suggest price volatility has significant implications concerning information linkages between markets. In light of the literature, we analyze the information flow in the
four markets using a multivariate version of the exponential generalized autoregres- sive conditional heteroscedasticity in mean EGARCH-M model along with the
generalized error distribution GED.
This study is important to the finance literature for the following reasons:
It is a timely topic because of the rapid growth of the red chips and H shares in recent years. The Chinese government is continuing its effort to privatize its
state-owned enterprises in order to raise capital to revitalize the operation of these enterprises.
It is important to study the return and return volatility of China-backed securities because almost one in every six companies listed on the SEHK
recently is controlled by a PRC interest. A new China security is listed almost every week on the SEHK. The growth of China-affiliated corporations is
reflected in a 109.6 increase in 1996 of the Credit Lyonnais Securities Asia Red Chip Index. The combined value of red chips and H shares on the SEHK was
approaching HK232 billion i.e. US30 billion in June 1997 Leung and Surry, 1997.
Past studies in China equities have focused on the return behavior of A and B shares listed on the Shanghai and Shenzhen Stock Exchanges. We believe that
insufficient research effort has been devoted to the return behavior and the relationship among H shares, red chips, Shanghai and Shenzhen equities. Our
study shows that stock returns of these Chinese stocks have fatter tails relative to the normal distribution. We have carried out our analysis using the
EGARCH-M model along with GED, which allows for variable kurtosis in the data.
Both types of shares H shares and red chips might be influenced by some common factors like political risk and government influence. Information
might have been transmitted between the issuers of red chips and the issuers of H shares. The return behavior of these two types of shares and the
return volatility between the two markets might be related. We, therefore examine the spillover effects among the H share, red-chip, Shanghai and
Shenzhen security markets. An examination of the linkages across the four markets may shed light on how investors perceive the information flow across
markets.
The paper is organized as follows. The next section presents the background to our research. The third section describes the research design and methodology.
Empirical results of this study are discussed in the fourth section. The final section gives some concluding remarks.
2. Background to the research
A brief history of China’s securities markets is described and selected literature on EGARCH models is reviewed in this section.
2
.
1
. History of China
’
s securities markets There are two major stock exchanges in China, namely, the Shanghai Stock
Exchange SHSE and the Shenzhen Stock Exchange SZSE. Both offer Class A shares A shares and Class B shares B shares of common stocks issued by
Chinese domiciled companies. B share and H share listings all carry the same rights as the A share listings. For example, they receive the same dividends although in
different currencies. For all intents, B and H shares are identical to A shares except for who can buy them; A shares are restricted to PRC citizens while B and H shares
are restricted to non-PRC citizens.
The SHSE formerly known as the Shanghai Securities Exchange was founded on November 26, 1990 and began to operate in December of the same year. Four
major classes of securities are listed on the SHSE as follows: equities A and B shares, debts government, corporate and financial debts, funds including other
trust beneficiary receipts, and other financial instruments. The SZSE was estab- lished on December 1, 1990. Five major types of securities are traded on the SZSE
as follows: stocks A and B shares, bonds corporate, convertible and treasury bonds, funds, warrantsrights and treasury bond repurchases. As of December
1998, there are 425 A shares and 52 B shares listed on the SHSE while there are 400 A shares and 54 B shares listed on the SZSE. At the same time, 41
China-domiciled companies have H shares listings in Hong Kong and there are 47 red chips listed on the SEHK Hang Seng Index Service Limited HSI web:
www.hsiservices.com.
Bailey 1994 and Johnson et al. 1994 provide preliminary empirical evidence on the financial characteristics of China’s equity markets. Bailey 1994 studied the
early evolutionary stage of both the Shanghai and Shenzhen stock markets and found that B-share returns displayed little or no correlation with international
equity index returns. The results of Bailey’s study imply that B shares can be considered good diversification investments for foreign investors and confirmed the
effectiveness of market segmentation in the A and B share markets. Poon et al. 1998 have also found that Chinese capital markets appear to be segmented.
Similarly, Johnson et al. 1994 examine the risks and returns on the SZSE over the period September 1, 1991 to September 5, 1993 and found that all equities listed on
the SZSE have extreme volatility.
Song et al. 1998 have recently investigated the relationship between return and volatility on the SHSE and SZSE in China during the period May 21, 1992 to
February 2, 1996 using GARCH models. The results of their study document significant volatility transmission between the two stock exchanges and the Chinese
stock. Su and Fleisher 1998 have also studied the return and risk behavior in Chinese stock markets in terms of local and global information variables that could
predict the excess returns of the Chinese stock markets. Their study indicates that the volatility of Chinese stock markets is time-varying and mildly persistent, also
that the market intervention policies of the Chinese government have influenced stock market volatility.
2
.
2
. Selected literature on EGARCH models The generalized autoregressive conditional heteroscedasticity GARCH models
have been widely applied in different time series studies Cheung and Ng, 1992a; Antoniou and Holmes, 1995; Chan and Wu, 1995; Tse and Booth, 1996; Liu et al.,
1996; Song et al., 1998. The GARCH models incorporate time-varying returns and time-varying volatility which can deal with the problem of autocorrelation and
heteroscedasticity in the time series data.
The GARCH model does not, however, address the issue of asymmetric volatility effects on stock returns.
3
It imposes a non-negativity constraint on the parameters of past conditional variance d and past volatility shock g in the volatility
equation such that the sum d
+
g must be B 1 for the volatility process to be
covariance stationary.
4
The Nelson 1991 EGARCH model relaxes the restrictions of the GARCH model and incorporates the asymmetric volatility effect in the
volatility equation. There are numerous papers using the EGARCH model to examine the behavior of stock returns of national stock markets, such as Cheung
and Ng 1992b, Koutmos et al. 1993, Episcopos 1996 and Booth et al. 1997. They all find that the EGARCH model can adequately capture the stochastic
behavior of return and volatility in stock markets.
3. Research design and methodology
