Regret Commission versus Regret Omission:
Evidence from the Taiwan Futures Exchange
Yi-Ling Chen
Department of Asia-Pacific Industrial and Business Management
National University of Kaohsiung, Taiwan
TEL: 886-7-5916571
[email protected]
Ming-Chun Wang
Department of Money and Banking, College of Finance and Banking,
National Kaohsiung First University of Science and Technology, Taiwan
TEL: 886-7-6011000 ext.3128
[email protected]
Teng Yuan Cheng∗
School of Finance, Nanjing Audit University, PR China
TEL: 86-25-58318523
[email protected]
Key Words: regret of commission, regret of omission, risk-taking
JEL: G02, G11
*
Corresponding author,
We wish to thank Taiwan Futures Exchange for making the data available.
1
Regret Commission versus Regret Omission:
Evidence from the Taiwan Futures Exchange
Abstract
This study proposes a proxy to measure the degree of regret for prior investment decision
and examines the regret theory suggested by Bell (1982) and Loomes and Sugden (1982).
Utilizing data on market participants in Taiwan’s futures markets, we support the
Kahnmenan and Tversky (1982)’s finding: regret of commission makes decision-makers
more risk-averse; on the contrary, regret of omission induces them more risk-seeking in the
future. We provide proper understandings and valuable insights of the attitude toward risks
of the prior regret of investors into their investment behavior.
Key Words: regret of commission, regret of omission, risk-taking
JEL: G02, G11
2
I. Introdution
As a proverb says “Regret eats your heart out”. Human beings feel regret and
disappointed after their prior errors of judgment or undoing optimal choice (Bell, 1982, 1983;
Landman, 1987a, 1987b, 1993; Loomes and Sugden, 1982, 1983; Sugden, 1985). Simonson
(1992) further defines regret is a kind of sorrow of a decision maker due to the outcome of a
comparison between something done or not done. Kahnmenan and Tversky (1982) also
suggest that people feel more regret while a negative outcome of action (regret of
commission) rather than inaction (regret of omission). The former will make them more riskaverse, but the latter will make them more risk-seeking in the future. In this paper, we
examine the extent to which regret influence the attitude of risk of futures investors’ behavior.
It is important for several reasons to discuss whether regret influences investors’
investment decisions. First, Bell (1982) and Loomes and Sugden (1982) foremost proposed
the regret theory to successfully explain some violations of the traditional economic axioms,
assuming rational agents will consider not only their expected payoffs but also regret
(opportunity losses) to maximize their utility. Many studies apply regret theory to financial
field such as demand for insurance, asset pricing, investment choices, asset allocation and
equity home bias (Braun and Muermann, 2004; Dodonova and Khoroshilov, 2005;
Michenaud and Solnik, 2008; Muermann, Mitchell and Volkman, 2006; Solnik, 2005).
Therefore, regret theory is another psychological model to assume rational agents whose
utilities are not limited to their monetary payoffs to explain their economic behavior.
Second, psychological research on the experience of regret of decision makers can be
found in Inman and Zeelenberg (2002), Markman et al., (1993) and Roese and Olson (1995).
They show that decision makers tend to be less regret to maintain the status than to change
it. Also, a large number of experimental studies demonstrate people experience regret more
strongly while taking actions rather than inaction (Baron and Ritov, 1994; Connolly, Ordòñez,
and Coughlan, 1997; Gilovich and Medvec, 1994, 1995; Gilovich, Medvec, and Chen, 1995;
Gleicher et al., 1990; Kahneman and Miller, 1986; Kahnmenan and Tversky, 1982; Landman,
1987a, 1987b, 1993; Miller and Taylor, 1995; N’gbala and Branscombe, 1997; Ordòñez and
Connolly, 2000; Ritov and Baron, 1995; Spranca, Minsk and Baron, 1991; Zeelenberg et al.,
1996; Zeelenberg, Van der Pligt, and Manstead, 1998; Zeelenberg, Van Dijk, and Manstead,
3
1998, 2000). Consequently, regret of commission causes people to take less risks, but regret
of omission results people in taking more risks.
Third, in financial markets, many empirical studies conclude that investors are
susceptible to realizing winning investment too soon while holding onto losing investment
for too long in order to avoid regret in the future, exhibiting disposition effect (Dhar and Zhu,
2006; Genesove and Mayer, 2001; Han and Grinblatt, 2005; Heath, Huddart and Lang, 1999;
Odean, 1998; Shefrin and Statman, 1985; Weber and Camerer, 1998). Kahneman and
Tversky (1979) offer prospect theory to explain the relationship between prior outcome and
subsequent attitude toward risks. These studies suggest that regret will influence investors’
attitude toward risks.
In sum, a proper understanding of the attitude toward risks of the prior regret of
investors may provide valuable insights into their investment behavior. However, financial
empirical literature on the relationship between the degree of prior regret and subsequent
risk-taking is scare. Our study tries to measure the magnitude of pervious regret of investors
to examine whether it can affect their attitude toward risk-taking. Accordingly, our main
contribution is that I initially offer a proxy to measure the degree of prior regret of investment
decision. In addition, based on Kahnmenan and Tversky (1982)’s finding: regret of
commission makes decision makers more risk-averse. On the contrary, regret of omission
induces them more risk-seeking in the future. Therefore the main hypothesis of this paper is
posited as follows:
Hypothesis: Investors' propensity to take more risks after their regret of omission rather than
regret of commission toward pervious investment decisions.
II.
Sample and Methodology
The primary dataset for this study consists of all intraday futures transaction and limit
order book records from the Taiwan Futures Exchange (TAIFEX) for 992 trading days
between January 1, 2004 and December 31, 2007. The contracts are Taiwan Stock Exchange
Capitalization Weighted Stock Index futures (TX, hereafter), Taiwan Stock Exchange. Our
data includes identifiers for the traders’ ID codes and whether the trade was a buy or sell, as
4
well as the price, the volume and the time for each transaction and order. In our sample, there
are 237,188 investors trading in the futures market during the four-year sample period.
Precisely following the approach in Coval and Shumway (2005) and Liu et al.
(2010), we study whether morning regret influence investors' risk-taking in the afternoon1.
This very short period offers a clean context for studying how prior regret influences
subsequent behavior. We then take the following steps to calculate investors’ degree of regret
and the level of risks that they subsequently take. First, we identify all trades on different
futures contracts made by each investor on every trading day. Within each trading day, we
divide all trades into morning versus afternoon trades using the time of the trade. Trading
sessions begin at 8:45 a.m. and close at 1:45 p.m. at TAIFEX. Therefore, we classify trades
before the mid-point of 11:15 a.m. as morning trades and those afterwards as afternoon
trades2.
To determine whether an investor feels regret toward his investment decision in a
morning, we compare the cancel (reducing quantity) order purchasing (selling) price and
order purchasing (selling) price which doesn’t make a transaction for each futures purchased
(sold) in the morning to the transaction price at 11:15 a.m.3 to determine whether that futures
is purchased (sold) for an opportunity gain or loss. We aggregate all opportunity losses from
the same account on the same morning to proxy the degree of morning regret of omission
per trader (cREGRETm, rREGRETm). Similarly, we compare the transaction purchasing
(selling) price in the morning to the transaction price at 11:15 a.m. to determine whether that
futures is purchased (sold) for an opportunity gain or loss. We aggregate all opportunity
losses from the same account on the same morning as a proxy to measure the degree of
morning regret of commission per trader (iREGRETm). Besides, we also consider the
quantity-weighted the morning regret of omission (cwREGRETm, rwREGRETm) and
commission (iwREGRETm).
As with risk taking in the afternoon trading session, the following proxies are used:
We also examine whether prior daily regret influences investors' subsequent daily risk-taking.
We also perform robustness check in which using 11 a.m. and 12 a.m. as the break-point to separate morning
versus afternoon trades.
3
Because trading may be sparse on some trading days, we look for the prevailing price within the half-hour
window around 11:15 a.m. and use the price that is closest to 11:15 a.m.
1
2
5
the number of orders and the number of trades. These measures reflect how actively investors
engage themselves in trading and serve as noisy proxies for risk-taking.4
Because of trader heterogeneity and high market volatility, morning regret, profit and
afternoon risk level can introduce significant noise to our analyses. Following Coval and
Shumway (2005), we control for this by normalizing the morning regret, profit and afternoon
risk measures. We calculate the mean and standard deviation of morning regret (profit) for
each trader and then demean each trader’s morning regret (profit) by the trader-specific
average of morning regret (profit) and divide each trader’s daily morning regret (profit) by
the standard deviation to obtain the trader’s normalized morning regret (profit). The
normalized afternoon risk measures are defined in a similar fashion. We calculate the mean
and standard deviation of the afternoon risks for each trader. We then demean each trader’s
afternoon risk by the trader-specific average of afternoon risk and divide the difference by
the trader-specific standard deviation of afternoon risk. We demean all measures with the
average measure for the trader in order to trace any ‘abnormal’ afternoon trading behavior.
We denote trader i’s normalized measure of afternoon risk on date t as RISKai to reflect trader
i’s various afternoon risk measures on date t. By construction, our risk measures have means
of zero and standard deviations of one for each trader.
In addition to examine our hypothesis: Investors' propensity to take more risks after
their regret of omission rather than regret of commission toward pervious investment
decisions. We separate morning regret of omission from morning regret of commission of our
sample and perform the following regressions to gain additional understanding about the
magnitude and robustness of the results separately. We next perform the following regression
analyses to directly control for the difference5
RISKa= a + b1 * REGRETm + b2 *PROFITm + b3 * REGRETm * PROFITm + b4 * RISKm + e
(1)
where RISKa is one of the measures of risk-taking in the afternoon. REGRETm is the morning
regret for each trader, calculated as the sum of the opportunity losses. PROFITm captures
the trading profit, which influences the traders’ risk attitude after morning trading. We also
Coval and Shumway (2005) also use the number of trades, trade sizes and total dollar risk. Liu et al.
(2008) use the number of orders, the number of trades, order size, trade size and the ratio of trades to orders.
Locke and Mann (2005) and O’Connell and Teo (2005) use VaR approach for positions in foreign currencies
futures and foreign currencies.
5
We also perform alternative specifications where we include the daily return and intra-day volatility of the
TAIEX index.
4
6
include the morning risk-taking to control for the findings that traders take greater or less
morning risks when they feel regret during morning sessions.
III. Empirical Results
We first relate afternoon risk measures to the outcome of morning trading sessions with
summary statistics in Table I. INDIVs execute the lowest average daily number of
trades/orders in the morning(5.08/6.32), compared to the other traders. Among all institutions,
QFIIs place the highest average daily number of trades in the morning. Regarding the average
daily morning number of orders, we found that the highest average daily morning number
was 482.13 for DBs. The average daily afternoon number of orders for INDIVs, QFIIs and
DBs was 6.35, 233.40 and 449.50, respectively, in the futures market. The daily afternoon
number of trades was 160.22 for QFIIs, which was the highest among all types of traders,
while individuals traded only 5.41 times per day. These results indicate that professional
traders (QFIIs and DBs) traded frequently, and this was especially true for QFIIs. As for
average daily morning profit, QFIIs make highest morning profit. With regard to the
measures of regret of commission or regret of omission, DBs were the most one among all
types of traders.
(Insert Table 1 about here)
Table 2 reports the different afternoon risk measures for trading days with morning
gains and losses. Of three types of traders and two measures of risk-taking, four show
increasing and two show decreasing risk-taking behavior in Panel A. Generally speaking,
most of the measures show increasing risk-taking behavior in the afternoon for morning
profitable traders, especially for QFIIs. The result shown in Panel B seems contrary. That is,
of three types of traders and two measures of risk-taking, four show decreasing and two show
increasing risk-taking behavior in Panel B. Generally speaking, most of the measures show
decreasing risk-taking behavior in the afternoon for morning unprofitable traders, especially
for QFIIs. The most striking result comparing Panel B with A is that the afternoon risk for
morning unprofitable traders are lower than for morning profitable traders. INDIVs with
morning profits place more orders (0.01238 vs. –0.01953), execute more trades (0.00458 vs.
–0.00708), and place significantly larger orders and trades after morning profits. QFIIs and
DBs also show the same trading behavior as INDIVs.
7
(Insert Table 2 about here)
In Table 3, we test the above differences and the result are significant at the one percent
significance level except QFIIs in number of trade measure. Regret of commission is
significantly increases in the afternoon for individual traders. However institutional traders
show insignificant change for regret of commission in the afternoon. We interpret the result
as individual traders are naive and regret their commission often; moreover; however because
institutional traders must follow institutional regulation, they do not show significant regret
of commission after their trades. Regarding delete order in regret of omission, individual
traders still show significantly decreases in the afternoon. Institutional traders still show
insignificantly change about delete order regret in the afternoon except measure dregret in
DBs. The result in regret of reduced order reports significantly increases in the afternoon for
individual traders and specially, the same for QFIIs. Yet DBs still show insignificant change.
Last, we examine whether regret of omission is greater than regret of commission. We use
difference between the deleted order regret (dregret, dwregret) and the realized regret (iregret,
iwregret). Similarly the result is significant for individual traders but insignificant for
institutional traders. Generally speaking, individual traders show significant change in regret
of commission and omission in the afternoon, yet institutional traders show few significant
change no matter regret of commission or omission in the afternoon. The results mean
individual traders have no a constant trading discipline, yet institutional traders are regulated
by some trading rule.
(Insert Table 3 about here)
In Table 4 and 5 we present results on afternoon risk taking and morning regret of
commission across all three types of investors. For the OLS results in Table 4, an increase of
one standard deviation in morning regret of commission leads to a change of approximately
3, and 3 percent of one standard deviation in the afternoon number of trades, orders,
respectively for INDIVs. Although the coefficients on the afternoon number of trades and
orders are small, they are statistically significant. As for QFIIs, we obtain very similar results.
An increase of one standard deviation yields a change of 4, and 2 percent of one standard
deviation in the afternoon number of trades, and orders, respectively.
8
Such findings provide strong support that INDIVs and QFIIs decrease their risk taking after
morning regret of commission. Next, using the quantity-weighted the morning regret of
commission in Table 5, we find INDIVs display risk-averse after their morning regret of
commission. An increase of one standard deviation yields a change of 1, and 2 percent of one
standard deviation in the afternoon number of trades, and orders, respectively for INDIVs.
(Insert Table 4 about here)
(Insert Table 5 about here)
On the other hand, how did the traders display their attitude of risk after morning regret
of omission? We first present results on afternoon risk taking and morning regret of omission
when executing the reducing quantity order in the morning. Although the coefficients on the
afternoon number of trades and orders are small, they are statistically significant. Next, using
another proxy variable, the quantity-weighted the morning regret of omission, in Table 7, we
obtain very similar results that five types of traders don’t show more risk-taking after the
morning regret of omission. We admit the reducing quantity order is not suitable to proxy the
morning regret of omission. Therefore, we adopt the cancel orders to replace the reducing
quantity order.
(Insert Table 6 about here)
(Insert Table 7 about here)
In Table 8, we first present results on afternoon risk taking and morning regret of
omission when executing the cancel orders in the morning. INDIVs, QFIIs and DBs have a
tendency towards take more risk after morning regret of omission. An increase of one
standard deviation yields a change of 4, 4, and 4 percent of one standard deviation in the
afternoon number of trades for INDIVs, QFIIs and DBs, respectively. While an increase of
one standard deviation leads a change of 2, 4, and 4 percent of one standard deviation in the
afternoon number of orders for INDIVs, QFIIs and DBs, respectively. The results support
our main hypothesis.
(Insert Table 8 about here)
9
(Insert Table 9 about here)
IV. Conclusions
The main contribution of this study is that we initially offer a proxy to measure the
degree of prior regret of investment decision and examine the regret theory suggested by Bell
(1982) and Loomes and Sugden (1982). In addition, we try to not only bridge the gap
between the psychological literature and financial literature in terms of the relationship
between pervious regret and subsequent risk-taking but also distinguish regret of commission
from regret of omission of investors’ attitude toward risk-taking (Kahnmenan and Tversky,
1982). Utilizing data on market participants in Taiwan’s futures markets, we make an attempt
to shed light on the decision-making process and complexity of human behavior in financial
markets.
Our findings emphasize that it is important to study not only how the reference point is
determined and how it influences behavior in isolated context, but also how people frame a
series of related events relative to dynamic benchmarks. In support of Kahnmenan and
Tversky (1982), our findings also confirm that it is important to investigate how investors
treat regret of omission versus regret of commission, which may be responsible for the
various relationships between prior outcome and subsequent risk-taking in the extant
literature. Consequently, future studies on behavioral decision-making from a broader
spectrum of financial markets, securities and investors are needed to generate a more
generalized framework of investor behavior.
10
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Table 1. Summary Statistics
There are a total of 237,188 investors and 992 trading days during the sample period between 1/2/2004
and 12/31/2007. We use cancel (reducing quantity) order to aggregate all opportunity losses from the
same account on the same morning to proxy the degree of morning regret of omission per trader
(cREGRETm, rREGRETm). On the other hand, we aggregate all transaction of opportunity losses from
the same account on the same morning as a proxy to measure the degree of morning regret of
commission per trader (iREGRETm). Besides, we also consider the quantity-weighted the morning
regret of omission (cwREGRETm, rwREGRETm) and commission (iwREGRETm). Morning profit is
calculated by estimating the realized profit/loss for the liquidating positions at 11:15 a.m. at each
trading day for each trader. Number of trades and orders are the number of TX futures trades/orders
that each trader executed during the respective time period. INDIVs are individual traders, QFIIs are
qualified foreign institutional investors, and DBs are dealers or brokers of futures commission
merchants.
14
Morning
Variable
Mean
Median
St. Dev.
Afternoon
Mean
Median
St. Dev.
All Trader-Days
Whole Period 1/1/2004-12/31/2007 (N=4,187,648)
INDIVs
QFIIs
iREGRET
-0.00055
-0.00053
0.03134
0.00009
0.00000
0.03640
iwREGRET
-0.00024
-0.00044
0.00619
0.00011
-0.00009
0.00567
rREGRET
0.02763
0.01000
0.07780
0.01121
0.00416
0.04138
rwREGRET
0.01711
0.00866
0.03856
0.00823
0.00366
0.02287
cREGRET
0.01418
0.00438
0.08626
0.00939
0.00285
0.14773
cwREGRET
0.00563
0.00286
0.01598
0.00309
0.00187
0.00919
PROFIT
$225.31
$1,200.00
$265,270.65
$1,529.25
$1,200.00
$858,204.75
NO of Trades
5.08
3.00
16.14
5.41
2.00
18.17
NO of Orders
6.32
3.00
21.40
6.35
3.00
24.69
iREGRET
-0.01068
-0.00154
0.66244
0.01615
0.00092
0.93844
iwREGRET
0.00016
-0.00009
0.00641
0.00008
0.00005
0.00691
rREGRET
0.07003
0.02536
0.12452
0.02131
0.00364
0.08968
rwREGRET
0.02808
0.01393
0.03349
0.00716
0.00237
0.01609
cREGRET
0.45742
0.01247
2.24386
0.43639
0.00777
2.37061
cwREGRET
0.00645
0.00203
0.02153
0.00309
0.00147
0.01067
$738,515.30
$3,400.00
$16,150,469.3
$2,405,010
$21,200.00
$29,316,450.7
NO of Trades
164.57
74.00
246.73
160.22
68.50
265.92
NO of Orders
245.12
55.00
541.29
233.40
58.00
533.76
iREGRET
-0.01734
-0.00139
0.46601
-0.02640
-0.00107
0.44629
iwREGRET
-0.00017
0.00000
0.00827
-0.00045
-0.00010
0.00778
rREGRET
0.19224
0.02514
0.49879
0.04075
0.00833
0.20781
rwREGRET
0.15427
0.01259
0.45154
0.02032
0.00459
0.07793
cREGRET
0.97447
0.03946
6.97627
0.90174
0.01295
6.20088
cwREGRET
0.02756
0.00756
0.07702
0.01235
0.00316
0.03094
$12,882.48
$2,800.00
$2,972,752.35
$73,927.69
$6,200.00
$7,360,473.23
NO of Trades
151.29
60.00
327.49
142.29
53.00
975.80
NO of Orders
482.13
50.00
1532.41
449.50
44.00
1524.65
PROFIT
DBs
PROFIT
15
Table 2. Risk Taking for Profitable and Losing Morning
There are 2,436,221 trader/day observations with morning profits in panel A and 1,751,427 trader/day
observations with morning losses in panel B between 1/2/2004 and 12/31/2007. We use cancel
(reducing quantity) order to aggregate all opportunity losses from the same account on the same
morning to proxy the degree of morning regret of omission per trader (cREGRETm, rREGRETm). On
the other hand, we aggregate all transaction of opportunity losses from the same account on the same
morning as a proxy to measure the degree of morning regret of commission per trader (iREGRETm).
Besides, we also consider the quantity-weighted the morning regret of omission (cwREGRETm,
rwREGRETm) and commission (iwREGRETm). Morning profit is calculated by estimating the
realized profit/loss for the liquidating positions at 11:15 a.m. at each trading day for each trader.
Number of trades and orders are the number of TX futures trades/orders that each trader executed
during the respective time period. All variables are first demeaned and then standardized by dividing
the raw observation by the trader-specific standard deviation. INDIVs are individual traders, QFIIs
are qualified foreign institutional investors, and DBs are dealers or brokers of futures commission
merchants.
Panel A Risk Taking for Profitable Morning
Morning
Variable
Mean
Median
St. Dev.
Afternoon
Mean
Median
St. Dev.
Observations with Morning Profits (N=2,436,221)
Normalized by Trader
INDIVs
QFIIs
iREGRET
-0.19758
-0.17464
0.91412
0.00453
-0.04508
0.96216
iwREGRET
-0.23507
-0.22266
0.90347
0.00077
-0.05335
0.95757
rREGRET
-0.00955
-0.29157
0.92134
-0.00115
-0.30427
0.93644
rwREGRET
-0.01097
-0.25387
0.92081
-0.00201
-0.29062
0.93440
cREGRET
0.01620
-0.17101
0.95335
0.00091
-0.14647
0.95808
cwREGRET
0.02315
-0.12828
0.95069
0.00079
-0.10425
0.95777
PROFIT
1.01236
0.94622
9.17449
0.88366
0.91713
12.84642
NO of Trades
-0.00513
-0.24996
0.96642
0.00458
-0.30790
0.97008
NO of Orders
0.01612
-0.22620
0.97882
0.01238
-0.27689
0.97551
iREGRET
-0.03205
0.01510
1.02286
0.01160
-0.00708
1.09407
iwREGRET
-0.04241
-0.02572
1.02250
-0.00216
0.00748
1.05488
rREGRET
0.00222
-0.35657
1.05018
0.01648
-0.31828
1.01815
rwREGRET
-0.05523
-0.32410
0.91994
0.02054
-0.31701
0.96497
cREGRET
0.02987
-0.15979
1.05528
0.00703
-0.17234
1.05817
16
DBs
cwREGRET
0.05132
-0.11037
1.06279
0.00249
-0.11014
1.04152
PROFIT
-9.46679
0.72408
166.71830
-5.16202
0.77657
325.14378
NO of Trades
0.00896
-0.31536
0.99063
0.01129
-0.32391
0.99430
NO of Orders
0.00736
-0.32413
0.98450
0.00887
-0.32169
0.98085
iREGRET
-0.05235
0.00926
0.91055
0.01002
0.05055
1.00043
iwREGRET
-0.09615
-0.07078
0.97064
0.00676
0.03030
0.96521
rREGRET
0.01580
-0.28174
1.03938
0.01463
-0.23664
1.10268
rwREGRET
0.01338
-0.26035
1.06190
0.00568
-0.25424
1.00603
cREGRET
0.01041
-0.23467
0.98899
0.00178
-0.20142
0.97425
cwREGRET
0.02214
-0.23531
1.02636
0.00912
-0.21134
1.02375
PROFIT
0.27346
0.96744
15.84333
0.26977
0.97148
64.67984
NO of Trades
-0.00260
-0.25451
0.99373
0.00482
-0.22505
1.02740
NO of Orders
0.01244
-0.27783
1.00051
0.00919
-0.28946
1.00448
Panel B Risk Taking for Losing Morning
Morning
Variable
Mean
Median
St. Dev.
Afternoon
Mean
Median
St. Dev.
Observations with Morning Losses (N= 1,751,427)
Normalized by Trader
INDIVs
QFIIs
iREGRET
0.27731
0.21170
0.99857
-0.00701
-0.02183
0.98329
iwREGRET
0.32993
0.29180
0.98468
-0.00119
-0.01423
0.99022
rREGRET
0.01974
-0.27281
0.94956
0.00233
-0.30592
0.94393
rwREGRET
0.02267
-0.22763
0.95052
0.00408
-0.28947
0.94803
cREGRET
-0.02624
-0.20989
0.99279
-0.00161
-0.14895
0.97062
cwREGRET
-0.03750
-0.18747
0.99634
-0.00139
-0.10831
0.97115
PROFIT
0.77683
0.94151
9.65873
0.89440
0.93868
21.59834
NO of Trades
0.00721
-0.24347
0.99883
-0.00708
-0.33158
0.97905
NO of Orders
-0.02265
-0.26965
0.98011
-0.01953
-0.31773
0.97096
iREGRET
0.03316
0.03490
0.96308
-0.01193
-0.00538
0.87943
iwREGRET
0.04387
0.02248
0.96263
0.00222
0.01240
0.92751
rREGRET
-0.00263
-0.35815
0.87426
-0.01896
-0.29691
0.94222
17
DBs
rwREGRET
0.06527
-0.26371
1.02949
-0.02364
-0.32113
1.00439
cREGRET
-0.03074
-0.18387
0.92584
-0.00732
-0.17027
0.92186
cwREGRET
-0.05281
-0.14781
0.91497
-0.00259
-0.10037
0.94143
PROFIT
19.63508
1.12472
622.03209
3.14964
1.09200
185.91683
NO of Trades
-0.00927
-0.34392
0.99833
-0.01161
-0.33463
0.99382
NO of Orders
-0.00761
-0.35089
1.00460
-0.00916
-0.34385
1.00790
iREGRET
0.05674
0.05465
1.08240
-0.01095
0.04797
0.99584
iwREGRET
0.10421
0.08382
1.01706
-0.00738
0.02180
1.03320
rREGRET
-0.01801
-0.27270
0.94339
-0.01634
-0.23123
0.86425
rwREGRET
-0.01526
-0.26085
0.91444
-0.00634
-0.25895
0.98737
cREGRET
-0.01140
-0.25343
1.00812
-0.00196
-0.20136
1.02376
cwREGRET
-0.02425
-0.25816
0.96588
-0.01002
-0.21297
0.96909
PROFIT
1.46489
1.01322
25.19444
0.90830
1.00892
21.89853
NO of Trades
0.00282
-0.25239
1.00305
-0.00527
-0.24354
0.96549
NO of Orders
-0.01348
-0.30477
0.99562
-0.01001
-0.30811
0.99134
18
Table 3 Tests of the Difference of Risk-taking between Morning and Afternoon
This table tests the differences between morning and afternoon risk-taking and regret (including
commission and omission). There are 2,436,221 trader/day observations during 1/2/2004 to
12/31/2007. We use cancel (reducing quantity) order to aggregate all opportunity losses from the
same account on the same morning to proxy the degree of morning regret of omission per trader
(cREGRETm, rREGRETm). On the other hand, we aggregate all transaction of opportunity losses
from the same account on the same morning as a proxy to measure the degree of morning regret of
commission per trader (iREGRETm). Besides, we also consider the quantity-weighted the morning
regret of omission (cwREGRETm, rwREGRETm) and commission (iwREGRETm). Number of
trades and orders are the number of TX futures trades/orders that each trader executed during the
respective time period. All variables are first demeaned and then standardized by dividing the raw
observation by the trader-specific standard deviation. INDIVs are individual traders, QFIIs are
qualified foreign institutional investors, and DBs are dealers or brokers of futures commission
merchants.
Investor
code
INDIVs
QFIIs
DBs
Variable
Difference
T-value
P-value
D.F.
Number of
trade
Number of
Order
Iregret(realize)
Iwregret(weight
ed realize)
dregret(delete)
dwregret(delete
)
rregret(reduce)
rwregret(reduce
)
Dreg-ireg
Dwreg-iwreg
Number of
trade
Number of
Order
Iregret(realize)
Iwregret(weight
ed realize)
dregret(delete)
dwregret(delete
)
rregret(reduce)
rwregret(reduce
)
Dreg-ireg
Dwreg-iwreg
Number of
trade
Number of
Order
Iregret(realize)
-0.0390
-63.63
<0.0001
4370471
-0.0644
-121.42
<0.0001
5547191
0.0554
0.0592
79.36
87.92
<0.0001
<0.0001
4369941
4369941
-0.0417
-0.0170
-36.17
-15.35
<0.0001
<0.0001
1454335
1454335
0.0158
0.0282
5.10
9.07
<0.0001
<0.0001
166467
166467
0.00618
-0.00186
-0.0119
5.71
-1.80
-1.37
<0.0001
0.0724
0.1715
2292682
2292682
12683
-0.0234
-2.99
0.0028
13403
0.00726
0.00243
0.57
0.20
0.5687
0.8440
12683
12683
-0.00519
0.0150
-0.38
1.14
0.7048
0.2533
9811
9811
0.1799
0.2801
2.58
4.83
0.0101
<0.0001
462
462
0.00421
-0.00468
-0.0276
0.26
-0.29
-3.17
0.7932
0.7700
0.0015
12222
12222
31609
-0.0415
-7.03
<0.0001
33085
0.00319
0.39
0.6958
31609
19
Iwregret(weight
ed realize)
dregret(delete)
dwregret(delete
)
rregret(reduce)
rwregret(reduce
)
Dreg-ireg
Dwreg-iwreg
0.00439
0.56
0.5779
31609
-0.0181
-0.00174
-2.37
-0.22
0.0176
0.8254
25551
25551
0.0194
0.0296
1.09
1.62
0.2771
0.1049
5946
5946
0.00694
0.00580
0.70
0.61
0.4825
0.5443
27448
27448
Table 4. Morning Regret of Commission and Afternoon Risk Taking (Regret after
Transaction)
We present parameter estimates and the corresponding t-statistics by fitting the data with pooled
OLS regression. The regression specification takes the form of Equation (1) in Section 2:
RISKa = a + b1 * REGRETm + b2 * PROFITm + b3 * REGRETm * PROFITm + b4 * RISKm + e (1)
where RISKa is the measure of risk-taking in the afternoon. We adopt two different measures of risktaking: the number of trades and the number of orders. REGRETm is a proxy to measure the degree
of morning regret of commission per trader (iREGRETm) which is aggregated all transaction of
opportunity losses from the same account on the same morning. PROFITm is the morning realized
profit for each trader. RISKm is the corresponding risk-taking measure in the morning. INDIVs are
individual traders, QFIIs are qualified foreign institutional investors, and DBs are dealers or brokers
of futures commission merchants.
Dependent Variable: Riska
Number of Trades
Indep.Var.
Intercept
REGRETm
PROFITm
CROSSm
RISKm
Number of Orders
INDIVs
QFIIs
DBs
INDIVs
QFIIs
DBs
coef
-0.0461***
-0.0354***
-0.0166***
-0.0513***
-0.0382***
-0.0181***
t-stat
(-70.02)
(-3.97)
(-3.27)
(-82.43)
(-4.52)
(-4.05)
coef
t-stat
-0.0255***
-0.0426***
-0.0178***
-0.0291***
-0.0162*
-0.0010
(-39.05)
(-4.78)
(-3.46)
(-46.68)
(-1.91)
(-0.23)
coef
t-stat
0.0025***
0.0011
0.0187***
0.0023***
-0.0116
0.0137***
(3.52)
(0.12)
(3.72)
(3.49)
(-1.37)
(3.06)
coef
t-stat
coef
t-stat
-0.0054***
(-15.35)
0.0031
(1.05)
-0.0007
(-0.48)
-0.0045***
(-13.32)
0.0057**
(2.03)
-0.0013
(-1.06)
0.2549***
0.5433***
0.5545***
0.3084***
0.5941***
0.6705***
(405.46)
(62.51)
(110.22)
(515.01)
(72.18)
(150.55)
20
Table 5. Morning Regret of Commission and Afternoon Risk Taking (QuantityWeighted Regret after Transaction)
We present parameter estimates and the corresponding t-statistics by fitting the data with pooled
OLS regression. The regression specification takes the form of Equation (1) in Section 2:
RISKa = a + b1 * REGRETm + b2 * PROFITm + b3 * REGRETm * PROFITm + b4 * RISKm + e (1)
where RISKa is the measure of risk-taking in the afternoon. We adopt two different measures of risktaking: the number of trades and the number of orders. REGRETm is a proxy to measure the degree
of quantity-weighted morning regret of commission per trader (iwREGRETm) which is
aggregated all quantity-weighted transaction of opportunity losses from the same account on the
same morning. PROFITm is the morning realized profit for each trader. RISKm is the corresponding
risk-taking measure in the morning. INDIVs are individual traders, QFIIs are qualified foreign
institutional investors, and DBs are dealers or brokers of futures commission merchants.
Dependent Variable: Riska
Number of Trades
Indep.Var.
Intercept
REGRETm
PROFITm
CROSSm
RISKm
Number of Orders
INDIVs
QFIIs
DBs
INDIVs
QFIIs
DBs
coef
-0.0460***
-0.0358***
-0.0165***
-0.0513***
-0.0387***
-0.0181***
t-stat
(-69.60)
(-4.01)
(-3.25)
(-81.95)
(-4.57)
(-4.05)
coef
t-stat
-0.0145***
-0.0131
-0.0034
-0.0182***
0.0017
0.0029
(-21.04)
(-1.43)
(-0.68)
(-27.83)
(0.19)
(0.63)
coef
t-stat
0.0054***
0.0012
0.0194***
0.0051***
-0.0132
0.0137***
(7.63)
(0.13)
(3.84)
(7.60)
(-1.57)
(3.06)
coef
t-stat
coef
t-stat
-0.0056***
(-13.37)
-0.0056
(-0.98)
0.0019
(0.71)
-0.0047***
(-11.68)
-0.0017
(-0.32)
-0.0014
(-0.58)
0.2561***
0.5435***
0.5551***
0.3094***
0.5943***
0.6706***
(409.04)
(62.67)
(110.39)
(517.94)
(72.25)
(150.70)
21
Table 6. Morning Regret of Omission and Afternoon Risk Taking (Regret after
Reducing Quantity Orders)
We present parameter estimates and the corresponding t-statistics by fitting the data with pooled
OLS regression. The regression specification takes the form of Equation (1) in Section 2:
RISKa = a + b1 * REGRETm + b2 * PROFITm + b3 * REGRETm * PROFITm + b4 * RISKm + e (1)
where RISKa is the measure of risk-taking in the afternoon. We adopt two different measures of risktaking: the number of trades and the number of orders. REGRETm is a proxy to measure the degree
of morning regret of omission per trader (rREGRETm) which is aggregated all reducing quantity
orders of opportunity losses from the same account on the same morning. PROFITm is the morning
realized profit for each trader. RISKm is the corresponding risk-taking measure in the morning.
INDIVs are individual traders, QFIIs are qualified foreign institutional investors, and DBs are
dealers or brokers of futures commission merchants.
Dependent Variable: Riska
Number of Trades
Indep.Var.
Intercept
REGRETm
PROFITm
CROSSm
RISKm
Number of Orders
INDIVs
QFIIs
DBs
INDIVs
QFIIs
DBs
coef
-0.0315***
-0.0380
-0.0072
-0.039***
-0.0403
-0.0072
t-stat
(-11.53)
(-1.18)
(-0.74)
(-15.32)
(-1.43)
(-0.86)
coef
t-stat
0.0068**
-0.0019
0.0355***
-0.0089***
-0.0267
-0.0210**
(2.29)
(-0.06)
(3.55)
(-3.13)
(-0.91)
(-2.38)
coef
t-stat
0.0033
0.0179
0.0373***
0.0063**
-0.0239
0.0187**
(1.12)
(0.56)
(3.79)
(2.28)
(-0.84)
(2.17)
coef
t-stat
coef
t-stat
-0.0058**
(-2.18)
0.0272
(0.78)
0.0087
(1.20)
-0.0068***
(-2.68)
0.0038
(0.12)
0.0058
(0.91)
0.2432***
0.5657***
0.5218***
0.3099***
0.6789***
0.6714***
(85.16)
(17.08)
(53.56)
(111.70)
(23.61)
(78.40)
22
Table 7. Morning Regret of Omission and Afternoon Risk Taking (QuantityWeighted Regret after Reducing Quantity Orders)
We present parameter estimates and the corresponding t-statistics by fitting the data with pooled
OLS regression. The regression specification takes the form of Equation (1) in Section 2:
RISKa = a + b1 * REGRETm + b2 * PROFITm + b3 * REGRETm * PROFITm + b4 * RISKm + e (1)
where RISKa is the measure of risk-taking in the afternoon. We adopt two different measures of risktaking: the number of trades and the number of orders. REGRETm is a proxy to measure the degree
of quantity-weighted morning regret of omission per trader (rwREGRETm) which is aggregated
all quantity-weighted reducing quantity orders of opportunity losses from the same account on the
same morning. PROFITm is the morning realized profit for each trader. RISKm is the corresponding
risk-taking measure in the morning. INDIVs are individual traders, QFIIs are qualified foreign
institutional investors, and DBs are dealers or brokers of futures commission merchants.
Dependent Variable: Riska
Number of Trades
Indep.Var.
Intercept
REGRETm
PROFITm
CROSSm
RISKm
Number of Orders
INDIVs
QFIIs
DBs
INDIVs
QFIIs
DBs
coef
-0.0315***
-0.0387
-0.007
-0.0388***
-0.0415
-0.0071
t-stat
(-11.52)
(-1.21)
(-0.72)
(-15.23)
(-1.47)
(-0.84)
coef
t-stat
coef
t-stat
coef
t-stat
coef
t-stat
0.0178***
(6.01)
0.0123
(0.36)
0.0287***
(2.95)
-0.0021
(-0.77)
-0.0211
(-0.69)
-0.0018
(-0.21)
0.0033
(1.11)
0.0031
(0.10)
0.0393***
(4.02)
0.0063**
(2.28)
-0.0323
(-1.12)
0.0192**
(2.25)
-0.0060**
(-2.20)
-0.1267**
(-2.48)
0.0069
(0.80)
-0.0059**
(-2.30)
-0.0610
(-1.34)
0.0025
(0.33)
0.2431***
0.5704***
0.5236***
0.3080***
0.6792***
0.6684***
(85.25)
(17.35)
(53.85)
(113.56)
(23.65)
(78.46)
23
Table 8. Morning Regret of Omission and Afternoon Risk Taking (Regret after
Cancel Orders)
We present parameter estimates and the corresponding t-statistics by fitting the data with pooled
OLS regression. The regression specification takes the form of Equation (1) in Section 2:
RISKa = a + b1 * REGRETm + b2 * PROFITm + b3 * REGRETm * PROFITm + b4 * RISKm + e (1)
where RISKa is the measure of risk-taking in the afternoon. We adopt two different measures of risktaking: the number of trades and the number of orders. REGRETm is a proxy to measure the degree
of morning regret of omission per trader(cREGRETm) which is aggregated all cancel orders of
opportunity losses from the same account on the same morning. PROFITm is the morning realized
profit for each trader. RISKm is the corresponding risk-taking measure in the morning. INDIVs are
individual traders, QFIIs are qualified foreign institutional investors, and DBs are dealers or brokers
of futures commission merchants.
Dependent Variable: Riska
Number of Trades
Indep.Var.
Intercept
REGRETm
PROFITm
CROSSm
RISKm
Number of Orders
INDIVs
QFIIs
DBs
INDIVs
QFIIs
DBs
coef
-0.0352***
-0.0302***
-0.0115**
-0.0339***
-0.0313***
-0.0121***
t-stat
(-41.09)
(-3.19)
(-2.19)
(-42.17)
(-3.51)
(-2.63)
coef
t-stat
coef
t-stat
coef
t-stat
coef
t-stat
0.0419***
(48.47)
0.0403***
(4.21)
0.0440***
(8.25)
0.0223***
(26.45)
0.0258***
(2.73)
0.0395***
(7.78)
0.0051***
(5.72)
0.0083
(0.87)
0.0171***
(3.24)
0.0078***
(9.16)
-0.0065
(-0.72)
0.0137***
(2.93)
0.0008
(1.30)
-0.0095*
(-1.84)
0.0078***
(3.94)
0.0018***
(2.99)
-0.0145***
(-2.95)
0.0031*
(1.75)
0.2809***
0.5402***
0.5480***
0.3333***
0.5921***
0.6589***
(328.09)
(57.25)
(103.01)
(398.15)
(63.37)
(130.20)
24
Table 9. Morning Regret of Omission and Afternoon Risk Taking (QuantityWeighted Regret after Cancel Orders)
We present parameter estimates and the corresponding t-statistics by fitting the data with pooled
OLS regression. The regression specification takes the form of Equation (1) in Section 2:
RISKa = a + b1 * REGRETm + b2 * PROFITm + b3 * REGRETm * PROFITm + b4 * RISKm + e (1)
where RISKa is the measure of risk-taking in the afternoon. We adopt two different measures of risktaking: the number of trades and the number of orders. REGRETm is a proxy to measure the degree
of quantity-weighted morning regret of omission per trader (cwREGRETm) which is aggregated
all quantity-weighted cancel orders of opportunity losses from the same account on the same
morning. PROFITm is the morning realized profit for each trader. RISKm is the corresponding risktaking measure in the morning. INDIVs are individual traders, QFIIs are qualified foreign
institutional investors, and DBs are dealers or brokers of futures commission merchants.
Dependent Variable: Riska
Number of Trades
Indep.Var.
Intercept
REGRETm
PROFITm
CROSSm
RISKm
Number of Orders
INDIVs
QFIIs
DBs
INDIVs
QFIIs
DBs
coef
t-stat
coef
t-stat
coef
t-stat
coef
t-stat
-0.0348***
(-40.58)
-0.0303***
(-3.20)
-0.0116**
(-2.21)
-0.0339***
(-42.16)
-0.0317***
(-3.54)
-0.0122***
(-2.65)
0.0272***
(30.80)
0.0078
(0.79)
0.0366***
(6.99)
0.0132***
(15.81)
0.0041
(0.44)
0.0282***
(6.06)
0.0054***
(6.04)
0.0040
(0.43)
0.0165***
(3.08)
0.0081***
(9.54)
-0.0109
(-1.21)
0.0137***
(2.90)
0.0015**
0.0025
0.0102***
0.0004
-0.0026
0.0015
(2.22)
(0.44)
(2.84)
(0.58)
(-0.48)
(0.47)
coef
t-stat
0.2839***
0.5467***
0.5540***
0.3380***
0.6002***
0.6714***
(332.65)
(58.86)
(106.12)
(416.39)
(68.03)
(144.64)
25