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2013. Vol.2, No.1, 32-35
Published Online February 2013 in SciRes
Copyright © 2013 SciRes.
An Empirical Study on the Overreaction of
Shanghai Stock Market
Hu Lin1*, Sha Zi-Jun1, Liu Xiu-Yi2, Chen Wen-Jun2
1University of Toyama, Toyama, Japan
2Central South University of Forestry and Technology, Changsha, China
Received November 12th, 2012; revised December 12th, 2012; accepted December 19th, 2012
Based on both Chinese and non-Chinese research results, this study uses the research methods of De
Bondt and Thaler, selects the trading data from January 2007 to June 2011 in stock market in Shanghai,
and tests whether there has been overreaction in the stock market. The empirical result shows more ab-
normal return of loser portfolio than that of winner portfolio, which indicates over-reaction of the stock
market. Moreover, the term is longer and the reversion degree of return is weaker. The result means that
the risk difference between winner and loser portfolios does not adequately explain the over-reaction. The
main reason for the overreaction we think is the institutional background and other constraining condi-
tions of the stock market in the Chinese mainland.
Keywords: Over-Reaction; Cumulative Abnormal Return; Risk Premium
Overreaction on stock market (OSM henceforth) is a major
event caused by dramatic change of stock price; it exceeds the
expected theoretical level, and then returns to its normal price
by way of reverse correction (Liu Li, 1999). De Bondt and
Richard are the forerunners in the study of OSM. According to
their research, there was reversion on stock return in the long
term because of investors’ irrational behavior (De Bondt &
Thaler, 1985). Lehmann (1990) identified the factors that re-
versed the market in a short time interval, but short-term prof-
itability can hardly be identified with overreaction. Rather, it is
probably a result of pressures of price in short-term or lacking
of liquidity (Lehmann, 1990).
From the late 1990s, Chinese scholars have studied the OSM
in China. Through analyzing the stock market in Shanghai,
Zhang Renji 张人骥, Zhu Pingfang 朱平方, and Wang Huai-
fang 王怀芳 (1998) identified a falling trend on winner port-
folio, but found no rising trend on loser portfolio. In other
words, they found no OSM in Shanghai. Likewise, in his study
of the Shenzhen stock market, Zhu Shaoxing 朱少醒 (2000)
found no OSM in China. Song Xianzhong 宋献中 and Tang
Sheng 汤胜 (2006) conducted empirical study on the topic of
overreaction and scale effect on the corporations listed in
A-share market in Shanghai. They found that the return of
winner portfolio higher in formation period is lower than that of
loser portfolio in the test period. Moreover, they found both the
existence of over-reaction, and the significant role played
therein by size of the companies, specifically, they found that
the return of small-scale winner portfolio was higher than that
of the large-scale loser portfolio. These results indicate that, for
the return of the listed corporations, the influence of scale effect
is higher than that of over-reaction.
Where OSM is concerned, these studies profoundly disagree.
But they seem inclined to accept reversion of price in the long
term. Regarding this phenomenon, no consensus has been
reached among Chinese scholars yet (Song Xianzhong & Tang
Sample Selection and Test Methods
This paper extracted randomly 100 stocks from the Shanghai
stock market, The timeframe under examination is set between
January 2007 and June 2011, and the data examined are the
daily closing prices in that period. Considering stock dividends
and right offerings, calculated for each stock is the return by the
price after excluded right. If a stock was in suspension, it meant
that the stock’s closing price remained the same. Based on the
sequence of the level of cumulative abnormal returns in forma-
tion period, the 20 top stocks constituted the winner portfolio,
and the loser portfolio was composed of the 20 lowest stocks.
The Sorting Methods in Formation Period
The formation period in the paper is divided into 3 months, 6
months, 12 months and 24 months and the corresponding test
period is divided into 1 month, 3 months, 6 months, and 12
months. Let the reference time be T0, the length of formation
period be T1, and the length of test period be T2, then (T0 − T1,
T1) is the formation period, and (T0, T0 + T2) is the test period.
If reference time were constantly, it could also get more com-
bination of formation period and test period. The formations
period and test period of these combinations do not overlap, but
the current test period and the next formation period may over-
The calculations of combined abnormal returns use market-
ing adjustment, as it was used by the Bolt, Nazareth and Zeluo.
The formula is i,ki,k m,k
,; . i1, ,n
Ri,k is yield of stock I in k month.
Rm,k is yield of market in k month.
Cumulative abnormal return of stock I in formation period is
HU L. ET AL.
The Test Methods in Test Period
Based on the sequence of the level of cumulative abnormal
returns in formation period, the 20 top stocks made the winner
portfolio and the 20 lowest stocks made the loser portfolio, then
the calculated average abnormal monthly returns of each com-
CAR AR (3)
CAR AR (4)
ARw,k is the average abnormal monthly returns of winner
portfolio, ARl,k is the average abnormal monthly returns of
loser portfolio, CARw,k is the average cumulative abnormal
monthly returns of winner portfolio, and CARl,k is the average
cumulative abnormal monthly returns of loser portfolio.
When calculating cumulative excess returns of each month’s
winner portfolio and loser portfolio in the test period, at a cer-
tain test level, if (CARl,k − CARw,k) is significantly above zero,
then there is over-reaction; If (CARl,k − CARw,k) is significantly
below zero, then there is inadequate response.
In the test period, once the difference (CARl,k − CARw,k) in
cumulative abnormal monthly returns between the loser and
winner portfolios significantly deviates from zero, we could get
the statistic T of t, and test significance of statistics at the 10%
level. Statistic T is as follows:
1,kw ,k12 12
CAR CARnn nn2
CARw,i,k is cumulative average abnormal returns of the stock
of i of winner portfolio in the k month, CARl,i,k is cumulative
average abnormal returns of the stock of i of loser portfolio in
the k month, is a separate variance of CARw,k and
According to the above methods and design, we get the de-
scriptive results from Table 1.
As shown in Table 1, when the formation period was 12
months or 24 months, and test period was one month, the aver-
age cumulative abnormal return of winner portfolio got slightly
higher than that of loser portfolio, which means that the per-
formance of winner portfolio of higher abnormal returns in
Average cumulative excess return of the winner and loser portfolios.
Test period CAR
One months Three months Six months Twelve months
Winner portfolio W −0.01091 −0.01118 −0.00393 −0.00229
Loser portfolio L 0.002313 0.001551 0.002912 0.003151
L-W 0.013233 0.012731 0.006842 0.005441
Value of t 1.5461 1.4192 1.2447 1.3853
Winner portfolio W −0.014 −0.00156 −0.00653 −0.00546
Loser portfolio L 0.016834 0.010044 0.012119 0.004968
L-W 0.030834 0.011604 0.018649 0.010428
Value of t 2.1109 1.5621 1.8849 1.2931
Winner portfolio W 0.006562 −0.00335 −0.01034 −0.00404
Loser portfolio L 0.00423 0.009084 0.016559 0.001974
L-W −0.002332 0.012434 0.026899 0.006014
Value of t −0.3019 1.2419 1.9973 1.3318
Winner portfolio W 0.005093 −0.00194 −0.01582 0.000971
Loser portfolio L 0.003396 0.008004 0.01385 0.002078
L-W −0.001697 0.009944 0.02967 0.001107
Value of t −0.6261 1.1173 1.7522 1.4208
ote: The level of statistical test is 5%, and threshold of t is 1.2856.
Copyright © 2013 SciRes. 33
HU L. ET AL.
formation period is significantly better than that of the loser
portfolio in the test period, and there was no over-reaction this
time. But other times, the average cumulative abnormal returns
of loser portfolio were higher than that of winner portfolio,
when the formation and test periods were six months and one
month respectively, the difference of the average cumulative
abnormal monthly return between the loser and winner portfo-
lios reached a maximum of 3.08%. In the significance test, the
difference between the winner and loser portfolios in abnormal
return reached the level of 10% in the test period, which sig-
nificantly deviates from zero. As for the degree of over-reaction,
no increase of its effect was observed as time went on from
Figures 1 and 2. Obviously, one who bought the ill-performed
loser portfolio at an early stage and sold the well-performed
winner portfolio could get significant arbitrage profit.
The Test of Risk Effect
The present study hypothesizes a “risk effect” of OSM. The
hypothesis takes OSM to be a reasonable reflection of the
changes in the risk, which is to be understood as a series of
negative abnormal returns capable of causing the fluctuations of
the value β of stock, and their resultant fluctuations of the ex-
pected return. Financial leverage is changing along with the
changes of securities prices. So the negative correlation be-
tween risk and market value is reasonable. If the risk is taken
into consideration, there may not be over-reaction. Using data
of the Belgian stock market, Vermaelen and Verstringe reex-
amined over-reaction and showed that over-reaction was a rea-
sonable reflection of the changes in the risk. Chan (1988) found
that because of the changing risk, there is weak reversion effect
in the abnormal returns (Chan, 1988), But studies previous to
Chan’s showed high abnormal returns, In order to prove the
high abnormal return on stock market at reversion effect in the
long-term, the present paper uses the following model of Chan
(1988) to test changing of the risk.
CAR chart of formation period of 6 months.
CAR chart of formation period of 12 months.
a,k 1,k w,k
Ra,k is the difference of the abnormal return between winner
and loser portfolios in period of k.
Rf,k is the risk-free interest rate in period of k which uses
bank deposit rates from the current 3 months.
Rm,k is the average return rate of the stock market in the same
Rl,k is the return rate of the loser portfolio in period of k.
Rw,k is the return rate of the winner portfolio in period of k.
Α is the abnormal return, and β is the risk factor.
Based on the data on formation period and test periods of 3
months and 6 months separately, could obtain the following
results could be obtained.
We can tell from Table 2, that, firstly α value at 5% level
was significant, secondly, the β value in the formation period of
six months and test period of six months was significant, and,
thirdly, the others were insignificant. This indicates that the
changing risk premium in reversion strategy does not ade-
quately explain the abnormal return. This conclusion supports
the finding of De Bondt and Thaler (1985). In the short term,
the arbitrage portfolio they created bought stocks of the loser
portfolio and sold stocks of winner portfolio, then, least square
method was used in a regression analysis to examine the dif-
ference of abnormal return between loser portfolio and winner
portfolio. And the conclusions showed β value of loser portfo-
lio in test period is 0.220, which is larger than winner portfolio;
the differences in risk therefore do not explain the arbitrage
According to the empirical analysis from January 2007 to
June 2011 on stock market in Shanghai, the conclusions are as
Firstly, there was OSM in China. And the overreaction was
not obvious except in the cases where the formation period was
twelve or twenty-four months while their corresponding test
periods were both one month. In the other periods there were
more obvious overreactions, as a general rule, the gradual
weakening of overreaction was accompanied with the prolong-
ing of test period. For example, the difference value of Cumu-
lative Abnormal Return of winners and losers was 0.0308 when
the formation period was six months and test period was one
month, but while the test period was twelve months, this value
Regression results of arbitrage portfolio of stock market in Shanghai.
Reversion strategy α β R2
X = 3, J = 3 Value of t0.021
X = 3, J = 6 Value of t0.029
X = 6, J = 3 Value of t0.131
X = 6, J = 6 Value of t0.037
Copyright © 2013 SciRes.
HU L. ET AL.
was only 0.0104.
Secondly, to prove that there was high abnormal return on
stock market at reversion effect in the long-term, the model of
Chan (1988) is used in our explanation of OSM to test the
changing of the risk. The results showed that the changing risk
premium with reversion effect did not well explain abnormal
The OSM in Shanghai can be partially explained by relevant
theories of behavioral finance, such as “conservative”, “charac-
terization of inspiration thinking”, “over-confidence”, “biased
self-attribution”, and other investment own cognitive biases.
However, we believed that except for these, we should take into
consideration the specific institutional background and market
structure of stock market in the Chinese mainland. Currently,
retail is what dominates the structure of stock market in the
Chinese mainland, where retail investors’ information is un-
available to institutional investors, hence the information
asymmetry between institutional investors and retail investors.
Under these constraints, investors in the Chinese mainland
often lack a philosophy of long-term investment, resulting in
large fluctuations in stock prices from which many investors
can make profit (Huang Jun & Chen Ping, 2009). In the entire
stock market, standardization is lacking in many places. False
information, fraud in financial reports, and manipulation often
occurred in listed corporations. Bankers’ manipulation may
cause a stock to soar in a short term or even a few years, but,
when these actions are exposed to securities’ and regulatory
authorities’ investigation, price of the stock may decline in a
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Copyright © 2013 SciRes. 35