This paper investigates market effects associated with China Security Index 300 (CSI 300) reconstitutions with sample period from April 2005 to Feb 2008. Several findings are listed as followings: Firstly, cumulative abnormal returns for added stocks increase slightly after announcements, while the returns for removed stocks decrease significantly though reverse immediately after index reconstitutions. Considering the whole event period, prices for deletions do not fall dramatically; it’s consistent with asymmetric change of investors’ awareness proposed by H Chen et al (2004). Secondly, both the results of cumulative abnormal returns and volume ratios do not provide evidence to support price pressure hypothesis or index membership hypothesis. We attribute those results to few funds tracking stock indices exactly with the same components and weights as which in the underlying indices in emerging markets, i.e., enhanced index funds are more familiar. Thirdly, the percentage of the additions’ (or deletions’) shares held by funds is not affected obviously by CSI 300 reconstitutions. Finally, we examine index change effects due to IPO that frequently occur in emerging markets, and find that additions witness a full reversal after the first trading day.

By combining (i) the economic theory of rational expectation bubbles, (ii) behavioral finance on imitation and herding of investors and traders and (iii) the mathematical and statistical physics of bifurcations and phase transitions, the logperiodic power law (LPPL) model has been developed as a flexible tool to detect bubbles. The LPPL model considers the faster-than-exponential (power law with finite-time singularity) increase in asset prices decorated by accelerating oscillations as the main diagnostic of bubbles. It embodies a positive feedback loop of higher return anticipations competing with negative feedback spirals of crash expectations. We use the LPPL model in one of its incarnations to analyze two bubbles and subsequent market crashes in two important indexes in the Chinese stock markets between May 2005 and July 2009. Both the Shanghai Stock Exchange Composite index (US ticker symbol SSEC) and Shenzhen Stock Exchange Component index (SZSC) exhibited such behavior in two distinct time periods: 1) from mid-2005, bursting in October 2007 and 2) from November 2008, bursting in the beginning of August 2009. We successfully predicted time windows for both crashes in advance [24, 1] with the same methods used to successfully predict the peak in mid-2006 of the US housing bubble [37] and the peak in July 2008 of the global oil bubble [26]. The more recent bubble in the Chinese indexes was detected and its end or change of regime was predicted independently by two groups with similar results, showing that the model has been well-documented and can be replicated by industrial practitioners. Here we present more detailed analysis of the individual Chinese index predictions and of the methods used to make and test them. We complement the detection of log-periodic behavior with Lomb spectral analysis of detrended residuals and (H, q)-derivative of logarithmic indexes for both bubbles. We perform unit-root tests on the residuals from the log-periodic power law model to confirm the Ornstein-Uhlenbeck property of bounded residuals, in agreement with the consistent model of ‘explosive’ financial bubbles [16].

In the last decade hundreds of companies from emerging markets have listed and issued their shares on American and European stock markets. Brazil, Russia, India, and China have been the main origins of issuers, and stock exchanges in the US, UK, and Luxembourg the main destinations involved in the process. These four home and three host markets are the empirical focus of our paper. We present an economic geography perspective on foreign listing, grounded in the geography of finance and the world city network approaches, emphasising the sub-national origins of foreign listed firms, the role of intermediaries, and competition for foreign listings. Our analysis, based on comprehensive up-to-date datasets on foreign listings and foreign equity issues, shows that issuers listing their shares abroad are predominantly large firms, coming from relatively high-growth, internationally oriented sectors, and headquartered overwhelmingly in the leading economic centres of their home countries. Key intermediaries in the foreign listing process are the global investment banks, operating out of the very same centres where the cross-listing firms and the host stock exchanges are located. Competition between host stock markets is affected significantly by the direct and indirect costs of foreign listing, including disclosure and corporate governance requirements. Both host markets and intermediaries exhibit a significant degree of specialisation in terms of the size, sector, and geographical origin of the issuers they serve. The market for foreign listing differs significantly between the BRIC countries, with the Chinese market offering the greatest potential, but facing considerable uncertainty.

This paper focuses on evidence from stock markets as it investigates the spillovers from the United States to mainland China and Hong Kong SAR during the subprime crisis. Using both univariate and multivariate GARCH models, this paper finds that China's stock market is not immune to the financial crisis, as evidenced by the price and volatility spillovers from the United States. In addition, HK's equity returns have exhibited more significant price and volatility spillovers from the United States than China's returns, and past volatility shocks in the United States have a more persistent effect on future volatility in HK than in China, reflecting HK's role as an international financial center. Moreover, the impact of the volatility from the United States on China's stock markets has been more persistent than that from HK, due mainly to the United States as the origin of the subprime crisis. Finally, as expected, the conditional correlation between China and HK has outweighed their conditional correlations with the United States, echoing increasing financial integration between China and HK.

There are many similarities between the US, the UK and the Chinese housing markets, including the movements of interest rates and house prices. Some Chinese banks, especially the Bank of China, have been exposed to the US mortgage securitization market. These have triggered a serious concern as to whether the US credit crunch and housing market crisis may be replicated in China. This paper shows that there are some significant differences between China and the West, especially the US and the UK. Compared with the US and other western industrialized economies, the booming house market in China has been supported by fast economic growth, rapid urbanization and high domestic savings. In addition, Chinese banks are less exposed to mortgage defaults than their western counterparts because house buyers are mainly urban and high income residents who are required to have high down payments. These Sino-Western economic and social differences suggest that the US credit crunch and housing market crisis may have some negative impacts on Chinese commercial banks and the overall economy but are unlikely to cause a similar financial and housing crisis in China despite the current struggling Chinese stock markets and a slowdown of house price growth.

The expected equity risk premium is a key input of many asset prcing models in finance. There exist a number of methods to estimate the risk premium. It is also well documented that the risk premium is time-varying. This paper briefly reviews two different approaches. More specifically, the historical average and relative estimation are taken into closer examination. The first approach is applied to estimate equity risk premium for stock markets in Great China when the stock markets were recovering from the bottom. Then the relative estimation approach is also adopted to empirical data to justify the findings in the first one, which takes into consideration the lower required rate of return for Chinese investors due to lack of investment opportunities. After making these adjustments, we find that risk premium in mainland China is close to risk premium for Hong Kong and Taiwan markets. All of those markets have higher risk premium compared to US market. The risk premium for Shanghai and Shenzhen market are about 8% and 10% respectively. For Hong Kong and Taiwan these numbers become 8% and 9%, where the long-term forward-looking risk premium for US market is about 4%.

The paper examines the price impact of mutual funds in the Chinese equity market from 2000 to 2007. We find there is strong positive correlation between stock returns and mutual fund holding and trading, and the price impact is more significant in mutual-fund buying than mutual-fund selling. Our findings support the hypothesis that the price impact is due to the information advantage of mutual funds.

Recent theoretical studies (Aggarwal and Wu,2006; Mei,Wu and Zhou,2004) show that trade-based stock price manipulation is a possible source of the momentum effect. This paper proposes three sets of testable hypotheses and provides empirical evidence for a manipulation-based explanation of momentum.Using weekly data on 14 CITIC industries in the Shanghai A-share market from 1997 to 2006, our analysis of industry momentum shows that cumulative returns first increase then decrease across holding periods, and the returns monotonically decrease across formation periods. This return pattern is consistent with a so-called”pump and dump”scheme,where momentum is created by manipulators and chased by speculators. We attribute the source of momentum to the positive own-autocorrelation, which dominates the cross-autocorrelation effect of industry returns. We also find that momentum profits are higher in the bull than in bear market, and most of the profits come from the gains of winning industries rather than the losses of losing industries. These empirical results,when related to some well-documented behavioral biases of Chinese speculators,tell us a possible stock-market manipulation story of momentum.

This paper investigates what drives the price disparity to vary in the “twin” shares (A shares traded largely by domestic investors while B- and H- shares traded mainly by foreign investors) in China. Extending the variance decomposition framework of Vuolteenaho (2002), we decompose the unexpected price disparity into two terms: difference in expected return news and difference in cash flow news. Our results show that difference in expected return news overwhelmingly dominates difference in cash flow news in driving the variation of the price disparity. This suggests that to a large extent, market or macro news, rather than firms’ specific news, moves the price disparity of the twin shares.

This paper studies the optimal scale and asset allocation of Sovereign Wealth Fund (SWF), taking China’s SWF as an example. We use the AR (1) process to simulate the future foreign exchange earnings of China and generate three patterns of the future earnings. With these three scenarios and based on Deaton’s precautionary saving model, we find that the optimal scale and asset allocation of China’s SWF mainly depend on the expected trend and fluctuation of the future foreign exchange earnings and expected yields that SWF can get. When foreign exchange earnings shows an upward trend, the scale of SWF should not be expanded even the expected investment yield is very high, and ratio of risky assets should be kept stable and high. When foreign exchange earnings is stabilized as its growth rate slows down, the scale of SWF has the positive correlation with the degree of earnings fluctuation and expected yield of investment, and also ratio of risky assets is generally lower. When foreign exchange earnings decrease, the scale of SWF should be expanded even the expected investment yield is not so high, and the ratio of risky assets is dependent on the characteristics of expected investment yields. We also conclude that investment policy of China’s SWF should follow Temasek’s investment model, under the current trend of China’s foreign exchange trend, and strive for high yield investment chances.