Investors seem to hold on to their losing stocks to a greater extent than they hold on to their winning stocks. This well-document behavioral regularity is termed disposition effect (Shefrin and Statman 1985). We set an experiment to replicate results from a previous study of the disposition effect (Weber and Camerer 1998), and further show that a subject’s gender may interfere with the effect’s detection.

Carlos, Mineto

Newton, Da Costa Jr

Sergio, Da Silva

English

Research Papers in Economics

Disposition effect and gender 
 
 
 
Newton Da Costa, Jr 
Department of Economics, Federal University of Santa Catarina 
Florianopolis SC 88049-970, Brazil 
and Pompeu Fabra University, Spain 
newton@cse.ufsc.br 
 
Carlos Mineto 
Staff, Pontifical Catholic University of Parana 
Curitiba PR 80215-901, Brazil 
c.laffitte@pucpr.br 
 
Sergio Da Silva 
Department of Economics, Federal University of Santa Catarina 
Florianopolis SC 88049-970, Brazil 
professorsergiodasilva@gmail.com 
Corresponding author 
 
 
 
 
Abstract 
 
Investors seem to hold on to their losing stocks to a greater extent than they hold on to their 
winning stocks.  This well-document behavioral regularity is termed disposition effect 
(Shefrin and Statman 1985).  We set an experiment to replicate results from a previous 
study of the disposition effect (Weber and Camerer 1998), and further show that a subject’s 
gender may interfere with the effect’s detection. 
 
JEL Classification: G11 
 
Keywords: disposition effect, behavioral finance, gender 1. Introduction 
 
Investors seem to hold on to their losing stocks to a greater extent than they hold on to their 
winning stocks.  This well-document behavioral regularity is termed disposition effect 
(Shefrin and Statman, 1985).  The effect is usually explained by utility assumptions of loss 
aversion (Kahneman and Tversky, 1979).  When judging gains and losses relative to a 
starting reference point (such as purchasing price), investors are risk averse toward gains 
and risk seeking toward losses (Weber and Camerer, 1998). 
A changing reference point also alters the disposition effect.  Yet once one allows 
the reference point to shift there is no extra need for assuming loss aversion (Grinblatt and 
Han, 2002).  A complete rationale for the disposition effect taking changing reference 
points into account demands extending Kahneman and Tversky’s prospect theory to 
consider risky choices in an intertemporal framework.  Here Loewenstein and Prelec (1992) 
generalize discounted utility theory and set an intertemporal prospect theory.  They also 
sketch an explanation for the disposition effect, though they do not consider changing 
reference points.  It is as follows.  The value function is convex in the loss domain, and 
then losses are less than proportionately painful.  And gains yield marginally increasing 
returns.  Thus there are incentives to holding on to the stock.  The incentives are reversed 
on the gain side, motivating investors to quickly sell stocks that have gained in value 
(Loewenstein and Prelec, 1992, p. 594).  (Comprehensive references on the disposition 
effect are provided elsewhere (Weber and Camerer, 1998)). 
  An alternative to intertemporal loss aversion in explaining the disposition effect is 
plain mean-reversion.  Investors might keep losing stocks just because they rationally guess 
they will gain in value in future. 
Ultimate tests proving the disposition effect in actual markets are difficult because 
investors’ decisions and expectations cannot be controlled in there.  Experiments can be run 
instead.  An experiment can be designed to match individual investors’ trading decisions 
with the prices at which they buy the stocks.  Here we replicate such an experiment (Weber 
and Camerer, 1998) only to find that a subject’s gender interferes with the disposition 
effect’s detection. 
  Generally gender differences may be involved in risk-taking (Byrnes et al., 1999).  
If anything, women are more risk-averse.  Yet experimental studies suggest women’s risk 
aversion to be framing dependent (Schubert et al., 2000).  In line with the latter we find the 
disposition effect in female subjects to vary with changing reference points. 
  Section 2 presents the hypotheses to be tested.  Section 3 describes the experiment 
design.  Section 4 presents results.  And Section 5 concludes. 
 
2. Hypotheses 
 
It only makes sense to talk about winning and losing stocks relative to a particular reference 
point.  In Shefrin and Statman (1985) investors judge gains and losses relative to an initial 
purchasing price.  They argue that the investors keep losing stocks because the pain of a 
further loss is less than the pleasure of recovering the purchasing price.  But the disposition 
effect vanishes if the reference point is current price.  If investors adjust their reference 
points as stock prices change, they make no distinction between winning and losing stocks.  
So a changing reference point matters for the disposition effect’s presence. The hypotheses in Weber and Camerer’s (1998) experiment are as follows. 
 
H1  Subjects sell more (less) stocks when the sale price is above (below) the purchasing 
price. 
 
H2   Subjects sell more (less) stocks when the sale price is above (below) the previous 
price. 
 
  Selling a stock requires a deliberate action.  Yet one can imagine an automatic 
selling at the end of a period.  Here subjects will repurchase the stocks at the same price 
they were automatically sold for.  Since rational investors will make no distinction between 
deliberate and automatic selling it is implied that 
 
H3  Subjects selling stocks deliberately show greater disposition effect than subjects 
selling stocks automatically. 
 
  Here we will find hypotheses H1 and H3 to hold.  Yet H2 will collapse for female 
subjects. 
 
3. Experiment design 
 
Subjects were asked to make portfolio decisions prior to each of 14 periods.  They had to 
buy or sell six stocks (A, B, C, D, E, and F) at pre-announced prices.  Each subject was 
endowed with fictitious 60,000 Brazilian reais (~ US$25,000).  A stock had to be bought at 
R$10,000 each.  Subjects could neither borrow nor sell short, and were not allowed to 
diversify their portfolios.  (No real money were involved, unlike in Weber and Camerer's 
where a tiny fraction of gains was paid; but even with no monetary reward we were able to 
reproduce their results.) 
Prices were generated randomly rather than being the result of subjects’ actions.  
This aims at isolating a possible disposition effect (where there is a tendency to buy and sell 
at distinct prices) from the process of price formation.  Prices were then announced on two 
stages.  (1) Each period a price could rise or fall according to the probabilities in Table 1.  
Subjects were informed of these chances of price rising or falling, but they still had to guess 
which stock (A− F) had which probability of price increase.  They reported their guesses on 
a questionnaire distributed in white sheet for male and pale-pink sheet for female subjects.  
(2) Being known whether an increase or drop were involved, the size of price rise or fall 
(whether R$1, R$3, or R$5) was determined randomly.  Figure 1 shows the resulting price 
series. 
  Two experiments were run to consider deliberate selling (experiment I) and 
automatic selling (experiment II).  Experiment I was conducted over four sessions.  Here 
subjects were sampled from 90 business undergraduates and 16 real estate business 
graduates from the Pontifical Catholic University of Parana, Brazil.  Of these, 52 were 
female and 54 were male.  Experiment II was run with two groups of business 
undergraduates.  The first group was made up of 35 students (11 males and 24 females), 
and the second one had 35 students (16 males and 19 females).  (Details of our experiments 
have been omitted since we closely mimic those of Weber and Camerer (1998).)  
4. Results 
 
To examine H1 we consider a first-in-first-out (FIFO) setting, where the stocks sold are 
those bought at the beginning.  To consider H2 we take a last-in-first-out (LIFO) setting, 
where the stocks sold are those bought at the end of previous period. 
  Table 2 shows results for the FIFO setting.  Overall the disposition effect is present.  
Here our null hypothesis is the number of sales with gain to be less or equal to the number 
of sales with loss.  We found 63 percent of all trades to result in gains and only 34 percent 
to end up in losses.  Trading stocks D and E were exceptions, exactly as in Weber and 
Camerer's.  (A Z statistics of 13.30 was significant at less than one percent.) 
  Table 3 shows more stocks to be sold as the previous prices increase.  More than 
half of all trades (60 percent) occur taking the last price as reference (Z = 8.28, p < 0.01).  
Thus the disposition effect is heightened when the purchasing price is compared to previous 
prices.  Yet table 4 shows the disposition effect to vanish when automatic selling is 
allowed.  Relatively more trades yield losses (50.1 percent).  This confirms H3 and is also 
in line with Weber and Camerer’s findings. 
H3 can also be evaluated for individual subjects by means of a disposition 
coefficient  () () SS SS α +− +− =− + , where S+ (S− ) is the number of sales following a 
higher (lower) price at the previous period.  The coefficient is zero if the number of stocks 
sold on with gain matches the number sold on with loss, in which case there is no 
disposition effect.  The coefficient is +1 (− 1) if a subject sells on following a gain (loss).  
For experiment I, we found α I  = 0.095 (t = 1.80, p = 0.075, one-tailed t-test).  And for 
experiment II, the disposition coefficient was not significantly different from zero (α II  = –
0.0023). 
  Considering gender differences does not matter for sale decisions using the 
purchasing price as a reference point.  Here the disposition effect in male and female 
subjects shows no significant difference (Tables 5a and 5b). 
Yet gender interferes with H2.  When reference point is the previous price the 
disposition effect still occurs with males but vanishes for female subjects (Tables 6a and 
6b).  For male subjects α  = 0.351 (t = 4.41, p < 0.01, one-tailed t-test).  And for the average 
of 52 female subjects the coefficient is negative, but nonsignificant for a one-tailed t-test (α  
= − 0.172). 
We speculate that female decisions violating H2 are brain-wired.  According to 
empathizing-systemizing theory (Baron-Cohen, 2002), due to superior visuospatial memory 
(i.e. the ability to remember the relative locations of objects) women do a first-class job of 
remembering landmarks.  This contrasts with reading maps, which is a specialty of the male 
“systemizing” brain.  Thus male and female brains might interpret changing reference 
points differently. Yet the issue is only likely to be settled using brain-scanning 
experiments, such as fMRI. 
The disposition effect may be caused by cognitive illusion (intertemporal loss 
aversion) but one cannot at first discard rational mean-reversion.  Table 7 shows girls doing 
61 percent of their purchases after the stocks had their prices increased.  They thus think 
that rising prices will tend to persist in future, i.e. price changes across the stocks were positively autocorrelated.  Yet boys show behavior consistent with mean-reversion 
(negative autocorrelation). 
 
5. Conclusion 
 
Whether the disposition effect is due to cognitive illusion (such as loss aversion) or rational 
behavior (mean-reversion) remains unsettled.  Yet the experiment in this paper shows that 
girls do not keep losing stocks and sell winners as the reference point shifts from the 
purchasing price to the previous price.  We speculate this might be related to the fact that 
male and female brains interpret changing reference points differently. Figure 1. Stock prices pre-announced in the experiment 
 
 
 
 
 
 
Table 1. Probabilities of Stock Price Increase 
Stock  A B C D E  F 
Probability of Price Increase (%)  35  45  50  50  55  65 
Symbol  −  −   −   0 0 +  +  + 
 
Table 2.  Testing H1. Sales with the Purchasing Price as the Reference Point 
Stock  A B C D E F  Overall* 
 Total 
% 
Total 
% 
Total
% 
Total
% 
Total
% 
Total
% 
Total 
% 
Sales with Gain  314 
81 
210 
54 
253 
87 
167 
46 
127 
44 
219 
68 
1290 
63 
Even   50 
13 
     5 0  
2 
Sales with Loss  72 
19 
128 
33 
39 
13 
197 
54 
159 
56 
101 
32 
696 
34 
Total  386 388 292 364 286 320  2036 
Note 
* Z = 13.30, p-value < 0.01 for the test of gains (1290) versus losses (696) 
 
0 
20 
40 
60 
80 
100 
120 
140 
160 
180 
0  1  2  3  4  5  6 7 8 9 10 11 12 13 14 
S
t
o
c
k
 
 
P
r
i
c
e
 
A 
B 
C 
D 
E 
F Table 3. Testing H2. Sales at t Using Previous Prices at t −  2 and t −  1 as Reference Points 
Experiment I: Deliberate Sales 
 
Price             Stock 
Trend  
 
A 
 
B 
 
C 
 
D 
 
E 
 
F 
 
Overall*
 
% 
t −  2     t −  1            
G         G  84  65  57  61  65  30  362   
L         G      20  42    16  78   
−          G  107 101 102 103  82  74  569   
Total  191 166 179 206 147 120  1009  60 
G         L  25  24  6    11  28  94   
L         L  47  37  17  26  39  34  200   
−          L  72 77 39 65 50 72  375   
Total 144  138  62  91  100  134  669  40 
Note 
G = gain, L = loss 
* Z = 8.28, p-value < 0.01 
 
Table 4.  Testing H3. Sales at t Using Previous Prices at t −  2 and t −  1 as Reference Points 
Experiment II: Automatic Sales 
 
Price             Stock 
Trend  
 
A 
 
B 
 
C 
 
D 
 
E 
 
F 
 
Overall*
 
% 
T −  2    t −  1            
G        G  206  138  153  135  130  56  818   
L        G  0  0  21  88  0  21  130   
−         G  234 173 207 223 179 105  1121   
Total  440 311 381 446 309 182  2069 49.9 
  0 0 0 0 0 0  0   
G        L  104  78  32  0  41  88  343   
L        L  66  143  68  62  111  145  595   
−         L  170 257 162 129 152 273  1143   
Total  340 478 262 191 304 506  2081 50.1 
Note 
* Z = − 0.20, p-value = 0.42  Table 5a.  Female Sales Using the Purchasing Price as a Reference Point 
Stock  A B C D E F  Overall* 
 Total 
% 
Total 
% 
Total 
% 
Total 
% 
Total 
% 
Total 
% 
Total 
% 
Sales with Gain  141 
71 
76 
44 
97 
78 
78 
39 
51 
38 
82 
61 
525 
55 
Even   23 
13 
    2 3  
2 
Sales with Loss  57 
29 
73 
42 
27 
22 
120 
61 
83 
62 
53 
39 
413 
43 
Total  198 172 124 198 134 135  961 
Note 
* Z = 3.69, p-value < 0.01 for the test of gains (525) versus losses (413) 
 
Table 5b.  Male Sales Using the Purchasing Price as the Reference Point 
Stock  A B C D E F  Overall* 
 Total 
% 
Total 
% 
Total 
% 
Total 
% 
Total 
% 
Total 
% 
Total 
% 
Sales with Gain  173 
92 
134 
62 
156 
93 
89 
54 
76 
50 
137 
75 
765 
71 
Even   27 
13 
    2 7  
3 
Sales with Loss  15 
8 
55 
25 
12 
7 
77 
46 
76 
50 
45 
25 
280 
26 
Total  188 216 168 166 152 182  1072 
Note 
* Z = 14.97, p-value < 0.01 for the test of gains (765) versus losses (283) 
 
Table 6a. Female Sales at t Using Previous Prices at t −  2 and t −  1 as Reference Points 
Experiment I: Deliberate Sales 
 
Price             Stock 
Trend  
 
A 
 
B 
 
C 
 
D 
 
E 
 
F 
 
Overall*
 
% 
t −  2    t −  1               
G        G  34  16  19  24  21  7  121   
L        G      8  19    3  30   
−         G  39 31  33 43  30  22  198   
Total 73  47  60  86  51  32  349  44 
G        L  20  11  3    8  17  59   
L        L  37  21  14  18  24  19  133   
−         L  57 46  27 48  32  43  253   
Total 114  78  44  66  64  79  445  56 
Note 
* Z = − 3.44, p-value < 0.01 
The null (sales with gain) of less then or equal to 50 percent cannot be rejected Table 6b. Male Sales at t Using Previous Prices at t −  2 and t −  1 as Reference Points 
Experiment I: Deliberate Sales 
 
Price             Stock 
Trend  
 
A 
 
B 
 
C 
 
D 
 
E 
 
F 
 
Overall* 
 
% 
t −  2    t −  1              
G        G  50  49  38  37  44  23  241   
L        G      12  23    13  48   
−         G  68 70 69 60  52  52  371   
Total  118 119 119 120 96 88  660  75 
G        L  5  13  3    3  11  35   
L        L  10  16  3  8  15  15  67   
−         L  15 31 12 17  18  29  122   
Total  30 60 18 25  36  55  224  25 
Note 
* Z = 14.63, p-value < 0.01 
 
 
Table 7.  Gender and Mean-Reversion 
 Subject’s  Gender  Prices Rising at t −  1 (%) 
G 
Prices Falling at t −  1 (%)
L 
Overall   47  53* 
Male   34  66**  Purchases at t 
Female 61  39 
Notes 
To check for mean-reversion, we test whether subjects buy more losing stocks (L) than 
winners (G)  
*   Z = 1.62, p-value < 0.10  
** Z = 7.43, p-value < 0.01 
  
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Disposition effect and gender

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