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The purpose of this paper is to explore the dynamic interdependence structure and risk spillover effect between the Chinese stock market and the US stock market.

This paper mainly uses the multivariate R-vine copula-complex network analysis and the multivariate R-vine copula-CoVaR model and selects stock price indices and their subsector indices as samples.

The empirical results indicate that the Energy, Materials and Financials sectors have leading roles in the interdependent structure of the Chinese and US stock markets, while the Utilities and Real Estate sectors have the least important positions. The comprehensive influence of the Chinese stock market is similar to that of the US stock market but with smaller differences in the influence of different sectors of the US stock market on the overall interdependent structure system. Over time, the interdependent structure of both stock markets changed; the sector status gradually equalized; the contribution of the same sector in different countries to the interdependent structure converged; and the degree of interaction between the two stock markets was positively correlated with the degree of market volatility.

This paper employs the methods of nonlinear cointegration and the R-vine copula function to explore the interactive relationship and risk spillover effect between the Chinese stock market and the US stock market. This paper proposes the R-vine copula-complex network analysis method to creatively construct the interdependent network structure of the two stock markets. This paper combines the generalized CoVaR method with the R-vine copula function, introduces the stock market decline and rise risk and further discusses the risk spillover effect between the two stock markets.

This study aims to link the financial cooperation in the Nordic region and the interdependence between the stock markets in this area. The main emphasis is placed on the evolution of this interdependence as the financial integration was proceeding.

Johansen’s cointegration technique and the exponential generalized autoregressive conditionally heteroskedastic model are applied to test the long-run and short-run interdependences, respectively, among Nordic stock markets. In particular, the recursive estimation approach is used to reveal the evolution of the interdependence between those markets.

The existence of two cointegrations over the sample period indicates that the markets depend on each other to some extent. The recursive estimation of Johansen’s model further reveals that the interdependence had been greatly improving until late 2008. The interdependence between those markets is also confirmed convincingly by the short-term dynamics, noting that the spillover effects between most pairs of stock volatilities are witnessed in the empirical results.

The findings show the dynamics of the long-run correlations between the Nordic stock markets, which imply the intrinsic response to the process of financial market reforms, the 2008 global financial crisis and the period after the crisis. The evidenced information about determinants of the interdependence between Nordic stock markets is sending strong signals to investors to enhance their investment strategies.

Most of the existing studies have been restricted to the static long-run and/or short-run interdependence among those markets. However, this study contributes to the literature by investigating the dynamics of interdependence among the Nordic stock markets over time; moreover, the evolution of the market interdependence is sketched closely to the process of the regional financial market reforms.

With growing interdependence between financial markets, the goal of this paper is to examine the dynamic interdependence between corporate equity and public real estate markets for the USA and a select group of seven European developed economies under a cross-country framework in crisis and boom market conditions. Dynamic interdependence is related to four measures of market linkages of “correlation, spillover, connectedness and causality”.

This study adopts a four-step investigation. The authors first estimate “time-varying variance–covariance spillovers and implied correlations” modeled with the bivariate BEKK-MGARCH methods. Second, the methods of Diebold and Yilmaz (2012, 2014) measure the conditional volatility spillover-connectedness effects across the corporate equity and public real estate markets based on a decomposition of the forecast error variance. Third, the authors implement nonlinear bivariate and multivariate causality tests to understand the lead-lag dynamics of the two asset markets' returns, volatilities and net directional volatility connectedness across different sample periods. Finally, the authors conclude the study by providing a portfolio hedging analysis.

The authors find that corporate equity and public real estate are moderately interdependent to the extent that their diversification benefits increases in the longer term. Moreover, the authors find increased corporate equity-public real estate causal dependence of the market groups of the European and international portfolios during the GFC and INTERCRISIS periods. The nonlinear causality test findings indicate that the joint information of asset markets can be a useful source of prediction for future innovation of market risks. Additionally, policy makers may also be able to employ conditional volatility and volatility connectedness as two other measures to manage market stability in the cross-asset market dependence during highly volatile periods.

One major take away from this academic research is since international portfolio investors are not only concerned the long-term price relationship but also the correlation structure and volatility spillover-connectedness, the conditional BEKK modeling, generalized risk connectedness analysis and nonlinear causal dependence explorations from this multi-country study can shed fresh light on the nature of market interdependence and magnitude of volatility connectedness effects in a multi-portfolio framework.

The hedging performance analysis for portfolio diversification and risk management indicates that industrial stocks (“pure” equities) are valuable assets that can improve the hedging performance of a well-diversified corporate equity-public real estate portfolio during crisis periods. For policymakers, the findings provide important information about the nature of causal links and predictability during the crisis and asset-market boom periods. They can then equip with this information to manage and coordinate market stability in cross corporate equity-real estate relationships effectively.

Although traditional research has in general reported at least a moderate degree of relationship between the two asset markets, investors' knowledge of stock-public real estate market linkage is somewhat inadequate and confine mostly to broad stocks (i.e. stocks that are exposed to public real estate influence) in a single-country context. In this paper, the authors examine the interdependence dynamics in a multi-country (multi-portfolio) context. A clear understanding their changing market relationships in a multi-country context is of crucial importance for portfolio investors, financial institutions and policy makers. Moreover, since the authors use an orthogonal stock market index, the authors allow global investors to understand the potential diversification benefits from stock markets that are beyond the public real estate market under different market conditions.

This study examines the relationship between Australia's stock market and the five largest international markets for the period 1991 through 2001. Preliminary findings, using correlation statistics, indicated potential benefits to international diversification for the Australian investor. Further analysis, conducted in the VAR framework using the Johansen cointegration method, found that the Australian market has short and long run linkages with the United States, while tests with other markets found little evidence of interdependence. Moreover, only the US market was found to Granger‐cause the Australian market.

The purpose of this paper is to examine the short‐term stock market interactions between US and six major Asian markets – China, India, Hong Kong, Singapore, South Korea and Taiwan. These six economies along with Japan and Australia have the largest stock exchanges in the Asia‐Pacific region. The importance of the US market to the Asian economies is the prime motivation for a quantitative assessment of its role in this region. The objective of this study is to measure the dynamic stock market interdependence of US and Asian newly industrialized economies (NIEs) (Hong Kong, Singapore, South Korea and Taiwan) and emerging market economies (EMEs) (China and India) post Asian crisis of 1997 and also to capture the market interactions during the sub‐prime crisis.

The study has employed Granger causality tests and generalized forecast error variance decomposition (FEVD) analysis to analyze the fluctuations in and the extent of short‐term interdependence between the US and Asian economies. VAR model was estimated to run the simulations for FEVD analysis.

The empirical results from FEVD analysis revealed the dominance of US stock market on Asian markets; the USA being a large economy of the world, an important trading partner and major supplier of capital to Asian region. Stock markets of Asia are not immune to the shocks originating in the USA although the effects of shocks vary considerably across markets. Further, an important implication is that major crisis events can influence the relationship among stock markets.

This is one of the first papers in the Asian context examining the interdependence with the US markets. Hence, even though most of the Asian economies went through liberalization, the macroeconomic and financial circumstances were very different before, after and during the process. This motivated the examination of the interactions between US and other Asian markets.

The purpose of this paper is to investigate the transmission of information (at return and volatility level) as well as the correlation between Kuala Lumpur Syariah and Jakarta Islamic Indices.

The daily return from July 4, 2000 to December 29, 2006 was employed in the bivariate VAR GJR‐GARCH model.

The results indicate significant unidirectional return and volatility transmissions from Kuala Lumpur Syariah and the Jakarta Islamic Indices. There is no evidence of asymmetric effects in volatility for both markets. However, volatility is highly persistent and mean‐reverting in each market. The findings also revealed that there is low correlation between the two Islamic stock markets investigated.

The data used in this study are limited to the Islamic stock markets located in South East Asia, concentrating more on the post‐economic crisis period analysis. Further research may be conducted using a different time period and frequency of data while utilizing more Islamic indices. In addition, future research may look at and compare the market interdependence of Islamic stock markets in different economic conditions such as the pre‐economic crisis period, during an economic crisis period or post‐economic crisis period.

Market participants such as investors and market analysts should include the Malaysian Islamic stock market in forecasting market price movement and the volatility of the Indonesian Islamic stock market. In addition, both the Kuala Lumpur Syariah and Jakarta Islamic Indices offer potential for diversification to investors who wish to create an Islamic portfolio investment. From the regulator point of view, this study highlighted the fact that the Jakarta Stock Exchange should consider the Malaysian Islamic stock market in setting its policy to control the volatility of the Indonesian Islamic stock market because the source of volatility in Indonesian market is not only from the market itself, but also from the Malaysian market. On the other hand, in controlling the volatility of the Islamic Malaysian market, Bursa Malaysia should only implement a policy related to the Malaysian market because the source of volatility only comes from the local markets. Finally, the policy makers in both markets do not need to implement long‐range measures to reduce the impact of volatility persistence in these markets.

This is the first paper to investigate information transmission and market interdependence between the Islamic stock markets in South East Asia.

This paper aims to attempt to re-capture the stock market contagion effect from the US to the BRIC equity markets during the recent global financial crisis in a multivariate framework. Apart from this, the study also identifies optimal portfolio hedging strategies to minimize the underlying portfolio risk during the period undertaken for the purpose of study.

To account for the dynamic interactions, the study uses vector autoregression (p) dynamic conditional correlation (DCC)-asymmetric generalized autoregressive conditional heteroskedastic (1,1) model in a multivariate framework, coupled with a monthly heat map relating to the co-movement between the US and the BRIC equity markets during the period 2007-2009. Finally, by following the studies, Hammoudeh et al. (2010) and Syriopoulos et al. (2015), the time-varying optimal portfolio hedge ratios and weights are computed.

The results report a contagion impact of the US subprime crisis (following the collapse of the Lehman Brothers) on the Indian and Russian stock markets only. On the other hand, a higher degree of interdependence between the US and Brazilian market has been observed. The US and Chinese equity markets indicate a relatively lower level of interdependence among themselves. The optimal hedge ratios are found to be most effective for a portfolio comprising the US and Chinese stocks even during the crisis period. A US investor should invest approximately 30 cents in the Indian market and rest of the 70 cents in the US market in a US$1 portfolio to minimize the portfolio risk without lowering the expected returns. During the crisis period (2007-2009), the optimal portfolio weights indicate a higher weightage to the BRIC stocks.

The results support the construction of optimal US–BRIC stock portfolios and provide an insight to the investors and policy makers both domestic as well as international, with regard to the contagion impact and interdependence, especially during a crisis period.

The study uses a DCC model in a multivariate framework instead of bivariate, wherein all the markets are factored into a single interaction framework across a very long period (2004-2014). Second, a heat map of monthly correlation combinations has been created for the period 2007-2009, to comprehend the contagion impact or interdependence among the markets. Finally, the study ascertains time-varying optimal hedge ratios and portfolio weights for a two asset portfolio, from a US investor viewpoint, making the study first of its kind in all the perspectives.

The purpose of this paper is to examine the short-term and long-term interdependence among the stock markets of Africa and Middle East region. It also attempts to analyze the pattern of volatility spillover among the regional stock markets.

The study has used Granger causality test, variance decomposition test of vector auto-regression (VAR) model, vector error correction model (VECM), multivariate generalized conditional heteroskedasticity (MGARCH-BEKK) models and Johansen and Juselius multivariate cointegration techniques.

The study finds that the interlinkages of the stock markets are not uniform across all the countries of the region. The stock market of Israel, South Africa and Jordan are found to be highly connected stock market of the region followed by Egypt and Botswana. The study also finds significant spillover of lagged standardized volatility across the stock markets of the region. But the magnitude of the response of volatility spillover and its persistence is very minimum. However, the stock markets are found to be co-integrated and expected to share long-run equilibrium relationships among each other.

The study has the scope to be extended to capture the time-varying integration of market returns with transmission of monetary policy and exchange rate changes within the region. The results obtained from this study may assist the firm managers and international investors to understand the key drivers of market connectedness.

Empirically investigating the pattern of stock market connectedness in Africa and Middle East region with advanced methodology over a long study period is the originality of this study.

The purpose of this paper is to investigate whether the relationship of interdependence and contagion between BRICS countries and emerging non-BRICS countries is similar to that observed between developed countries and emerging BRICS countries.

The authors analyzed 15 markets: 5 BRICS, 5 developed (USA, Japan, Germany, England and France) and 5 emerging markets (Mexico, Indonesia, Turkey, Iran and Poland). Based on the time series of returns of the main stock indexes of each country, referring to the period from 2008 to 2018, the authors applied Granger causality tests, vector auto-regression and the dynamic conditional correlation-GARCH model.

The results led to the rejection of the main hypothesis and showed adherence to the behaviors predicted in the literature for the relations between the groups of markets.

This paper, besides analyzing the interdependence between markets in times of crisis, analyzes the effect of contagion between developed and emerging markets.

The assessment of interdependence between stock markets is an important aspect of international portfolio management. The purpose of this paper is to examine and highlight the diversification potential of South Asian stock markets vis-à-vis developed and European stock markets.

The developed stocks markets include USA and UK, and South Asian stock markets include India, Pakistan and Sri Lanka while DJ STOXX 600 index is used to represent the European stock markets. Monthly data are used to examine long-run relationship through ARDL bound testing approach and estimates are obtained using DLOS. Short-term dynamics are captured through vector error correction-based Granger causality.

South Asian stock markets are closely linked with each other; similarly, developed/European markets are interlinked. US stock market not only impacts European stock markets, it also Granger cause South Asian stock markets. The findings suggest increase in comovement of South Asian stock markets with the global markets after financial crises of 2007-2008.

The diversification benefits of South Asian stock markets for international investors are still evident due to their low relationship (in both long and short run) with developed/European stock markets.

Given the emergence of South Asian stock markets, new insight on their relationship with developed stock markets can provide interesting findings for international portfolio diversification. The South Asian equity markets are an important source of investment because of their immense growth and weak correlation with international markets.