• The Journal of the Convergence on Culture Technology
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• v.5 no.3
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• pp.113-118
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• 2019

This study analyzed how interdependence between China, Hong Kong, Taiwan and Singapore stock markets changed after the implementation of Shanghai-Hong Kong Stock Connect system using the EGARCH-GED model that allow simultaneous analysis of return and variability. Since the implementation of this system, the interdependence of Taiwan stock market with the Greater China stock markets has been weakened, and the interdependence of Singapore's stock market with the Greater China stock markets has not been exist. On the other hand, he interdependence between China and Hong Kong stock markets has been shown to be significantly enhanced since the implementation of this system. This is appears to be the result of improved conditions for Chinese and Hong Kong investors to invest in the two stock markets following the implementation of this system. Thus, considering the portfolio investment in the Greater China stock markets, the investors will need to develop their investment strategies in light of these facts that the weakening interdependence of the Taiwan and Singapore securities markets and the strengthening interdependence of the Chinese and Hong Kong securities markets.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1075-1084
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• 2012

This study examines stock market co-movement among three China stock markets: Shanghai stock market, Shenzhen stock market, Hongkong stock market. US stock market leads three China stock markets and Honkong stock market leads Shanghai and Shenzhen stock market. But there are no lead-lag effects among China stock markets after controlling US stock market effect. These results could be important for the investors and firms that are interested in China stock markets.

• The Journal of Asian Finance, Economics and Business
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• v.1 no.1
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• pp.5-14
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• 2014

This paper empirically examines the short-run and long-run causal relationship between stock market prices and exchange rates in Chinese stock markets using monthly data from January 2002 to December 2012 retrieved from the National Bureau of Statistics of the People's Republic of China. Unit root, cointegration tests, vector error correction estimates, block exogeneity Wald tests, impulse responses, variance decomposition techniques and structural break tests are employed. This study found 1) long-run causality from exchange rates to stock prices in Chinese stock markets and 2) short-run causality from Japanese yen and Korean won exchange rates to stock prices in the Shanghai Stock Exchange strongly prevails while in the Shenzhen Stock Exchange weakly prevails. The impact of the global financial crisis from 2007 to 2009 on Chinese stock markets was insignificant.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1337-1341
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• 2010

The paper investigates linkages between the Korea stock market and each of the major Asia-Pacific stock markets, namely those of the Japan, China, Australia, New-Zealand, We employs the Johansen technique to test for pairwise cointergration between the Korea stock market and each of the major Asia-Pacific stock markets. The major stock indices of the markets are used, from 1 September 2006 to 31 August 2010. The results from the test implies that the Korea market is not cointergrated with any of the major Asia-Pacific markets during the period. Our study implies that there are no long-run linkages between the Korea and any of the major Asia-Pacific stock markets.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.1
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• pp.127-136
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• 2016

The purpose of this research is to conduct a comparative study on the characteristics of daily volatility spillovers across the stock markets of Korea, China, and Japan. We employ generalized spillover definition and measurement developed by Diebold & Yilmaz (2009, 2012). The sample period is January 5, 1993 to September 25, 2015. From a static full-sample analysis, we find that 8.60% of forecast error variance comes from volatility spillovers. From a 250-day rolling-sample analysis, we discover that there exist significant volatility fluctuations in the stock markets of Korea, China and Japan, expecially during the Asian Financial Crisis (1998-1999) and the US Credit Crisis (2008-2009) after the collapse of Lehman Brothers. From the net directional spillovers across three countries, we come upon that there is neither a definite leader nor a significant follower during the sample period.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.77-88
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• 2021

The stock markets in the BRICS (Brazil, Russia, India, China and South Africa) countries are the leading emerging markets globally. Therefore, it is pertinent to ascertain the critical drivers of stock market development in these economies. The currrent study empirically investigates to identify the linkages between stock market development, key macro-economic factors and institutional factors in the BRICS economies. The study covers the time period from 2000 to 2017. The dependent variable is the country's stock market development and the independent variables consist of six macroeconomic variables and five institutional variables. The study employs a panel cointegration test, Fully Modified OLS (FMOLS), a Pooled Mean Group (PMG) approach and a heterogeneous panel non-causality test.The findings of the study indicate co-integration among the selected variables across the BRICS stock markets. Long-run estimations reveal that five macroeconomic variables and four variables related to institutional quality are positive and statistically significant. Further, short-run causalities between stock market capitalization and selected variables are detected through the test of non-causality in a heterogeneous panel setting. The findings suggest that policymakers in the BRICS countries should enhance robust macroeconomic conditions to support their financial markets and should strengthen the institutional quality drivers to stimulate the pace of stock market development in their countries.

• International Area Studies Review
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• v.18 no.3
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• pp.67-88
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• 2014

The Chinese stock market has increasingly strengthened its market power on other stock markets due to rapid growth of its economy. In this context, this study investigated return spillover effect as well as asymmetric volatility spillover effect using a VAR-Bivariate EGARCH model among stock markets(China, US, Japan, Korea). Furthermore, we conjectured the impact of 2008 global financial crisis on the spillover effect of the Chinese stock market. In our empirical results, the Chinese stock market has a weak return spillover effect to other markets(US, Japan, Korea), but after the global financial crisis, its return spillover effect becomes stronger among other stock markets. In addition, the Chinese stock market have strengthened its asymmetric volatility spillover effect on other stock markets after the Global financial crisis. As a result, the Chinese stock market has an strong influence on other stock markets.

• Journal of Contemporary Eastern Asia
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• v.19 no.1
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• pp.97-122
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• 2020

This paper examines the existence of herd behaviour in fifteen (15) global stock markets, which consist of Developed Markets (Canada, Hong Kong, Japan, Singapore and the United Kingdom), Advanced Emerging Markets (Brazil, Malaysia, Mexico, Poland and South Africa) and Secondary Emerging Markets (Chile, China, Indonesia, the Philippines and Russia) by using Cross Sectional Absolute Deviation (CSAD) method of Chiang and Zheng (2010). It also seeks to explore the impact of social factors such as prosperity, education, ageing society, industry orientation and gender on the existence of market-wide herding. The findings of this paper indicate that herd behaviour exists in Singapore (Developed Market), Mexico, Poland and South Africa (Advanced Emerging Markets) and China and the Philippines (Secondary Emerging Markets). No evidence of herding is observed for Canada, Hong Kong, Japan, United Kingdom, Brazil, Malaysia, Chile, Indonesia and Russia. Ageing society is also found to have significant impact on the existence of herd behaviour. Nonetheless, prosperity, education, industry orientation and gender are found to be insignificant to herding. This study sheds some light on whether social factors determine herding behaviour in the 15 selected stock markets.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.165-173
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• 2017

The purpose of this study was to analyze the correlation and volatility of Korea and neighboring East Asia stock markets. East Asian stock markets were selected for Japan, China, Hong Kong and Taiwan by economically and geographically close with Korea. If you understand the volatility and the correlation between Korea and the East Asian stock market, it may be helpful in predicting investment. And It may reduce the risk of investing of asset allocation in global portfolio level. For this using the national monthly return data for the last 163 months, I was calculating and comparison the rate and correlation, and regression analysis. Result of the correlation analysis, Korea have shown a low correlation with China. while showing a high correlation with Taiwan and Hong Kong. China has been forming its own market in East Asia and showing a low correlation with other countries exception Hong Kong. Hong Kong has been determined as the highest harmonization within the East Stock Market.

• Management & Information Systems Review
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• v.32 no.4
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• pp.189-207
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• 2013

Using high-frequency data for 2 years, this study investigates intraday lead-lag relationship between stock index and stock index futures markets in Korea and China. We found that there are some differences in price discovery and volatility transmission between Korea and China after the stock index futures markets was introduced. Following Stoll-Whaley(1990) and Chan(1992), the multiple regression is estimated to examine the lead-lag patterns between the two markets by Newey-West's(1987) heteroskedasticity and autocorrelation consistent covariance matrix(HAC matrix). Empirical results of KOSPI 200 shows that the futures market leads the cash market and weak evidence that the cash market leads the futures market. New market information disseminates in the futures market before the stock market with index arbitrageurs then stepping in quickly to bring the cost-of-carry relation back into alignment. The regression tests for the conditional volatility which is estimated using EGARCH model do not show that there is a clear pattern of the futures market leading the stock market in terms of the volatility even though controlling nonsynchronous trading effects. This implies that information in price innovations that originate in the futures market is transmitted to the volatility of the cash market. Empirical results of CSI 300 shows that the cash market is found to play a more dominant role in the price discovery process after the Chinese index started a sharp decline immediately after the stock index futures were introduced. The new stock index futures markets does not function well in its price discovery performance at its infancy stage, apparently due to high barriers to entry into this emerging futures markets. Based on EGAECH model, the results uncover strong bi-directional dependence in the intraday volatility of both markets.