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This paper investigates the global financial integration of the Gulf Cooperation Council markets, which is important for financial economists, global investors and policymakers.

The first step is to estimate a benchmark one-factor model and multifactor models over the entire sample period to obtain the time-invariant global integration estimates for the Gulf Cooperation Council markets. Because the global integration of the Gulf Cooperation Council markets may be time varying, the second step is to use 24-month rolling regressions to estimate the time-varying integration estimates. To explicitly test for structural breaks in global integration, this study applies a supremum Wald test to endogenously search for structural breaks.

Empirically, consistent evidence suggests that the Gulf Cooperation Council markets are increasingly integrated with international equity markets at different levels of financial development and from different regions. However, compared to other emerging and frontier markets, the global integration of the Gulf Cooperation Council markets is still relatively low, suggesting that these markets still offer significant diversification benefits for global investors.

This study contributes to the literature by systematically investigating the global integration of the Gulf Cooperation Council markets with monthly data (to account for the gradual information diffusion in international equity markets) and a longer sample period (to more robustly identify the trend in the global integration).

Financial integration has played an essential role in achieving economic growth in the members of the Association of Southeast Asian Nations (ASEAN). However, its effects on economic growth in the region in the long run have been underexamined. This paper examines these effects for the ASEAN member countries.

A fully modified ordinary least squares (FMOLS) estimation is used to take into account two critical econometric issues in panel data analysis, including (1) cross-sectional dependence and (2) slope heterogeneity. The dynamic ordinary least squares estimation is also used for robustness analysis. The authors use the generalized least squares estimation to examine the effects in the short run.

This study’s empirical results confirm the important role of financial integration to economic growth in the ASEAN countries in the short term. However, the effects appear to disappear in the long term. The authors also find capital, labor, and human development positively contribute to economic growth in the region. International trade plays a significant role in supporting economic growth in the ASEAN in the short run. However, its effect seems to weaken in the long run.

The growth effects of financial integration in the ASEAN region in the long term have largely been neglected. As such, the authors examine these effects using updated data on financial integration. The authors extend this study’s analysis by considering foreign direct investment and financial depth as the alternative proxies for financial integration. Other estimation technique is also used as the robustness check.

The aim of this study is to examine the nature and determinants of stock market integration between India and other Asia–Pacific countries (Malaysia, Hong Kong, Singapore, South Korea, Japan, China, Indonesia, the Philippines, Thailand and Taiwan) over the period 1991–2021.

Unit root tests, the dynamic conditional correlation-Glosten Jagannathan and Runkle-generalized autoregressive conditional heteroscedasticity (DCC-GJR-GARCH), pooled ordinary least squares (OLS) regression and random effects models are employed for the analysis.

The empirical results show that the DCC between each pair of sample countries is less than 0.5, indicating weak ties between the pairs of sample countries. Also, the DCC between India and other Asia–Pacific stock markets is positive and low, implying low level of integration. The correlation between India and China stock markets is found to be the highest, implying significant level of integration. The main reason for it would be strong economic linkages and bilateral trade relationship between India and China. Moreover, gross domestic product (GDP), interest rate (IR), consumer price index (CPI)-inflation and money supply (MS) differentials are the major driver of stock market integration between India and other Asia–Pacific countries.

The findings of the study have important implications for investors, portfolio managers and policymakers. It is found that the DCC between India and other Asia–Pacific countries (considered in the study) except China is low, which indicates weak ties between the pairs of sample countries. This implies that the Indian stock market provides good investment opportunities for foreign investors. Also, investors and portfolio managers can attain more diversified benefits and can minimize country risk by investing across Asia–Pacific countries. Further, knowledge about the factors that integrate the Indian stock market with the other Asia–Pacific stock markets will help policymakers frame suitable economic and financial stabilization policies.

This study contributes to the extant literature: first, by examining the linkages of Indian stock market with other Asia–Pacific countries; second, although previous studies confirmed the existence of linkages among the various stock markets, few researchers pay attention to the factors driving the process of stock market integration. This study provides additional evidence by examining the significant macroeconomic factors driving the process of such integration in the Asia–Pacific region considered under the study.

The study investigates the co-movements amongst real estate investments trust (REITs). This study examines the co-movements between the world and individual countries' REITs and the co-movements amongst country-pair REITs. This study explores the responsiveness of the REITs markets' co-movements to the 2008 global financial crisis (GFC), the coronavirus disease 2019 (COVID-19) pandemic and the Russian–Ukraine conflict.

The study employs a wavelet coherency technique and relies on data from six REITs markets over the 1995–2022 period.

The evidence shows a generally high level of coherency between the global and the country's REITs. The findings further indicate higher co-movements between some country pairs and a lower co-movement for others. The results suggest that the REITs markets increased in co-movements around the 2008 GFC, the COVID-19 pandemic and the Russian–Ukraine conflict. These increased co-movements mostly lasted for a short period suggesting REITs markets contagion around these global events. The results generally suggest interdependence between the global and the country's REITs. Additionally, interdependence is observed for some of the country-pair REITs.

The evidence indicates that REITs markets respond to global events. Thus, the increasing co-movement amongst REITs observed in this study may expose domestic REITs to global crisis. However, this study provides opportunities for minimising the cost of capital for real estate projects. Also, REITs provide limited diversification gains around crisis times. Therefore, countries need to open the REITs markets to global investors whilst pursuing policies to ensure the resilience of the REITs markets to global events. Investors should also take note of the declining geographic diversification gains from some country-pair REITs portfolios.

BRICS (Brazil, Russia, India, China, and South Africa) a group of five emerging nations that are expected to lead the global economy by the year 2050. The growth potential of these nations attracts investors from all over the world who are in search of maximizing the return on their investments and limiting the losses to the lowest possible level. The purpose of this research study is to determine whether or not Indian stock market investors can diversify their stock market portfolios into other BRICS economies.

A daily frequency of stock market closing data for the BRICS nations over a period of 2013–2021 has been considered and several econometric techniques have been applied. Starting with the Granger causality test for checking the direction of causality. The VAR technique is applied to find out whether the movement in the Indian stock market is influenced by its own past values or the past values of the other BRICS nations, and lastly, the DCC-MGARCH technique is applied to check the degree of integration or the volatility spillover from the Indian stock market to the stock markets of other BRICS nations.

The results of the study indicated that in both the short term and long term, stock market volatility is spilling over from the Indian stock market to the stock markets of other BRICS nations. Hence, the study suggests that BRICS nations cannot be a destination for portfolio diversification for Indian stock market investors.

The stock markets of emerging nations experience high volatility, which creates confusion for investors as to whether to invest or to abstain from portfolio diversification. At present, there is a gap in the existing literature to capture the stock market volatility of BRICS nations. This research study fills this research gap and confirms that BRICS nations cannot be a destination for portfolio diversification. Moreover, equity market experts, portfolio managers and researchers can all take advantage of this study.

It has been argued in the literature that structural changes in the financial markets, such as integration, have the potential to cause herding behavior or correlated behavioral patterns in traders. The purpose of this study is to investigate whether there is any financial herding behavior in the Latin American Integrated Market (MILA), a transnational stock market composed of Chile, Peru, Colombia and Mexico stock exchanges and whether there is any ARCH or GARCH effect in the herding behavior models.

This study uses the modified return dispersion approach on daily index return data. The sample period is from January 03, 2002 to May 07, 2019. The data are obtained from the MILA database. To count time-varying volatilities in herding models, the authors run ARCH family regression with GARCH (1,1) settings. Hwang and Salmon (2004) model is used as a robustness test.

The authors found strong herding behavior under the general market conditions and moderate and partial herding behavior under some specified markets circumstances, such as bull and bear markets and high-low volatility states. Moreover, the pre-MILA period exhibits more herding behavior than the post-MILA period. The empirical results show that most of the ARCH and GARCH effects are statistically significant, implying that the past information of stock returns and market volatility significantly affect the volatility of following periods, which can also explain the formation of herding tendency among investors. Finally, the results of the robustness tests (Hwang and Salmon, 2004) confirm herding in all periods, except full sample period for Mexico and post-MILA period for Mexico and Colombia.

This study investigates the herding behavior in the MILA market in terms of market return, volatility and timing. A limitation of the paper is that the authors have not included other factors on the formation of herding behavior, such as macroeconomic factors, effects of regional or international markets and policy influences. The authors will explore the issue in the extension of the paper.

As MILA is the first virtual integration of stock exchanges without merging, the study provides useful findings and draws good inferences of herding behavior in the MILA market in terms of market return, volatility and timing which are useful for academics, investors and policymakers in their investment and decision makings.

The paper provides useful findings and draws good inferences of herding behavior in the MILA market in terms of market return, volatility and timing which are not only useful in practical implications, but also in social implications.

This study contributes to the herding literature by examining four different hypotheses in respect of the unique case of transnational stock exchange without fusions or corporate mergers, where each market maintains its independence and regulatory autonomy. The authors also contribute to the literature by including both ARCH and GARCH effects in the herding behavioral models along the Hwang and Salmon (2004) approach.

The paper investigates the dynamic relationship among the stock markets of South Asian Association of Regional Cooperation (SAARC) countries during the COVID-19 pandemic.

Daily time-series data of four SAARC countries: India, Bangladesh, Pakistan, and Sri Lanka, from February 13th, 2013 to March 31st, 2021 are used. The study considers stock prices prior to the blowout of COVID-19 and during the onset of the pandemic. The novel estimation procedure of the autoregressive distributed lag model is used while the results are also confirmed by post-estimation techniques.

The study confirms that the COVID-19 contagion has adversely influenced the stock returns of SAARC countries. The findings signify that the pattern of cointegration has significantly different regularities in the pattern of causality in the long run and short run during the COVID-19 crisis. Overall, the study revealed that the COVID-19 pandemic has weakened the dynamic connection among the stock markets of SAARC countries.

To dampen uncertainties generated by the COVID-19 pandemic, the authorities and central banks should be equipped with efficient strategies and guidelines to cope with the crisis created by the pandemic. Further, governments should focus on assuaging the panic faced by investors and enhancing the confidence of domestic as well as foreign investors. Further, the weakened integration of financial markets during the crisis offers opportunities for speculative and arbitrage gains for investors.

The research work is an innovative effort to analyze the impression led by COVID-19 on the SAARC stock markets integration.

This paper aims to examine if the market risk premiums of the Gulf Cooperation Council (GCC) countries are particularly higher on prescheduled US monetary policy announcement days. The findings shed light on the causality relationship from the state of the global economy to the GCC equity markets as well as their integration with the rest of the world.

The author takes the standard event-study approach, following Fama et al. (1969). As the announcement days are prescheduled, the impact of the announcements on the GCC markets' risk premia allows for test of causality, while other studies address predictability and association.

The author finds that excess returns are higher, both economically and statistically, on announcement days in most individual GCC countries and the region overall. Moreover, additional compensations may not appear on the exact days of announcement in a few countries; rather, on the days right before or after announcements, possibly due to information leakage or gradual diffusion. My results show that there is a causal relationship from the state of the global economy to the GCC equity markets' risk premia. This new evidence supports integration between the Gulf region's and the world's financial markets.

The evidence of risk–return transmission from US monetary policy announcements to GCC countries' equity indices supports integration between the region's and the world's financial markets. The study results will help guide investors' and corporations' investing, capital budgeting and portfolio evaluation decisions.

This paper extends the announcement literature (Savor and Wilson 2013, 2014) by examining the responses of the GCC countries, the major players of the global oil markets. The empirical analysis documents a causal relationship from the state of the global economy, as revealed by US monetary policy announcements, to the GCC equity indices. This new evidence supports increased integration between the Gulf region and the world, a finding that investors and corporations should consider when making investing, capital budgeting and portfolio evaluation decisions.

This study aims to examine the tail connectedness between the Chinese and Association of Southeast Asian Nations (ASEAN) stock markets. More specifically, the authors measure the return spillovers at three quantile levels: median (t = 0.5), lower extreme (t = 0.05) and upper extreme (t = 0.95). The connectedness at extreme upper and lower quantiles provides insightful information to investors regarding tail risk propagation, which ultimately suggests that investors adjust their portfolios according to the extreme bullish and bearish market conditions.

The authors employ the quantile connectedness approach of Ando et al. (2022) to examine the quantile transmission mechanism among the ASEAN and Chinese stock markets.

The results show significant evidence of a higher level of connectedness between Chinese and ASEAN stock markets at extreme upper and lower quantiles compared to the median quantiles, which suggests the use of a quantile-based connectedness approach instead of an average-measure-based one. Furthermore, the time-varying connectedness analysis shows that the total spillovers reach the highest peaks during the global financial crisis, the Chinese stock market crash and the COVID-19 pandemic at the upper, lower and median quantiles. Finally, the static and dynamic pairwise spillovers between the Chinese and ASEAN markets vary over quantiles as well.

This study is the first attempt to examine quantile vector autoregression (VAR)-based return spillovers between China and ASEAN stock markets during different market statuses. Besides, the COVID-19 has intensified the uncertainty in Asian countries, mainly China and ASEAN economies.

The authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crises episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak).

The authors use the GARCH and Wavelet approaches to estimate causalities and connectedness.

According to the findings, China and developed equity markets are connected via risk transmission in the long term across various crisis episodes. In contrast, China and emerging equity markets are linked in short and long terms. The authors observe that China leads the stock markets of India, Indonesia and Malaysia at higher frequencies. Even China influences the French, Japanese and American equity markets despite the Chinese crisis. Finally, these causality findings reveal a bi-directional causality among China and its developed trading partners over short- and long-time scales. The connectedness varies across crisis episodes and frequency (short and long run). The study's findings provide helpful information for portfolio hedging, especially during various crises.

The authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crisis episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak). Previously, none of the studies have examined the connectedness between Chinese and its trading partners' equity markets during these all crises.