Financial Market Analysis: Integration between Chinese Stock Markets and International Stock Markets - Term Paper Example

 Financial Market Analysis For the last 30 years, the world has witnessed great developments in information technology, growth of multinational companies and liberalization of financial systems and capital markets that has led to shifts in prices and integration of domestic and international money markets (Di Giovanni, Levchenko & Zhang, 2012). This has led to dependent of domestic markets on the global money market environment although full integration has not been achieved due to differences in levels of growth, structure of the economy and the different timing of various business cycles in different countries. The information regarding the structure and properties of correlations among global financial markets is critical to appraise the probable advantages of international portfolio diversification (Motamen-Samadian, 2006, p79). This fact has motivated many scholars to examine the return correlations across international markets using time varying correlation models with in the multivariate GARCH framework. The key focal point in the latest literature has been to reveal the expected ascendant trend in the correlation and nature of dynamic co-movements, however, although liberalization in the monetary markets had started in as early as 1980s, the diverse results of previous pragmatic research does not allow an agreement on expected rising trend in co-movements within financial markets up to 2000s. Correlations among monetary markets have a time varying nature and tend to amplify mostly during unstable times, on the other hand, report that the response of correlations to the volatility is asymmetrical and correlations rise during high volatile bear markets. Since the beginning of 21st century, literature shows that there has been increasing trend in correlation among financial markets especially among developed countries and countries within the same geographical area, for instance, in the European Union, countries that are members of the union have the highest correlation in their money markets. Using data from weekly transactions between January 8, 1987 and February 7, 2002 and an asymmetric and generalized version of Dynamic Conditional Correlation GARCH (DCC-GARCH) model of Engle (2002), they explore the relationship composition of 21 nations' stock and bond markets from Europe, America and Australasia. Experimental results show rising trend in connection between financial markets mainly in Europe and a structural break in correlations in January 1999, which happen together with the introduction of Euro as a single currency. It is also noted that the relationships between Australasian grouping, Americas and Europe seem to be unmoved from the developments in Euro area. It is argued that the depreciation of the euro vs the US dollar immediately after the beginning of euro may be due to rise in the link between stock markets of EMS member nations which led investors to diversify their portfolios less on EU nations and more on the US leading capital movement from Europe to the US due to new portfolio weights adjusted to the changes in the relationship. Silvennoinen and Teräsvirta (2009) use smooth transition conditional correlation (STCC) model within the MGARCH framework to observe the properties of conditional correlations among DAX index in Germany, CAC40 index in France, FTSE index in UK and HSI index in Hong Kong with weekly data for the period from the first week of December 1990 to the last week of April 2006. It is established that the relationships between the stock market indices rise to higher points in the spring of 1999, CAC-DAX, CAC-FTSE and DAX-FTSE exceed 0.9, 0.85 and 0.8 respectively. They also show that the rising conditional correlation within stock markets in western nations are influenced by the intensity of instability (Charles, & Darné, 2009, p121) Since 1999, in related work, Aslanidis et al (2010) analyze the relationship structure between S&P500 and FTSE indices where they discover that the rising trend in conditional correlation reaches to 0.9 around February 2000 and although unpredictability plays an important part before 2000 it loses its importance after that time. China's two major securities markets, the Shanghai Securities Exchange and the Shenzhen Stock Exchange, were started on December 19, 1990 and July 3, 1991, respectively. The shares that were originally included on these security markets are known as A-shares and were only transacted by Chinese populace in terms of Renminbi. In 1992, another category of shares, B-shares, was introduced for foreign investors and although they were denominated in Renminbi, they were transacted in foreign currency; all transactions and dividends payment of B-shares are in US dollars in Shanghai and Hong Kong dollars in Shenzhen. The quantity of listed companies has rose very quickly from 53 to 894 since 1992 and by the end of 2010, Shanghai Stock Exchange had been listed as the 5th largest stock market in the globe by market capitalization, which stood at US$ 2.7 trillion (Huang & Yang, 2000, P57) China has started a number of structural changes and liberalization policies since 1999 with the introduction of securities law, which in 2001 allowed domestic investors to start trading B-shares. Following the opening of qualified overseas institutional investor programme which has reduced the restrictions on A-shares, eligible foreign traders started to trade A-shares in July 2003 and by May 2006, eligible domestic institutional traders were approved to trade in overseas developed stock markets. These two programmes were as a result of China’s commitment to free up its financial markets during its entrance to the World Trade organization (WTO) in December 2001. Besides, China also dedicated itself to list its large state-owned corporations on overseas stock markets and let overseas companies be listed on the stock markets in China; however, these two policy actions took place at the end of 2006. With these structural alterations, China seems to be committed to becoming one of the leading world economies and to swiftly integrate with other global economies (Yu, Fung & Tam, 2010, p2879). Following these reforms and economic assimilation of China with other nations of the world, a considerable rise in the correlation of Chinese stock markets with developed money markets is expected, experimental applications are not providing proof in favour of these prospects. Li (2007) applied BEKK specification to study the connection between China and the US stock markets for daily data from January, 2000 to August, 2005 and found no express instability spill over between the US and China stock markets (Gregoriou, 2009, p123). Moreover, Lin et al (2009) employs DCC-GARCH model to analyse dependence among China and global markets and does not find proof of a rising trend. Moon and Yu (2010) postulate that the poor findings of both papers in favour of a rising trend may be because of short samples excluding the time, which the impact of structural reforms and liberalization policies had been realised in the money markets of China. Moon and Yu (2010) do not find an growing trend in their paper analysing every day return rates of stock markets in China and in the United States from January, 1999 to June, 2007, but they identify a structural break at the end of 2005 and report symmetrical and asymmetrical unpredictability spill over effect from United States to China stock markets and symmetrical unpredictability spill over effect from China to United States since then (Johansson & Ljungwall, 2009, p844). Several empirical studies have studied long-term relations and short-term vibrant causal linkages between major developed markets and emerging Asian markets. Majority of these studies found out that financial integration in global markets have rose since the Asian financial crisis of 1997. Several scholars have used co-integration tests and Granger no-causality test to examine the subject of equity market assimilation with mainland China and also between the China and Hong Kong markets (Yao, Luo & Morgan, 2010, p390). Recently published studies expanded their evaluation of lead-lag and co-integration associations into the returns of the stock markets in the China region as well as their relationships with United States and Japan; Chan and Lo (2000) investigated lead-lag relationships between the returns of the 4 mainland markets in China and in Hong Kong and Taiwan markets. Using the stock indices every day returns up to 1997, they found that A-share markets in Shanghai and Shenzhen were strongly linked to each other but not with the other 5 stock markets, there is also proof of considerable lead-lag relationship between Hong Kong, Shanghai (B-share) and Taiwan, with Hong Kong as the most important market in stock returns. Huang et al (2000) discovered that no co-integration existed between United States, Japanese and market in the larger Chinese area. By applying the Granger causality test, they established that stock prices change in United states (rather than Japan) can be used to forecast those in Hong Kong and Taiwan markets, while price change in the Hong Kong stock market go in front the Taiwan market by 1 day. Similar to the findings by Chan and Lo (2000), Huang et al (2000) established that there is a considerable reaction link between the Shanghai and Shenzhen A-markets. Data from their co-integration tests in Groenewold et al (2004) is dependable with that of Huang et al (2000) who found co-integration between the 2 mainlands A-share index for the interlude before the predicament in Asia, which vanished after the predicament. They also found a big but relatively remote lead-lag link between the 2 mainland A-share markets; also, after the Asian predicament, there was proof that Hong Kong had a weak predicative strength from returns in the mainland. Although there are some differences between these researches, all research theorised that Chinese stock markets are still relatively remote within the larger China region despite the contributions they have made in showing the interdependencies and lead-lag relationships among the stock markets. However, it has several shortfalls To start with, Greoneword et al (2004) is an article that talks about post Asian financial crisis term up to early 2001. It can be said that according to the past 3 to 4 years post crises data is inadequate for testing co integration because the tested co integration can be temporary phenomenal and easily disappear . A relatively longer data is used for co integration test for the post crisis period and the utmost significance is that the nine year period used is adequate for examining the effects of the recent government policy amendments associated with the opening of the A and B share markets. Secondly, prior research concentrated on China;s A-shares, ignored B shares, and their interactions with the B shares. Research on B shares is important for us to put in mind a fundamental issue about china’s segmented A-B share regime (Graham, Kiviaho & Nikkinen, 2012, p37). Hardly have the past papers talked about the issue of the impact of the opening of the B market on the integration between A and B shares and also between the Chinese markets and the entire global markets (Yilmaz, 2010, p309). The occasion of the opening of the b share market can be more essential than the Asian financial crisis on the Chinese market, because the Chinese markets were not affected by the Asian crisis compared to the neighbouring countries as a result of inconvertibility of its currency (Singh, Kumar & Pandey, 2010, p59). Both shanghai A and B market indices are taken instead of combined two indices of shanghai and Shenzhen a share markets in to one portfolio index as in Greonewold et al (2004). It is beyond doubt that the two separate indices bring about more information than one artificially combined concerning the co integration and causality relations. This document also drops Shenzhen A and B share market indices for both markets as a result of their negligibility in capitalisation and much lesser liquidity in their each day trading. Thirdly, past investigation looked only on the short-term interaction by testing Granger causality on the first-difference VARs. They were only capable of making use of standard Granger F-test in the first difference framework. The absence of long-term equilibrium relationship between the markets examined made it difficult for them to run Granger no-causality test based on the vector error correction model (VECM) as they do not consider any incidence of long-term relationship in the multivariate system. Their investigation is only essential in getting short run temporal causality (Tiwari, Dar, Bhanja & Shah, 2013, p452). This document associates long-term co integration more rationally and more economically meaningful than the past articles. Finally, this investigation practices the use of monthly price index data rather than the daily data used in the past studies to get rid of the high level of daily price data. The diagnostic check clearly shows that all indices are diversified in these two periods. This shows that co integration and Granger non-causality test by use of VAR models based on monthly data are tougher than the ones based on each day prices (Awokuse, Chopra & Bessler, 2009, p551). The purpose of this to test the long-term causality and co integration between shanghai A and B markets and amid this markets and the Hong Kong, Taiwanese , USA and Japanese markets. It went through the markets over two essential periods that is before and after the Asian crisis of 1997 to 1198 and covered the period of opening of Chinese A and B markets. It is clear that co integrating relations have been merged amid the Shanghai A share market and other china broader market regions and between this markets and with those of the USA. Integration has occurred between the Hong Kong main market and the Shanghai main market excluding the B share long term market because the relationship in trade and direct foreign investment in general have greatly improved in the recent past (Mishra, 2010, p246). On top of the existence of the co integrating relationship amid the Shanghai A and other markets, substantial evidence derived from my causality test was found. Its noticed that not only has the Chinese share A market haven’t been influenced by Hong Kong h-share market but also put an impact on other markets such as the Taiwanese and Japanese markets because it opened to investors in 2002. This control can be observed by the recent stock plunge brought about by a sell-off in shanghai a-share market in February 2007 (Johansson, 2010, p303). It is evident that there is no proof to support that these two shanghai market have been co integrated. The A and B share markets are far from getting to the long-term integration and have still remained apart. Even though the Chinese A-share market has come up with their long term equilibrium with other markets, her Chinese A-share market continues to be independent from A-share and other markets; this is because the B-share market is open to the local retail investors. The reason behind the separation between the A and B-share market may be due to inadequate mainland institutional investors given the permission to invest in B-shares and that B-share markets have been gradually more marginalised as many foreign investors fled them after local investors got in to the market and skilled institutional investors were given the permit to invest in Chinese A-shares. An amalgamation of A and B markets became main concern in the government. A deeper look in to these issues could attract a reward (Chan & Lo, 2000, P53). As a chief action after china’s WTO succession, her QFII program introduced in 2001, opened china’s securities markets and also allowed overseas investors to take positions in those markets an purchase stakes in Chinese companies. This helped in sharing china’s phenomenon growth. QFII regulation is a development in china’s financial market and has given permit for relations between the Chinese and the worldwide markets as said in the confirmation of co integration relationship in the Chinese markets and other regional markets. In the mean time QFII’s generation of long term and stable capital, their focus on companies with strong fundamentals, financial transparency and good authority, could bring about the success of Chinese markets (Wu, 2009, p164). Although in the recent past the Chinese markets have gone through a hasty development and have a hope for a bright future, the still emerging markets (this is the separation between the Chinese markets and those that are isolated.) could bring a major dispute to the investors. Findings show that the investors could also have an advantage by investing in Chinese equity markets. If a comparison is taken between the matured markets such as the Hong Kong, USA, Japan and Taiwan we find that the potential spread in investing in Chinese markets may be a bit larger as a result of a poor linkage with international markets. According to this background b-share may offer a better diversification potential among the Chinese stock markets because this market may poorly integrated with the other markets References Aslanidis, N. & Osborn, D.R. & Sensier, M. (2010) Co-movements between US and UK stock prices: the role of time-varying conditional correlations. International Journal of Finance & Economics, 15(4), 366-380. Awokuse, T. O., Chopra, A., & Bessler, D. A. (2009). Structural change and international stock market interdependence: evidence from Asian emerging markets. Economic Modelling, 26(3), 549-559. Chan, B. & W. Lo, 2000, "Financial Market Integration in the Greater China Bloc: Evidence from Causality Investigation of Stock Returns," Asia Pacific Journal of Finance 3, 53-69. Charles, A., & Darné, O. (2009). The random walk hypothesis for Chinese stock markets: Evidence from variance ratio tests. Economic Systems, 33(2), 117-126. Di Giovanni, J., Levchenko, A. A., & Zhang, J. (2012). The Global Welfare Impact of China: Trade Integration and Technological Change (PDF Download). International Monetary Fund. Engle,R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Graham, M., Kiviaho, J., & Nikkinen, J. (2012). Integration of 22 emerging stock markets: A three-dimensional analysis. Global Finance Journal, 23(1), 34-47. Huang, B.-N. & Yang, C.-W (2000), "Financial Markets Integration and Segmentation under regional Economic Blocs: A Dynamic Conditional Correlation Approach", Advances in Pacific Basin Business, Economics, and Finance. Volume 4, JAI Press, Stamford, Conn. Johansson, A. C. (2010). China's financial market integration with the world. Journal of Chinese Economic and Business Studies, 8(3), 293-314. Johansson, A. C., & Ljungwall, C. (2009). Spillover effects among the Greater China stock markets. World Development, 37(4), 839-851. Li, H. (2007). International linkages of the Chinese stock exchanges: A multivariate GARCH analysis. Applied Financial Economics, 17 (4), 285-297. Lin, K.P. &Menkveld, A.J. & Yang, Z. (2009) Chinese and world equity markets: A review of the volatilities and correlations in the first fifteen years. China Economic Review, 20(1), 29–45 Mishra, R. K. (2010). Stock market integration and volatility spillover: India and its major Asian counterparts. Research in International Business and Finance, 24(2), 235-251. Moon, G. & Yu, W. (2010). Volatility Spillovers between the US and China Stock Markets: Structural Break Test with Symmetric and Asymmetric GARCH Approaches. Global Economic Review, 39(2)129-149 Silvennoinen, A. & Teräsvirta,T.(2005). Multivariate autoregressive conditional heteroskedasticity with smooth transitions in conditional correlations. Working Paper Series in Economics and Finance No. 577, SSE/EFI. Singh, P., Kumar, B., & Pandey, A. (2010). Price and volatility spillovers across North American, European and Asian stock markets. International Review of Financial Analysis, 19(1), 55-64. Tiwari, A. K., Dar, A. B., Bhanja, N., & Shah, A. (2013). Stock market integration in Asian countries: Evidence from wavelet multiple correlations. Journal of Economic Integration, 441-456. Yao, S., Luo, D., & Morgan, S. (2010). Bank share prices and stock market integration in Greater China. Journal of the Asia Pacific economy, 15(4), 388-395. Yilmaz, K. (2010). Return and volatility spillovers among the East Asian equity markets. Journal of Asian Economics, 21(3), 304-313. Yu, I. W., Fung, K. P., & Tam, C. S. (2010). Assessing financial market integration in Asia–equity markets. Journal of Banking & Finance, 34(12), 2874-2885. Wu, Z. (2009). Financial sector reform and the international integration of China. London: Routledge. Gregoriou, G. N. (2009). Stock market volatility. Boca Raton: CRC Press. Motamen-Samadian, S. (2006). Global stock markets and portfolio management. Basingstoke [England: Palgrave Macmillan. Read More