A note on momentum and contrarian strategies across price limit regimes: Evidence from China's A-share market

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A note on momentum and contrarianstrategies across price limit regimes:Evidence from China's A-share marketPai-Lung Chou a , Chin-Chia Chang b & Jia-Jun Lin ca Department of Risk Management and Insurance , NationalKaohsiung First University of Science and Technology , No. 2 JhuoyueRd, Nanzih District Kaohsiung City , 811 , Taiwan R.O.C.b Institute of Finance and Banking , National Kaohsiung FirstUniversity of Science and Technology , No. 2 Jhuoyue Rd, NanzihDistrict Kaohsiung City , 811 , Taiwan R.O.C.c Department of Marketing and Logistics Management , ChaoyangUniversity of Technology , No. 2 Jhuoyue Rd, Nanzih DistrictKaohsiung City , 811 , Taiwan R.O.C.Published online: 18 Jun 2013.

To cite this article: Pai-Lung Chou , Chin-Chia Chang & Jia-Jun Lin (2011) A note on momentum andcontrarian strategies across price limit regimes: Evidence from China's A-share market, Journal ofInformation and Optimization Sciences, 32:5, 1185-1199, DOI: 10.1080/02522667.2011.10700113

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* E-mail: [email protected]† E-mail: [email protected]§ E-mail: [email protected]

A note on momentum and contrarian strategies across price limit regimes: Evidence from China’s A-share market

Pai-Lung Chou *

Department of Risk Management and InsuranceNational Kaohsiung First University of Science and TechnologyNo. 2 Jhuoyue Rd., Nanzih DistrictKaohsiung City 811Taiwan, R. O. C.

Chin-Chia Chang †

Institute of Finance and BankingNational Kaohsiung First University of Science and TechnologyNo. 2 Jhuoyue Rd., Nanzih DistrictKaohsiung City 811Taiwan, R. O. C.

Jia-Jun Lin §

Institute of ManagementNational Kaohsiung First University of Science and TechnologyNo. 2 Jhuoyue Rd., Nanzih DistrictKaohsiung City 811Taiwan, R. O. C.

AbstractThis paper applies stochastic dominance with and without risk-free assets to examine

the profi tability of momentum strategies in the wake of the regime transition after the imple-

mentation of price limits in China’s A-share market. According to our evidence, winner port-

folios stochastically dominate loser portfolios at the second-order stochastic dominance over

the horizon of 6 to 12 months with price limits. In contrast, higher returns appear on loser

portfolios that dominate the returns on winner portfolios without price limits. This evidence,

which agrees with the delayed price discovery hypothesis, gives rise to a positive autocor-

Journal of Information & Optimization SciencesVol. 32 (2011), No. 5, pp. 1185–1199

© Taru Publications

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1186 P. L. CHOU, C. C. CHANG AND J. J. LIN

relation of stock returns and provides the rationale for the stock prices of winner portfolios

that exhibit signifi cant price continuation phenomenon.

Keywords: Stochastic dominance; Momentum strategies; China’s A-share market; Price limitsJEL classifi cation: C14; G11; G14

1. Introduction

Ever since De Bondt and Thaler [2] and Jegadeesh and Titman [4]

drew academic attention to the overreaction and underreaction for US

stock market, and both of them have remained the most hotly debated

anomalies in the asset-pricing literatures. The stock market overreaction

hypothesis asserts that portfolios of prior losers are found to outperform

prior winners because most investors tend to overreact to the unexpected

and recent information. In contrast, the underreaction hypothesis is de-

fi ned as a situation that the stock price gradually corresponds the actual

implication of new information after a period of time, induced by individ-

uals fail to react to recent information completely. Jegadeesh and Titman

[4] propose underreaction of stock market based on two signifi cant condi-

tions of momentum eff ect: buying the past winners portfolios and selling

the past loser portfolios to generate signifi cant positive returns over 3- to

12-month holding periods. Lehmann [7] and Jegadeesh [3] separately pro-

pose that the existence of contrarian profi ts in 1-week and 1-month hori-

zons are interpreted as evidenced by signifi cant stock price overreactions

to information.

However, there is little debate that government intervention or re-

strictions, which might delay price discovery and result in variation in

momentum eff ect. Ma et. al., [10] assert stock prices should reverse the

original trend and move toward the intrinsic value, as evidenced by over-

shooting prices of limit-hit stocks that eventually reverse to the fundamen-

tal value. Opponents argue that the limit bound prevents suff icient price

adjustment to refl ect principle information and reach the new equilibrium

level (Lehmann [8]). If price movements are restricted, the stock prices

continue the same direction toward their true prices in subsequent trading

period, which is consistent with the delayed price discovery hypothesis

(Kim and Rhee [5]). In view of above literatures, we conjecture that there

exists an inconsistent momentum eff ect before and after the implementa-

tion of price limits on China’s stock markets.

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MOMENTUM AND CONTRARIAN STRATEGIES 1187

Additionally, considering various investors’ risk preferences, this pa-

per applies the Stochastic Dominance (SD) theory to reexamine momen-

tum strategies further. Main practical superiority of SD is that it makes

no assumptions about the distribution forms of return-on-investment and

fewer restrictive assumptions about investors’ utility functions. Accord-

ingly, we can compare the entire return distributions between losers and

winners instead of the mean portfolio return only without specifying an

asset pricing model.

The rest of this paper is organized as follows. Section 2 describes data

and the SD theory. Section 3 presents the empirical results of the profi t-

ability of momentum strategies before, during and after price limits. Fi-

nally, Section 4 concludes the paper.

2. Data and methodology

2.1. Data and sample selection

This analysis uses monthly returns on A-shares stock listed in Shang-

hai Stock Exchange (SHSE) and Shenzhen Stock Exchange (SZSE) during

July 1993 to December 2006. However, both exchanges adopted the 10%

price limit mechanism based on previous day’s closing price since Decem-

ber 16, 1996. To explore whether the profi tability of our sample can persist

through institutional transition while implementing the momentum strat-

egies, we divide the sample period into three subperiods and execute the

momentum strategies in the time before, during and after setting regula-

tion on price limits.1 Following Jegadeesh and Titman [4], Rouwenhorst

[11] and Lee and Swaminathan [6], we employ a similar methodology

to construct momentum portfolios and use a rebalancing mechanism of

monthly portfolios.

2.2. Stochastic dominance

The most common criteria of SD theory are First-, Second- and Third-

order Stochastic Dominance (FSD, SSD and TSD) respectively. Suppose an

investor has to choose between two risky assets, W and L, and returns on W asset exceed that on asset L when the momentum eff ect exists in stock

market. Let FW and GL be the cumulative distributions of the two risky

1 In our study, the momentum strategy is calculated as follows: for example, if winners

and losers are determined over the formation/holding period of 12 months under a cho-

sen starting point, portfolio returns could be calculated based on the forward/afterward 12

months of above starting point, respectively.

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assets, the return x take any value from [a, b], and U be a utility function. 2

Generally, asset W dominates asset L by FSD, if the Cumulative Density

Function (CDF) of W lies, roughly speaking, to the right of the CDF of L.

This means that, regardless of investors’ risk preferences, the chance of

earning higher returns from FW is always greater than GL . Then, all such

investors who are non-satiated (i.e., U1 ) will agree that FW is preferred to

GL by the FSD if and only if:

( ) ( ) ( ) ( ) , ,F R f x dx G R g x dx R a ba

R

aW L

R6/ # / ! 5 ?# # (1)

where ( )f x and ( )g x are the density functions of risky assets W and L respectively.

Considering the type of a risk averter, an asset W dominates an asset L at the SSD for all non-decreasing concave utility functions (i.e., U2 ) if

and only if:

( ) ( ) ( ) ( ) , ,FF R F x dx GG R G x dx R a bW Wa

R

L La

R6/ # / ! 5 ?# # (2)

where ( ) ( )F x f y dyWa

x/ # and ( ) ( )G x g y dyL

a

x/ # separately denote the

areas under FW and GL .

TSD requires the decision maker to be non-decreasing concave utility

functions with convex marginal utility (i.e., U3 ). The condition on the dis-

tributional relationship between the two risky assets can be furthermore

relaxed if and only if:

( ) ( ) ( ) ( ) , ,FFF R FF x dx GGG R GG x dx R a bR

a

R

W Wa

L L 6/ # / ! 5 ?# # (3)

where ( ) ( )FF x F y dyWa

x/ # and ( ) ( )GG x G y dyL

a

x/ # .

When the riskless asset is allowed, the SD analysis is denoted by Sto-

chastic Dominance with Riskless Asset (SDR). We redefi ne new variables

Wa and Lb as follows: (1 )W W ra a= + -a and (1 ) ,L L rb= + -b where

a and b are both positive constants. 3 Then, let FWa and GLb be the CDFs

2 The utility function class is denoted by Ui, where , , .i 1 2 3= U1 includes all u with

;u U02 2l includes all u with ,u 02l and ;u 02m and U3 includes all u with ,u 02lu 02m and u 02n .

3 The riskless asset r is the nominal riskless interest rate.

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of Wa and ,Lb respectively. The distribution set of all possible mixes of W and r will be denoted by ,FWa" , and that of L and r will be labeled as

.GLb" , Finally, we defi ne that FWa" , dominates GLb" , in the SDR frame-

work, if and only if for every element G GL L!b b" , there exists at least

one element in FWa" , which dominates it. Hence, scheme Wα dominates

scheme Lb by FSDR if and only if:

b( ) ( ) ( ) ( ) , ,F R f x dx G R g x dx R a ba

R

a

R

LW 6/ # / !a ba 5 ?# # (4)

where ( )f xa and ( )g xb are density functions for the riskless and risky

assets Wa and Lb , respectively.

Wa dominates Lb by SSDR and TSDR if and only if:

( ) ( ) ( ) ( ) , ,FF R F x dx GG R G x dx R a ba

R

a

R

W W L L 6/ # / !a a b b 5 ?# # (5)

( ) ( ) ( )FFF R FF x dx GGG Ra

R

W W L/ #a a b#

( ) , ,GG x dx R a ba

R

L 6/ !b 5 ?# (6)

where ( ) ( )F x f y dya

xW / aa # and ( ) ( )G x g y dy

a

x

L /b b# separately signify

the areas under Fwa and GLb . ( ) ( )FF x F y dya

x/ aWa # and ( )GG xL /b

( )G y dya

x

b# .

3. Empirical results

3.1. Profi tability of momentum strategies

The formation period returns for the loser, winner and momentum

(W-L) portfolios are presented in Table 1. Obviously, a very strong mo-

mentum eff ect exists for both extreme portfolios during formation peri-

ods. Table 2 depicts the average monthly returns of holding period under

such strategy. Results obtained from the full sample period are shown in

Panel A of table 2. Without setting price limits, a portfolios ranking of the

fi rst subperiod (Panel B) starts from July 1994 to November 1995. Losers

average monthly returns in holding periods of 1-, 6-, 9- and 12-month are

larger than winners, especially in 9 and 12 months, suggest that contrarian

strategies are signifi cantly profi table. Panel C reports that similar results

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Tabl

e 1

Form

atio

n pe

riod

ave

rage

mon

thly

retu

rns

of lo

ser,

win

ner a

nd m

omen

tum

por

tfol

ios

Fo

rmati

on

per

iod

L

ose

r (L

) W

inn

er (

W)

W-L

R

etu

rn

t-st

ati

stic

S

kew

nes

s R

etu

rn

t-st

ati

stic

S

kew

nes

s R

etu

rn

t-st

ati

stic

S

kew

nes

s

A. F

ull s

ampl

e

1-m

on

th

-9.5

3

(-11.6

1)*

* 1.4

0

16.9

3

(7.9

5)*

* 4.7

7

26.4

1

(14.3

3)*

* 5.5

8

3-m

on

th

-15.4

0

(-13.7

6)*

* 0.6

5

33.7

2

(10.4

6)*

* 1.8

7

48.4

4

(18.7

4)*

* 2.3

5

6-m

on

th

-20.7

4

(-16.3

2)*

* 0.0

4

52.9

5

(10.8

0)*

* 1.8

2

73.6

8

(17.8

6)*

* 2.4

8

9-m

on

th

-25.2

9

(-17.4

2)*

* 0.3

4

72.1

7

(11.3

3)*

* 1.7

2

97.4

3

(18.0

2)*

* 1.8

9

12-m

on

th

-28.0

3

(-16.4

5)*

* 0.6

7

97.6

2

(11.3

2)*

* 1.7

1

125.6

4

(16.4

0)*

* 2.0

1

B. S

ubpe

riod

1

1-m

on

th

-8.7

9

(-1.9

5)*

1.7

7

21.9

7

(1.8

4)*

3.3

4

30.4

7

(3.8

0)*

* 3.2

9

3-m

on

th

-15.1

4

(-1.2

8)

1.1

1

40.3

3

(2.3

1)*

* 0.3

7

54.8

8

(3.8

9)*

* 1.9

9

6-m

on

th

-23.5

4

(-4.8

6)*

* 0.3

2

47.5

5

(4.0

0)*

* 1.7

9

71.0

9

(9.3

3)*

* 0.4

4

9-m

on

th

-33.4

5

(-6.9

3)*

* -0

.10

56.5

9

(5.6

4)*

* 2.2

8

90.0

3

(12.2

7)*

* 0.5

1

12-m

on

th

-41.3

2

(-8.0

6)*

* 0.9

7

120.1

4

(4.0

2)*

* 2.6

4

161.4

6

(5.4

3)*

* 2.5

9

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C. S

ubpe

riod

2

1-m

on

th

-9.3

0

(-4.3

7)*

* -0

.10

29.7

3

(4.2

1)*

* 2.7

1

38.9

2

(5.1

2)*

* 3.5

6

3-m

on

th

-13.8

1

(-4.7

4)*

* 0.5

6

66.6

7

(6.8

4)*

* 0.6

9

77.1

9

(8.9

2)*

* 1.3

2

6-m

on

th

-15.1

9

(-4.7

3)*

* 0.3

2

118.9

9

(6.7

3)*

* 0.3

5

134.0

9

(8.5

3)*

* 0.6

6

9-m

on

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-13.3

5

(-3.6

5)*

* 0.5

7

168.0

1

(7.9

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8

(9.7

5)*

* 0.1

1

12-m

on

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-12.2

8

(-3.0

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213.6

3

(8.3

0)*

* 0.0

5

225.8

9

(9.9

9)*

* -0

.09

D. S

ubpe

riod

3

1-m

on

th

-9.7

2

(-13.8

4)*

* 0.0

1

12.7

1

(11.6

0)*

* 1.7

4

22.4

3

(27.9

5)*

* 1.1

5

3-m

on

th

-15.8

5

(-14.6

5)*

* 0.2

3

23.9

6

(10.8

6)*

* 1.1

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39.8

2

(26.9

5)*

* 1.1

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6-m

on

th

-21.6

9

(-15.9

0)*

* 0.2

6

36.7

2

(11.4

6)*

* 0.7

5

58.4

0

(26.6

5)*

* 0.7

4

9-m

on

th

-26.9

5

(-17.9

6)*

* 0.3

3

49.9

7

(11.0

3)*

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0

(21.8

0)*

* 1.0

5

12-m

on

th

-29.7

8

(-17.1

5)*

* 0.7

1

63.4

2

(10.6

1)*

* 0.8

3

93.1

9

(19.8

8)*

* 1.0

5

Not

es:

** D

eno

tes

sig

nifi

can

ce a

t th

e 5%

lev

el o

r h

igh

er.

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for strategies and has exhibition in the second subperiod, from December

1995 through December 1997 among transition period of price limits, is

relatively more violent for losers in return reversal by t-test than that in the

fi rst subperiod. The results for the third subperiod are shown in Panel D

over formation and holding periods after price limits, from January 1998

Table 2Holding period average monthly returns of loser, winner and

momentum portfolios

Formation period Loser (L) Winner (W) W-L

Return t-statistic Return t-statistic Return t-statistic

A. Full sample

1-month 2.32 (1.83) 1.44 (1.28) -0.88 (-1.88)

3-month 1.19 (1.13) 4.34 (3.81)** 3.15 (4.44)**

6-month 3.32 (2.36)** 4.98 (3.49)** 1.66 (2.70)**

9-month 8.25 (4.17)** 7.07 (3.94)** -1.19 (-1.40)

12-month 14.48 (4.72)** 9.20 (4.11)** -5.28 (-2.89)**

B. Subperiod 1 1-month 6.33 (0.75) 5.64 (0.83) -0.64 (-0.29)

3-month -4.43 (-1.28) 8.75 (2.31)** 13.08 (3.89)**

6-month 0.10 (0.03) -2.00 (-0.81) -2.10 (-0.82)

9-month 14.32 (2.30)** 2.98 (0.74) -11.34 (-3.37)**

12-month 44.44 (2.77)** 12.48 (1.90) -32.38 (-2.95)**

C. Subperiod 2

1-month 6.07 (2.40)** 4.85 (1.64) -1.20 (-0.79)

3-month 9.66 (3.18)** 11.34 (3.71)** 0.80 (1.14)

6-month 16.94 (5.10)** 16.86 (4.30)** -0.12 (-0.04)

9-month 24.57 (5.08)** 18.95 (4.20)** -5.78 (-2.17)**

12-month 29.37 (5.89)** 15.85 (3.52)** -13.36 (-4.10)**

D. Subperiod 3

1-month 0.63 (0.77) -0.20 (-0.26) -0.83 (-2.34)**

3-month -0.01 (-0.01) 1.74 (1.47) 1.76 (2.98)**

6-month 0.34 (0.22) 3.12 (1.97)** 2.78 (5.10)**

9-month 2.93 (1.41) 4.70 (2.25)** 1.77 (2.90)**

12-month 5.29 (2.00)** 6.89 (2.50)** 1.57 (1.96)**

Notes: ** Denotes signifi cance at the 5% level or higher.

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through December 2005. Obviously, when investing in China’s A-share

market, investors adopt two strategies in various holding periods, namely

the 3-, 6-, 9- and 12-month momentum strategies and a 1-month contrar-

ian strategy that generated signifi cantly return, respectively.

Diff erent results are founded in the specifi c holding periods with

price limits or not. Firstly, returns of winners after price limits are signifi -

cantly and positively higher than those before price limits in the 6-, 9- and

12-month holding periods. On the contrary, average monthly returns of

losers are larger than those of winners in the non-price restraint market

excluding the 3-month holding periods. Next, all returns of the winner-

minus-loser portfolio are evidently profi table at the 5% signifi cance level

after price limits. However, only the 9- and 12-month with contrarian

strategies provide signifi cant returns before price limits.

3.2. Results of stochastic dominance tests

This section applies the SD algorithm based on Levy [9] to exam-

ine the dominance relationship between the losers and winners. Table 3

identifi es loser and winner portfolios appeared in SD eff icient sets for full

sample and various subperiods. By setting up price limits, SD and SDR

tests confi rm that winners stochastically dominate losers in 3-, 6-, 9- and

12-month holding periods, which is conversely found at winners in the

dominated portfolios for 1-month.

Several implications of SD evidences can be drawn according to the

obtained results. The FSD criterion means that investors’ preferences tend

to prefer more money to less money when utility functions are non-de-

creasing. Figure 1 presents the cumulative distribution curves of losers

Figure 1Cumulative return distribution of loser and winner in the 3-month

period of subperiod 1

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Tabl

e 3

Res

ults

of s

toch

astic

dom

inan

ce te

st fo

r los

er a

nd w

inne

r por

tfol

ios

Ho

ldin

g p

erio

d

1-m

on

th

3-m

on

th

6-m

on

th

9-m

on

th

12-m

on

th

F

SD

S

SD

F

SD

S

SD

F

SD

S

SD

F

SD

S

SD

T

SD

T

SD

R

FS

D

SS

D

TS

D

SS

DR

(1.9

8%

≤ r f

≤ 1

0.9

8%

)

(1.9

8%

≤rf

≤10.9

8%

)

A. F

ull s

ampl

eL

ose

r +

+

+

–

+

–

+

+

+

+

+

+

+

+

Win

ner

+

–

+

+

+

+

+

+

+

–

+

+

+

–

1-m

on

th

3-m

on

th

6-m

on

th

9-m

on

th

12-m

on

th

F

SD

S

SD

F

SD

F

SD

S

SD

T

SD

S

SD

R

FS

D

SS

D

FS

D

(1

.98%

≤ r f

≤ 1

0.9

8%

)

B. S

ubpe

riod

1

Lo

ser

+

+

–

+

+

+

+

+

+

+

Win

ner

+

–

+

+

+

+

–

+

–

–

1-m

on

th

3-m

on

th

6-m

on

th

9-m

on

th

12-m

on

th

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F

SD

S

SD

F

SD

S

SD

T

SD

T

SD

R

(1.9

8%

≤ r f

≤ 1

0.9

8%

) F

SD

S

SD

F

SD

S

SD

F

SD

C. S

ubpe

riod

2

Lo

ser

+

+

+

+

+

–

+

+

+

+

+

Win

ner

+

–

+

+

+

+

+

–

+

–

–

1-m

on

th

3-m

on

th

6-m

on

th

9-m

on

th

12-m

on

th

F

SD

S

SD

T

SD

S

SD

R

(1.9

8%

≤ r f

≤ 1

0.9

8%

) F

SD

S

SD

F

SD

S

SD

F

SD

S

SD

F

SD

S

SD

D. S

ubpe

riod

3

L

ose

r +

+

+

+

+

–

+

–

+

–

+

–

Win

ner

+

+

+

–

+

+

+

+

+

+

+

+

Not

e: F

rom

th

e T

aiw

an

Eco

no

mic

Jo

urn

al

Ch

ina D

ata

base

, “r f ”

is

the

an

nu

al

risk

-fre

e ra

te, w

hic

h fl

uct

uate

d b

etw

een

1.9

8%

an

d 1

0.9

8%

du

rin

g

July

1994 t

o D

ecem

ber

2005. E

ff ic

ien

t p

ort

foli

os

mark

ed b

y “

+”, in

eff i

cien

t p

ort

foli

os

mark

ed b

y “

–”. T

he

cum

ula

tiv

e d

istr

ibu

tio

n c

urv

e o

f eff

ici

ent

po

rtfo

lio

s li

es t

o t

he

rig

ht

of

that

of

ineff

ici

ent

po

rtfo

lio

s, a

sig

n i

nd

icati

ng

th

at

eff i

cien

t p

ort

foli

os

do

min

ate

in

eff i

cien

t p

ort

foli

os

is c

on

clu

siv

e.

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and winners in the 3-month holding period of subperiod 1. Obviously, the

cumulative distribution curve of winners lies to below and to right of that

of losers. According to the FSD criterion, winners dominate losers in the

3-month holding period (as showed in Panel B).

In addition, Figure 2 describes the cumulative distribution curves of

losers and winners for subperiod 1 in the 1-month holding period, how-

ever, cross each other about at -6.95% and 95.01% of returns. The SSD cri-

terion discloses decision-making principles for investors who prefer more

money to less money and are risk-averse with non-decreasing concave

utility functions. The diff erent fi ndings are revealed under SSD criterion:

the performances of loser dominate the returns of winners since utility

gain from the positive areas to the left of 90.38% exceeds the reduction

in the expected utility losses between -2.32% and 6.95%. The results will

be much stronger if investors can borrow or lend with the risk-free in-

terest rates. For 1.98% r# #f 10.98%, the fi ndings of the SSDR eff icient

set in the 6-month holding period exhibits that loser’ returns outperform

the returns on winners without setting price limits. Specifi cally, Figure 3

shows that the performance of losers dominates returns on winners since

utility gain from the positive areas when the quantiles of the cumulative

distribution, 0.5P $ exceeds the reduction in the expected utility losses

for 0.5P # . 4



4 The quantiles of the cumulative distribution, P is given by 26.09% ( 1/2) 0.17% ;P P- =

hence, . ,P 0 50= where 26.09% is the highest return between losers and winners, and 0.17%

is the monthly risk-free rate (see Levy (2006)).

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Finally, the TSD criterion defi nes the decision making principles for

investors that are risk-averse individual with decreasing absolute risk

aversion must prefer positive skewness. This is a consequence of the de-

creasing absolute risk aversion: if payoff levels of investors increase, the

individual’s degree of absolute risk aversion decreases, making them

more willing to accept the more risky assets. If loser and winner port-

folios’ curve and be mixed with a risk-free return rate, winner dominate

loser by TSDR criterion for the 3-month holding period of subperiod 2.

Figure 4 indicates that the performance of winners dominates returns on

losers since utility gain from the positive areas exceeds the reduction in





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the expected utility losses. Although the cumulative distribution of win-

ners to the left of the loser’s distribution expresses a downward of -5.77%

and an upward of 26.38%, this preference may be attributed to the fact that

the distribution of winner returns is more right-skewed than that of loser

return (see Table 1).

6. Conclusion

This study employs the Stochastic Dominance (SD) theory to examine

the momentum eff ect in China’s A-share market from July 1993 to De-

cember 2006. When the price limits is implemented, the contrarian profi ts

could have been signifi cantly attained by buying losers and selling win-

ners in the 1-month holding period. In terms of the distribution of returns,

as well as price limits, if investors are allowed to borrow and lend money

at a risk-free interest rate, losers’ returns dominant winners’ returns by

the SSDR criterion. The momentum strategies of buying winners and sell-

ing losers generate signifi cant profi ts in the 3-month holding period be-

fore and after price limits. Without setting price limits, the cumulative

distribution of returns on winners completely dominates that on losers

according to the FSD criterion. The SSD criterion is suitable to adopt in a

period after price limits and could be ascribed to the positive area from the

expected utility gain exceeding the reduction in the expected utility loss

for the winner portfolios.

These fi ndings have important implications that momentum profi ts

are concentrated after price limits, and contrarian profi ts are evident be-

fore and during price limits for varied strategies of 6-, 9- and 12-month

holding periods. In summary, the exhibition of signifi cant price continu-

ation phenomenon on stock prices of winner portfolios can be attributed

to the delayed price discovery caused by price limits. Price limits delay

equilibrium price discovery to such an extent that the consequence gives

rise to a positive autocorrelation of stock returns. Similarly, our evidences

support the view that the stock prices of winners easily hint ceiling lim-

its and demonstrate signifi cant price continuation, is consistent with the

so-called delayed price discovery eff ects. Another circumstance which

the stock prices of losers easily hint fl oor limit and exhibit price reversal

reported by Chen et. al., [1] and Wong et. al., [12]. By the way of imple-

menting price limits in China’s A-share market, the fi nal fi ndings have

characterized most past research on this phenomenon which exhibits in-

vestors’ underreaction to the short-term information and overreaction to

the one-month period trends.

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References

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limits and stock characteristics: Evidence from the Shanghai and

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[2] W. F. M. De Bondt and R. H.Thaler, Does the stock market overreact?

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[4] N. Jegadeesh and S. Titman, Return to buying winners and selling

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[9] H. Levy, Stochastic dominance: Investment decision making under

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[10] C. K. Ma, R. P. Rao and R. S. Sears, Volatility, price resolution, and

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Received December, 2010

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Documents

A note on momentum and contrarian strategies across price limit regimes: Evidence from China's A-share market