, Germany and the United Kingdom significantly affect liquidity changes in Asian countries like India, China, Singapore and Japan. The results revels that on average, each Asian market receives 7% spillover from the global markets and 16% from regional markets. During the financial crisis, the average regional spillover increased to 20% and the global spillover increased to 11%. Thus, in Asia, the regional spillover is higher than the global spillover. Our results support the demand side hypothesis and suggest that it is the trade and portfolio investments that drive the liquidity spillovers. Our findings have potential implications for international investors, policy makers and market regulators.     

Return and volatility spillovers between china and world oil markets

We examine return and volatility spillovers between China and world oil markets. This topic is of great importance because China is the world's second-largest oil importer and has exhibited substantial growth in oil consumption. Extending Diebold and Yilmaz's (2012) method of catching spillover dynamics, it is found that return and volatility spillovers between China and world oil markets are bi-directional and asymmetric. The Chinese oil market is highly affected by world oil markets and exerts an influence on world oil markets, although to a lesser extent. Moreover, the volatility spillover index has increased significantly since the peak of the last financial crisis in September 2008. Although the US oil market impacts China's market most in terms of spillover, the influence of China's oil market on the world oil market has intensified in recent years.     

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.     

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.     

Mena Stock Markets Integration: Pre and Post Global Financial Crisis

This paper examines the short‐ and long‐run linkages in pre and post global financial crisis among Middle East and North Africa (MENA) stock markets, between MENA and Chinese stock markets and also between MENA and developed (United States and United Kingdom) stock markets. Results indicate that both long‐run co‐integration relationships and short‐run causal linkages among MENA stock markets increased in post‐crisis than that in pre‐crisis sub‐period. The degree of integration between MENA and Chinese stock markets increased in post‐crisis than pre‐crisis. We also find that the degree of integration between MENA and developed (United States and United Kingdom) stock markets increased in post‐crisis than that in pre‐crisis. The presence of increased linkages among MENA markets, and between MENA and Chinese stock markets and also between MENA and developed (United States and United Kingdom) markets has important implications for portfolio investors and policy makers.     

Asymmetric causality between Australian inbound and outbound tourism flows

We employ the asymmetric version of the Granger causality test to assess how Australian inbound and outbound tourism flows across 49 markets (countries) are driven by the sign-dependent variations in departure series or vice versa. A multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) model is also estimated to study the time-varying co-volatility between inbound and outbound tourism growth rates. We find that rising co-volatility spillovers between inbound and outbound tourism are statistically significant for a number of markets. The six markets that are most susceptible to global shocks are China, Hong Kong, Papua New Guinea, Singapore, South Africa and the United Kingdom. China is by far the largest of these markets and, except for the United Kingdom, both arrivals and departures for each of these countries represent growing markets for Australia. We present recommendations for policymakers and destination management organizations (DMOs) to assist in developing customized strategies targeting resilient inbound markets in order to optimize tourism performance and reduce potential losses in times of crisis.     

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.     

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.     

Where does return and volatility come from? The case of Asian ETFs

We analyze return and volatility of Asian iShares traded in the U.S. The difference in trading schedules between the U.S. and Asia offers a unique market setting that allows us to distinguish various return and volatility sources. We find Asian ETFs have higher overnight volatility than daytime volatility, explained by public information released during each local market's trading session. Local Asian markets also play an important role in determining each Asian ETF return. Nonetheless, returns for these funds are highly correlated with U.S. markets, indicative of the effects of investor sentiment and location of trade. Finally, returns in the U.S. market Granger-cause returns in all six Asian markets are analyzed.     

Has the Asian crisis changed the role of foreign investors in emerging equity markets: Taiwan's experience

This paper examines whether the 1997 Asian crisis changed the trading behaviors of foreign investors and of local institutional investors in Taiwan's stock market. There is little evidence that the Asian crisis changed the relationship between equity flows and market returns in Taiwan's stock market but there is evidence that volatility effects and volatility spillover were strengthened after the crisis. The general findings are (i) feedback trading arguments are much stronger than information arguments; (ii) relationships between returns and sale changes are the weakest but volatility effects using sale measures are the strongest; (iii) strong volatility effects and volatility spillover are found after the crisis; and (iv) the results for domestic institutional investors are slightly stronger than those for foreign investors.     

Information Linkages between Chinese and World Copper Futures Markets

In this paper, we examine the price discovery process and volatility spillover effects in informationally linked futures markets. Using synchronous trading information from the Shanghai Futures Exchange (SHFE), the New York Mercantile Exchange (NYMEX), and the London Metal Exchange (LME) for copper futures from 2000 to 2012, we show that the cointegration relationships of these futures markets changed during 2006–2008. The results indicate that there is a bidirectional relationship in terms of price and volatility spillovers between the LME and NYMEX and the SHFE, with a stronger effect from the LME and NYMEX to the SHFE (versus the effect from the SHFE to the LME and NYMEX) prior to 2006. Our results also highlight the increasingly prominent role of the SHFE in the price formation process and cross-volatility spillover effects since 2008. Finally, we show that volatility spillover has important implications for constructing optimized portfolios for copper investors.     

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.     

Return spillovers around the globe: A network approach

We study the connectedness of a sample of 40 stock markets across five continents using daily closing prices and return spillovers based on Granger causality. All possible 1560 return spillovers between 40 markets create a complex network of relationships between equity markets around the world. Apart from analyzing the topological and time-varying properties of the created networks, we also identify the determinants of the connectedness of equity markets over time. Adjusting for non-synchronous trading, our modelling approach leads to evidence that the probability of return spillover from a given stock market to other markets increases with market volatility and market size and decreases with higher foreign exchange volatility. We empirically show that the temporal proximity between closing hours is important for information propagation; therefore, choosing markets that trade during similar hours bears an additional risk to investors because the probability of return spillovers increases.     

THE DYNAMIC RELATION BETWEEN RETURNS,TRADING VOLUME,AND VOLATILITY: LESSONS FROM SPILLOVERS BETWEEN ASIA AND THE UNITED STATES

This paper investigates the dynamic relationship between index returns, return volatility, and trading volume for eight Asian markets and the US. We find cross‐border spillovers in returns to be non‐existent, spillovers in absolute returns between Asia and the US to be strong in both directions, and spillovers in volatility to run from Asia to the US. Trading volume, especially on the Asian markets, depends on shocks in domestic and foreign returns as well as on volatility, especially those shocks originating in the US. However, only weak evidence is found for trading volume influencing other variables. In the light of the theoretical models, these results suggest sequential information arrivals, with investors being overconfident and applying positive feedback strategy. Furthermore, new information causes price volatility to rise due to differences in its interpretation among traders, but the subsequent market reaction takes the form of adjustment in price level, not volatility. Lastly, the intensity of cross‐border spillovers seems to have increased following the 1997 crisis, which we interpret as evidence of increased noisiness in prices and diversity in opinions about news originating abroad. Our findings might also help to understand the nature of financial crises, to predict their further developments and consequences.     

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.     

The linkages,persistence, asymmetry in the volatility,the price discovery and efficiency,and the effect of the US subprime mortgage financial crisis on the spot and the futures market’s returns: the case of India

This article examines the effects of persistence, asymmetry and the US subprime mortgage crisis on the volatility of the returns and also the price discovery, efficiency and the linkages and causality between the spot and futures volatility by using various classes of the ARCH and GARCH models, and through the Granger’s causality. We have used two indices: one for spot and the other for futures, for the daily data from 12 June 2000 to 30 September 2013 from Nifty stock indices. We have then tested for ARCH effects, and subsequently employed various models of the ARCH and GARCH conditional volatility. The GARCH(1,1) model is found to be significant, and it implies that the returns are not autocorrelated and have ‘short memory’. It supports the hypothesis of the efficiency of the markets. The negative ‘news’ has more significant effect on volatility, corroborating the ‘leverage impact’ in finance on market volatility. We have also tested the volatility spillover effects. The two methods we employed support the spillover effects and the causality is bidirectional. We also have used the dummy variable for the US subprime mortgage financial crisis and found that they are statistically significant. Indian stock market is thus integrated to the world stock markets.     

ASIAN FINANCIAL LINKAGE: MACRO‐FINANCE DISSONANCE

How are Asian financial markets interlinked and how are they linked to markets in developed countries? What is the main driver of fluctuations in Asian financial markets as well as real economic activity? To answer these questions, we estimate the spillover index proposed by Diebold and Yilmaz and gauge the degree of interaction in both financial markets and real economic activity among Asian economies. We first show that the degree of the international spillover in stock markets is uniform, irrespective of the groups of countries concerned, such as the G3 and ASEAN4. This suggests the importance of global common shocks in stock markets. We then discuss the macro‐finance dissonance. In stock and bond markets, the United States has been the main driver of fluctuations. However, China has emerged as an important source of fluctuations in real economic activity.     

Volatility transmission between Islamic and conventional equity markets: evidence from causality-in-variance test

This study examines whether a volatility/risk transmission exists between the Dow Jones Islamic stock and three conventional stock markets for the United States, Europe and Asia during the pre- and the in- and post-2008 crisis periods. It also explores the volatility spillover dynamics between those markets and US Monetary policy, oil prices, global financial risk and uncertainty factors. The recently developed Hafner and Herwartz (2006)’s causality-in-variance test provides evidence of risk transfers between these seemingly different equity markets, indicating a contagion between them during the full sample and the subperiods. The volatility structure of these markets is dominated by short-run volatility in the first period and by high long-run volatility in the second period. The volatility impulse response analysis indicates a similar volatility transmission pattern although it is characterized by a more volatile and short-lived structure in the second period. It also appears that the Islamic equity market responds to shocks from the risk factors and not from the oil price and the US economic policy uncertainty index during both periods.     

人民币即期汇率与NDF汇率关系的实证分析

以人民币即期汇率与NDF汇率为例研究境内市场与境外市场的信息传递。主要利用GARCH模型描述人民币即期汇率与NDF的变动并检验人民币即期汇率与NDF之间的均值溢出效应和波动溢出效应。得到的主要结论为,人民币NDF市场对人民币即期汇率市场有均值溢出效应,人民币即期汇率和NDF之间有双向波动溢出效应。这表明信息流由境外市场传导至境内市场,人民币即期汇率市场受到境外市场因素的影响,境外人民币NDF市场是境内即期市场的先导。     

Volatility spillover and multivariate volatility impulse response analysis of GFC news events

This article applies two measures to assess spillovers across markets: the Diebold and Yilmaz’s (2012) spillover index and the Hafner and Herwartz’s (2006) analysis of multivariate GARCH models using volatility impulse response analysis. We use two sets of data, daily realized volatility (RV) estimates taken from the Oxford-Man RV library, for the S&P500 and the FTSE, plus 10 years of daily returns series for the New York Stock Exchange Index and the FTSE 100 index. Both data sets capture both the global Financial Crisis (GFC) and the subsequent European Sovereign Debt Crisis (ESDC). The spillover index captures the transmission of volatility to and from markets, plus net spillovers. The Volatility Impulse Responses (VIRF) have to be calibrated to conditional volatility estimated at a particular point in time. We explore the impact of three different shocks, the onset of the GFC, the height of the GFC, and the impact of the ESDC. Our modelling includes leverage and asymmetric effects applying a multivariate GARCH model, and further analysis using both BEKK and diagonal BEKK (DBEKK) models. We find the impact of negative shocks is larger, but shorter in duration, in this case a difference between 3 and 6 months.