Trade and Investment Linkages and Stock Market Long‐Run Relationship

This paper aims to examine whether the intensity of trade and investment linkages among the countries matter for their stock market long‐run relationship. To achieve this, we classify Australia's bilateral trade and investment partners into major, medium and minor. Empirical findings of an asymmetric generalised dynamic conditional correlation generalised autoregressive conditional heteroskedasticity model show that correlations are time varying and increased significantly during the global financial crisis (GFC). Results of multivariate cointegration test confirm the long‐run equilibrium relationship between the stock markets of Australia and its major partners in the pre‐GFC and during GFC. Based on the full‐sample results, it indicates that the GFC has segmented the stock markets from the long‐run equilibrium relationship. Granger non‐causality test results on full sample show that Australian stock market causes only the New Zealand market while the USA, the UK, Germany, Canada, Switzerland and Italy drives the Australian market. Our results therefore suggest that the intensity of bilateral trade and investment linkages among the countries matter for their stock markets' long‐term relationship.     

Economic integration and stock market dynamic linkages: evidence in the context of Australia and Asia

Countries are becoming economically integrated and it is contended that this will also lead to their financial markets becoming integrated. This contention is important since international financial market integration diminishes portfolio diversification benefits and creates contagion risk. We test this contention in this article in the context of the Australasian region. Australia and Asia have experienced very significant economic integration through a rapid growth in their bilateral trade. We utilize a battery of econometric techniques – cointegration, asymmetric generalized dynamic conditional correlations and panel regression models. As expected, we find that trade intensity significantly drives the interdependence between their stock markets in both the short run and the long run. Thus, given the ever increasing economic integration in this region, this finding implies that their stock markets face the risk of contagion, and that investors in these markets would also be confronted with the prospect of lower diversification benefits.     

Stock market integration between new EU member states and the Euro-zone

This paper measures the degree in stock market integration between five Eastern European countries and the Euro-zone. A potentially gradual transition in correlations is accommodated by smooth transition conditional correlation models. We find that the Czech, Slovenian and Polish markets have increased their correlation to the Euro-zone from 1997 to 2008. However, this is not a broad-based phenomenon across Eastern Europe. The results also show that the increase in correlations is not a reflection of a world-wide phenomenon of financial integration but is mainly driven by EU-related developments.     

Could the global financial crisis improve the performance of the G7 stocks markets?

Financial crises are normally associated with negative effects on financial markets. In this article, we investigate whether the most recent global financial crisis (GFC) had any positive impact on the G7 (Canada, France, Germany, Italy, Japan, the United Kingdom and the United States) indices. To conduct the analysis we employ the mean–variance (MV) analysis, CAPM statistics, Hurst exponent, runs test, multiple variation ratio test and stochastic dominance (SD) tests. Our MV and CAPM results conclude that most of the G7 stock indices are significantly less volatile. The results from Hurst exponent, run tests and multiple variation ratio confirm that efficiency improved in the post-GFC period. Finally, our SD results conclude that there is no arbitrage opportunity and the markets are efficient due to the GFC, and, in general, investors prefer investing in the indices after the GFC. Overall, we conclude that the GFC led to markets that are more efficient and mature, confirming that crises can also have positive impacts on stock markets. These findings provide important information for investors and market regulators.     

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.     

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.     

How does economic policy uncertainty drive gold–stock correlations? Evidence from the UK

In this article, we investigate the effects of economic policy uncertainty (EPU) on correlations between the UK stock market and gold market. We find that less certain economic policies result in lower correlations, while more certain economic policies result in higher correlations. The correlations are symmetric and show no structural breaks caused by the recent financial crisis. The recent financial crisis has not changed EPU effects on the correlations. The effects of one positive one-standard-deviation shock of the logarithmic change rate of the EPU on the correlations last approximately 19 months.     

Regional spillovers across transitioning emerging and frontier equity markets: A multi-time scale wavelet analysis

The episodic wave of crises experienced across the global financial markets over the past two decades has raised questions surrounding the vulnerability of transitioning emerging and frontier equity markets to exogenous shocks. These markets, by design, have lacked the institutional or financial architecture supporting their capital base compared to more established markets. We make the initial attempt to examine four such stock markets (Saudi Arabia, UAE, South Africa and Israel). We perform multi-timescale analysis using wavelet-based time and frequency decompositions in order to investigate (i) whether the shocks transmitted were pure contagion or fundamental-based and (ii) also whether the dynamic evolution of stock market integration was mainly short-term or long-term. We find that prior to the 2008/09 US subprime crisis, the shocks generated pure contagion in contrast to the subprime crisis that reveals evidence supportive of fundamental-based contagion. Further, when exploring the dynamics of market integration, we find that integration strengthens over time as opposed to any immediate short-term outcome. This supports policies engendered to promote stock market resiliency and stability.     

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.     

Can cryptocurrencies be a safe haven: a tail risk perspective analysis

Cryptocurrencies are one of the most promising financial innovations of the last decade. Different from major stock indices and the commodities of gold and crude oil, the cryptocurrencies exhibit some characteristics of immature market assets, such as auto-correlated and non-stationary return series, higher volatility, and higher tail risks measured by conditional Value at Risk (VaR) and conditional expected shortfall (ES). Using an extreme-value-theory-based method, we evaluate the extreme characteristics of seven representative cryptocurrencies during 08 August 2015–01 August 2017. We find that during the sub-period of 01 August 2016–01 August 2017, there are finite loss boundaries for most of the selected cryptocurrencies, which are similar to the commodities, and different from the stock indices. Meanwhile, we find that left tail correlations are much stronger than right tail correlations among the cryptocurrencies, and tail correlations increased after August 2016, suggesting high and growing systematic extreme risks. We also find that cryptocurrencies to be both left tail independent, and cross tail independent with four selected stock indices, which implies part of the safe-haven function of the cryptocurrencies, indicating their ability to be a great diversifier for the stock market as gold, but not enough to be a tail hedging tool like gold.     

The Impact of the GFC on Sectoral Market Efficiency: Non‐linear Testing for the Case of Australia

This paper investigates the efficiency of the Australian stock market during the period of volatility and disruption associated with the Global Financial Crises (GFC). Furthermore, the investigation seeks to observe any divergence in market efficiency between industry sectors that demonstrate differing economic performance across the period. Spanning a time period of 2000–2015, the data are split into three periods of distinct economic conditions: a pre‐crisis period of relatively high growth, the GFC period of disruption and contraction, and a post‐GFC period of relatively low growth. Five sector indices listed on the Australian Securities Exchange are analysed to search for evidence of market efficiency (Real Estate, Consumer Discretionary, Financials, Materials, and Metals and Mining). A range of non‐linear tests are applied in order to systematically investigate the structure of the market in each sector. The results highlight the cointegrated nature of non‐linearity across related sectors, and also demonstrate that different industries within the same economy can reveal highly diverse patterns of non‐linearity and market efficiency in response to financial crisis.     

News and correlations of CEEC-3 financial markets

We employ DCC-MGARCH models to investigate conditional correlations between six CEEC-3 financial markets. In general, the highest correlations exist between Hungary and Poland in foreign exchange and stock markets. Short-term money markets are somewhat isolated from each other. We find that the associations of CEEC-3 exchange rates versus euro are weaker than those versus the US dollar. The persistence of the effect of shocks on the time-varying correlations is strongest for foreign exchange and stock markets, indicating a tendency toward contagion. In searching for the origins of financial market volatility in the CEEC-3, we uncover some evidence of Granger-causality on the foreign exchange markets. Finally, using a pool model, we investigate the impact of euro area, US, and CEEC-3 news on the correlations. Apart from ECB monetary policy news, we observe no broad effects of international news on correlations; instead, local news exerts an influence, which suggests a dominance of country- or market-specific circumstances.     

Virtual integration of financial markets: a dynamic correlation analysis of the creation of the Latin American Integrated Market

This article investigates the role of virtual integration of financial markets on stock market return co-movements. In May of 2011, the Chilean, Colombian and Peruvian stock markets virtually integrated their stock exchanges and central securities depositories to form the Latin American Integrated Market (MILA). We utilize the dynamic conditional correlation model proposed by Engle (2002) to identify a statistically significant positive correlation between these markets. Moreover, we find strong evidence that the creation of the MILA increased the levels of dynamic correlation between stock returns. A higher correlation was also found during the dot-com bubble and the 2007 financial crises. Our results imply a decline in gains from international diversification by holding portfolios consisting of diverse stocks of these countries.     

Determinants of stock market comovements among US and emerging economies during the US financial crisis

By analyzing the dynamic conditional correlations (DCC) of the daily stock returns of 10 emerging economies in comparison with those of the US for the period of 2006–2010, we find different patterns of crisis spillover among 10 emerging economies. While a group of countries has three distinctive phases of crisis spillover (contagion, herding, and post-crisis adjustment), other groups show different phases of crisis spillover. It is also shown that increases in CDS spread and TED spread decrease conditional correlations while increases in foreign institutional investment, exchange market volatility, and the VIX index of the S&P 500 increase conditional correlations.     

我国证券市场流动性溢出效应的实证研究

2008年金融危机中的一个重要金融现象是流动性溢出效应.本文以我国沪深两市交易的国债和股票为样本,利用VAR技术分析了股票市场与债券市场之间的流动性溢出效应问题.由于我国股票市场的规模远大于交易所交易债券,我们发现存在显著的股市流向债市的流动性溢出效应,而债市流向股市的流动性溢出效应统计上却不显著.同时我们发现各个市场自身的收益率和波动率对其流动性也有着显著的影响.最后我们还发现两市自身的流动性存在着很强的自相关性.证据表明当我国资本市场出现流动性不足时,尤其要加强对股票市场流动性风险的防范和监管.同时也反映出我国要大力发展债券市场的必要,使股市和债市的流动性相互影响相得益彰.     

Dynamic Correlation Analysis of Asian Stock Markets

This paper examines the stock market linkages within the Asia-Pacific region and between Asian markets and the U.S. market over the period of January 2000 to June 2010, employing the dynamic conditional correlation GARCH model. Our results show that there exist very high correlations among the stock markets during the 2008 financial crisis. Therefore, consistent with the finding in literature, there are no diversification benefits during the financial crisis. However, our results show that there are still substantial opportunities for global investors to improve the risk-return performance between China and other markets during the sample period. In addition, we find evidence that the U.S. market significantly affects the stock markets in the Asia-Pacific region. Using T-GARCH model, there is a strong evidence of an asymmetric effect on conditional variance except stock markets in China and Malaysia.     

Modelling the dependence structures of Australian iTraxx CDS index

In contrast to market expectations, the correlation between credit default swap (CDS) spreads and their respective stock prices in Australia was found to be positive. The global financial crisis (GFC) affected the nonlinear association between the two asset classes with firms experiencing financial distress and stock prices plummeting. CDSs issuers reacted to such exogenous shocks by increasing their risk premiums on their spreads, reflecting the increased inherent risk. By splitting the data into pre- and post-GFC contexts and by employing the use of Archimedean copulas, we observe a negative co-movement in the post-GFC period. This finding is robust to several equity indices. Overall, such result is critical for investors engaging in arbitrageur activities.     

Daily market news sentiment and stock prices

In recent years there has been a tremendous growth in readily available news related to traded assets in international financial markets. This financial news is now available through real-time online sources such as Internet news and social media sources. The increase in the availability of financial news and investor’s ease of access to it has a potentially significant impact on market stock price movement as these news items are swiftly transformed into investors sentiment which in turn drives prices. In this study, we use the Thomson Reuters News Analytics (TRNA) data set to construct a series of daily sentiment scores for Dow Jones Industrial Average (DJIA) stock index constituents. We use these daily DJIA market sentiment scores to study the influence of financial news sentiment scores on the stock returns of these constituents using a multi-factor model. We augment the Fama–French three-factor model with the day’s sentiment score along with lagged scores to evaluate the additional effects of financial news sentiment on stock prices in the context of this model using Ordinary Least Square (OLS) and Quantile Regression (QR) to analyse the effect around the tail of the return distribution. We also conduct the analysis using the seven-day simple moving average (SMA) of the scores to account for news released on non-trading days. Our results suggest that even when market factors are taken into account, sentiment scores have a significant effect on Dow Jones constituent returns and that lagged daily sentiment scores are often significant, suggesting that information compounded in these scores is not immediately reflected in security prices and related return series. The results also indicate that the SMA measure does not have a significant effect on the returns. The analysis using Quantile Regression provides evidence that the news has more impact on left tail compared to the right tail of the returns.     

Trading with Tigers: A Technical Analysis of Southeast Asian Stock Index Futures

ABSTRACT

Our paper examines the profitability of technical trading rules in Southeast Asian (SEA) ‘tiger cub’ stock index futures markets during and after the global financial crisis (GFC) of 2007/2008. Using daily closing price data from 2007 to 2012, we explore technical trading rules such as exponential moving averages (EMA (20), EMA (100), EMA (20,100)) and moving average convergence divergence (MACD) in Indonesia, Malaysia, the Philippines and Thailand. The findings reveal that after applying trading rules that account for transaction costs and risk, abnormal profits cannot be achieved above a naı¨ve ‘buy-and-hold’ strategy (with the exception of EMA (100) and EMA (20,100) in Indonesia, and EMA (20,100) in both the Philippines and Thailand). There appears to be some degree of success with the application of longer-term trading rules; however, unless transaction costs can be reduced, investors are best advised to pursue passive investment approaches. Despite the economic uncertainty associated with the GFC and ongoing market volatility, it appears that SEA tiger cub stock index futures markets are weak-form efficient.     

Integration of world leaders and emerging powers into the Malaysian stock market: A DCC-MGARCH approach

This paper examines the financial integration of two world leaders (the U.S. and Japan) and two emerging powers (China and India) into the Malaysian stock market. A DCC-MGARCH approach is employed to examine the correlations among these countries in a time-variant manner to indicate the degree of financial integration among the countries. It is found that the financial integration between Malaysia and China started to evolve in April 2004. Strong financial integration between the stock markets in India and Malaysia was observed. In contrast, the volatility spillover effect from the U.S. to Malaysia disappeared, especially in the short term. Nevertheless, the study suggests that in the long run, investors in Malaysia could gain by diversifying their portfolios in China and Japan relative to India and the U.S.