scholarly journals The Three Musketeers Relationships between Hong Kong, Shanghai and Shenzhen Before and After Shanghai–Hong Kong Stock Connect

2019 ◽  
Vol 11 (14) ◽  
pp. 3845 ◽  
Author(s):  
Andy Wui-Wing Cheng ◽  
Nikolai Sheung-Chi Chow ◽  
David Kam-Hung Chui ◽  
Wing-Keung Wong
Keyword(s):  
Hong Kong ◽  
Stock Market ◽  
Granger Causality ◽  
Stock Markets ◽  
Financial Integration ◽  
Mainland China ◽  
Causality Analysis ◽  
Cointegration Tests ◽  
China Stock Market ◽  
Hong Kong Stock Market

This study examines the sustainability of financial integration between China (represented by Shenzhen and Shanghai) stock markets and Hong Kong stock market over the period of pre and post launch of the Stock Connect Scheme. This paper aims to fill the gap in the financial literature by providing empirical research on the dynamics of the financial integration process, and examining the sustainability of financial integration among the three Chinese stock markets. We apply cointegration and both linear and nonlinear causalities to investigate whether the Shanghai–Hong Kong Stock Connect has any impact on both market capitalizations and market indices of Hong Kong, Shanghai, and Shenzhen markets. Through cointegration tests and linear Granger causality techniques, it was found that the stock markets from mainland China are increasingly influencing the Hong Kong stock market after the introduction of the Stock Connect Scheme; however, when using nonlinear Granger causality analysis for confirming China market dominance, the result shows an reverse relationship whereby the Hong Kong stock market is still relevant to understand and predict China stock market after the introduction of the Stock Connect Scheme. Overall, our findings support the view that the Shanghai–Hong Kong Stock Connect has a significant impact on both market capitalizations and market indices of the Hong Kong, Shanghai, and Shenzhen markets, but Hong Kong stock market is still relevant to understand and predict China stock market after the introduction of the Stock Connect Scheme. The change in share premium difference between mainland China’s domestic A-share markets and Hong Kong’s H-share market could change investors’ appetites or sentiments. Further research includes examining whether there is any functional relationship including nonlinear relationship and studying the dynamic drivers of the relationships.

The Shanghai-Hong Kong Stock Market

2015 ◽  
Vol 07 (03) ◽  
pp. 36-45
Author(s):  
Jing WAN
Keyword(s):  
Hong Kong ◽  
Stock Market ◽  
Capital Markets ◽  
Capital Market ◽  
Stock Markets ◽  
Market Access ◽  
Mainland China ◽  
Opening Up ◽  
Hong Kong Stock Market ◽  
The Capital Market

The Stock Connect scheme launched on 17 November 2014 was the first mutual market access between mainland China and Hong Kong stock markets. It is the biggest move ever in the opening up of the capital market. Experiences accumulated will be of great value to mainland regulators who will decide on how these experiences could be utilised for China’s future opening up of its capital markets and for accelerating renminbi internationalisation.

scholarly journals Analysing portfolio diversification opportunities in selected stock markets of North and South America and their impact on the textile sector: An empirical case study

2021 ◽  
Vol 72 (04) ◽  
pp. 398-407
Author(s):  
RAMONA BIRAU ◽  
CRISTI SPULBAR ◽  
AJMAL HAMZA ◽  
EJAZ ABDULLAH ◽  
ELENA LOREDANA MINEA ◽  
...  
Keyword(s):  
Stock Market ◽  
Granger Causality ◽  
Stock Markets ◽  
Financial Integration ◽  
Stock Exchange ◽  
Portfolio Diversification ◽  
Causality Test ◽  
International Portfolio Diversification ◽  
Integration Test ◽  
Textile Sector

This empirical study investigates the financial integration linkages among the sample stock markets of Canada, Mexico,United States (for both New York Stock Exchange, i.e. NYSE and NASDAQ), Panama, Brazil, Chile, Peru, Venezuela,Jamaica, Trinidad, and Tobago during the period from January 2001 to April 2019. This research study also examinesthe impact of selected stock market dynamics on the textile sector. International portfolio diversification has been animportant subject of research in financial fraternity since the emergence of Modern Portfolio Theory in 1952. This studyexamines the portfolio diversification opportunities in the 11 stock markets of Americas.International diversificationamong stock market indices has proven to be fruitful in the past. Certain tests have been used to determine opportunitiesfor diversification are correlation test, pairwise co-integration test, multiple co-integration test and granger causality test.The empirical results show that stock market indices share low correlation among other and they are not highlyco-integrated whereas results of Granger causality test exhibit an unidirectional relationship among few stock marketsin short run.

A quantile regression approach to evaluate the relative impact of global and local factors on the MENA stock markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Slah Bahloul ◽  
Nawel Ben Amor
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Stock Returns ◽  
Stock Markets ◽  
Financial Integration ◽  
Ordinary Least Squares ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
The Impact

PurposeThis paper investigates the relative importance of local macroeconomic and global factors in the explanation of twelve MENA (Middle East and North Africa) stock market returns across the different quantiles in order to determine their degree of international financial integration.Design/methodology/approachThe authors use both ordinary least squares and quantile regressions from January 2007 to January 2018. Quantile regression permits to know how the effects of explanatory variables vary across the different states of the market.FindingsThe results of this paper indicate that the impact of local macroeconomic and global factors differs across the quantiles and markets. Generally, there are wide ranges in degree of international integration and most of MENA stock markets appear to be weakly integrated. This reveals that the portfolio diversification within the stock markets in this region is still beneficial.Originality/valueThis paper is original for two reasons. First, it emphasizes, over a fairly long period, the impact of a large number of macroeconomic and global variables on the MENA stock market returns. Second, it examines if the relative effects of these factors on MENA stock returns vary or not across the market states and MENA countries.

scholarly journals Understanding the Interdependency between the Nifty 50 Future Index and the Advanced Future Stock Market through Econometrics

2019 ◽  
Vol 8 (4) ◽  
pp. 3660-3664
Keyword(s):  
Hong Kong ◽  
Stock Market ◽  
Granger Causality ◽  
Foreign Exchange ◽  
Financial Market ◽  
Stock Prices ◽  
Economic Condition ◽  
The Future ◽  
Bidirectional Movement ◽  
High Degree

In recent times the stock market is accepted as a tool to measure the economic condition of a nation. It is found that the Indian financial market as highly volatile due to the lower value of rupees in foreign exchange with the dollar. This motivated the researchers to measure the interdependencies of [Nifty 50 future (India), Nikkei 225(Japan), NASDAQ 100 Futures (USA), Dow Jones 30 (USA), SSEC (China), Hang Seng Future (Hong Kong), and FTSE 100 (London)]. The analysis covers monthly stock prices for a period of 10years from April 2008 to March 2018. The measurement of interdependencies is studied through granger causality and correlation after the confirmation of the non-normality of data and stationary of data. The result shows a high degree of correlation between NASDAQ and Dow Jones shows 98.76% followed by 96.89% between Nifty 50 future and NASDAQ. The co-movement result of Nifty 50 future through granger causality states Nifty 50 future can explain the future stock market of Nikkei (Japan) and SSEC (China) and the Hang Seng future (Hong Kong) has a bidirectional movement with Nifty 50 futures. The study is useful for the investors to identify the interdependencies of the indices and understand the movement in a significant manner.

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