4
Ri ,t   0    1i ,k D
k 1
Day
kt
26
   2i ,k D
k 1
Int
kt
12
   3i ,k Ri ,t  k   i ,t
k 1
 NS i ,t

NS i ,t
 i ,t 1   i   i ,1
( i ,t  0)   i , 2
( i ,t  0)   i X i ,t  i ,t  ui ,t 1
NTi ,t
 NTi ,t

Estimation Results :  i ,1  0 and  i , 2  0
DPIN BASE i , j 
NBi , j
NTi , j
( i , j  0) 
NS i , j
NTi , j
( i , j  0)
25
20
Percent
15
10
5
0
0.27 0.29 0.31 0.33 0.35 0.37 0.39 0.41 0.43 0.45 0.47 0.49 0.51 0.53 0.55 0.57 0.59 0.61 0.63 0.65 0.67 0.69 0.71 0.73
DPIN
The DPIN_BASE measure yields adequate cross-sectional
variation across stocks
DPIN DISP i , j
 NBi , j

NS i , j

( i , j  0) 
( i , j  0) ( Ri , j 10; j 1 )  0
NTi , j
 NTi , j

Ri , j 10; j 1  0
30
25
Percent
20
15
10
5
0
0.075 0.090 0.105 0.120 0.135 0.150 0.165 0.180 0.195 0.210 0.225 0.240 0.255 0.270 0.285 0.300 0.315 0.330 0.345 0.360 0.375 0.390 0.405
DPIN_DISP
DPIN_DISP distribution mimics that of DPIN_BASE, but with
slightly less than half the mean and median
DPIN SIZE i , j
LTi , j
 NBi , j

NS i , j

( i , j  0) 
( i , j  0) ( LTi , j )
NTi , j
 NTi , j

30
25
Percent
20
15
10
5
0
0.135 0.150 0.165 0.180 0.195 0.210 0.225 0.240 0.255 0.270 0.285 0.300 0.315 0.330 0.345 0.360 0.375 0.390 0.405 0.420 0.435 0.450 0.465 0.480 0.495
DPIN_SIZE_Med
DPIN_SIZE distribution mimics that of PIN (Easley et al. 2002)
with similar mean, median, left skew, and long right tail
Measure
Mean Median STD
Min
Max
DPINBASE
0.458
0.455
0.036
0.274
0.733
DPINDISP
0.215
0.215
0.029
0.073
0.401
DPINSIZE
0.231
0.227
0.027
0.133
0.500
The means and medians of the refined DPINs are quite close to
the PIN measure of Easley et al. (2002): 0.191 and 0.185
1
DPIN_BASE
DPIN_DISP
0.8
DPIN_SIZE
DPIN
0.6
0.4
0.2
0
1993
1995
1997
1999
2001
2003
2005
2007
Year
Yearly C-S average DPINs mimic that of PIN (Easley et al.
2002) with little year-to-year variation or with much stability
over time
Measure
High/Low
No.
Firms
DPINBASE
High
Low
1,899
2,306
819,299
5,448,227
7.051
0.760
103,740
591,708
DPINDISP
High
Low
2,046
2,159
1,265,812
5,340,255
6.094
1.241
162,587
569,050
DPINSIZE
High
Low
1,721
2,484
534,357
5,313,942
7.715
0.751
67,367
581,898
Size
Illiquidity
Volume
Stocks with higher DPIN are more opaque as they are associated
with much smaller firm size, lower volume, and higher illiquidity
Measure
Mean
Median
STD
25th %
75th %
DPINBASE
0.447
0.431
0.297
0.250
0.600
DPINDISP
0.212
0.000
0.301
0.000
0.417
DPINSIZE
0.222
0.000
0.289
0.000
0.429
The STDs are much higher and the medians for the two refined
DPINs are zero, hence no information events for many intervals
2.1
DPIN_BASE
1.9
DPIN_DISP
1.7
DPIN_SIZE
x Average
1.5
1.3
1.1
0.9
0.7
0.5
9:45
10:15 10:45 11:15 11:45 12:15 12:45 13:15 13:45 14:15 14:45 15:15 15:45
Time
The U-shaped intraday pattern is consistent with the clustering
of uninformed trading and the corresponding strategic informed
trading (Kyle 1985, Admati and Pfleiderer 1988)
DPIN_SMALL
1.6
1.4
x Average
1.2
1
0.8
0.6
0.4
9:45
10:15 10:45 11:15 11:45 12:15 12:45 13:15 13:45 14:15 14:45 15:15 15:45
Time
Stealth trading: informed traders break up large orders into a
series of small trades to hide their information (Barclay and
Warner 1993, Chakravarty 2001, Alexander and Peterson 2007)
Ri , j   i , 0   i ,1 Rm , j   i , j
2
i ,t
R
FSRVi ,t  log[(1  R ) / R ]
2
i ,t
2
i ,t
FSRVi ,t    1,t DPIN i ,t   2,t DPIN i ,t 1   t ' X i ,t   i ,t
FSRVi ,t    1,t DPIN i ,t   2,t DPIN i ,t 1   t ' Z i ,t   i ,t
FSRV
DPINBASE
DPINBASE, t-1
FSRV
FSRV
0.558***
(28.55)
0.467***
(24.29)
0.270***
(16.91)
0.093***
(7.64)
DPINDISP
DPINDISP,t-1
DPINSIZE
DPINSIZE,t-1
Wald
1411.5***
343.24***
0.640***
(21.63)
0.569***
(21.90)
947.39***
 DPIN and its lag are jointly significant at the 1% level
 Informed trading causes firm-specific return variation – Roll √
∆FSRV
∆DPINBASE
∆DPINBASE, t-1
∆FSRV
∆FSRV
0.150***
(8.31)
0.054***
(2.99)
∆DPINDISP
0.194***
(11.07)
0.033*
(1.77)
∆DPINDISP,t-1
∆DPINSIZE
∆DPINSIZE,t-1
Wald
77.87***
125.79***
0.145***
(5.32)
0.072***
(2.72)
34.61***
 ∆DPIN and its lag are jointly significant at the 1% level
 Informed trading causes firm-specific return variation – Roll √