Search results

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.

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.

This study aims to apply Benford’s law to examine the earnings management of companies listed in emerging ASEAN-5 countries: Indonesia, Malaysia, Philippines, Thailand and Vietnam.

The authors follow Amiram et al. (2015) to measure deviations from Benford’s law of the first digits of numbers reported in financial statements. The authors use the Jones-modified performance-match model (Jones, 1991; Dechow et al., 1995; Kothari et al., 2005) to estimate accrual earnings management. The authors use a sample of 47,389 observations of listed companies in ASEAN-5 countries from 2006 to 2019. The authors also run ordinary least squares (OLS) regressions to test the hypotheses.

The authors find that the first digits of numbers reported in the financial statements of companies in the sample closely conform to Benford’s law. Further evidence shows that the deviation from Benford’s law is positively related to abnormal accruals. The relationship between deviation from Benford’s law and abnormal accruals is more pronounced for the post-international financial reporting standards adoption period. The results survive for some robustness checks.

The authors show that Benford’s law holds for financial statements of companies listed in the emerging ASEAN-5 countries.

Auditors could use Benford’s law as an analytical procedure to assess the risks of material misstatements. Also, other users could apply Benford’s law on audited financial statements to foresee undetected misstatements.

The authors provide original evidence that financial statements of ASEAN-5 countries follow Benford’s law. The evidence supports the usefulness of Benford’s law in developing markets.

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.

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 evaluates the role of institutional framework and macroeconomic instability on financial market development among emerging economies.

The study uses panel data compiled from 32 countries from the sub-region of Sub-Sahara Africa (SSA), covering the period starting from 1996 to 2019. Empirical analyses were carried out using the two-step system generalized method of moments (TS-GMM) statistical framework.

Reviewed results suggest that institutional quality, effective governance and corruption control have a significant positive impact on financial market development among economies in the sub-region. Further empirical estimates show that macroeconomic risk and macroeconomic uncertainty have significant adverse effects on financial market development. Additionally, reported empirical estimates suggest that an improved institutional framework has the potential to lessen the adverse effect of macroeconomic instability on financial market development among economies in the sub-region.

The uniqueness of this empirical inquiry compared to related studies in the present literature stems from the fact that studies employing similar empirical approaches on the subject matter for economies in the sub-region are rare. Additionally, the analysis pursued in this study employs critical variables whose impact on financial market performance in the sub-region has not been examined per our review. These variables include indexes such as macroeconomic risk and institutional quality, which are unique to this study based on their construction; these indexes are generated using a principal component analysis procedure with different underlying variables compared to what may be found in the literature.

This study examines the extreme quantile connectedness and spillovers between West Texas Intermediate (WTI) crude oil futures and ten Vietnamese stock market sectors. Knowledge of such links is important to both investors and policymakers in understanding the transmission of shocks across markets.

The authors employ the extreme quantile connectedness methodology of Ando et al. (2022).

Initial results show that the size of spillovers is higher during bearish markets than bullish markets and under major financial, political, energy and pandemic events. The oil market is a net receiver of spillovers during downward markets and net contributors during upward markets. The banking sector is a net contributor of spillovers, whereas consumer discretionary and consumer staples are net receivers for different quantiles. The role of the remaining sectors as net receivers/contributors is sensitive to the quantiles. Oil has a large spillover effect on the electricity sector for all quantiles. Comparing all crises, oil offers the best hedging effectiveness to the Vietnamese sector during the coronavirus disease 2019 (COVID-19) crisis. Moreover, oil was a cheap hedge asset during oil crises. Finally, oil provides the highest hedging effectiveness for healthcare during the global financial crisis (GFC) and consumer staples during the European debt crisis (EDC), oil crisis and COVID-19.

Acknowledging the presence of heterogeneity in the relation between oil and economic sectors under different market conditions, this study is the first to examine the extreme quantile connectedness between oil and Vietnamese sectors.

The objective of this research is to identify the economic, demographic, sanitary and even cultural factors which explain the variability in the cross-section of returns in different markets globally during the first weeks after the outbreak of COVID-19.

Building on the event study methodology and using seemingly unrelated equations, the authors created several indicators on the impact of the pandemic in 75 different markets. Then, and using cross-sectional regressions robust to heteroscedasticity and using an algorithm to select independent variables from more than 30 factors, the authors determine which factors were behind the different stock market reactions to the pandemic.

Higher currency depreciation, inflation, interest rate or government deficit led to higher returns, while higher life expectancy, ageing population, GDP per capita or health spending led to the opposite effect. However, the positive effect of competitiveness and the negative effect of income inequality stand out for their statistical and economic significance.

This research provides a global view of investors' reaction to an extreme and unique event. Using a sample of 75 capital markets and testing the relevance of more than 30 variables from all categories, it is, to the authors' knowledge, the largest and most ambitious study of its kind.

This paper aims to investigate the dynamic volatility connectedness among 13 G20 countries by using the volatility indices.

The connectedness approach based on the time-varying parameter vector autoregression model has been used to investigate the linkage. The period of study is from 1 January 2014 to 20 April 2023.

This analysis revealed that volatility connectedness among the countries during COVID-19 and Russia–Ukraine conflict had increased significantly. Furthermore, analysis has indicated that investors had not anticipated the World Health Organization announcement of COVID-19 as a global pandemic. Contrarily, investors had anticipated the Russian invasion of Ukraine, evident in a significant rise in volatility before and after the invasion. In addition, the transmission of volatility is from developed to developing countries. Developed countries are NET volatility transmitters, whereas developing countries are NET volatility receivers. Finally, the ordinary least square regression result suggests that the volatility connectedness index is informative of stock market dynamics.

The connectedness approach has been widely used to estimate the dynamic connectedness among market indices, cryptocurrencies, sectoral indices, enegy commodities and metals. To the best of the authors’ knowledge, none of the previous studies have directly used the volatility indices to measure the volatility connectedness. Hence, this study is the first of its kind that has used volatility indices to measure the volatility connectedness among the countries.

This study addresses the empirical results of the spillover effect with export as the primary economic activity that enhances local businesses' total factor productivity (TFP). A learning mechanism is expected to be generated and used as the basis for the policy implication.

This study adopted the Cobb–Douglas function and multiple estimation approaches, including the generalized method of moments, the Olley–Pakes and the Levinsohn–Petrin estimation techniques. The findings were estimated based on the panel data of a Vietnamese local businesses survey conducted by the General Statistics Office of Vietnam (GSO) from 2010 to 2019.

The results showed that the highest TFP belongs to the businesses in the Southeast region, the Mekong Delta region, the mining industry and the foreign-invested enterprises. The lowest impacted TFP are businesses in the Northwest region and agricultural, forestry and fishery sectors. In addition, the estimated results also show that the positive spillover effect on TFP is shown through forward and backward linkage. The negative spillover effect is expressed through the backward and horizontal channels.

This study offers original empirical evidence on the learning mechanisms via which exports contribute to productivity improvement in a developing Asian economy, so making a valuable contribution to the existing academic literature in this domain. The findings of this research make a valuable contribution to the advancement of understanding on the many ways via which spillover effects manifest such as horizontal, forward, backward and supplied-backward linkage.

The study's findings indicate that it is advisable for governments to give priority to the development and improvement of forward and supply chain linkages between exporters and local suppliers. This approach is recommended in order to optimize the advantages derived from export spillovers. At the organizational level, it is imperative for enterprises to strengthen their technological and managerial skills in order to efficiently incorporate knowledge spillovers that originate from overseas partners and trade counterparts.

This study sheds new evidence on the export spillover effect on productivity in emerging economies, with Vietnam as the case study. The paper contributes to the research's originality by adopting novel methodological aspects to estimate local businesses' impact on total factor productivity.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0373