Long Window Tests of China’s Stock Market Efficiency in Different Sectors around the Disclosure of A

Abstract: 10 stock sectors are selected in Shanghai and Shenzhen stock market’s as samples. By event study， the change of stock’s cumulative abnormal return rate around the data of annual report disclosure was analyzed among the year 2004-2008. The market reaction pattern of such kind of news was summarized in order to test the efficiency of China’s stock market and its trend before and after the comprehensive completion of the Share-trading Reform and the implementation of new Accounting Standards. The conclusion is that Chinese stock markets response more accurately to ROE and EPS; its efficiency continued to decline in 2005 and 2006， but there was a gradual increase in 2007 and in 2008; and in general the capital market do not reach the semi-strong efficiency， but the machinery industry and biopharmaceutical industry have done.

Key words: EMH; Semi- strong Efficiency; Information Disclosure

doi : 10 . 3969 / j . issn . 1673 - 0194 . 2009 . 21 . 030

CLC number:F830Article character:AActicle ID:1673 - 0194(2009)21 - 0095 - 04

1Introduction

A unique characteristic of the Chinese stock markets (the Shanghai and Shenzhen exchanges) is the segmentation between non-tradable stock and tradable community， and these two types of stock formed a “different shares of different prices to different rights”market system and structure [1]. The share-trading reform has been the most significant reform of the system since the establishment of China’s securities markets.

The share-trading reform， which started in 2005 and finished in 2007， resolved these problems in Chinese stock market. All shareholders of the same company would have the same right， including major shareholders and tradable-share shareholders. An interesting issue that arises from this regulatory change concerns the efficiency of the markets..

The main objective of this paper is to investigate the change and trend of Chinese capital market efficiency before and after the share-trading reform， which is from 2004 to 2008.

2A Brief Review of the Literature

The efficient market hypothesis states that markets impound new information quickly and without bias into security prices， beginning with Fama[2] . There are a number of studies researching the efficiency of Chinese stock market. Qiuyigan[3] had found that 52% articles，published in Chinese major magazines between 1993 to 2001， thought that China’s stock market reached or came close to the weak efficiency， while 40% not yet reaching and others 8%.

3Data and Preliminary Statistics

This paper adopts event-study method， and takes disclosure of annual report as every company’s event， which is the information the stock price responds to. By investigating the extent and direction of stock price’s change around the annual report disclosure date， this paper tests the effectiveness that the share-trading reform brings to Chinese securities market efficiency. The idea of event study method is that if a capital market reaches semi-strong efficiency， the cumulative abnormal rate of return no longer change after public disclosure of information (the annual report).

3.1Financial information

This paper selects three financial indexes as the evidence of grouping， and these are return on equity (ROE)， earnings per share (EPS) and net operating cash flow per share (NOCFPS). According to each financial index， every industry is divided into two groups: good-news group and bad-news group.

3.2Subsamples of companies

This paper chooses 10 industries from Shanghai and Shenzhen stock markets， and does overall research into each industry.

3.3The time window of event study

In this paper， according to the disclosure date of annual financial report， the estimate-period window contains 70 days， including 60 days forward and 10 days backward. Considering that the annual report may be leaked outside before， and in the light of past experience in similar studies， this paper select annual report public disclosure date as the 0 day， 10 days before the 0 day and 10 days after it as the event window. The time window of event study is as follows:

4Research and Analysis

4.1Cumulative abnormal return rate (AR)

On the basis of Capital Asset Pricing Model， this paper calculates every stock’s βcoefficient with the data of estimate-period window. Rather， the β is get by fitting the estimate-period window data through 1，2，3，4 times and pass the 0.05 test of significance. With every stock’s at least the four regression equations， its average expected return rate is available. The abnormal return rate is the difference of actual return rate and expected return rate.

4.1.1Calculating the daily actual return rate (Ri，t)

Ri，t =t [-60，-11]

Ri，t is the return rate of Company i at the date of t， where Pi，t is the Company I’s stock price at the date of t.

4.1.2Calculating the daily stock market return rate (Rt)

Rt =t [-60，-11]

Rt is the return rate of the stock market at the date of t， where It is the market index at the date of t.

4.1.3Calculating the daily expected return rate (R’i，t)

R’i，t = αi，n +(βi，n× Rnt ) + εni，t

t [-60，-11]，n {1，2，3，4｝

R’i，t is the expected return rate of Company i at the date of t， where αi，n and are βi，nthe results of Company i by the n times fitting with the data between [-60，-11].

4.1.4Calculating the daily abnormal return rate (ARi，t)

ARi，t =

t [-10，+10]，n {1，2，3，4｝，q {1，2，3，4｝

ARi，t is the daily abnormal return rate of Company i at the date of t， where q is the times that the regression equations pass 0.05 significance test.

4.1.5Calculating the average daily abnormal return rate (ARt)

ARt = ARi，t t [-10，+10]，

ARt is the average daily abnormal return rate of a industry’s good-news group or bad-news group at the date of t， where N is the number of companies in good-news group or bad-news group.

4.1.6Calculating the cumulative abnormal return rate (CARt)

CARt =AR(-10， t) t [-10，+10]，

CARt is the cumulative abnormal return rate a industry’s good-news group or bad-news group from data -10 to date t.

4.1.7Significance test

Doing the T significance test to the cumulative abnormal return rate of each industry’s good-news and bad-news， if passing the test， the result is accepted.

4.1.8Drawing the cumulative abnormal return rate

In order to see the trend of the cumulative abnormal return rate intuitively， this passage draws it around the annual financial report disclosure data.

4.1.9Design the evaluation standard.

To compare the trend of the cumulative abnormal return rate of each industry’s good-news group and bad-news group， this paper designs an evaluation standard to give each draw a number. The standard is as follows:

4.3Analysis

4.3.1Comparison between the three financial index

As noted above， every industry is divided into good-news group and bad-news group according to the three financial indexes respectively. The number of ‘Total’ in Table 2 shows all industries’ degree of deviation from the standard semi-strong capital market efficiency. It is obvious that the capital market responses more accurately to the grouping by ROE and by EPS.

4.3.2The trend of capital market efficiency's change in the 5 years

The number of ‘Sum’ in Table 2 shows the change of the degree of deviation from the standard semi-strong capital market efficiency according to the three financial indexes respectively. It can clearly be seen that the market efficiency continued to decline in 2005 and 2006， but there was a gradual increase in 2007 and in 2008. The reasons are as follows:

(1) The share-trading reform led to a speculative bull market atmosphere in 2005 and 2006， which brought a lot of stock market bubble. Therefore， the market efficiency declined in 2005 and 2006.

(2) In 2007， there were two historic things happened: the comprehensive completion of share-trading reform and the implementation of new Accounting Standards， which made the listed companies’accounting treatment more standardized and the disclosure of information more fair and accurate. These two things stabilized China’s capital market， and the efficiency increased.

4.3.3Comparison between the 10 industries

The number of each industry grouped by ROE and EPS in Table 2 shows only the capital markets of BIOLOGY and MACHINE have reached semi-strong efficiency. The reasons are as follows:

(1) Compared with other industries， these two sectors contain a larger number of listed companies， and the average time of listing is significantly longer than other industries. Namely， they have gone through a long process of development. The time of listing is as follows:

(2) Machinery industry is an important equipment industry to large-scale modernization of any nation; therefore， China introduced a series of industrial policy measures and laws to guide and support the development of machinery industry. To deepen the reform of state-owned enterprises， China encourages private enterprises to participate in merger and acquisition of machinery industry， which lead to that there are 8 Chinese companies in the biggest 50 machinery companies in the world.

(3) China’s total of more than 6300 pharmaceutical companies， ranking second in the world. Chinese biopharmaceutical companies have been doing limit invest in research and development of new medicines; most companies imitate foreign products， and the same production is produced by many enterprises， which results in the phenomenon of high competition in this industry.

5Conclusion

Chinese stock markets response more accurately to ROE and EPS.

Chinese stock markets’efficiency continued to decline in 2005 and 2006， but there was a gradual increase in 2007 and in 2008.

Chinese stock markets in general do not reach the semi-strong efficiency， but the machinery industry and bio-pharmaceutical industry develop rapidly，have reached.

References

[1] Suzanne G MFifield， Juliana Jetty. Further Evidence on the Efficiency of the Chinese Stock Markets: A Note[J] . Research in International Business and Finance， 2008， 22(3): 351-361

[2] E F Fama. Efficient Capital Markets: A Review of Theory and Empirical Work[J] . Journal of Finance， 1970， 25(2): 383-417.

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