Profitability of contrarian strategies in the Chinese stock market
aa r X i v : . [ q -f i n . T R ] M a y Profitability of contrarian strategies in the Chinese stockmarket
Huai-Long Shi , Zhi-Qiang Jiang , Wei-Xing Zhou
Abstract
This paper reexamines the profitability of loser, winner and contrarian portfolios in the Chinese stockmarket using monthly data of all stocks traded on the Shanghai Stock Exchange and Shenzhen StockExchange covering the period from January 1997 to December 2012. We find evidence of short-term andlong-term contrarian profitability in the whole sample period when the estimation and holding horizonsare 1 month or longer than 12 months and the annualized returns of contrarian portfolios increaseswith the estimation and holding horizons. We perform subperiod analysis and find that the long-termcontrarian effect is significant in both bullish and bearish states while the short-term contrarian effectdisappears in bullish states. We compare the performance of contrarian portfolios based on differentgrouping manners in the estimation period and unveil that decile grouping outperforms quintile groupingand tertile grouping, which is more evident and robust in the long run. Generally, loser portfolios andwinner portfolios have positive returns and loser portfolios perform much better than winner portfolios.Both loser and winner portfolios in bullish states perform better than those in the whole sample period.In contrast, loser and winner portfolios have smaller returns in bearish states in which loser portfolioreturns are significant only in the long term and winner portfolio returns become insignificant. Theseresults are robust to the one-month skipping between the estimation and holding periods and for thetwo stock exchanges. Our findings show that the Chinese stock market is not efficient in the weak form.These findings also have obvious practical implications for financial practitioners.
Introduction
The Efficient Markets Hypothesis is a cornerstone of modern finance [1,2]. However, there is accumulatingevidence for the presence of market anomalies, such as the momentum effect and the contrarian effect.The momentum effect describes the empirically observed tendency for rising asset prices to rise furtherand falling prices to keep falling, while the contrarian effect describes the price reversal phenomenonstating that stocks that perform the best (worst) in the past tend to reverse to perform well (poorly)over the subsequent periods. The momentum and contrarian effects have attracted wide attention in theacademic community and in the financial industry as well in the past two decades.Jegadeesh and Iitman conduct the first research on the momentum effect [3]. By setting 16 combina-tions of different estimation and holding horizons, investors would get abnormal returns in the holdingperiod through purchasing the best performing stock (winner) portfolio and selling the worst performingstock (loser) portfolio in the estimation period. They find that 15 out of the 16 arbitrage portfoliosyield statistically significant returns in the next 3 to 12 months, which also confirms the existence of theintermediate-term momentum effect. The research on the contrarian effect was initially conducted inRef. [4]. They use monthly data of hundreds of individual stocks listed on the New York Stock Exchangefrom 1926 to 1982, and construct the winner portfolio of 35 best performed stocks in the past 3 years andthe loser portfolio of 35 worst performed stocks in the past 3 years. They find empirical evidence thatin the next three years, the loser portfolio performs better than the winner portfolio with a 25% higheraverage cumulative return, which indicates the existence of a long-term contrarian effect.Early investigations of momentum and contrarian effects focused on the US market. These twoanomalies have also been found in other markets later. Rouwenhorst investigates 12 European stockmarkets from 1980 to 1995 and reports that the winner portfolio results in an average monthly return 1%higher than the loser portfolio [5]. Chan et al. [6] and Chou et al. [7] find the short-horizon contrarianeffect in the Japanese market. Baytas and Cakici report the presence of a long-term contrarian effect inseven non-US markets [8]. Hameed and Ting find the price reversal in the Malaysian market [9]. Kanget al. reveal that there was a short-term contrarian effect and an intermediate-term momentum effectin the Chinese market [10]. Naughton et al. also find the momentum effect in China [11]. Additionally,the momentum and contrarian effects have been discovered in the markets of different financial products.Grinblatt et al. utilize the data of 155 mutual fund companies from 1975 to 1984 and find that about77% mutual funds that applied momentum strategy gained statistically significant higher returns thanthe rest [12]. Asness et al. investigate the correlation between the value and momentum effects ininternational markets, and discover a universal momentum effect in different regions and different assetclasses [13]. The research in Ref. [14] draws similar conclusions.The original momentum and contrarian effects were based on cross-sectional prices or returns ofassets, also called “price momentum” [3, 7, 10]. More and more kinds of momentum or contrarian effectswere explored in a body of further studies about market anomalies, which in turn partially explainedthe presence of momentum and contrarian effects. On the basis of price momentum, various factorscontaining firm-specific information were taken into consideration. Investors can construct zero-costarbitrage portfolios in terms of more information and get higher profits. These factors include firmcapitalization [3, 5], stock price [15, 16], book-to-market ratio [17], trading volume [11, 18], and so on.Moreover, the assets could be divided into portfolios with different styles according to these firm-specificinformation factors and the momentum or contrarian effect about style portfolio (style investing) alsoattracted wide attention as well [19, 20]. Studies on specific industrial sectors unveil that the momentumand contrarian effects can obtain much more profits in industrial sectors [21, 22]. Note that the resultsabout the momentum and contrarian effects vary with changing market states [23] and seasonality [24].There are also studies on individual stocks and stock market indexes [25], which is beyond the scope ofthis work.With the increasing importance of China in the world economy, more and more related researcheshave been carried out on the Chinese stock market. It has been shown that the Chinese stock market andthe US stock market are uncorrelated [26] and even negatively correlated in some periods [10]. In early1990s, two stock exchanges, the Shanghai Stock Exchange (SHSE) and the Shenzhen Stock Exchange(SZSE), were established in China. Compared with other mature financial markets, the data size of theChinese market is relatively smaller, which may lead to imprecise results. The trading mechanisms of theChinese market differ from other markets and keep self-improving. In the Chinese market, the majorityof investors are retail investors, causing larger irrational and speculative behaviors. These situations maycontribute differently to some anomaly phenomena. It is not surprising that studies about the momentumand contrarian effects in the Chinese stock market report mixed results. The conclusions of momentumand contrarian effects are often associated with the length of the estimation and holding periods and thesample periods under investigation. In general, the horizons can be divided into short term (3 months orless), intermediate term (3 to 12 months) and long term (more than 12 months).Most studies report that there is a long-term contrarian effect in the Chinese stock market. Usingmonthly data of 53 individual stocks listed on the SHSE and the SZSE from January 1993 to December2000, Wang and Zhao discover a statistically significant contrarian effect with the estimate period rangingfrom 1 to 3 years and the holding period from 1 to 5 years [27]. Li and Li investigate A-shares on the SHSEand the SZSE from January 1996 to December 2002 and reveal that the market exhibits a contrarianeffect in horizons more than 1 year [28]. Using monthly data of A-shares traded on the SHSE and theSZSE from January 1995 to December 2002, Luo and Wang also draw the similar conclusion [29]. Similarresults can be found in later studies [30–37].In the short term and intermediate term, the conclusions are mixed. For example, Kang et al. usethe data of individual stocks from 1993 to 2000 and find the existence of a short-term (1, 2, 4, 8, and12 weeks) contrarian effect and a statistically significant momentum effect in the intermediate term (12,16, 20, and 26 weeks) [10]. Based on A-share data in the SHSE and the SZSE from January 1995 toDecember 2001, Zhu et al. verify the presence of a significant momentum effect with both estimation andholding periods less than 4 weeks [38]. Zhu et al. find a statistically significant contrarian effect with theestimation and holding periods less than 5 days [39]. Liu and Qin use monthly data of constituent stocksof the SHSE 180 Index from July 2002 to September 2005 and report the presence of a momentum effectwith the horizons less than 12 months [40]. Pan et al. find the existence of a momentum effect in weeklyreturns and a contrarian effect in monthly returns [37, 41]. There are also studies finding no significantmomentum or contrarian effects in the short term or in the intermediate term [27, 31, 35].The different conclusions in the above-mentioned studies can be attributed to the following factors.(1) Different data samples. Some studies use part of the individual stocks listed on the SHSE and theSZSE [27], while others use data of all A-shares [34, 35, 38]. (2) Different sample periods. For example,Wang and Zhao [27] and Kang et al. [10] use the sample period from 1993 to 2000, Zhu et al. [39] studythe period from 1996 to 2001, Lu and Zou [34] investigate the period from 1998 to 2005, and Naughtonet al. [11] consider the period from 1995 to 2005. (3) Different sampling frequencies. Some researchersuse monthly data [3,11], while some others adopt daily and weekly data [10,38,39,41]. (4) Other factors.It is found that the bid-ask spread, non-synchronous trading as well as the lack of liquidity would enlargethe momentum and contrarian effects [42–44]. To avoid these, the common approach is to skip certaintime intervals between the estimation period and the holding period [3, 38]. Studies that do not adoptthis interval-skipping approach may lead to different results [27, 34].With more data available, it is worth to re-examine the contrarian and momentum effects in theChinese stock market. We use monthly return data of all A-shares listed on the SHSE and the SZSEfrom January 1997 to December 2012 to construct the winner and loser portfolios, which forms zero-costarbitrage portfolios. In the estimation period for stock ranking, one needs to determine the number ofstock groups. Different studies on the momentum and contrarian effects have adopted different groupingways, including decile grouping, quintile grouping and tertile grouping [3, 10, 13, 27, 41]. For variousmarkets, different grouping ways may lead to significantly different results. This paper will take intoaccount these three grouping ways for comparison. Most of the previous studies about the Chinesemarket take the A-share market as a whole. Since the features of A-shares listed on these two stockexchanges are not similar, we investigate the momentum and contrarian effects in the SHSE and theSZSE independently. For instance, the A-share stocks listed on the SHSE generally have higher marketcapitalization compared with those in the SZSE. However, empirical analysis in this study fails to verifyany significant differences between the results of the two exchanges.
Materials and Methods
Data
There are two stock exchanges – Shanghai Stock Exchange (SHSE) and Shenzhen Stock Exchange (SZSE)– in mainland China, and the Chinese stock market contains an A-share market and a B-share market.Most stocks are traded only in the A-share market, while a small proportion of stocks are traded in bothmarkets. At the end of 2012, there are 944 A-share stocks and 54 B-share stocks in the SHSE and 1528A-share stocks and 53 B-share stocks in the SZSE (Table 1). Different from A-share stocks, B-shareswere not accessible to domestic investors until February 2001, and the B-share stock market has lowerliquidity and market value. As described in Table 1, by the end of 2012, the B-share stocks accounted for5 .
41% and 3 .
35% in the SHSE and the SZSE, the market value of B-share stocks only accounted for 0 . .
11% in the SHSE and the SZSE, the trading value of B-share stocks took up 0 .
25% in the SHSEand 0 .
30% in the SZSE, and the A-share market had larger number of investors and higher turnover rate.Therefore, our analysis is carried out upon the Chinese A-share stock market, which can be representativeof the Chinese domestic investment environment. Because the average market capitalizations of SHSEstocks (16.73 billion CNY per stock) and SZSE stocks (4.64 billion CNY per stock) are significantlydifferent, we shall investigate separately the A-share stocks in the two exchanges for comparison.
Table 1. Basic information about Chinese stock market by the end of 2012. ± Method
Like most studies about the cross-sectional momentum or contrarian effect [11,41], we follow the procedureproposed by [3] to construct J − K portfolios. For a given “current” month t = 0, all the stocks aresorted according to their returns in the past J months from t = − J to t = 0 (Fig. 2). We divide thestocks into several groups. For comparison, decile grouping, quintile grouping and tertile grouping areadopted. The group of stocks with the worst performance in the estimation is called loser portfolioLOS( J, K ) and the group with best performance is called winner portfolio WIN(
J, K ). One then adopts
SHSESZSE
Figure 1. The evolution of stock amounts on the SHSE and the SZSE. the contrarian strategy by buying the loser portfolio and selling the winner portfolio. The contrarianportfolio CON(
J, K ) is held for K months. We examine the equal-weighted average returns per annum ofthe loser portfolio, the winner portfolio, and the contrarian portfolio during the holding period, denotedby L J,K , W J,K and C J,K respectively. The contrarian effect is verified if the time series of returns forcontrarian portfolios turn out to be statistically positive. Conversely, there would be the momentumeffect.
Figure 2. The estimation and holding periods.
The estimation period is J months and theholding period is K months. Empirical results
The case of identical estimation and holding horizons ( J = K ) We study the performance of the three portfolios in the whole period (1997-2012) with same estimationperiod and holding period for the three ranking groupings. The periods range from one month to fouryears: J = K ∈ { J, K | , , , , , , , , } . Table 2 reports the equal-weighted average annualreturns for the loser, winner and contrarian portfolios by taking a long position of each portfolio in theholding period. Comparing the two panels, we find that the results are qualitatively similar with minordifferences. Table 2. The annualized returns of the loser, winner, and contrarian portfolios formed based on decile grouping with J = K for the whole sample period 1997-2012. t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -statPanel A: SHSE Panel A1: Decile grouping
LOS 0.213 2.22 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.086 0.88 0.175 1.92 0.185 2.03 ∗ ∗ ∗ ∗∗ ∗∗ CON 0.128 3.41 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel A2: Quintile grouping
LOS 0.228 2.33 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.107 1.07 0.186 1.99 ∗ ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ CON 0.120 3.58 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel A3: Tertile grouping
LOS 0.227 2.30 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.126 1.24 0.193 2.03 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ CON 0.101 3.62 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B: SZSE
Panel B1: Decile grouping
LOS 0.193 2.05 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.091 0.87 0.159 1.71 0.187 1.86 0.199 1.86 0.217 1.89 0.197 2.11 ∗ ∗ ∗∗ ∗∗ CON 0.102 2.54 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B2: Quintile grouping
LOS 0.203 2.13 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.094 0.92 0.170 1.79 0.193 1.93 0.207 1.96 0.217 2.03 ∗ ∗ ∗∗ ∗∗ ∗∗ CON 0.109 3.33 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B3: Tertile grouping
LOS 0.207 2.12 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.110 1.06 0.172 1.82 0.202 2.05 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ CON 0.097 3.71 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ This table reports the average annualized returns and the corresponding t-statistics adjusted for heteroscedasticity and autocorrelationof the loser (LOS), winner (WIN) and contrarian (CON) portfolios, which are formed based on J -month lagged returns and held for K months with J = K . In ranking the J -month lagged returns, decile grouping, quintile grouping and tertile grouping are adopted. Thesample period is January 1997 to December 2012. The superscripts * and ** denote the significance at 5% and 1% levels, respectively.The returns of all the portfolios are positive. This finding is not surprising because the Chinese markethas an overall rise. The returns of the loser portfolios are larger than those of the winner portfolios,indicating the presence of investor overreaction [4, 45, 46]. The performance of the contrarian strategyis worse than the simple strategy of buying loser portfolio. The positive returns of winner portfoliosindicate that the contrarian strategy profits mainly come from the loser portfolio.Nearly all the strategy portfolios could gain the statistically significant positive return when theholding horizons are beyond about 18 months or equal to 1 month. When the horizon is 6 or 12 months,there is no significant evidence for the presence of the contrarian effect or the momentum effect. Thefinding of long-term contrarian effect is consistent with most literature about the Chinese stock market.The short-term contrarian effect may be due to no time gap between the estimation and holding period,which could exaggerate the contrarian effect because of some measurement errors. We will discuss furtherin the rest of the paper.A close scrutiny unveils that the return C J,K of contrarian portfolios decreases at first and then risesup with the horizon J or K , which can be characterized as a U-shape relation. For example, on the basisof decile grouping for SHSE stocks, the CON(1 ,
1) portfolio produces an annual return of 12 . ,
6) portfolio decreases to 1 . .
7% for CON(48 ,
48) with increasing horizon J . It is worthy noting that [7] report a similar andmore general U-shape relationship between the returns and the horizons when investigating the contrarianeffect in the Japanese market.Table 2 also shows the impact of different grouping methods. The annualized return of loser portfolioson both exchanges decreases with the number of groups from tertile to decile for small J and increasesfor long horizons J . For the winner portfolios on both exchanges, the annualized return is smaller whenthere are more groups. Combining these observations, the trend of returns of the contrarian portfolioson short horizons is mixed; however, on long horizons, the return increases with the number of groups. The case of varying J and K We now perform more comprehensive analysis with varying J and K for decile, quintile and tertilegroupings. The results of decile grouping are presented in Table 3 for SHSE stocks and in Table 4 forSZSE stocks. The values of estimation horizons J and holding horizons K range from one month tofour years. Panels A, B and C report the results for loser portfolios, winner portfolios, and contrarianportfolios, respectively. The results based on quintile grouping and tertile grouping for the two exchangesare similar to the case of decile grouping and shown in Table S1 for quintile grouping of SHSE stocks,Table S2 for quintile grouping of SZSE stocks, Table S3 for tertile grouping of SHSE stocks, and Table S4for tertile grouping of SZSE stocks. According to Table 3 and Table 4, the most intriguing feature is that all annualized returns are positive.Panel A illustrates that, for both exchanges, all the loser portfolios result in positive returns across all estimationand holding horizons, and all the returns are statistically significant at the 5% level except for a few portfoliosat small horizons. The profits of winner portfolios on both exchanges, as shown in panel B, are also positivefor all combinations of J and K , which suggests that the profits of contrarian portfolios are mainly contributedby the loser portfolios. The significance of results for winner portfolios differ by the holding horizons K . Noreturns of the winner portfolios are significant at the 5% level when K ≤
6, while all returns are significantlypositive when K ≥
30. The contrarian portfolios are formed by selling the winner portfolios and buying theloser portfolios. Panel C shows that all the contrarian portfolios yield positive returns, which implies the absenceof the momentum effect on both exchanges during the whole sample period. All the returns are significantlypositive when the holding horizon K = 1, except for CON(12 ,
1) on the SHSE, which indicates the presence of theshort-term contrarian effect, consistent with the most previous literatures such as [10] and [34] on shorter sampleperiods. When the estimation horizon J is larger than one year, most returns are significantly positive despite ofthe holding periods, suggesting the presence of both short-term and long-term contrarian effects, which is againconsistent with other works such as [27], [47], [28], and [35] for shorter sample periods. Table 3. The annualized returns of the loser, winner, and contrarian portfolios on the SHSE formed based on decilegrouping with varying J and K for the whole sample period 1997-2012. K = 1 6 12 18 24 30 36 42 48 J Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Panel A: Loser portfolio ∗ ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
12 0.221 2.05 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
18 0.248 2.27 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.249 2.26 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.278 2.54 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.303 2.64 ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.301 2.75 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.304 2.62 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B: Winner portfolio ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗
12 0.140 1.48 0.165 1.87 0.185 2.03 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗
18 0.118 1.23 0.147 1.66 0.169 1.87 0.185 1.91 0.193 2.02 ∗ ∗ ∗ ∗∗ ∗∗
24 0.115 1.17 0.142 1.59 0.164 1.82 0.177 1.87 0.190 1.96 0.191 2.19 ∗ ∗ ∗∗ ∗∗
30 0.092 0.97 0.131 1.48 0.156 1.74 0.174 1.80 0.188 1.92 0.190 2.17 ∗ ∗ ∗∗ ∗∗
36 0.103 1.06 0.139 1.55 0.163 1.78 0.179 1.84 0.191 1.91 0.192 2.15 ∗ ∗ ∗∗ ∗∗
42 0.110 1.13 0.132 1.50 0.158 1.72 0.182 1.83 0.194 1.90 0.192 2.18 ∗ ∗ ∗∗ ∗∗
48 0.095 0.96 0.118 1.33 0.158 1.70 0.184 1.85 0.190 1.93 0.186 2.23 ∗ ∗ ∗∗ ∗∗ Panel C: Contrarian portfolio ∗∗ ∗ ∗ ∗ ∗ ∗ ∗∗
18 0.129 2.20 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.134 2.38 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.186 3.37 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.200 3.28 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.191 3.26 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.209 3.29 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Table 4. The annualized returns of the loser, winner, and contrarian portfolios on the SZSE formed based on decilegrouping with varying J and K for the whole sample period 1997-2012. K = 1 6 12 18 24 30 36 42 48 J Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Panel A: Loser portfolio ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
12 0.264 2.22 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
18 0.261 2.33 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.284 2.49 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.281 2.59 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.300 2.71 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.336 2.89 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.325 2.83 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B: Winner portfolio ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗
12 0.141 1.44 0.158 1.65 0.187 1.86 0.208 1.95 0.210 2.09 ∗ ∗ ∗∗ ∗∗ ∗∗
18 0.109 1.11 0.146 1.54 0.176 1.78 0.199 1.86 0.213 1.97 0.211 2.29 ∗ ∗∗ ∗∗ ∗∗
24 0.120 1.20 0.150 1.57 0.173 1.74 0.203 1.79 0.217 1.89 0.205 2.17 ∗ ∗ ∗∗ ∗∗
30 0.116 1.11 0.145 1.49 0.185 1.79 0.217 1.85 0.220 1.86 0.197 2.11 ∗ ∗ ∗∗ ∗∗
36 0.150 1.42 0.167 1.65 0.201 1.86 0.218 1.85 0.215 1.89 0.198 2.20 ∗ ∗ ∗∗ ∗∗
42 0.130 1.24 0.173 1.65 0.201 1.79 0.212 1.81 0.208 1.88 0.191 2.18 ∗ ∗ ∗∗ ∗∗
48 0.115 1.08 0.157 1.48 0.184 1.62 0.197 1.71 0.196 1.83 0.183 2.09 ∗ ∗ ∗∗ ∗∗ Panel C: Contrarian portfolio ∗ ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗ ∗ ∗
18 0.153 2.62 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗ ∗∗
24 0.165 2.39 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.165 2.23 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.151 2.21 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.206 2.72 ∗∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.211 2.60 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Holding Period K E s t i m a t i o n P er i o d J SHSE_Loser_Decile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 0.050.10.150.20.250.3 Holding Period K E s t i m a t i o n P er i o d J SHSE_Winner_Decile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 0.050.10.150.20.250.3 Holding Period K E s t i m a t i o n P er i o d J SHSE_Contrarian_Decile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 0.050.10.150.20.250.3Holding Period K E s t i m a t i o n P er i o d J SZSE_Loser_Decile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 00.050.10.150.20.250.30.35 Holding Period K E s t i m a t i o n P er i o d J SZSE_Winner_Decile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 00.050.10.150.20.250.30.35 Holding Period K E s t i m a t i o n P er i o d J SZSE_Contrarian_Decile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 00.050.10.150.20.250.30.35
Figure 3. Contour plots of the average annualized returns based on decile grouping withvarying estimation and holding horizons.
The left panel is for loser portfolios, the middle panel isfor winner portfolios, and the right panel is for contrarian portfolios. The top panel is for the SHSEstocks and the bottom is for the SZSE stocks.Table 3 and Table 4 show that the average annualized returns depend on the values of J and K . Tobetter explore this dependence, we illustrate the contours of returns based on decile grouping in Fig. 3.We also show the results in Figure S1 for quintile grouping and in Figure S2 for tertile grouping. Thevalues of J and K are 1 month and multiples of 3 months up to 4 years. Similar results are obtained forquintile grouping and tertile grouping. The top panel is for the SHSE stocks and the bottom panel is forthe SZSE stocks. The corresponding contour patterns are roughly similar for the same type of portfolio.However, different types of portfolio exhibit very different contour patterns.For the loser portfolios, the return L J,K increases roughly with J and K . A closer scrutiny unveilsmore details. There is a valley around J = 9 and K = 6, which are the portfolios with the worstperformance. The best performance is achieved if one ranks the stocks according to their profits inthe past four years and holds the loser portfolio for two years (SZSE) or longer (SHSE). The highestannualized return is 36.2% for the LOS(48 ,
36) portfolio on the SHSE and 36.9% for the LOS(48 ,
24) andLOS(42 ,
30) portfolios on the SZSE.When the holding horizon K is short, say no longer than 1 year, the annualized returns of the winnerportfolios are almost independent of the holding horizon J . When the holding horizon is longer than1 year, the winner returns decrease with increasing estimation horizon. When the estimation horizon J is fixed, the winner portfolio return increases first and decreases with the holding horizon K . Whenthe estimation horizon is very short (say, J = 1) and the holding horizon is around 2 years, the winnerportfolio return is the highest.The annualized returns of contrarian portfolios depend more on the estimation horizon J than onthe holding horizon K . A evident trend is that C J,K increases with J for fixed K . For fixed J , thereturn C J,K decreases first and then increases, showing a V-shape pattern. Hence, the best performanceis achieved for portfolios formed on long estimation horizons and held for very short (1-3 months) andespecially for very long (3-4 years) horizons. Under these conditions, the profits are very significant. For1instance, the CON(48 ,
1) portfolio provide an average annualized return of 20 .
9% for the SHSE stocksand 21 .
1% for the SZSE stocks.
The relative profits of contrarian portfolios with different ranking groups
In the literature, three grouping methods are adopted in the formation of portfolios, including decilegrouping [3, 27], quintile grouping [10, 41], and tertile grouping [13]. For the Chinese stock market,the results are qualitatively similar for different grouping methods. We now investigate the relativeperformances of these grouping methods. For each of the three grouping methods, we form winner, loserand contrarian portfolios based on different combinations of estimation and holding horizons with J and K belonging to { , , , , , , , , } . For each portfolio, say WIN( J, K ), we obtain the return timeseries W J,K,g ( t ) for each grouping g and determine the averages of return differences between different g ’s, h W J,K,g ( t ) − W J,K,g ( t ) i t . The resulting average return differences and the associated t-statistics ofthe winner, loser and contrarian portfolios for the two exchanges are presented in Table S5-Table S10.Table 5 shows the results for J = K .Panel A of Table 5 reports the average return differences for the loser portfolios with J = K in the twoexchanges. Most of the return differences are negative for short horizons and positive for long horizons.For short horizons, some of return differences are significantly negative while other are insignificant. Forlong horizons, especially when J = K ≥
30 for SHSE stocks and J = K ≥
24 for SZSE stocks, all returndifferences are significantly positive. This panel suggests that, if one buys loser portfolios, she shouldadopt long horizons and use the decile grouping to form her portfolios to obtain high and robust profits.These findings also hold when the estimation horizon and the holding horizon are not fixed identical.Panel B of Table 5 reports the average return differences for the winner portfolios with J = K inthe two exchanges. The most significant feature is that all return differences are negative. The negativereturn difference is more likely to be significant if the horizons are longer. When J is not necessary equalto K , the results have only slight differences, as shown in Table S7 and Table S8. For the comparison ofquintile grouping and tertile grouping ( G − G ), all 81 combinations of J and K have negative returndifferences for the SHSE stocks, and only 3 out of the 81 combinations (WIN(12 , ,
1) andWIN(42 , G − G ), only 2 combinations (WIN(1 , , , G − G ), all 81combinations have negative return differences for the SHSE stocks, and there are 3 combinations havepositive return differences for the SZSE stocks which are not significant at the 5% level. Therefore, if oneadopts the strategy to buy winner portfolios, it is better to use tertile grouping and long estimation andholding horizons.Panel C of Table 5 reports the average return differences for the contrarian portfolios with J = K inthe two exchanges. There are positive and negative return differences. All negative return differences arenot significant at the 5% level and the corresponding horizons are not longer than one year. For horizonslonger than one year, all the return differences are positive and most are significant at the 1% level. If wedo not fix J = K , the results are similar. Therefore, if an investor wants to adopt the contrarian strategy,she should use decile grouping and long-term lagged returns to rank stocks to construct her portfolio andhold it for a long period. Table 5. Relative performance of different grouping methods based on the same strategy of portfolios with J = K forthe whole sample period 1997-2012. R t -stat ∆
R t -stat ∆
R t -stat ∆
R t -stat ∆
R t -stat ∆
R t -stat ∆
R t -stat ∆
R t -stat ∆
R t -statPanel A: Loser portfolios
Panel A1: SHSE G − G ∗∗ -0.005 -1.96 0.001 0.49 0.004 1.59 0.006 1.99 ∗ ∗∗ ∗∗ ∗∗ G − G -0.014 -1.60 -0.007 -1.56 -0.016 -4.29 ∗∗ -0.010 -2.01 ∗ -0.002 -0.51 0.021 5.43 ∗∗ ∗∗ ∗∗ ∗∗ G − G -0.014 -1.03 -0.016 -2.59 ∗ -0.021 -4.06 ∗∗ -0.009 -1.52 0.002 0.28 0.027 4.97 ∗∗ ∗∗ ∗∗ ∗∗ Panel A2: SZSE G − G -0.004 -0.54 -0.009 -2.08 ∗ -0.001 -0.19 0.010 2.70 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ G − G -0.009 -0.84 -0.014 -2.34 ∗ -0.005 -1.12 -0.004 -0.58 0.026 3.79 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ G − G -0.013 -0.85 -0.023 -2.61 ∗ -0.006 -0.85 0.006 0.74 0.040 4.08 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B: Winner portfolios
Panel B1: SHSE G − G -0.018 -2.40 ∗ -0.007 -2.07 ∗ -0.014 -4.43 ∗∗ -0.020 -7.57 ∗∗ -0.024 -8.80 ∗∗ -0.016 -5.68 ∗∗ -0.009 -3.16 ∗∗ -0.009 -3.26 ∗∗ -0.012 -3.46 ∗∗ G − G -0.022 -1.79 -0.010 -2.07 ∗ -0.005 -1.27 -0.015 -3.98 ∗∗ -0.009 -2.31 ∗ -0.009 -2.49 ∗ -0.005 -1.63 -0.017 -4.51 ∗∗ -0.025 -4.75 ∗∗ G − G -0.040 -2.45 ∗ -0.018 -2.50 ∗ -0.019 -3.15 ∗∗ -0.035 -6.74 ∗∗ -0.032 -6.87 ∗∗ -0.025 -4.71 ∗∗ -0.014 -2.65 ∗∗ -0.026 -6.00 ∗∗ -0.037 -8.01 ∗∗ Panel B2: SZSE G − G -0.016 -1.76 -0.003 -0.65 -0.009 -2.66 ∗∗ -0.017 -4.74 ∗∗ -0.013 -2.72 ∗∗ -0.013 -3.25 ∗∗ -0.008 -3.08 ∗∗ -0.009 -2.86 ∗∗ -0.011 -4.41 ∗∗ G − G -0.003 -0.25 -0.011 -1.76 -0.005 -1.09 -0.008 -1.80 -0.000 -0.03 -0.011 -2.29 ∗ -0.015 -3.74 ∗∗ -0.013 -2.77 ∗∗ -0.018 -3.73 ∗∗ G − G -0.019 -1.00 -0.014 -1.56 -0.015 -2.06 ∗ -0.025 -3.86 ∗∗ -0.013 -1.47 -0.024 -3.16 ∗∗ -0.023 -4.44 ∗∗ -0.021 -3.60 ∗∗ -0.030 -5.36 ∗∗ Panel C: Contrarian portfolios
Panel C1: SHSE G − G ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ G − G ∗∗ ∗∗ ∗∗ ∗∗ G − G ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel C2: SZSE G − G ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ G − G -0.006 -0.40 -0.003 -0.35 0.000 0.04 0.004 0.53 0.026 2.92 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ G − G ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ This table reports the differences of the average annualized returns and the corresponding t -statistics of two strategies that are differentonly in the grouping methods. The three panels are for the loser, winner and contrarian portfolios, respectively. In the first row, G , G and G stand for tertile, quintile and decile groupings. The sample period is January 1997 to December 2012. The superscripts * and** denote the significance at 5% and 1% levels, respectively.3 The profits of contrarian portfolios in different exchanges
As mentioned in
Materials and Methods , the SHSE and the SZSE have different features, such as marketvalue per stock, which may lead to different results in the two exchanges. However, the results resentedso far are qualitatively similar for both exchanges. Now we intend to investigate quantitatively thecontrarian return differences between the SHSE and the SZSE. We first obtain the time series of returnsdifference for each contrarian portfolio with the stocks listed on different exchanges, and then calculatetheir averages. The results are reported in the Table 6.Panel A shows the results for contrarian portfolios based on decile grouping. There are three contrar-ian portfolios (CON(12 , ,
30) and CON(24 , , , , , Table 6. Comparison of the performance of contrarian portfolios in the two exchanges for the whole sample period1997-2012. K = 1 6 12 18 24 30 36 42 48 J Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Panel A: Decile grouping ∗ -0.017 -1.49 -0.004 -0.43 0.012 1.0318 -0.023 -0.59 -0.028 -1.74 -0.007 -0.52 -0.000 -0.02 -0.019 -1.62 -0.029 -2.34 ∗ -0.021 -1.78 0.002 0.20 0.011 1.1424 -0.030 -0.67 -0.006 -0.35 0.010 0.63 0.014 0.77 -0.019 -1.40 -0.030 -2.61 ∗ -0.019 -1.90 -0.005 -0.61 0.012 1.1530 0.021 0.45 0.013 0.68 0.025 1.34 0.030 1.44 -0.002 -0.14 -0.022 -1.91 -0.015 -1.43 0.009 0.97 0.036 2.88 ∗∗
36 0.049 1.01 0.016 0.71 0.024 1.05 0.021 0.97 -0.001 -0.06 -0.020 -1.62 -0.005 -0.44 0.021 1.85 0.036 2.67 ∗∗
42 -0.015 -0.25 0.014 0.56 0.027 1.11 0.023 1.09 -0.007 -0.46 -0.017 -1.51 0.003 0.28 0.023 1.71 0.040 3.19 ∗∗
48 -0.002 -0.03 0.025 0.88 0.029 1.23 0.016 0.78 -0.003 -0.23 -0.007 -0.62 -0.006 -0.47 0.014 0.95 0.028 2.09 ∗ Panel B: Quintile grouping ∗∗
12 -0.018 -0.75 -0.022 -2.50 ∗ -0.006 -0.67 0.003 0.26 -0.011 -1.14 -0.015 -2.02 ∗ -0.014 -1.97 -0.004 -0.58 0.008 1.1018 -0.032 -1.11 -0.028 -2.88 ∗∗ -0.009 -1.11 -0.001 -0.11 -0.007 -0.91 -0.017 -2.33 ∗ -0.011 -1.76 0.005 0.79 0.015 2.18 ∗
24 -0.025 -0.89 -0.008 -0.80 0.006 0.58 0.019 1.56 0.001 0.13 -0.009 -1.37 0.000 0.02 0.016 2.15 ∗ ∗∗
30 0.008 0.26 0.011 1.00 0.025 2.03 ∗ ∗∗ ∗∗
36 0.012 0.33 0.023 1.60 0.028 1.93 0.029 2.18 ∗ ∗∗ ∗∗
42 0.002 0.04 0.001 0.09 0.022 1.35 0.025 1.79 0.006 0.58 0.005 0.73 0.025 3.22 ∗∗ ∗∗ ∗∗
48 -0.011 -0.27 0.011 0.64 0.025 1.73 0.015 1.17 -0.005 -0.45 -0.003 -0.31 0.008 0.86 0.016 1.51 0.020 1.90
Panel C: Tertile grouping ∗ -0.006 -0.94 -0.003 -0.35 -0.001 -0.10 -0.001 -0.22 -0.002 -0.51 -0.002 -0.35 0.015 2.95 ∗∗
12 -0.021 -1.03 -0.024 -3.76 ∗∗ -0.007 -1.07 0.003 0.43 0.001 0.28 -0.001 -0.14 -0.004 -0.82 0.004 0.80 0.017 2.80 ∗∗
18 -0.020 -0.94 -0.020 -2.69 ∗∗ -0.002 -0.26 0.004 0.75 0.001 0.15 -0.006 -1.24 -0.002 -0.54 0.011 2.43 ∗ ∗∗
24 -0.016 -0.66 -0.007 -0.93 0.006 0.94 0.016 2.17 ∗ ∗∗ ∗∗
30 -0.008 -0.31 0.006 0.86 0.025 3.11 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.023 0.89 0.025 2.77 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 -0.009 -0.32 -0.002 -0.21 0.009 0.95 0.006 0.79 -0.002 -0.26 0.004 0.70 0.025 3.53 ∗∗ ∗∗ ∗∗
48 -0.004 -0.13 0.005 0.44 0.015 1.36 0.002 0.24 -0.001 -0.06 0.010 1.16 0.019 2.27 ∗ ∗ ∗∗ This table reports the differences of average annualized returns of contrarian portfolios in the SHSE and SZSE and the corresponding t -statistics. The return differences are the SHSE returns minus the SZSE returns. The contrarian portfolios are formed based on J -month lagged returns and held for K months.5 Robustness check
In this section, two approaches are adopted to check the robustness of the findings. First, we performsubperiod analysis through dividing the whole sample period into two subperiods delimited by the onsetof the largest and most infamous crash in the history of China’s stock market. One subperiod is fromJanuary 1997 to September 2007 and the other is from October 2007 to December 2012. Second, thecase of skipping one month between the estimation and holding periods is considered to avoid possiblemeasurement errors.
Subperiod analysis
Figure 4 illustrates the evolution of daily closing prices of the Shanghai Stock Exchange Composite Index.The SHSE composite index was merely 99 .
98 on 19 December 1990, which is the first day when SHSEtook into operation. By the end of 1996, the index reached 917.02, about ten times of the initial index.The market then experienced bulls and bears and kept climbing to the peak about 6092.06 on 16 October2007. The historical intraday high was 6124.04 on the same day. Afterwards, the index declined sharply,and entered the long-term adjustment stage. In 2009, the market experienced a bubble [48]. However,the index is far lower than the historical high. At the end of 2012, the index was 2269 . Figure 4.
Evolution of the Shanghai Stock Exchange Composite Index from December 1990 toDecember 2012.It is thus necessary to check the robustness of our findings during subperiods. Subperiod analysis isfrequently-used in literatures [3,7,41]. We divide the whole sample period (1997-2012) into two subperiods,January 1997 to September 2007 and October 2007 to December 2012. The former period represents along-term rising stage of the market, while the latter one represents an adjustment stage. The results arepresented in Table 7 for the SHSE stocks and Table 8 for SZSE stocks, in which all portfolios are formedwith identical estimation and holding horizons, that is, J = K .For the loser portfolios in the first subperiod (Panel A of both tables), almost all annualized returnsare significantly positive at the 5% level for the SHSE stocks except for two LOS(6 ,
6) portfolios basedon decile grouping and quintile grouping, while almost all annualized returns are significantly positivefor the SZSE stocks. For the loser portfolios in the second subperiod (Panel B of both tables), the6annualized returns are positive but not significant when J ≤
24 and significantly positive when J ≥ J ≥
24. A loser portfolio results in significantly higher profits in the first subperiod that is bullish onaverage. However, despite the market status, strategies of buying loser portfolios are unlikely to incurlosses and are very likely to earn money. We also observe that loser portfolios have better performancesif the horizons are longer. For the winner portfolios in the first subperiod, all the annualized returns arepositive for both exchanges. Moreover, winner portfolios with K ≥
30 give significant positive returnsat the 5% level and other portfolios with shorter horizons may have significant and insignificant positivereturns. In contrast, although most annualized returns in the second subperiod are positive, no returnis significantly positive nor negative. These observations have a simple intuitive explanation. When themarket is bullish, loser portfolios will rebound to rise and winner portfolios will continue to rise. Whenthe market is bearish, loser portfolios will reverse with a higher probability, while winner portfolios willbear pressure to continue rising. Table 7. The annualized returns of the loser, winner and contrarian portfolios formed based on J -month laggedreturns and held for K months with J = K for SHSE stocks in two subperiods. t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -statPanel A: 1997/01-2007/09 Panel A1: Decile grouping
LOS 0.258 2.29 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.191 1.67 0.271 2.37 ∗ ∗ ∗ ∗ ∗∗ ∗∗ CON 0.066 1.55 -0.055 -1.42 0.007 0.17 0.087 2.45 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel A2: Quintile grouping
LOS 0.272 2.35 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.213 1.79 0.275 2.34 ∗ ∗ ∗ ∗ ∗ ∗∗ ∗∗ CON 0.059 1.54 -0.044 -1.49 0.023 0.70 0.083 2.70 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel A3: Tertile grouping
LOS 0.275 2.37 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.223 1.85 0.276 2.31 ∗ ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ CON 0.052 1.55 -0.031 -1.38 0.019 0.74 0.058 2.40 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B: 2007/10-2012/12
Panel B1: Decile grouping
LOS 0.122 0.71 0.126 0.75 0.130 0.96 0.148 1.41 0.205 1.84 0.248 2.28 ∗ ∗∗ ∗∗ ∗∗ WIN -0.131 -0.78 -0.023 -0.18 0.012 0.12 0.059 0.72 0.067 0.89 0.063 1.03 0.044 1.13 0.029 0.85 0.004 0.14CON 0.253 3.92 ∗∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B2: Quintile grouping
LOS 0.137 0.78 0.116 0.70 0.144 1.06 0.155 1.50 0.193 1.84 0.222 2.16 ∗ ∗∗ ∗∗ ∗∗ WIN -0.108 -0.63 -0.000 -0.00 0.028 0.27 0.074 0.88 0.080 1.03 0.075 1.15 0.054 1.32 0.040 1.23 0.018 0.53CON 0.245 4.53 ∗∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B3: Tertile grouping
LOS 0.129 0.73 0.115 0.70 0.144 1.08 0.159 1.56 0.190 1.84 0.208 2.08 ∗ ∗∗ ∗∗ ∗∗ WIN -0.073 -0.42 0.021 0.15 0.050 0.46 0.089 1.04 0.099 1.23 0.093 1.35 0.076 1.66 0.058 1.64 0.038 1.09CON 0.202 4.97 ∗∗ ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ This table reports the results of strategy portfolios in the SHSE during two subperiods. The values of J and K for different strategies areindicated in the first row. The top panel is for first subperiod, from January 1997 to September 2007, and the bottom is for the secondsubperiod from October 2007 to December 2012. The superscripts * and ** denote the significance at 5% and 1% levels, respectively.8We now turn to the contrarian portfolios. In the first subperiod, the returns with J ≥
18 aresignificantly positive and that with J ≤
12 are insignificant for SHSE stocks, and the returns with J ≥ J ≤
18 are insignificant for SZSE stocks. In addition, a givenportfolio performs better in the SHSE than in the SZSE. We also find that contrarian portfolios basedon more groups have higher annualized returns than portfolios based on less groups. For instance, theannualized return of CON(48 ,
48) based on decile grouping is greater than that on tertile grouping by0.102 on the SHSE and by 0.083 on the SZSE. In the second subperiod, almost all annualized returnsare significantly positive, except for the two CON(18 ,
18) portfolios based on decile grouping and quintilegrouping on the SHSE and for CON(6 ,
6) based on decile, quintile and tertile groupings on the SZSE. Agiven portfolio performs better in the SZSE than in the SHSE. Again, portfolios based on more groupsresult in higher returns. For instance, the annualized return of CON(48 ,
48) based on decile grouping isgreater than that on tertile grouping by 0.087 on the SHSE and by 0.157 on the SZSE. Hence, when aninvestor adopts contrarian strategies, it is better to invest in SHSE stocks during bullish states and inSZSE stocks during bearish periods. Table 8. The annualized returns of the loser, winner and contrarian portfolios formed based on J -month laggedreturns and held for K months with J = K for SZSE stocks in two subperiods. t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -statPanel A: 1997/01-2007/09 Panel A1: Decile grouping
LOS 0.245 2.27 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.209 1.66 0.246 2.10 ∗ ∗ ∗ ∗ ∗∗ ∗∗ CON 0.035 0.70 -0.046 -1.14 0.011 0.22 0.054 1.28 0.086 2.43 ∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel A2: Quintile grouping
LOS 0.246 2.24 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.193 1.57 0.245 2.06 ∗ ∗ ∗∗ ∗∗ ∗∗ CON 0.054 1.32 -0.025 -0.82 0.022 0.60 0.058 1.83 0.071 2.68 ∗∗ ∗∗ ∗∗ ∗ ∗∗ Panel A3: Tertile grouping
LOS 0.251 2.22 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.191 1.54 0.237 2.00 ∗ ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ CON 0.059 1.80 -0.006 -0.27 0.020 0.73 0.033 1.46 0.053 2.31 ∗ ∗ ∗ ∗ ∗∗ Panel B: 2007/10-2012/12
Panel B1: Decile grouping
LOS 0.089 0.51 0.123 0.71 0.177 1.19 0.224 2.05 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN -0.151 -0.90 -0.024 -0.19 0.012 0.12 0.050 0.64 0.059 0.88 0.049 0.91 0.022 0.60 0.005 0.19 0.008 0.25CON 0.240 4.68 ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B2: Quintile grouping
LOS 0.114 0.65 0.126 0.72 0.180 1.22 0.220 1.92 0.273 2.25 ∗ ∗ ∗∗ ∗∗ ∗∗ WIN -0.107 -0.62 0.012 0.09 0.041 0.38 0.071 0.83 0.072 1.00 0.069 1.14 0.049 1.28 0.027 0.92 0.013 0.40CON 0.221 5.36 ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B3: Tertile grouping
LOS 0.117 0.65 0.130 0.76 0.180 1.24 0.210 1.82 0.247 2.13 ∗ ∗ ∗∗ ∗∗ ∗∗ WIN -0.057 -0.32 0.037 0.27 0.066 0.58 0.092 1.02 0.098 1.24 0.094 1.44 0.070 1.65 0.050 1.48 0.032 0.87CON 0.174 5.14 ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ This table reports the results of strategy portfolios in the SZSE during two subperiods. The values of J and K for different strategies areindicated in the first row. The top panel is for first subperiod, from January 1997 to September 2007, and the bottom is for the secondsubperiod from October 2007 to December 2012. The superscripts * and ** denote the significance at 5% and 1% levels, respectively.0We also study the relationship between the returns of contrarian portfolios based on varying J and K in the two subperiods. The results are illustrated in Figure S3 for the first subperiod and in Figure S4for the second subperiod. The main findings are qualitatively the same as in Tables 7 and 8. The contourplots provide more information. It is evident that the returns of the cases based on three differentgrouping ways co-move positively with J . The dependence of the returns on the holding horizon K differin different subperiods. Specifically, during the first subperiod, the relation between contrarian returnsand K can be depicted as a U-shape, that is, the returns reduce at first and then increase with K .However, during the second subperiod, the relationship can be depicted as an L-shape, which suggeststhat the returns would decrease at first and then become steady with increasing K . Robustness to measurement
We have observed significant short-term contrarian effect when J = K = 1 in the full period 1997-2012and in the bearish subperiod 2007-2012, but not in the bullish subperiod 1997-2007. The short-termcontrarian effect might be attributed to some factors such as bid-ask bounce and lagged reaction [42, 49].In order to avoid measurement errors caused by these factors, a common approach is to skip some timeinterval between the estimation period and the holding period [7, 10]. We use one month as the skippinginterval and perform the analysis on the whole sample period for loser, winner and contrarian portfolioswith J = K . The results are reported in Table 9, which are compared with Table 2.For the loser portfolios on the SHSE (Panel A of Table 9), most of the returns reduce after theone-month skipping. The most remarkable reduction is happened for the LOS(6 ,
6) portfolios (0.019 fordecile grouping, 0.014 for quintile grouping and 0.012 for the tertile grouping). The reduction of returnsfor LOS(1 ,
1) portfolios based on the quintile and tertile groupings is slightly lower. For other loserportfolios, the return reduction is minor. For the loser portfolios on the SZSE (Panel B of Table 9), weobserve slightly different behaviors. After skipping one month, the returns of LOS(1 ,
1) portfolios increaseslightly and the returns of LOS(6 ,
6) portfolios decrease mildly. For other loser portfolios, both increaseand decrease in the annualized returns are observed; However, the degree of change is minor. Overall,skipping one month does not change the significance of the annualized returns of loser portfolios. For thewinner portfolios, most of the annualized returns increase after skipping one month. When K ≥
12, thedifferences are ignorable. When J = 1 and J = 6, we observe a large increase. However, the returns arestill insignificant.For the contrarian portfolios, the returns with J ≥
12 after skipping one month change slightly of order0.001 and are thus not significant. However, the returns of CON(1 ,
1) and CON(6 ,
6) reduce remarkably.For instance, in the case of decile grouping for SHSE stocks, the average annual returns of CON(1 , ,
6) in Table 2 are 0 .
128 and 0 . ,
1) and CON(6 ,
6) decrease to 0 .
108 and − . ,
1) still has statistically significant return, which indicates that there is no measurement errors.The reduction of contrarian returns is mainly due to the higher profits of winner portfolios after skippingone month. It is clear that the short-term contrarian effect still exists though the average returns ofcontrarian portfolios reduce. It is trivial that skipping one month will not impact the profitability oftrading strategies on the long run so that the long-term contrarian effect also exist.It is also interesting to investigate the return differences of contrarian portfolios based on the threedifferent grouping ways. In the short run, there is evidence showing that quintile grouping performsbetter than tertile grouping at the 5% significance level. However, no significant difference is observedbetween decile grouping and other two groupings. In the long run, decile grouping outperforms quintilegrouping and quintile grouping outperforms tertile grouping. We also study the relationship betweenreturns of the contrarian portfolios with varying J and K in the case of one-month skipping (Figure S5).We find that, the returns of contrarian portfolios increase with the estimation horizon J . The patternswith respect to the holding horizon K are more complicated and similar to those for the original strategieswithout one-month skipping. Table 9. The results for skipping one month between J and K for the whole sample period 1997-2012. t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -stat Ret t -statPanel A: SHSE Panel A1: Decile grouping
LOS 0.214 2.15 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.106 1.04 0.189 2.01 ∗ ∗ ∗ ∗ ∗∗ ∗∗ CON 0.108 3.55 ∗∗ -0.022 -0.56 0.041 1.22 0.086 3.07 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel A2: Quintile grouping
LOS 0.222 2.24 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.126 1.23 0.196 2.05 ∗ ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ CON 0.097 3.87 ∗∗ -0.016 -0.51 0.050 1.83 0.080 3.22 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel A3: Tertile grouping
LOS 0.215 2.16 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.145 1.44 0.203 2.10 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ CON 0.070 3.52 ∗∗ -0.011 -0.48 0.039 1.79 0.060 3.01 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B: SZSE
Panel B1: Decile grouping
LOS 0.221 2.09 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.095 0.99 0.173 1.78 0.186 1.83 0.199 1.85 0.215 1.88 0.194 2.12 ∗ ∗ ∗∗ ∗∗ CON 0.126 3.41 ∗∗ -0.002 -0.05 0.059 1.45 0.088 2.60 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B2: Quintile grouping
LOS 0.208 2.03 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.102 1.07 0.179 1.85 0.192 1.91 0.211 1.99 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ CON 0.106 3.54 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B3: Tertile grouping
LOS 0.209 2.04 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ WIN 0.128 1.30 0.180 1.88 0.203 2.06 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ CON 0.081 3.42 ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ This table reports the average annualized returns and the corresponding t -statistics adjusted for heteroscedasticity and autocorrelationof the loser, winner and contrarian portfolios, which are formed based on J -month lagged returns and held for K months with J = K .There is a one-month skip between the estimation and holding horizons.2 Conclusion
Following the seminal work of Jegadeesh and Titman [3], we investigate the performance of loser portfolios,winner portfolios and contrarian portfolios in the Chinese stock market. The analysis is performed onthe monthly returns of all A-share stocks listed on the Shanghai Stock Exchange and the Shenzhen StockExchanges. The two samples of SHSE stocks and SZSE stocks cover the period from January 1997 toDecember 2012.We find the presence of the contrarian effect in both exchanges across short, intermediate and longhorizons. The profits of portfolios depend on the estimation and holding horizons. Especially, longerestimation and holding horizons lead to more profitable contrarian portfolios. When adding one-monthtime interval between the estimation and holding periods, the results still suggest the existence of sig-nificant short-term and long-term contrarian effects even though the profits are decreasing substantiallywhen J = K = 1. We also conduct subperiod analysis. The long-term contrarian effect is very robust tothe subperiods analysis, while the results for short estimation and holding horizons vary with differentmarket states. The short-term contrarian effect is more explicit when the market is in a bearish stage.Additionally, we study the impact of grouping ways on the performance of portfolios. Specifically,decile, quintile and tertile groupings are adopted. We find that the contrarian portfolios based on decilegrouping are more profitable than those based on quintile and tertile groupings. This conclusion is moreexplicit when the estimation and holding horizons are longer than 12 months. These findings remainvalid to the robustness checks based on subperiod analysis and one-month skipping. Acknowledgments
This work was partially supported by the National Natural Science Foundation of China (11075054and 71131007), Shanghai “Chen Guang” Project (2012CG34), Program for Changjiang Scholars andInnovative Research Team in University (IRT1028), and the Fundamental Research Funds for the CentralUniversities.
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Holding Period K E s t i m a t i o n P er i o d J SHSE_Loser_Quintile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 0.050.10.150.20.250.3 Holding Period K E s t i m a t i o n P er i o d J SHSE_Winner_Quintile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 0.050.10.150.20.250.3 Holding Period K E s t i m a t i o n P er i o d J SHSE_Contrarian_Quintile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 0.050.10.150.20.250.3Holding Period K E s t i m a t i o n P er i o d J SZSE_Loser_Quintile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 00.050.10.150.20.250.3 Holding Period K E s t i m a t i o n P er i o d J SZSE_Winner_Quintile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 00.050.10.150.20.250.3 Holding Period K E s t i m a t i o n P er i o d J SZSE_Contrarian_Quintile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 00.050.10.150.20.250.3
Figure S1.
The contour figures, including the top panel for the case of SHSE and the bottom panelfor the SZSE, show the results of strategy portfolios based on the quintile grouping. The figures fromleft to right corresponds to the case of
LOS KJ , W IN KJ and CON KJ , J, K ∈ {
J, K | J, K = 1 , ∗ N, N = 1 , , ..., } . The sample period is from January 1997 to December2012. Holding Period K E s t i m a t i o n P er i o d J SHSE_Loser_Tertile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 0.050.10.150.20.250.3 Holding Period K E s t i m a t i o n P er i o d J SHSE_Winner_Tertile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 0.050.10.150.20.250.3 Holding Period K E s t i m a t i o n P er i o d J SHSE_Contrarian_Tertile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 0.050.10.150.20.250.3Holding Period K E s t i m a t i o n P er i o d J SZSE_Loser_Tertile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 0.050.10.150.20.250.3 Holding Period K E s t i m a t i o n P er i o d J SZSE_Winner_Tertile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 0.050.10.150.20.250.3 Holding Period K E s t i m a t i o n P er i o d J SZSE_Contrarian_Tertile
1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 1 3 6 912151821242730333639424548 0.050.10.150.20.250.3
Figure S2.
The contour figures, including the top panel for the case of SHSE and the bottom panelfor the SZSE, show the results of strategy portfolios based on the tertile grouping. The figures from leftto right corresponds to the case of
LOS KJ , W IN KJ and CON KJ , J, K ∈ {
J, K | J, K = 1 , ∗ N, N = 1 , , ..., } . The sample period is from January 1997 to December2012. Holding Period K E s t i m a t i o n P er i o d J SHSE_Contrarian_Decile
1 6 12 18 24 30 36 42 48 1 612182430364248 −0.0500.050.10.15 Holding Period K E s t i m a t i o n P er i o d J SHSE_Contrarian_Quintile
1 6 12 18 24 30 36 42 48 1 612182430364248 −0.04−0.0200.020.040.060.080.10.120.14 Holding Period K E s t i m a t i o n P er i o d J SHSE_Contrarian_Tertile
1 6 12 18 24 30 36 42 48 1 612182430364248 −0.0200.020.040.060.080.1Holding Period K E s t i m a t i o n P er i o d J SZSE_Contrarian_Decile
1 6 12 18 24 30 36 42 48 1 612182430364248 −0.04−0.0200.020.040.060.080.10.120.14 Holding Period K E s t i m a t i o n P er i o d J SZSE_Contrarian_Quintile
1 6 12 18 24 30 36 42 48 1 612182430364248 −0.0200.020.040.060.080.1
Holding Period K E s t i m a t i o n P er i o d J SZSE_Contrarian_Tertile
1 6 12 18 24 30 36 42 48 1 612182430364248 00.010.020.030.040.050.060.070.080.09
Figure S3.
The contour figures, including the top panel for the case of SHSE and the bottom panelfor the SZSE, show the results of
CON s based on the three different grouping ways during the firstsubperiod. The sample period is from January 1997 to September 2007. The figures from left to rightcorresponds to the cases based on decile grouping, quintile grouping and tertile grouping.
J, K ∈ {
J, K | J, K = 1 , ∗ N, N = 1 , , ..., } Holding Period K E s t i m a t i o n P er i o d J SHSE_Contrarian_Decile
1 6 12 18 24 30 36 42 48 1 612182430364248 0.050.10.150.20.25 Holding Period K E s t i m a t i o n P er i o d J SHSE_Contrarian_Quintile
1 6 12 18 24 30 36 42 48 1 612182430364248 0.020.040.060.080.10.120.140.160.180.20.22 Holding Period K E s t i m a t i o n P er i o d J SHSE_Contrarian_Tertile
1 6 12 18 24 30 36 42 48 1 612182430364248 0.020.040.060.080.10.120.140.160.18Holding Period K E s t i m a t i o n P er i o d J SZSE_Contrarian_Decile
1 6 12 18 24 30 36 42 48 1 612182430364248 0.050.10.150.20.250.30.350.4 Holding Period K E s t i m a t i o n P er i o d J SZSE_Contrarian_Quintile
1 6 12 18 24 30 36 42 48 1 612182430364248 0.050.10.150.20.25 Holding Period K E s t i m a t i o n P er i o d J SZSE_Contrarian_Tertile
1 6 12 18 24 30 36 42 48 1 612182430364248 0.020.040.060.080.10.120.140.160.180.20.22
Figure S4.
The contour figures, including the top panel for the case of SHSE and the bottom panelfor the SZSE, show the results of
CON s based on the three different grouping ways during the secondsubperiod. The sample period is from October 2007 to December 2012. The figures from left to rightcorresponds to the cases based on decile grouping, quintile grouping and tertile grouping.
J, K ∈ {
J, K | J, K = 1 , ∗ N, N = 1 , , ..., } . Holding Period K E s t i m a t i o n P er i o d J SHSE_Contrarian_Decile
1 6 12 18 24 30 36 42 48 1 612182430364248 −0.0200.020.040.060.080.10.120.140.160.18
Holding Period K E s t i m a t i o n P er i o d J SHSE_Contrarian_Quintile
1 6 12 18 24 30 36 42 48 1 612182430364248 00.020.040.060.080.10.12 Holding Period K E s t i m a t i o n P er i o d J SHSE_Contrarian_Tertile
1 6 12 18 24 30 36 42 48 1 612182430364248 00.020.040.060.080.1Holding Period K E s t i m a t i o n P er i o d J SZSE_Contrarian_Decile
1 6 12 18 24 30 36 42 48 1 612182430364248 00.020.040.060.080.10.120.140.160.18 Holding Period K E s t i m a t i o n P er i o d J SZSE_Contrarian_Quintile
1 6 12 18 24 30 36 42 48 1 612182430364248 0.020.040.060.080.10.12 Holding Period K E s t i m a t i o n P er i o d J SZSE_Contrarian_Tertile
1 6 12 18 24 30 36 42 48 1 612182430364248 0.010.020.030.040.050.060.070.080.090.1
Figure S5.
The contour figures, including the top panel for the case of SHSE and the bottom panelfor the SZSE, show the results of
CON s based on the three different grouping ways when skipping onemonth between estimation and holding period. The sample period is from January 1997 to December2012. The figures from left to right corresponds to the cases based on decile grouping, quintile groupingand tertile grouping.
J, K ∈ {
J, K | J, K = 1 , ∗ N, N = 1 , , ..., } . Table S1.
The annualized returns of the loser, winner, and contrarian portfolios on the SHSE formed based on J -month lagged returnsand held for K months by adopting the quintile grouping for the whole sample period 1997-2012. K = 1 6 12 18 24 30 36 42 48 J Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat
Panel A: Loser portfolio ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
12 0.227 2.11 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
18 0.245 2.28 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.245 2.28 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.271 2.47 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.281 2.57 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.285 2.58 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.281 2.56 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B: Winner portfolio ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗
12 0.147 1.52 0.168 1.86 0.190 2.09 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗
18 0.123 1.28 0.156 1.73 0.181 1.99 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗
24 0.119 1.24 0.155 1.70 0.175 1.93 0.191 2.04 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗
30 0.120 1.24 0.146 1.62 0.170 1.89 0.188 1.99 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗
36 0.118 1.21 0.145 1.60 0.169 1.86 0.185 1.96 0.195 2.07 ∗ ∗ ∗∗ ∗∗ ∗∗
42 0.116 1.19 0.148 1.62 0.169 1.86 0.185 1.97 0.199 2.10 ∗ ∗ ∗∗ ∗∗ ∗∗
48 0.120 1.22 0.139 1.53 0.168 1.85 0.190 2.02 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ Panel C: Contrarian portfolio ∗∗ ∗ ∗ ∗ ∗∗ ∗ ∗∗ ∗ ∗ ∗ ∗∗
18 0.122 2.76 ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.126 2.82 ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.151 3.27 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.164 3.44 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.169 3.31 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.161 3.24 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ This table reports the average annualized returns and the corresponding t-statistics adjusted for heteroscedasticity and autocorrelation of theloser, winner and contrarian portfolios, which are formed by ranking the stocks based on their J -month lagged returns, adopting the quintilegrouping, and holding for K months. The values of J and K for different strategies are indicated in the first collum and the first row respectively.The sample period is January 1997 to December 2012. The superscripts * and ** denote the significance at 5% and 1% levels, respectively. Table S2.
The annualized returns of the loser, winner, and contrarian portfolios on the SZSE formed based on J -month lagged returnsand held for K months by adopting the quintile grouping for the whole sample period 1997-2012. K = 1 6 12 18 24 30 36 42 48 J Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat
Panel A: Loser portfolio ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗
12 0.242 2.16 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
18 0.260 2.36 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.259 2.36 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.265 2.44 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.277 2.52 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.302 2.66 ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.292 2.61 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B: Winner portfolio ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗
12 0.144 1.48 0.160 1.69 0.193 1.93 0.217 2.07 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗
18 0.107 1.10 0.147 1.55 0.180 1.83 0.207 1.96 0.222 2.13 ∗ ∗ ∗∗ ∗∗ ∗∗
24 0.108 1.10 0.149 1.55 0.177 1.83 0.208 1.92 0.217 2.03 ∗ ∗ ∗∗ ∗∗ ∗∗
30 0.121 1.21 0.152 1.58 0.187 1.86 0.213 1.93 0.218 2.01 ∗ ∗ ∗∗ ∗∗ ∗∗
36 0.125 1.25 0.161 1.65 0.194 1.90 0.213 1.95 0.218 2.02 ∗ ∗ ∗∗ ∗∗ ∗∗
42 0.134 1.32 0.156 1.59 0.189 1.83 0.209 1.90 0.218 2.00 ∗ ∗ ∗∗ ∗∗ ∗∗
48 0.121 1.16 0.150 1.53 0.180 1.76 0.204 1.85 0.212 1.93 0.198 2.19 ∗ ∗ ∗∗ ∗∗ Panel C: Contrarian portfolio ∗∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗ ∗∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗ ∗∗
24 0.151 2.86 ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.144 2.68 ∗∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.151 2.73 ∗∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.168 3.02 ∗∗ ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.172 2.98 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ This table reports the average annualized returns and the corresponding t-statistics adjusted for heteroscedasticity and autocorrelation of theloser, winner and contrarian portfolios, which are formed by ranking the stocks based on their J -month lagged returns, adopting the quintilegrouping, and holding for K months. The values of J and K for different strategies are indicated in the first collum and the first row respectively.The sample period is January 1997 to December 2012. The superscripts * and ** denote the significance at 5% and 1% levels, respectively. Table S3.
The annualized returns of the loser, winner, and contrarian portfolios on the SHSE formed based on J -month lagged returnsand held for K months by adopting the tertile grouping for the whole sample period 1997-2012. K = 1 6 12 18 24 30 36 42 48 J Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat
Panel A: Loser portfolio ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
12 0.220 2.06 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
18 0.238 2.25 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.245 2.28 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.253 2.36 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.275 2.54 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.264 2.45 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.262 2.43 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B: Winner portfolio ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗
12 0.148 1.52 0.177 1.90 0.204 2.20 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗
18 0.138 1.42 0.170 1.84 0.201 2.17 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.131 1.35 0.166 1.79 0.193 2.09 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.123 1.27 0.157 1.72 0.185 2.03 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.124 1.27 0.155 1.69 0.184 2.01 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗
42 0.123 1.26 0.159 1.72 0.186 2.02 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗
48 0.136 1.37 0.163 1.75 0.192 2.05 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel C: Contrarian portfolio ∗∗ ∗ ∗∗ ∗ ∗ ∗∗ ∗ ∗ ∗ ∗∗
18 0.101 2.90 ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.114 3.23 ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.129 3.61 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.151 4.18 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.141 3.77 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.127 3.36 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ This table reports the average annualized returns and the corresponding t-statistics adjusted for heteroscedasticity and autocorrelation of theloser, winner and contrarian portfolios, which are formed by ranking the stocks based on their J -month lagged returns, adopting the tertilegrouping, and holding for K months. The values of J and K for different strategies are indicated in the first collum and the first row respectively.The sample period is January 1997 to December 2012. The superscripts * and ** denote the significance at 5% and 1% levels, respectively. Table S4.
The annualized returns of the loser, winner, and contrarian portfolios on the SZSE formed based on J -month lagged returnsand held for K months by adopting the tertile grouping for the whole sample period 1997-2012. K = 1 6 12 18 24 30 36 42 48 J Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat Return t-stat
Panel A: Loser portfolio ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
12 0.232 2.08 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
18 0.245 2.24 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.250 2.29 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.254 2.32 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.255 2.35 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.270 2.43 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.264 2.38 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B: Winner portfolio ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗
12 0.139 1.41 0.163 1.71 0.202 2.05 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗
18 0.124 1.26 0.159 1.65 0.197 2.01 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.120 1.23 0.156 1.62 0.191 1.96 0.222 2.11 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗
30 0.117 1.19 0.153 1.60 0.197 1.99 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗
36 0.127 1.27 0.166 1.69 0.198 2.00 ∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗∗
42 0.120 1.20 0.159 1.62 0.191 1.91 0.214 2.02 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗
48 0.133 1.31 0.159 1.62 0.190 1.89 0.210 1.99 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ Panel C: Contrarian portfolio ∗∗ ∗∗ ∗ ∗ ∗ ∗∗ ∗∗ ∗ ∗∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗ ∗ ∗
24 0.130 3.13 ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗ ∗
30 0.137 3.23 ∗∗ ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗
36 0.128 3.02 ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.150 3.57 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.131 2.84 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ This table reports the average annualized returns and the corresponding t-statistics adjusted for heteroscedasticity and autocorrelation of theloser, winner and contrarian portfolios, which are formed by ranking the stocks based on their J -month lagged returns, adopting the tertilegrouping, and holding for K months. The values of J and K for different strategies are indicated in the first collum and the first row respectively.The sample period is January 1997 to December 2012. The superscripts * and ** denote the significance at 5% and 1% levels, respectively. Table S5.
The return difference of loser portfolios formed based on different grouping ways of the SHSE stocks. K = 1 6 12 18 24 30 36 42 48 J ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat Panel A: G − G ∗∗ -0.005 -2.17 ∗ -0.007 -2.47 ∗ -0.000 -0.10 -0.000 -0.08 0.001 0.36 0.002 1.02 0.001 0.5112 0.007 0.99 -0.007 -2.27 ∗ -0.005 -1.96 -0.006 -2.44 ∗ -0.005 -2.14 ∗ -0.002 -1.00 0.001 0.50 -0.001 -0.24 -0.000 -0.1418 0.007 0.93 -0.004 -1.22 0.001 0.33 0.001 0.49 0.002 0.86 0.003 1.13 0.006 2.36 ∗ ∗ ∗
24 -0.000 -0.01 -0.001 -0.35 0.005 1.82 0.004 1.49 0.004 1.59 0.004 1.53 0.006 2.78 ∗∗ ∗∗ ∗∗
30 0.018 2.31 ∗ ∗ ∗∗ ∗∗ ∗ ∗∗ ∗∗ ∗∗
36 0.006 0.67 0.010 2.80 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.021 2.42 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.019 1.99 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B: G − G ∗∗ -0.007 -1.85 -0.007 -1.73 -0.007 -1.84 -0.004 -0.97 -0.001 -0.23 -0.003 -0.7012 -0.006 -0.58 -0.013 -2.65 ∗∗ -0.016 -4.29 ∗∗ -0.009 -2.53 ∗ -0.005 -1.36 0.000 0.05 0.010 2.77 ∗∗ ∗∗ ∗∗
18 0.002 0.19 -0.014 -2.45 ∗ -0.011 -2.37 ∗ -0.010 -2.01 ∗ -0.011 -2.16 ∗ -0.005 -1.10 0.003 0.64 0.008 1.86 0.008 1.7624 0.004 0.37 -0.009 -1.49 -0.007 -1.45 -0.005 -1.08 -0.002 -0.51 0.004 0.96 0.007 1.93 0.011 2.37 ∗ ∗∗
30 0.007 0.56 0.006 1.08 0.002 0.53 0.006 1.47 0.010 2.72 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.022 1.74 0.005 0.64 0.005 1.19 0.008 1.92 0.015 3.36 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.016 1.13 0.013 1.81 0.013 2.30 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.023 1.38 0.012 1.47 0.015 2.32 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel C: G − G ∗ -0.018 -3.67 ∗∗ -0.014 -2.73 ∗∗ -0.007 -1.42 -0.007 -1.48 -0.003 -0.67 0.001 0.28 -0.002 -0.3512 0.001 0.05 -0.020 -3.12 ∗∗ -0.021 -4.06 ∗∗ -0.015 -3.01 ∗∗ -0.011 -2.00 ∗ -0.002 -0.46 0.012 2.45 ∗ ∗ -0.010 -1.61 -0.009 -1.52 -0.009 -1.50 -0.003 -0.47 0.008 1.69 0.013 2.41 ∗ ∗
24 0.004 0.26 -0.010 -1.31 -0.002 -0.32 -0.001 -0.21 0.002 0.28 0.007 1.45 0.014 2.66 ∗∗ ∗∗ ∗∗
30 0.025 1.49 0.011 1.49 0.009 1.66 0.013 2.75 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.028 1.56 0.014 1.59 0.017 3.11 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.037 1.97 0.026 2.98 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.041 1.84 0.028 2.79 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ This table reports the differences of the average annualized returns and the corresponding t-statistics adjusted for heteroscedasticity andautocorrelation of two loser strategies that are different only in the grouping methods for SHSE stocks. The three panels are for the loser,winner and contrarian portfolios, respectively. In the first row, G , G and G stand for tertile, quintile and decile groupings. The sampleperiod is January 1997 to December 2012. The superscripts * and ** denote the significance at 5% and 1% levels, respectively. Table S6.
The return difference of loser portfolios formed based on different grouping ways of the SZSE stocks. K = 1 6 12 18 24 30 36 42 48 J ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat Panel A: G − G ∗ -0.008 -3.33 ∗∗ -0.009 -3.10 ∗∗ -0.009 -2.98 ∗∗ -0.002 -0.75 -0.003 -1.02 -0.001 -0.21 -0.001 -0.626 -0.001 -0.06 -0.009 -2.08 ∗ -0.009 -2.82 ∗∗ -0.011 -3.50 ∗∗ -0.008 -2.66 ∗∗ -0.002 -0.80 -0.001 -0.46 0.002 0.74 0.001 0.2812 0.011 1.35 -0.003 -0.73 -0.001 -0.19 -0.001 -0.32 0.009 2.23 ∗ ∗∗ ∗∗ ∗∗ ∗∗
18 0.016 1.47 0.006 1.62 0.011 3.28 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.009 0.94 0.003 0.78 0.010 2.79 ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.010 1.07 0.009 2.54 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.022 2.07 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.032 2.52 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.029 1.99 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B: G − G ∗∗ -0.009 -1.94 -0.010 -2.43 ∗ -0.008 -1.63 -0.002 -0.54 0.000 0.07 -0.002 -0.546 -0.003 -0.20 -0.014 -2.34 ∗ -0.006 -1.40 -0.006 -1.46 -0.002 -0.47 0.008 1.98 0.008 1.82 0.005 1.33 0.007 1.8412 0.022 1.44 -0.010 -1.90 -0.005 -1.12 -0.007 -1.21 0.003 0.73 0.014 2.45 ∗ ∗ ∗ ∗∗
18 0.001 0.07 -0.007 -1.10 -0.005 -0.93 -0.004 -0.58 0.007 1.00 0.015 2.28 ∗ ∗∗ ∗∗ ∗∗
24 0.025 1.46 0.003 0.43 -0.004 -0.50 0.009 1.31 0.026 3.79 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.016 0.98 0.014 2.11 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.024 1.39 0.023 2.80 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.034 1.42 0.033 3.17 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.033 1.12 0.027 2.48 ∗ ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel C: G − G ∗∗ -0.018 -2.69 ∗∗ -0.019 -3.34 ∗∗ -0.010 -2.00 ∗ -0.005 -1.01 -0.000 -0.05 -0.004 -0.756 -0.003 -0.17 -0.023 -2.61 ∗ -0.016 -2.58 ∗ -0.017 -2.79 ∗∗ -0.010 -1.83 0.006 1.05 0.006 1.19 0.008 1.32 0.008 1.4612 0.032 1.62 -0.013 -1.68 -0.006 -0.85 -0.008 -1.00 0.012 1.86 0.025 3.42 ∗∗ ∗∗ ∗∗ ∗∗
18 0.017 0.81 -0.001 -0.08 0.005 0.67 0.006 0.74 0.023 2.64 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.034 1.51 0.006 0.63 0.006 0.80 0.017 1.93 0.040 4.08 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.026 1.17 0.023 2.71 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.045 1.91 0.041 3.47 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.066 1.96 0.051 3.50 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.061 1.62 0.051 3.44 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ This table reports the differences of the average annualized returns and the corresponding t-statistics adjusted for heteroscedasticity andautocorrelation of two loser strategies that are different only in the grouping methods for SZSE stocks. The three panels are for the loser,winner and contrarian portfolios, respectively. In the first row, G , G and G stand for tertile, quintile and decile groupings. The sampleperiod is January 1997 to December 2012. The superscripts * and ** denote the significance at 5% and 1% levels, respectively. Table S7.
The return difference of winner portfolios formed based on different grouping ways of the SHSE stocks. K = 1 6 12 18 24 30 36 42 48 J ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat Panel A: G − G ∗ -0.011 -3.37 ∗∗ -0.008 -2.85 ∗∗ -0.009 -3.84 ∗∗ -0.009 -3.88 ∗∗ -0.009 -3.71 ∗∗ -0.006 -2.48 ∗ -0.004 -1.66 -0.003 -1.066 -0.011 -1.33 -0.007 -2.07 ∗ -0.008 -2.68 ∗∗ -0.010 -4.30 ∗∗ -0.014 -6.00 ∗∗ -0.010 -3.90 ∗∗ -0.005 -1.79 -0.007 -2.81 ∗∗ -0.009 -3.98 ∗∗
12 -0.000 -0.03 -0.009 -2.28 ∗ -0.014 -4.43 ∗∗ -0.016 -5.21 ∗∗ -0.017 -6.27 ∗∗ -0.013 -4.61 ∗∗ -0.006 -1.81 -0.008 -2.66 ∗∗ -0.010 -3.79 ∗∗
18 -0.015 -1.69 -0.014 -3.78 ∗∗ -0.019 -6.29 ∗∗ -0.020 -7.57 ∗∗ -0.020 -7.92 ∗∗ -0.017 -6.20 ∗∗ -0.013 -4.66 ∗∗ -0.016 -7.28 ∗∗ -0.016 -7.11 ∗∗
24 -0.012 -1.38 -0.011 -2.71 ∗∗ -0.017 -5.50 ∗∗ -0.021 -8.39 ∗∗ -0.024 -8.80 ∗∗ -0.021 -8.79 ∗∗ -0.015 -5.76 ∗∗ -0.018 -7.86 ∗∗ -0.018 -8.96 ∗∗
30 -0.004 -0.38 -0.011 -2.56 ∗ -0.015 -5.09 ∗∗ -0.018 -6.84 ∗∗ -0.020 -7.22 ∗∗ -0.016 -5.68 ∗∗ -0.013 -4.26 ∗∗ -0.014 -6.07 ∗∗ -0.014 -6.59 ∗∗
36 -0.006 -0.70 -0.010 -2.67 ∗∗ -0.015 -4.62 ∗∗ -0.019 -6.86 ∗∗ -0.018 -6.32 ∗∗ -0.013 -4.13 ∗∗ -0.009 -3.16 ∗∗ -0.012 -4.95 ∗∗ -0.015 -7.30 ∗∗
42 -0.007 -0.73 -0.012 -2.92 ∗∗ -0.016 -5.21 ∗∗ -0.022 -7.95 ∗∗ -0.017 -6.75 ∗∗ -0.013 -4.72 ∗∗ -0.010 -4.30 ∗∗ -0.009 -3.26 ∗∗ -0.014 -4.99 ∗∗
48 -0.016 -1.33 -0.024 -4.96 ∗∗ -0.024 -7.29 ∗∗ -0.023 -7.41 ∗∗ -0.020 -7.30 ∗∗ -0.016 -5.15 ∗∗ -0.013 -4.65 ∗∗ -0.012 -3.62 ∗∗ -0.012 -3.46 ∗∗ Panel B: G − G ∗ -0.017 -4.31 ∗∗ -0.015 -4.24 ∗∗ -0.014 -4.60 ∗∗ -0.017 -5.31 ∗∗ -0.013 -3.97 ∗∗ -0.007 -1.97 -0.008 -2.23 ∗
12 -0.007 -0.66 -0.003 -0.55 -0.005 -1.27 -0.009 -2.60 ∗ -0.013 -3.78 ∗∗ -0.009 -2.64 ∗∗ -0.007 -1.52 -0.007 -1.45 -0.016 -4.31 ∗∗
18 -0.005 -0.38 -0.009 -1.50 -0.012 -2.77 ∗∗ -0.015 -3.98 ∗∗ -0.015 -4.08 ∗∗ -0.015 -3.64 ∗∗ -0.009 -2.09 ∗ -0.012 -3.11 ∗∗ -0.016 -4.87 ∗∗
24 -0.004 -0.35 -0.013 -2.21 ∗ -0.012 -2.83 ∗∗ -0.014 -4.10 ∗∗ -0.009 -2.31 ∗ -0.012 -3.05 ∗∗ -0.010 -2.92 ∗∗ -0.010 -2.87 ∗∗ -0.010 -3.43 ∗∗
30 -0.028 -2.29 ∗ -0.015 -3.09 ∗∗ -0.015 -3.63 ∗∗ -0.013 -3.38 ∗∗ -0.010 -2.81 ∗∗ -0.009 -2.49 ∗ -0.007 -2.06 ∗ -0.008 -2.30 ∗ -0.010 -3.23 ∗∗
36 -0.014 -1.02 -0.006 -1.00 -0.006 -1.35 -0.006 -1.53 -0.005 -1.17 -0.004 -0.90 -0.005 -1.63 -0.008 -2.70 ∗∗ -0.013 -4.62 ∗∗
42 -0.006 -0.48 -0.016 -2.29 ∗ -0.011 -2.41 ∗ -0.004 -0.79 -0.005 -0.97 -0.005 -1.03 -0.008 -1.96 -0.017 -4.51 ∗∗ -0.021 -5.63 ∗∗
48 -0.025 -1.61 -0.021 -3.08 ∗∗ -0.010 -2.09 ∗ -0.006 -1.19 -0.008 -1.55 -0.009 -1.79 -0.008 -1.70 -0.019 -4.27 ∗∗ -0.025 -4.75 ∗∗ Panel C: G − G ∗ -0.019 -3.08 ∗∗ -0.014 -2.54 ∗ -0.014 -2.53 ∗ -0.015 -3.32 ∗∗ -0.011 -2.07 ∗ -0.007 -1.42 -0.002 -0.55 -0.002 -0.496 -0.026 -1.51 -0.018 -2.50 ∗ -0.025 -4.45 ∗∗ -0.025 -5.25 ∗∗ -0.028 -6.69 ∗∗ -0.027 -6.22 ∗∗ -0.017 -3.83 ∗∗ -0.014 -2.73 ∗∗ -0.017 -3.50 ∗∗
12 -0.007 -0.44 -0.012 -1.51 -0.019 -3.15 ∗∗ -0.025 -4.72 ∗∗ -0.029 -6.25 ∗∗ -0.022 -4.25 ∗∗ -0.013 -1.87 -0.015 -2.15 ∗ -0.026 -5.19 ∗∗
18 -0.019 -1.08 -0.023 -2.79 ∗∗ -0.031 -4.92 ∗∗ -0.035 -6.74 ∗∗ -0.035 -7.10 ∗∗ -0.031 -5.46 ∗∗ -0.022 -3.42 ∗∗ -0.028 -5.49 ∗∗ -0.032 -7.42 ∗∗
24 -0.016 -0.90 -0.023 -2.84 ∗∗ -0.029 -4.76 ∗∗ -0.035 -7.20 ∗∗ -0.032 -6.87 ∗∗ -0.032 -7.09 ∗∗ -0.025 -4.98 ∗∗ -0.027 -5.81 ∗∗ -0.029 -6.87 ∗∗
30 -0.031 -1.64 -0.026 -3.33 ∗∗ -0.029 -4.87 ∗∗ -0.032 -5.98 ∗∗ -0.030 -5.86 ∗∗ -0.025 -4.71 ∗∗ -0.019 -3.53 ∗∗ -0.021 -4.63 ∗∗ -0.024 -5.66 ∗∗
36 -0.021 -1.03 -0.016 -1.86 -0.021 -3.07 ∗∗ -0.025 -4.46 ∗∗ -0.023 -3.85 ∗∗ -0.016 -2.49 ∗ -0.014 -2.65 ∗∗ -0.019 -4.79 ∗∗ -0.028 -6.90 ∗∗
42 -0.013 -0.69 -0.027 -2.85 ∗∗ -0.028 -4.34 ∗∗ -0.026 -4.57 ∗∗ -0.022 -3.45 ∗∗ -0.018 -2.87 ∗∗ -0.018 -3.56 ∗∗ -0.026 -6.00 ∗∗ -0.035 -8.04 ∗∗
48 -0.041 -2.10 ∗ -0.045 -4.40 ∗∗ -0.034 -5.14 ∗∗ -0.029 -4.99 ∗∗ -0.028 -4.63 ∗∗ -0.025 -4.63 ∗∗ -0.021 -3.58 ∗∗ -0.031 -6.31 ∗∗ -0.037 -8.01 ∗∗ This table reports the differences of the average annualized returns and the corresponding t-statistics adjusted for heteroscedasticity andautocorrelation of two winner strategies that are different only in the grouping methods for SHSE stocks. The three panels are for the loser,winner and contrarian portfolios, respectively. In the first row, G , G and G stand for tertile, quintile and decile groupings. The sampleperiod is January 1997 to December 2012. The superscripts * and ** denote the significance at 5% and 1% levels, respectively. Table S8.
The return difference of winner portfolios formed based on different grouping ways of the SZSE stocks. K = 1 6 12 18 24 30 36 42 48 J ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat Panel A: G − G ∗∗ -0.014 -4.85 ∗∗ -0.012 -4.21 ∗∗ -0.011 -3.69 ∗∗ -0.008 -3.18 ∗∗ -0.008 -3.46 ∗∗ -0.008 -3.66 ∗∗ -0.008 -3.14 ∗∗ ∗ -0.011 -3.24 ∗∗ -0.006 -2.14 ∗ -0.000 -0.12 -0.003 -0.8712 0.006 0.54 -0.003 -0.86 -0.009 -2.66 ∗∗ -0.010 -2.29 ∗ -0.015 -4.19 ∗∗ -0.014 -4.55 ∗∗ -0.008 -2.39 ∗ -0.005 -1.43 -0.007 -2.31 ∗
18 -0.017 -1.58 -0.012 -2.73 ∗∗ -0.017 -5.44 ∗∗ -0.017 -4.74 ∗∗ -0.014 -3.76 ∗∗ -0.012 -3.38 ∗∗ -0.012 -3.20 ∗∗ -0.012 -3.32 ∗∗ -0.013 -4.95 ∗∗
24 -0.012 -1.14 -0.008 -1.58 -0.013 -3.86 ∗∗ -0.013 -2.86 ∗∗ -0.013 -2.72 ∗∗ -0.011 -2.83 ∗∗ -0.012 -3.12 ∗∗ -0.012 -3.88 ∗∗ -0.014 -4.67 ∗∗
30 0.004 0.31 -0.001 -0.22 -0.011 -2.54 ∗ -0.008 -1.64 -0.011 -2.13 ∗ -0.013 -3.25 ∗∗ -0.011 -3.08 ∗∗ -0.008 -2.68 ∗∗ -0.009 -2.79 ∗∗
36 -0.001 -0.09 -0.004 -0.79 -0.005 -1.01 -0.004 -0.99 -0.009 -2.13 ∗ -0.009 -2.64 ∗∗ -0.008 -3.08 ∗∗ -0.008 -3.16 ∗∗ -0.009 -3.51 ∗∗
42 0.014 1.18 -0.004 -0.64 -0.002 -0.41 -0.004 -1.00 -0.006 -1.27 -0.008 -2.55 ∗ -0.010 -3.01 ∗∗ -0.009 -2.86 ∗∗ -0.009 -3.33 ∗∗
48 -0.013 -0.99 -0.010 -1.52 -0.009 -2.03 ∗ -0.006 -1.26 -0.008 -1.93 -0.015 -4.12 ∗∗ -0.015 -4.94 ∗∗ -0.010 -3.17 ∗∗ -0.011 -4.41 ∗∗ Panel B: G − G ∗ -0.007 -1.33 -0.011 -2.43 ∗ -0.016 -3.52 ∗∗ -0.017 -4.48 ∗∗ -0.010 -2.24 ∗ -0.011 -2.56 ∗
12 -0.003 -0.23 -0.002 -0.31 -0.005 -1.09 -0.009 -2.28 ∗ -0.014 -2.67 ∗∗ -0.011 -2.20 ∗ -0.007 -1.51 -0.007 -1.78 -0.008 -2.27 ∗
18 0.002 0.14 -0.001 -0.19 -0.004 -0.81 -0.008 -1.80 -0.009 -1.88 -0.006 -1.66 -0.003 -0.62 -0.004 -0.98 -0.009 -2.39 ∗
24 0.012 0.65 0.001 0.21 -0.004 -0.76 -0.006 -1.12 -0.000 -0.03 -0.004 -0.84 -0.007 -1.63 -0.010 -2.13 ∗ -0.011 -2.13 ∗
30 -0.005 -0.33 -0.007 -0.93 -0.001 -0.24 0.004 0.73 0.002 0.31 -0.011 -2.29 ∗ -0.017 -4.13 ∗∗ -0.013 -3.01 ∗∗ -0.011 -2.41 ∗
36 0.024 1.59 0.006 0.79 0.007 1.03 0.005 0.67 -0.003 -0.49 -0.014 -3.06 ∗∗ -0.015 -3.74 ∗∗ -0.014 -3.43 ∗∗ -0.016 -4.37 ∗∗
42 -0.004 -0.27 0.017 2.10 ∗ ∗∗ -0.016 -3.57 ∗∗ -0.013 -2.77 ∗∗ -0.018 -3.77 ∗∗
48 -0.006 -0.36 0.008 0.85 0.004 0.40 -0.007 -1.02 -0.016 -3.03 ∗∗ -0.015 -3.24 ∗∗ -0.013 -3.61 ∗∗ -0.015 -3.65 ∗∗ -0.018 -3.73 ∗∗ Panel C: G − G ∗ -0.018 -3.00 ∗∗ -0.013 -1.93 -0.015 -2.20 ∗ -0.012 -2.07 ∗ -0.011 -2.02 ∗ -0.010 -2.05 ∗ -0.008 -1.696 -0.019 -0.92 -0.014 -1.56 -0.017 -2.44 ∗ -0.013 -1.80 -0.020 -2.94 ∗∗ -0.027 -4.22 ∗∗ -0.023 -4.53 ∗∗ -0.010 -1.60 -0.014 -2.20 ∗
12 0.003 0.13 -0.005 -0.59 -0.015 -2.06 ∗ -0.020 -2.90 ∗∗ -0.029 -4.61 ∗∗ -0.025 -3.90 ∗∗ -0.015 -2.46 ∗ -0.012 -1.98 -0.015 -2.82 ∗∗
18 -0.015 -0.67 -0.013 -1.37 -0.022 -3.07 ∗∗ -0.025 -3.86 ∗∗ -0.023 -3.23 ∗∗ -0.018 -3.02 ∗∗ -0.014 -2.19 ∗ -0.016 -2.40 ∗ -0.022 -4.19 ∗∗
24 -0.001 -0.02 -0.006 -0.63 -0.017 -2.36 ∗ -0.019 -2.37 ∗ -0.013 -1.47 -0.015 -2.17 ∗ -0.019 -2.80 ∗∗ -0.022 -3.36 ∗∗ -0.025 -3.73 ∗∗
30 -0.002 -0.07 -0.008 -0.71 -0.012 -1.38 -0.004 -0.43 -0.009 -0.85 -0.024 -3.16 ∗∗ -0.028 -4.37 ∗∗ -0.021 -3.50 ∗∗ -0.020 -3.37 ∗∗
36 0.023 0.94 0.001 0.10 0.002 0.21 0.001 0.06 -0.012 -1.27 -0.023 -3.65 ∗∗ -0.023 -4.44 ∗∗ -0.022 -4.15 ∗∗ -0.025 -5.14 ∗∗
42 0.010 0.43 0.014 1.15 0.010 0.87 -0.002 -0.20 -0.015 -1.73 -0.026 -4.17 ∗∗ -0.025 -4.56 ∗∗ -0.021 -3.60 ∗∗ -0.027 -4.98 ∗∗
48 -0.018 -0.76 -0.002 -0.15 -0.006 -0.46 -0.013 -1.31 -0.024 -3.21 ∗∗ -0.030 -4.86 ∗∗ -0.028 -5.68 ∗∗ -0.025 -4.95 ∗∗ -0.030 -5.36 ∗∗ This table reports the differences of the average annualized returns and the corresponding t-statistics adjusted for heteroscedasticity andautocorrelation of two winner strategies that are different only in the grouping methods for SZSE stocks. The three panels are for the loser,winner and contrarian portfolios, respectively. In the first row, G , G and G stand for tertile, quintile and decile groupings. The sampleperiod is January 1997 to December 2012. The superscripts * and ** denote the significance at 5% and 1% levels, respectively. Table S9.
The return difference of contrarian portfolios formed based on different grouping ways of the SHSE stocks. K = 1 6 12 18 24 30 36 42 48 J ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat Panel A: G − G ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗
12 0.007 0.55 0.002 0.44 0.009 2.05 ∗ ∗ ∗∗ ∗∗ ∗
18 0.021 1.82 0.010 1.82 0.020 4.65 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.012 0.96 0.009 1.85 0.022 4.86 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.022 1.61 0.016 2.88 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.012 0.88 0.020 3.66 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.028 1.84 0.025 3.93 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.034 2.16 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B: G − G ∗ ∗∗ ∗∗ ∗∗
18 0.007 0.38 -0.005 -0.61 0.001 0.15 0.005 0.67 0.004 0.70 0.009 1.35 0.012 1.83 0.020 3.38 ∗∗ ∗∗
24 0.009 0.51 0.004 0.46 0.005 0.75 0.009 1.36 0.006 0.86 0.015 2.44 ∗ ∗∗ ∗∗ ∗∗
30 0.035 2.00 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.036 1.91 0.011 1.27 0.012 1.87 0.014 2.36 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.022 1.26 0.028 3.49 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.048 2.26 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel C: G − G ∗∗ ∗∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
18 0.029 1.05 0.004 0.34 0.021 2.18 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.021 0.81 0.013 1.17 0.027 3.20 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.057 2.09 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.049 1.75 0.031 2.62 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.050 1.88 0.053 4.39 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.082 2.74 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ This table reports the differences of the average annualized returns and the corresponding t-statistics adjusted for heteroscedasticityand autocorrelation of two contrarian strategies that are different only in the grouping methods for SHSE stocks. The three panelsare for the loser, winner and contrarian portfolios, respectively. In the first row, G , G and G stand for tertile, quintile and decilegroupings. The sample period is January 1997 to December 2012. The superscripts * and ** denote the significance at 5% and 1%levels, respectively. Table S10.
The return difference of contrarian portfolios formed based on different grouping ways of the SZSE stocks. K = 1 6 12 18 24 30 36 42 48 J ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat ∆ R t-stat Panel A: G − G ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
18 0.033 2.08 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.021 1.42 0.010 1.69 0.023 4.30 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.007 0.44 0.011 1.44 0.021 3.66 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.023 1.34 0.022 2.65 ∗∗ ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.017 0.98 0.021 2.52 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.041 2.05 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel B: G − G ∗∗ ∗∗ ∗∗ ∗∗
12 0.025 1.23 -0.008 -0.91 0.000 0.04 0.003 0.32 0.017 2.27 ∗ ∗∗ ∗∗ ∗∗ ∗∗
18 -0.001 -0.06 -0.006 -0.68 -0.001 -0.15 0.004 0.53 0.016 1.85 0.021 2.82 ∗∗ ∗∗ ∗∗ ∗∗
24 0.014 0.57 0.002 0.20 0.001 0.06 0.014 1.56 0.026 2.92 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.021 0.95 0.020 2.02 ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗
36 -0.001 -0.03 0.018 1.51 0.015 1.28 0.021 1.82 0.031 2.96 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.038 1.28 0.016 1.08 0.019 1.39 0.025 2.05 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.039 1.13 0.019 1.29 0.021 1.55 0.025 1.83 0.039 3.31 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ Panel C: G − G ∗∗ ∗∗ ∗ ∗∗
12 0.029 1.01 -0.008 -0.63 0.009 0.80 0.012 0.93 0.041 4.15 ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
18 0.032 1.01 0.012 0.95 0.027 2.52 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
24 0.035 1.04 0.012 0.86 0.024 2.00 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
30 0.028 0.82 0.031 1.99 ∗ ∗∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
36 0.022 0.65 0.040 2.23 ∗ ∗ ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
42 0.055 1.31 0.037 1.80 0.038 2.05 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗
48 0.080 1.73 0.053 2.50 ∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ ∗∗ This table reports the differences of the average annualized returns and the corresponding t-statistics adjusted for heteroscedasticity andautocorrelation of two contrarian strategies that are different only in the grouping methods for SZSE stocks. The three panels are for theloser, winner and contrarian portfolios, respectively. In the first row, G , G and G10