The Behavior of Prices, Trades and Spreads for Canadian IPO’s€¦ · positive number of traded shares and have trade-by-trade returns less TABLE 1. IPO’s By Year Year IPO’s

*Financial support from the Concordia FRDP (Faculty Research and Development Program), Ned Goodman Chair in Investment Finance, SSQRC_CIRPÉE, SSQRC, IFM2 and SSHRC (Social Sciences and Humanities Research Council of Canada) are gratefully acknowledged. We appreciate comments and suggestions from participants at presentations at the Multinational Finance Conference (Paphos 2002), Northern Finance Association Conference (Calgary 1999) and Financial Management Association Conference (Orlando 1999), and the research assistance provided by Gang Li.

(Multinational Finance Journal, 2005, vol. 9, no. 3/4, pp. 215–236)© Multinational Finance Society, a nonprofit corporation. All rights reserved. DOI: 10.17578/9-3/4-4

1

The Behavior of Prices, Trades andSpreads for Canadian IPO’s

Lawrence KryzanowskiConcordia University, Canada

Skander Lazrak Brock University, Canada

Ian RakitaConcordia University, Canada

Microstructure effects for 359 TSX listed IPO’s in the period 1984–2002are examined. Based on first day returns, earning positive mean returns is verydifficult even when most IPO’s are purchased at the offer price. Mean dailytrade volume for the first five days of IPO trading is large relative to the meansfor the first thirty days and for longer periods. The dollar volume of sells isalways significantly larger than that of buys suggesting that institutionalinvestors are active on the sell side in the aftermarket. Liquidity as measured byquoted depth is initially large and decays rapidly over time. Gross returns areoften low or negative, and average round-trip trade costs increase from 1.5% to2.9% and 1.8% to 3.7% for more and less patient traders, respectively, over thefirst nine months of trading for an average IPO. Early amortized spreads arerelatively large due to large initial share turnover (JEL: G10, G15).

Keywords: initial public offerings; microstructure; spreads; decimalization.

I. Introduction

The importance of frictions in capital markets has been acknowledgedat least as far back as 1968 when Demsetz published his seminal article

Multinational Finance Journal216

1. See, for example, Choi, Salandro and Shastri (1988), Glosten and Harris (1988),George, Kaul and Nimalendran (1991), Stoll (1989), and Huang and Stoll (1997).

2. Beaulieu, Ebrahim and Morgan (2003) examine the 1991 move to decimalization forToronto Stock Exchange 35 Index Participation Units, and find that price discovery isinfluenced by tick size.

3. Some notable exceptions include Hegde and Miller (1989) who find that bid-askspreads for IPO’s are on average about 25 percent less than those for seasoned stocks and thatthis difference persists for eight weeks post IPO; Glascock, Hughes and Varshney (1998) whoconclude that bid-ask spreads for REIT IPO’s are significantly larger than for common stocksand funds; Ellis, Michaely and O’Hara (2000) who establish the fact that lead underwritersare the dominant IPO market-makers and that they act to stabilize prices for poorlyperforming new issues; Aggarwal and Conroy (2000) who determine that the price discoveryprocess is influenced by the time of day when IPO trading begins; and Nandha and Sawyer(2002) who find that in the Indian IPO market the relationship between ex-ante uncertaintyand information asymmetry proxies and the level of underpricing varies between par (a fixedprice of 10 rupees) and premium (priced above par) new issues.

that included a model of market maker activity wherein he demonstratedthat the bid-ask spread could be interpreted as a cost of immediacy.Thereafter, the literature in this area has grown dramatically. WhileDemsetz (1968) concentrated on order processing costs, other papersexamined components of the bid-ask spread that also includedasymmetric information and inventory holding costs.1

Market microstructure research has also been strongly driven byorder flow characteristics and related security market rules andregulations. The determination of equilibrium prices and how they varyover time are critically affected by rules regarding minimum tick sizesas well as by other trade features such as share volume and tradefrequency. Therefore, the move to decimalization has been an importantdeterminant of liquidity and trade cost and has received significantattention by researchers. For the 1996 move to decimalization on theToronto Stock Exchange (TSX), Chung et al. (1996), Ahn et al. (1996,1998), Bacidore (1997), Porter and Weaver (1997), and others, findsignificant reductions in quoted and effective spreads for TSX-listedstocks post-decimalization.2 Bessembinder (2003) analyzes the 2001move to decimalization on the NYSE and Nasdaq and notes that quotedspreads decline significantly on each market and that liquidity supply isnot adversely affected.

The literature on initial public offerings (IPO’s) is extensive andconcentrates to a large degree on underpricing and its associateddeterminants. In contrast, substantially less published work exists on themarket microstructure of new equity offerings.3 Given this deficiency

217Canadian IPO’s Stock Behavior

in the literature, the primary objective of this paper is to examinespecific microstructure characteristics of a sample of Canadian commonstock IPO’s over a relatively long period of time (1984–2002). To thisend, we examine trade and quote behavior and returns over variousinitial time intervals stretching out to 180 trading days post IPO.Additionally, we examine the impact that the 1996 move todecimalization on the Toronto Stock Exchange (TSX) had on tradecosts, depth, number of trades, volume and returns.

This research is of particular interest to both private and institutionalinvestors who need to better understand the costs and risks that they arelikely to bear as participants in the IPO aftermarket. It also is ofimportance to underwriters who typically act as market makers for newissues and to market regulators who are charged with the responsibilityof ensuring that the new issue process and trading in the aftermarket isfair to all participants.

The remainder of this paper is organized as follows. In the nextsection the sample and data set are described. In section three, returnsare briefly considered. We report on the results of our investigation intoshort run trade activity, as measured primarily by share volume insection four. In section five, we examine two dimensions of tradeliquidity, as measured by quoted depth and spreads, where variousrelative and absolute measures are used to capture the latter. In sectionsix, amortized spreads are examined. Concluding remarks are offered insection seven.

II. Sample and Description of the Data

For the period 1984–92, Canadian IPO’s are identified using the TSXAnnual New Listings Report and cross matching each new listing (sinceit need not be an IPO) with a prospectus that identifies the issue as beingan IPO. For the period 1993–2002, the Record of New Issues publishedby the Financial Post is employed. This database lists new Canadianissues of all types (classes of debt, equity and preferred shares). Debt,unit offerings and preferred shares are filtered out as are issues withoffer prices below $2.

Next, trade-by-trade data are extracted from the Equity Historydatabase compiled by the TSX. This database contains the time stamp,bid, ask, transaction price, depth, and volume for all TSX trades andquotes. In the next sections of this paper, we specifically examine the


4. The final sample consists of 370 IPO’s. Since we have access to the Equity Historydatabase from the middle of 1984, four IPO’s were dropped from the sample since they wereissued in the first few months of 1984. Seven other IPO’s were sold on a “when issued” basis.These IPO’s have different risk characteristics and trade several days prior to the start ofregular share trading on the TSX. According to a document issued by Market RegulationServices Incorporated - Canada’s independent securities trading regulator, trades on a whenissued basis will be cancelled if the Exchange determines that the security underlying thetrade will not be issued. To maintain sample homogeneity, these issues were also droppedalthough we conducted our analysis both with and without these issues and they had nodiscernible influence on the final results.

trade and quote data for periods up to (trading) days 5, 30, 90 and 180post IPO. Thus, this study examines microstructure effects that extendapproximately 9 calendar months after the start of secondary markettrading.

The final sample contains 359 new issues.4 Table 1 gives ayear-by-year account of the number of IPO’s included in the sample. Itis interesting to note the relatively large number of issues in 1986 andin 1987 (i.e., up to the world-wide market crash) and the limited numberof issues for the five subsequent years. The years 2001 and 2002 showrestricted activity following the bursting of the telecom and techbubbles.

Concerning quotes, we only include those that fall between 9:30 amand 4:00 pm and for which the bid is less than ask, are both positive,and for which the spread is less than 30 percent of the mid-spread.Pre-open and halt quotes are ignored. To be included, trades must occurbetween 9:30 am and 4:00 pm, have positive transaction prices for apositive number of traded shares and have trade-by-trade returns less

TABLE 1. IPO’s By Year

Year IPO’s in Sample Year IPO’s in Sample

1984 4 1994 351985 3 1995 131986 53 1996 391987 28 1997 321988 1 1998 91989 6 1999 151990 4 2000 301991 4 2001 41992 11 2002 61993 62 Total 359


5. The raw sample consists of 2,947,583 quote lines and 2,285,698 trade lines. Thefilters eliminate 1.16% and 0.90% respectively of the quotes and trade lines.

6. See Jay Ritter’s website link at http://bear.cba.ufl.edu/ritter/Int.pdf.

FIGURE 1.—Mean Daily Returns Over 180 Days Post IPO for 359New TSX Issues in the Period 1984–2002.

than or equal to 50 percent. Trades also are excluded if they havespecial conditions attached related to settlement, delayed delivery orcancellation.5 We assume that the associated quote is posted at least 5seconds before a trade. Finally, the Lee and Ready (1991) algorithm isused to sign each trade.

III. Returns

Although an analysis of returns is not the primary focus of this study, afew comments are worth mentioning since they add to the growingworld wide evidence aimed at highlighting the underpricing of IPO’s.Of the 359 new issues in the sample, 50.1 percent (180 of 359 issues)are underpriced. This is consistent with the percentage of underpricedIPO’s (49.1%) reported in an earlier study by Chung, Kryzanowski andRakita (2000).

The fact that IPO returns are significantly positive at the start ofsecondary market trading has been well documented in numerousinternational studies.6 For the present sample, day-one mean (median)returns are 6.65 (0.2) percent. Since initial median returns areindistinguishable from zero the typical investor will probably not earn

I P O M e a n D a ily R e tu rn s

-1 . 0 %

-0 . 5 %

0 . 0 %

0 . 5 %

1 . 0 %

1 . 5 %

2 . 0 %

2 . 5 %

3 . 0 %

3 . 5 %

4 . 0 %

4 . 5 %

5 . 0 %

5 . 5 %

6 . 0 %

6 . 5 %

7 . 0 %

0 2 0 4 0 6 0 8 0 1 0 0 1 2 0 1 4 0 1 6 0 1 8 0

D a y s f r o m s ta r t o f tra d in g

Mea

n re

turn

s


7. Only two of 38 countries listed on Jay Ritter’s website have similar low initial meanreturns. The country with the lowest recorded initial mean return is Denmark at 5.4% for 117new issues in the period 1984–1998. Austria had the same first day mean return of 6.3% forthe period 1984–2002 (83 IPO’s) as did the aggregate group of three Canadian studies (500IPO’s) listed.

a short term profit. The initial mean return found here is among thesmallest of any country where a formal study has been conducted.7

Figure 1 shows the daily evolution of mean returns. After relativelylarge first day positive returns, daily unadjusted mean returns appear tobounce around randomly within a narrow band (–0.5% to %0.5%)through to the end of the sample period.

Table 2 gives a more detailed breakdown of the distribution of firstday mean returns for the IPO sample and serves to highlight howdifficult it is to earn positive first day returns for Canadian IPO’s evenwhen purchases are made at the offer price. Consider an uninformedinvestor who naively adopts a policy of investing in every available IPOlisted on the TSX. Assume that the universe of possible IPO’s availablefor investment is the sample selected in this study. As is usually thecase, hot IPO’s will be oversubscribed and the investor will receive asmall allocation or more likely no allocation of shares for these IPO’s.According to table 2, if the investor misses out on investing in all issueswith first day returns above 100 percent (these are the IPO’s with thethree largest first day returns in the sample having a mean first dayreturn of 155.8%) but still invests in the remaining 99.16 percent of thesample, the first day return before trade costs would drop from 6.65percent to 5.40 percent. Missing out on IPO’s with first day returnsabove 20 percent (these are the top forty-five new issues in terms of first

TABLE 2. Distribution of First Day TSX IPO Returns

First Day Number of Sample Percentage of Sample First DayReturns IPO’s Represented IPO’s Represented Mean Return

< 178% All 359 100.00% 6.65%< 100% 356 99.16% 5.40%< 50% 348 96.94% 4.05%< 40% 341 94.99% 3.21%< 30% 330 91.92% 2.18%< 20% 314 87.47% 1.06%< 10% 278 77.44% –0.64%


day returns) but investing in the remaining 87.47 percent of the samplewould produce a first day mean return of only 1.06 percent. Finallymissing out on IPO’s with first day returns above 10 percent (the top 81issues) but investing in more than three-quarters of the remainingsample would actually produce a negative first day mean return of 0.64percent before trade costs. The inescapable conclusion is that being ableto buy the majority of TSX listed IPO’s at the offer price does notguarantee a positive first day mean return and may in fact result in anaverage loss.

Even the relatively low short term return encountered here isstrongly influenced by the price run up in the post-decimalizationperiod, which embodies the tech and telecom bubbles of the later 1990s.The pre-decimalization (prior to April 15, 1996) mean return for 234IPO’s (65.2 percent of the sample) was 4.1 percent whereas thepost-decimalization mean return for 125 IPO’s (34.8 percent of thesample) was 11.4 percent. The pre (post)-decimalization median initialreturn was 0 percent (1.7 percent).

IV. Dollar Volume

Transactions and volume are known to convey information to marketparticipants. The onset of secondary market trading in a new stockmarks the beginning of the price discovery process wherein opposingforces of supply and demand are influenced by a stream of informationultimately resulting in a price that is suppose to reflect the value of thestock. Conventional belief is that the start of trading for most IPO’s istypically marked by unusually high trading frequency and share volume.This exaggerated trading frequency and share volume decays steadilyover time and generally reaches a stable long-term level pending therelease of new and significant information that normally causes ashort-term jump in these two market activity measures.

Comments focusing on dollar volume and differences compared totrading frequency are reported when they exist. Specifically, the dollarvolume of trades for the sample of 359 IPO’s for periods of 5, 30, 90and 180 trading days post issue are examined. In calendar time, thiscorresponds to from one week up to about nine months after the start ofsecondary market trading. Dollar share volume for each IPO trade in thefirst 180 days of post-IPO trading is obtained by finding the product ofthe number of shares traded and its associated transaction price. The


TA

BL

E 3

.IP

O V

olum

e St

atis

tics

and

Sta

tist

ical

Tes

ts o

f D

olla

r V

olum

e fo

r IP

O B

uys

Ver

sus

Sells

Dol

lar

Vol

ume

Dol

lar

Vol

ume

of B

uys

Sta

tist

ic5

3090

180

530

9018

0

For

Ful

l Per

iod:

Mea

n2,

370,

474

979,

259

674,

964

670,

729

1,02

7,83

144

4,58

430

2,80

331

2,46

2M

edia

n41

8,06

320

7,04

715

0,60

612

6,02

316

1,26

081

,676

65,6

6257

,857

Std

. Dev

.7,

692,

286

3,04

0,84

12,

519,

753

3,00

0,71

63,

609,

911

1,43

7,63

21,

128,

564

1,42

5,11

7F

or P

re-d

ecim

aliz

atio

n P

erio

dM

ean

1,07

7,64

944

8,74

030

4,35

725

0,08

641

6,60

718

4,61

613

0,74

510

9,41

7M

edia

n26

3,84

715

0,75

611

7,97

610

4,84

095

,914

59,2

5152

,132

44,6

04S

td. D

ev.

3,15

5,05

61,

029,

389

679,

716

561,

379

1,20

8,93

443

9,98

830

7,87

325

9,25

0F

or P

ost-

deci

mal

izat

ion

Per

iod

Mea

n4,

790,

642

1,97

2,39

01,

368,

739

1,45

8,17

32,

172,

042

931,

243

624,

897

692,

562

Med

ian

989,

157

405,

747

249,

305

188,

768

433,

056

183,

388

110,

074

88,1

72S

td. D

ev.

11,9

61,1

884,

814,

528

4,08

8,77

74,

944,

201

5,73

1,67

12,

288,

442

1,82

7,18

82,

348,

158

(Con

tinu

ed)


TA

BL

E 3

.(C

onti

nued

)

Dol

lar

Vol

ume

of S

ells

Dol

lar

Vol

ume

Rat

ios

Sta

tist

ic5

3090

180

530

9018

0

For

Ful

l Per

iod

Mea

n1,

342,

643

534,

675

372,

160

358,

267

0.89

49b

0.85

58c

0.86

49c

0.86

10c

Med

ian

239,

253

111,

962

81,4

0472

,420

0.68

96c

0.75

71c

0.78

86c

0.81

04c

Std

. Dev

.4,

204,

450

1,64

0,76

71,

415,

674

1,58

6,74

10.

8298

0.56

060.

4748

0.44

95F

or P

re-d

ecim

aliz

atio

n P

erio

dM

ean

661,

042

264,

124

173,

613

140,

669

0.85

81c

0.80

43c

0.82

10c

0.80

39c

Med

ian

160,

723

89,9

6368

,387

60,2

850.

6626

c0.

7374

c0.

7739

c0.

7824

c

Std

. Dev

2,04

7,90

361

2,23

437

7,82

630

5,39

10.

8002

0.55

900.

4625

0.39

19F

or P

ost-

deci

mal

izat

ion

Per

iod

Mea

n2,

618,

600

1,04

1,14

774

3,84

176

5,61

10.

9636

0.94

790.

9426

0.96

22M

edia

n56

4,87

420

3,89

612

1,21

610

1,85

20.

7469

c0.

8086

b0.

8879

c0.

8851

b

Std

. Dev

.6,

374,

792

2,58

2,89

92,

303,

093

2,61

4,78

70.

8813

0.55

370.

4879

0.52

32

Not

e: a

, b a

nd c

indi

cate

sig

nifi

canc

e at

the

0.10

, 0.0

5 an

d 0.

01 le

vels

. Thi

s ta

ble

repo

rts

vari

ous

cros

s-se

ctio

nal s

tati

stic

s fo

r th

e av

erag

edo

llar

vol

ume

of tr

ades

und

iffe

rent

iate

d an

d di

ffer

enti

ated

as

buys

or

sell

s fo

r th

e sa

mpl

e of

359

IP

O’s

for

the

firs

t 5, 3

0, 9

0 an

d 18

0 da

ys o

ftr

adin

g po

st-I

PO

for

the

enti

re p

erio

d an

d fo

r th

e pe

riod

s be

fore

and

aft

er th

e in

trod

ucti

on o

f de

cim

aliz

atio

n by

the

Tor

onto

Sto

ck E

xcha

nge

(TS

X) o

n A

pril

15,

199

6. B

uys

and

sell

s ar

e in

ferr

ed u

sing

the

algo

rith

m o

f Lee

and

Rea

dy (1

991)

. The

dol

lar v

olum

e of

eac

h tr

ade

is o

btai

ned

by m

ulti

plyi

ng th

e nu

mbe

r of s

hare

s tr

aded

by

the

trad

e pr

ice.

Dol

lar

trad

e vo

lum

es a

re f

irst

agg

rega

ted

on a

dai

ly b

asis

for e

ach

IPO

, and

then

the

tim

e-se

ries

ave

rage

is c

alcu

late

d fo

r ea

ch I

PO

for

eac

h of

the

four

pos

t-IP

O p

erio

ds. T

he ta

ble

also

rep

orts

thre

e su

mm

ary

stat

isti

cs f

or th

ecr

oss-

sect

iona

l di

stri

buti

ons

of t

he t

ime-

seri

es a

vera

ges

for

the

rati

os o

f th

e do

llar

vol

ume

of b

uys

to t

he d

olla

r vo

lum

e of

sel

ls f

or t

he I

PO

sam

ple.

Fol

low

ing

the

clas

sifi

cati

on o

f ea

ch t

rade

as

a bu

y or

sel

l fo

r ea

ch I

PO

, th

e ra

tio

of t

he d

olla

r vo

lum

e of

buy

s an

d se

lls

are

then

aggr

egat

ed o

n a

dail

y ba

sis

and

the

tim

e-se

ries

ave

rage

is c

alcu

late

d fo

r ea

ch o

f th

e fo

ur p

ost-

IPO

trad

ing

peri

ods

(the

fir

st 5

, 30,

90

and

180

days

). F

inal

ly, c

ross

-sec

tion

al s

tati

stic

s ar

e co

mpu

ted

for

the

rati

os f

or e

ach

peri

od a

nd th

e ap

prop

riat

e st

atis

tica

l tes

t is

cond

ucte

d. T

he n

ull

hypo

thes

is th

at th

e cr

oss-

sect

iona

l mea

n (m

edia

n) is

equ

al to

one

aga

inst

an

appr

opri

ate

alte

rnat

ive

is te

sted

usi

ng a

t– (

Wil

coxo

n) te

st.


daily values then are averaged for each IPO over the number of days ineach of the four post-IPO trading periods. Sample statistics are thencalculated cross-sectionally and appear in table 3. Initially, for eachIPO, the time-series mean of the dollar volume of daily trades(un)differentiated by trade direction is determined for each stock foreach of the four periods. Differentiating by trade direction involvesclassifying each trade as a buy or sell according to the Lee and Ready(1991) algorithm.

As expected, the dollar volume of trades per day for the first fivedays of trading in the life of an IPO is large relative to the means for thefirst thirty days and for longer periods. The distribution of the dollarvolume of trades, dollar volume of buys and dollar volume of sells isskewed with the mean not only exceeding the median in every case butalso exceeding the 75th percentile (not shown) in the majority of cases.There is rarely much of a further decline in the mean or median afterday ninety. Volatility, as measured by the standard deviation of thecross-section of company means, declines rapidly after day five andexhibits some stability and even limited growth after day ninety.

The post-decimalization period is distinguished by a dramaticincrease in the dollar volume of trades, dollar volume of buys and dollarvolume of sells compared to respective pre-decimalization levels foreach of the four post-IPO trading periods. The mean dollar volume oftrades for the five-day post-IPO period in the post-decimalization period(4.79 million) is more than four times the corresponding mean in thepre-decimalization period (1.08 million). This increased trade activityremains relatively stable for all four post-IPO periods, and is due at leastin part to the dot-com boom at the end of the millennium. The mediandollar volume of trades for the 180-day post-IPO period is only 188,768(coupled with a median number of daily trades of only 14.87), whichsuggests that many of the IPO’s are thinly traded. The dollar volume ofdaily buys never exceeds the corresponding dollar volume of daily sells,and this is true in both pre- and post-decimalization periods.

The rightmost four columns under the heading “Dollar VolumeRatios” in table 3 contain cross-sectional statistical tests of ratios ofdollar volume of buys to dollar volume of sells. While qualitativelysimilar results for dollar volume ratios and trade frequency ratios (notshown) are obtained, there is one notable exception. While the mean(median) number of buys is larger (and predominantly statisticallysignificant) compared to the mean (median) number of sells for eachpost-IPO period following the onset of decimalization, such is not the


TA

BL

E 4

.St

atis

tica

l Tes

ts F

or I

PO

Vol

ume

Rat

ios

Dol

lar

Vol

ume

Dol

lar

Vol

ume

of B

uys

Dol

lar

Vol

ume

of S

ells

5/30

5/90

5/18

030

/180

90/1

805/

305/

905/

180

30/1

8090

/180

5/30

5/90

5/18

030

/180

90/1

80

Ful

l Per

iod

Mea

n2.

16c

3.40

c4.

23c

1.82

c1.

20c

2.06

c3.

22c

4.03

c1.

79c

1.20

c2.

19c

3.51

c4.

40c

1.86

c1.

21c

Med

ian

2.12

c3.

04c

3.61

c1.

77c

1.24

c2.

00c

2.74

c3.

16c

1.66

c1.

25c

2.19

c3.

11c

3.77

c1.

81c

1.25

c

Std

. Dev

.0.

942.

123.

160.

840.

311.

062.

383.

520.

970.

351.

052.

323.

400.

880.

33P

re-d

ecim

aliz

atio

nM

ean

1.93

c2.

82c

3.51

c1.

70c

1.21

c1.

85c

2.69

c3.

36c

1.66

c1.

20c

1.95

c2.

91c

3.66

c1.

74c

1.21

c

Med

ian

1.85

c2.

50c

2.79

c1.

67c

1.25

c1.

82c

2.20

c2.

48c

1.53

c1.

24c

1.88

c2.

62c

2.72

c1.

71c

1.24

c

Std

. Dev

.0.

861.

822.

680.

770.

300.

972.

053.

030.

930.

340.

981.

972.

970.

820.

32P

ost-

deci

mal

izat

ion

Mea

n2.

59c

4.47

c5.

58c

2.05

c1.

20c

2.45

c4.

21c

5.29

c2.

05c

1.21

c2.

64c

4.63

c5.

79c

2.09

c1.

21c

Med

ian

2.60

c4.

32c

4.98

c1.

99c

1.23

c2.

40c

3.74

c4.

08c

1.97

c1.

28c

2.69

c4.

55c

4.91

c2.

09c

1.26

c

Std

. Dev

.0.

942.

243.

530.

900.

331.

122.

633.

991.

000.

371.

052.

503.

710.

940.

34

Not

e: a

, b a

nd c

indi

cate

sig

nifi

canc

e at

the

0.10

, 0.0

5 an

d 0.

01 le

vels

, res

pect

ivel

y, u

sing

a t–

test

for

the

mea

n ra

tios

and

usi

ng a

Wil

coxo

nte

st f

or th

e m

edia

n ra

tios

. Thi

s ta

ble

repo

rts

thre

e su

mm

ary

stat

isti

cs (m

ean,

med

ian

and

stan

dard

dev

iati

on) f

or th

e cr

oss-

sect

iona

l dis

trib

utio

nsof

the

rati

os f

or th

e ti

me-

seri

es a

vera

ge d

olla

r vo

lum

es o

f tr

ades

und

iffe

rent

iate

d an

d di

ffer

enti

ated

as

buys

or

sell

s fo

r th

e sa

mpl

e of

359

IP

O’s

for v

ario

us p

airi

ngs

of th

e fi

rst 5

, 30,

90

and

180

days

of t

radi

ng p

ost-

IPO

for t

he e

ntir

e pe

riod

and

for t

he p

erio

ds b

efor

e an

d af

ter t

he in

trod

ucti

onof

dec

imal

izat

ion

by th

e T

oron

to S

tock

Exc

hang

e (T

SX

) on

Apr

il 1

5, 1

996.

Buy

s an

d se

lls

are

infe

rred

usi

ng th

e al

gori

thm

of

Lee

and

Rea

dy(1

991)

. For

eac

h IP

O, t

he d

olla

r vo

lum

es o

f tr

ades

are

fir

st a

ggre

gate

d on

a d

aily

bas

is, t

hen

the

tim

e-se

ries

ave

rage

is c

alcu

late

d fo

r ea

ch o

f th

efo

ur p

ost-

IPO

trad

ing

peri

ods,

and

fina

lly

the

rati

o of

the

tim

e-se

ries

ave

rage

s fo

r var

ious

pai

rs o

f the

four

pos

t-IP

O tr

adin

g pe

riod

s ar

e co

mpu

ted.

Thu

s, “

5/30

” in

dica

tes

a co

mpa

riso

n in

volv

ing

the

firs

t fiv

e-to

-30

days

of

trad

ing

post

-IP

O f

or th

e re

spec

tive

dol

lar v

olum

e of

trad

e m

etri

c. T

henu

ll h

ypot

hesi

s th

at th

e cr

oss-

sect

iona

l mea

n (m

edia

n) is

equ

al to

one

aga

inst

an

appr

opri

ate

alte

rnat

ive

is te

sted

usi

ng a

t– (

Wil

coxo

n) te

st.


8. Two outliers were removed from the analysis for the five-day ratio of the dollarvolume of buys to the dollar volume of sells. One company (MNT Limited) had over$252,000 of buyer initiated trades in the five-day period versus less than $3,000 of sellerinitiated trades and produced a ratio that was close to 86. Another company (MajesticElectronic) had a ratio that was in excess of 8. These two extreme values had little effect onthe nonparametric test but when included, they inflated the standard deviation dramatically(4.59 for the full period and 5.65 for the pre-decimalization period) thereby producing aninsignificant t-statistic.

9. All ratios are strongly significant for both tests due in large part to the relatively

case for dollar volume of buys versus dollar volume of sells. The dollarvolume of sells is always larger than that of buys for each post-IPOperiod with the ratio of buys to sells being generally significantlydifferent from one at the 5% level or better. This suggests thatinstitutional investors are active on the sell side. While this observationis compelling, its verification is left for future research.8

A series of statistical tests for the ratios for each of the three dollarvolume variables (undifferentiated and differentiated as buys and sells)for various pairs of post-IPO periods are conducted next by firstdividing, for example, the five-day mean dollar volume of trades by its30-day counterpart for each IPO. A cross sectional mean (median) foreach ratio for each trade activity metric is then calculated and aparametric t-test (a nonparametric Wilcoxon test) of the null hypothesisthat the mean (median) is equal to one against an appropriate alternativeis performed. The comparisons are, in turn, for the first five dayscompared to the first 30, 90 and 180 days, and for the first 30 dayscompared to the first 180 days, and for the first 90 days compared to thefirst 180 days. Results appear in table 4.

Both statistical tests indicate that the ratios comparing the first fivetrading days post-IPO are significantly different from one at the 0.01level for all three trade activity metrics. Furthermore, the magnitudes ofthese ratios for each metric increase monotonically as the first fivetrading days are compared in succession to its counterpart for the first30, 90 and 180 trading days post-IPO. The ratios for the first 30-to-180trading days are significantly different from one for each trade activitymetric, and are generally less than two for the full period as well as forthe pre- and post-decimalization periods. Similar comments can be madewhen considering the ratios for the first 90-to-180 trading days for eachof the three trade activity metrics. Mean and median levels for eachmetric are only about 20% larger for the first 90 versus the first 180trading days post-IPO.9


small degree of variability that exists in each of the sets of ratios for each pairing of post-IPOtime periods. From the full sample of 359 IPO’s, twenty stocks were issued in 1995 and 1996and overlapped the April 15, 1996 change to decimalization. As a robustness check, all ratiosare re-computed with these twenty stocks excluded. Although the ratios change marginally,all ratios remain statistically significant at the 0.01 level.

10. Goldstein and Kavajecz (2000) observe a decrease in depth when most NYSE stocksmoved to a 1/16th minimum price increment in June 1997.

V. Quoted Depth and the Bid-Ask Spread

Liquidity is an important aspect of any well functioning market. This istrue in particular for new stocks where the efficiency of the pricediscovery process may be hampered by restrictions encountered byinvestors seeking to acquire or sell their shares. As documentedpreviously, the dollar volume of shares traded and the number of tradesare exceptionally large during the early days of secondary markettrading. It is not surprising therefore to observe that the number ofshares made available for trading by suppliers of liquidity is initiallylarge and declines significantly over time. As is shown in table 5, meandepth for the first five days (90,840) is accompanied by similarly largemean depths pre- and post-decimalization (105,073 and 64,197,respectively). These levels decrease monotonically as the post-IPOwindow is extended to day180. The decline in depth post-decimalizationis inconsistent with the argument advanced by Harris (1994) for changesin tick sizes (i.e., price discreteness) who suggests that ceteris paribuswhen the price of liquidity (i.e., the spread) is reduced, the quantitysupplied will fall.10 The decline in depth post-decimalization may alsoimply that institutional investors bear higher trading costs for CanadianIPO’s as large orders are fractured when met by inadequate supply at agiven price.

There are several potentially important conclusions that can beextracted from an examination of the four spread measures appearing intable 5. Consistent with the large initial trading volume, dollar quotedspreads are smallest for the period ending at day 5 according to bothmetrics (mean and median) for the full period (0.176 and 0.150). Thisis also true pre- and post-decimalization. This measure jumps noticeablyfor the mean (0.273) and median (0.234) for the full period for the first180 days as well as during the pre- (0.248 and 0.224) andpost-decimalization (0.319 and 0.277) periods. The increase is steadyover the 30, 90 and 180 days periods. The post-decimalization dollar


TA

BL

E 5

.IP

O D

epth

and

Spr

ead

Stat

isti

cs

Quo

ted

Dep

thD

olla

r Q

uote

d S

prea

dP

ropo

rtio

nal Q

uote

d S

prea

d

Sta

tist

ic5

3090

180

530

9018

05

3090

180

For

Ful

l Per

iod

Mea

n90

840

5366

937

695

3250

60.

1755

0.21

040.

2473

0.27

260.

0206

0.02

430.

0290

0.03

27M

edia

n43

513

3112

325

234

2218

20.

1498

0.18

180.

2099

0.23

440.

0177

0.02

150.

0254

0.02

80S

td. D

ev.

1574

2481

547

5126

943

121

0.14

750.

2039

0.18

930.

1821

0.01

470.

0155

0.01

870.

0224

For

Pre

-dec

imal

izat

ion

Per

iod

Mea

n10

5073

5815

039

495

3294

50.

1726

0.19

410.

2241

0.24

790.

0218

0.02

470.

0279

0.03

04M

edia

n40

847

3057

225

116

2215

20.

1555

0.18

310.

2047

0.22

390.

0197

0.02

290.

0254

0.02

81S

td. D

ev.

1850

1893

293

5745

847

535

0.08

130.

0947

0.11

420.

1539

0.01

260.

0139

0.01

500.

0160

For

Pos

t-de

cim

aliz

atio

n P

erio

dM

ean

6419

745

279

3432

731

684

0.18

070.

2410

0.29

070.

3189

0.01

830.

0235

0.03

120.

0371

Med

ian

4563

531

439

2540

722

883

0.11

970.

1688

0.23

230.

2774

0.01

450.

0182

0.02

600.

0273

Std

. Dev

.78

287

5230

236

981

3348

70.

2245

0.31

910.

2758

0.21

930.

0179

0.01

820.

0241

0.03

06

(Con

tinu

ed)


TA

BL

E 5

.(C

onti

nued

)

Dol

lar

Eff

ecti

ve S

prea

dP

ropo

rtio

nal E

ffec

tive

Spr

ead

Sta

tist

ic5

3090

180

530

9018

0F

or F

ull P

erio

dM

ean

0.14

300.

1691

0.19

320.

2095

0.01

650.

0187

0.02

240.

0248

Med

ian

0.12

540.

1408

0.15

980.

1776

0.01

450.

0159

0.01

930.

0215

Std

. Dev

.0.

1221

0.21

640.

1767

0.13

820.

0130

0.01

160.

0144

0.01

61F

or P

re-d

ecim

aliz

atio

n P

erio

dM

ean

0.13

770.

1487

0.16

840.

1830

0.01

750.

0188

0.02

140.

0228

Med

ian

0.12

740.

1385

0.15

450.

1677

0.01

550.

0164

0.01

860.

0209

Std

. Dev

.0.

0665

0.07

370.

0798

0.08

740.

0140

0.01

060.

0126

0.01

17F

or P

ost-

deci

mal

izat

ion

Per

iod

Mea

n0.

1529

0.20

760.

2399

0.25

940.

0147

0.01

880.

0244

0.02

88M

edia

n0.

1043

0.14

380.

1881

0.22

380.

0121

0.01

570.

0207

0.02

23S

td. D

ev.

0.18

610.

3505

0.27

370.

1923

0.01

080.

0133

0.01

710.

0216

Not

e: T

his

tabl

e re

port

s va

riou

s cr

oss-

sect

iona

l sta

tist

ics

for

aver

age

dept

h an

d va

riou

s sp

read

mea

sure

s fo

r th

e sa

mpl

e of

359

IPO

’s fo

r the

firs

t 5, 3

0, 9

0 an

d 18

0 da

ys o

f tra

ding

pos

t-IP

O fo

r the

ent

ire

peri

od a

nd fo

r the

per

iods

bef

ore

and

afte

r the

intr

oduc

tion

of d

ecim

aliz

atio

n by

the

Tor

onto

Sto

ck E

xcha

nge

(TS

X)

on A

pril

15,

199

6. Q

uote

d D

epth

s ar

e fi

rst a

ggre

gate

d on

a d

aily

bas

is f

or e

ach

IPO

, and

then

the

tim

e-se

ries

aver

age

is c

alcu

late

d fo

r eac

h IP

O fo

r eac

h of

the

four

pos

t-IP

O p

erio

ds.

A s

imil

ar a

ppro

ach

is ta

ken

for e

ach

of th

e sp

read

mea

sure

s. T

he D

epth

vari

able

is c

alcu

late

d fr

om th

e fo

rmul

a: Q

uote

d D

epth

=[(

bid

* bi

d si

ze+

ask

* a

sk s

ize)

/2].

The

Dol

lar

Quo

ted

Spr

ead

is s

impl

y th

e di

ffer

ence

betw

een

the

ask

and

the

bid.

The

Pro

port

iona

l Quo

ted

Spr

ead

is e

qual

to th

e D

olla

r Quo

ted

Spr

ead

divi

ded

by th

e m

id s

prea

d. T

he D

olla

r Eff

ecti

veS

prea

d is

the

abso

lute

val

ue o

f th

e di

ffer

ence

bet

wee

n th

e tr

ansa

ctio

n pr

ice

and

the

mid

spr

ead.

Fin

ally

, the

Pro

port

iona

l Eff

ecti

ve S

prea

d is

the

Dol

lar

Eff

ecti

ve S

prea

d di

vide

d by

the

mid

spr

ead.


11. The trade costs, on average, for a typical IPO (i.e., based on the medians) in thepost-decimalization period for each of the post-IPO periods for both trader situations arelower than those reported in the text for an average IPO (i.e., based on the means) due to theright skewness (mean greater than the median) that exists in all of the trade cost distributionsfor the post-decimalization period.

12. Similar to the analysis done for dollar volume (and number of trades), tests ofsignificance of depth and the four spread variables for the first 5 days compared to the first90 and 180 days, for the first 30 days compared to the first 180 days, and for the first 90 days

quoted spread is generally larger than the similar pre-decimalizationvalue. This apparently anomalous finding can be explained by notingthat this measure does not adjust for price and the post-decimalizationperiod is influenced in particular by significant price inflation during thetelecom/tech boom. The proportional quoted spread does adjust forprice and a monotonic increase at each point in time for the full periodas well as for the pre- and post-decimalization periods is accompaniedby larger pre-decimalization values for the post-IPO periods ending atday 5 and day 30 in particular.

The dollar effective spread and the proportional effective spread alsoare shown in table 5. Consistent monotonic increases in both spreadvariables can also be observed for periods out to day 180. It isinteresting to note that for the proportional effective spread, pre- andpost-decimalization values are similar for the post-IPO period ending atday 5 and are in fact identical for the period ending at day 30. What iseven more relevant for investors is the observation that secondarymarket trading over the first nine calendar months generates materialround-trip trade costs before accounting for brokerage commissions. Toillustrate, an investor who used a similar mix of executed market andlimit orders for the IPO’s in the post-decimalization period paid, onaverage, round trip trade costs of 1.47%, 1.88%, 2.44% and 2.88% overthe first 5, 30, 90 and 180 days, respectively, of post-IPO trading for anaverage IPO. Similarly, a less patient investor who always tradedagainst the posted quotes (i.e., used market orders) in thepost-decimalization period paid, on average, round trip trade costs of1.83%, 2.35%, 3.12% and 3.71% over the first 5, 30, 90 and 180 days,respectively, of post-IPO trading for an average IPO.11 Thus, therelatively high cost of trading before accounting for brokeragecommissions for Canadian IPO’s coupled with generally low or negativereturns for investors who do not purchase shares in the primary market,suggest that the majority of new issues will be poor performers in theshort run.12


compared to the first 180 days also were conducted. Since these were all significant at lessthan 1%, the discussion and the associated tables have been suppressed to save space.

FIGURE 2. — Median Daily Percentage Amortized Spreads Over the180 Event Days Post IPO For 359 TSX IPO’s Issued During1984–2002.

VI. The Amortized Spread

The amortized spread is investigated next. Most empirical studies thatconsider the importance of the bid-ask spread in asset pricing ignore theimpact of amortizing the cost of the spread over investors’ holdingperiods. Chalmers and Kadlec (1998) find that the amortized spread isquite small in a study of AMEX and NYSE stocks over the period1983-1992. The amortized spread at the end of day T is summed over alldaily trades (τ) and is defined as:

(1)1t t t

tT

T T

P M VAS

P SO

τ

=

−=∑

where *Pt – Mt* is the absolute value of the effective spread (i.e., theabsolute value of the transaction price less the prevailing mid-spread),Vt is the volume of shares associated with each trade, and PT SOT

represents the firm’s market value of equity at the end of day T. Table6 contains summary statistics for the amortized spread for the fullsample at different points of time as well as for the samples of pre- and


TA

BL

E 6

.IP

O A

mor

tize

d Sp

read

Sta

tist

ics

and

Stat

isti

cal T

ests

Am

orti

zed

Spr

ead

(%)

× 1

03A

mor

tize

d S

prea

d C

ompa

riso

ns (

%)

× 1

03

Sta

tist

ic5

3090

180

5/30

5/90

5/18

030

/180

90/1

80F

or F

ull P

erio

dM

ean

6.50

772.

7996

2.20

642.

0880

0.37

02c

0.43

01c

0.44

18c

0.07

12c

0.01

18a

Med

ian

4.21

512.

1894

1.80

401.

6174

0.18

64c

0.21

60c

0.22

93c

0.04

81c

0.01

72a

Std

. Dev

.7.

9697

2.41

711.

9076

1.91

620.

6099

0.70

730.

7262

0.19

040.

1209

For

Pre

-dec

imal

izat

ion

Per

iod

Mea

n6.

0198

2.81

992.

2556

2.00

190.

3190

c0.

3764

c0.

4016

c0.

0818

c0.

0254

c

Med

ian

3.89

342.

2157

1.86

901.

6870

0.15

44c

0.19

45c

0.20

18c

0.04

98c

0.01

90c

Std

. Dev

.7.

5368

2.41

751.

8149

1.48

440.

5716

0.66

460.

6862

0.17

170.

0872

For

Pos

t-de

cim

aliz

atio

n P

erio

dM

ean

7.41

732.

7617

2.11

432.

2492

0.46

56c

0.53

03c

0.51

68c

0.05

12c

–0.0

135

Med

ian

4.69

862.

1823

1.58

611.

6015

0.66

75c

0.29

22c

0.27

06c

0.04

32c

0.01

18b

Std

. Dev

.8.

6779

2.42

562.

0745

2.53

390.

6675

0.77

340.

7930

0.22

050.

1641

Not

e: a

, b a

nd c

indi

cate

sig

nifi

canc

e at

the

0.10

, 0.0

5 an

d 0.

01 le

vel r

espe

ctiv

ely,

usi

ng a

t–te

st fo

r the

mea

n di

ffer

ence

s an

d us

ing

a W

ilco

xon

test

for

the

med

ian

diff

eren

ces.

Thi

s ta

ble

repo

rts

vari

ous

cros

s-se

ctio

nal s

tati

stic

s fo

r th

e av

erag

e am

orti

zed

spre

ad f

or th

e sa

mpl

e of

359

IP

O’s

for

the

firs

t 5,

30,

90

and

180

days

of

trad

ing

post

-IP

O f

or t

he e

ntir

e pe

riod

and

for

the

sam

e pe

riod

s be

fore

and

aft

er t

he i

ntro

duct

ion

ofde

cim

aliz

atio

n by

the

Tor

onto

Sto

ck E

xcha

nge

(TS

X) o

n A

pril

15,

199

6. U

nder

the

four

col

umns

hea

ded

by “

Am

orti

zed

Spr

ead”

, am

orti

zed

spre

ads

are

firs

t agg

rega

ted

on a

dai

ly b

asis

for e

ach

IPO

, and

then

the

tim

e-se

ries

ave

rage

is c

alcu

late

d fo

r eac

h IP

O fo

r eac

h of

the

four

pos

t-IP

O p

erio

ds.

Fin

ally

, the

cro

ss-s

ecti

onal

mea

ns, m

edia

ns a

nd s

tand

ard

devi

atio

ns o

f the

se c

ross

-sec

tion

al a

vera

ges

are

calc

ulat

ed a

nd th

en s

cale

d by

mul

tipl

ying

each

res

ult

by 1

03 . U

nder

the

fiv

e co

lum

ns h

eade

d by

“A

mor

tize

d S

prea

d C

ompa

riso

ns”,

sum

mar

y st

atis

tics

(sc

aled

by

a fa

ctor

of

103 )

for

the

diff

eren

ces

betw

een

the

cros

s-se

ctio

nal

aver

ages

for

var

ious

pai

rs o

f th

e fo

ur p

ost-

IPO

tra

ding

per

iods

are

rep

orte

d. T

hus,

“5/

30”

indi

cate

s a

com

pari

son

invo

lvin

g th

e fi

rst

five

-to-

30 d

ays

of t

radi

ng p

ost-

IPO

for

the

res

pect

ive

amor

tize

d sp

read

sta

tist

ic.

The

nul

l hy

poth

esis

tha

t th

ecr

oss-

sect

iona

l mea

n (m

edia

n) is

equ

al to

zer

o is

test

ed u

sing

a t–

(W

ilco

xon)

test

.


13. The median daily pre- and post-decimalization amortized spreads have been omittedfrom figure 2 for this reason.

post-decimalization new issues. Tests of significance for comparisonsof amortized spreads over four post-IPO periods are also shown.

The mean (median) amortized spread in the initial 5 days of IPOtrading is relatively large at a scaled (by 1,000) percent value of 6.5077(4.2151). This is due in large part to the substantially higher level ofshare turnover on the first day of secondary market trading. Figure 2makes this last observation even more apparent as the median day-oneamortized spread for the full sample is large at 8 percent (scaled) andthen declines rapidly and remains fairly stable at less than 0.5 percent(scaled) after day 30. Post-decimalization day one amortized spreads arerelatively large at a scaled 12.81 percent compared to pre-decimalizationday-one amortized spreads (scaled to 6.46 percent). After day one thereis virtually no difference between median daily pre- andpost-decimalization amortized spreads.13

After day 5 mean (median) amortized spreads decline noticeably outto day 30 and then level off. A similar pattern is obtained for the pre-and post-decimalization issues although the post-decimalization mean(median) is higher in the initial 5-day period.

Statistical tests for comparisons between mean amortized spreads atvarious post-IPO points in time appear in table 6. Apart from threespecific comparisons, all remaining comparisons indicate significantdifferences according to both parametric and nonparametric tests at lessthan the 0.01 level. The median difference between the mean 90-dayamortized spread and the mean 180-day amortized spread is significantat the 0.10 level. The post-decimalization mean difference between themean 90-day amortized spread and the mean 180-day amortized spreadis not significant at all while the median for the samepost-decimalization comparison is significant at the 0.05 level.

VII. Concluding Remarks

Through the examination of 359 TSX listed IPO’s over the period1984-2002 several important findings emerge. First, an investigation offirst day returns indicates how difficult it is to earn positive meanreturns even when an IPO is purchased at the offer price. While thepurchase of every IPO produces an average initial day return (pre-trade


costs) of 6.65 percent, the purchase of a typical IPO only produces acorresponding return of 0.2 percent. Subsequent average daily returnsare not statistically different from zero. Furthermore, missing out on thebest initial performing IPO’s but investing in more than three-quartersof the remaining sample can produce negative first day returns evenwhen trade costs are ignored.

Second, the mean dollar volume of trades per day for the first fivedays of IPO trading is large relative to the means for the first thirty daysand for longer periods. The distribution of the dollar volume of trades,dollar volume of buys and dollar volume of sells is right skewed andlevels off after day ninety. A similar decay is observed for dollarvolume volatility over the same initial time period.

Third, following the move to decimalization in April of 1996 by theTSX, there is a dramatic increase in the dollar volume of trades, dollarvolume of buys and dollar volume of sells compared to respectivepre-decimalization levels for each of the four post-IPO trading periodsexamined herein. Even though trade activity increasespost-decimalization it appears that many of the IPO’s are still thinlytraded.

Qualitatively similar results for number of trades are obtained withone apparent exception. While the mean (median) number of buys islarger (and generally significant) compared to the mean (median)number of sells for each post-IPO period following the onset ofdecimalization, such is not the case for a comparison between the dollarvolume of buys and the dollar volume of sells. The dollar volume ofsells is always larger than that of buys for each post-IPO period with theratio of buys to sells being generally significantly different from one. Inturn, this suggests that institutional investors may be active on the sellside. This observation will be explored in greater detail in subsequentresearch.

Fourth, a series of parametric and nonparametric tests are conductedfor the ratios for each of three dollar volume variables for the first fivedays compared to the first 30, 90 and 180 days, and for the first 30 dayscompared to the first 180 days, and for the first 90 days compared to thefirst 180 days. Both statistical tests indicate that the ratios comparingthe first five trading days post-IPO are significantly different from onefor three trade activity metrics. Furthermore, the magnitudes of theseratios for each metric increase monotonically as the first five tradingdays are compared in succession to counterparts for the first 30, 90 and180 trading days post-IPO.


Fifth, liquidity is examined via depth and spread measures. Depth isinitially large and declines significantly over time. The observed declinein depth post-decimalization suggests that institutional investors arelikely to bear higher trading costs for Canadian IPO’s as large orders aresplit up due to inadequate supply at a given price. Dollar quoted spreadsare smallest at day 5 both pre- and post-decimalization withpost-decimalization values exceeding those during thepre-decimalization period due at least in part to significant priceinflation during the telecom/tech boom. On the other hand, proportionalquoted spreads increase monotonically at each point in time for the fullperiod as well as for the pre- and post-decimalization periods.

Secondary market trading in IPO’s over the first nine calendarmonths can generate substantial round-trip trade costs before brokeragecommissions that can, for example, be in excess of 3.7 percent for theleast patient traders for an average IPO. The relatively high costs oftrading together with the material probability of low or negative grossreturns make it difficult for investors transacting in secondary marketsto earn short-run profits in Canadian IPO’s.

Sixth, an examination of the amortized spread in the first 5 days ofIPO trading for the full sample and for pre- and post-decimalizationperiods suggest that high initial turnover is the cause of unusually highinitial amortized spreads. These elevated levels quickly decline andstabilize after day 30. Furthermore virtually no difference existsbetween median daily pre- and post-decimalization amortized spreadsafter day one.

References

Aggarwal, R., and Conroy, P. 2000. Price discovery in initial public offeringsand the role of the lead underwriter. The Journal of Finance 55:2903–2922.

Ahn, H. J.; Cao, C. Q. and Choe, H. 1996. Tick size, spread and volume.Journal of Financial Intermediation 5:1 (January):2–22.

Ahn, H. J.; Cao, C. Q. and Choe, H. 1998. Decimalization and competitionamong stock markets: Evidence from the Toronto Stock Exchange cross-listed securities. Journal of Financial Markets 1:1 (April):51–87.

Bacidore, J. M. 1997. The impact of decimalization on market quality: Anempirical investigation of the Toronto Stock Exchange. Journal ofFinancial Intermediation 6:92–120.

Beaulieu, M. C.; Ebrahim, S. K. and Morgan, I.G. 2003. Does tick size


influence price discovery? Evidence from the Toronto Stock Exchange. TheJournal of Futures Markets 23:49–66.

Bessembinder, H. 2003. Trade execution costs and market quality afterdecimalization. Journal of Financial and Quantitative Analysis38:747–777.

Chalmers, J. and Kadlec, G. 1998. An empirical examination of the amortizedspread. Journal of Financial Economics 48:159–188.

Choi, J. Y.; Salandro, D. and Shastri, K. 1988. On the estimation of bid-askspreads: Theory and evidence. Journal of Financial and QuantitativeAnalysis 23:219–230.

Chung, R.; Kryzanowski, L. and Zhang, H. 1996. Decimalization’s winners andlosers. Canadian Investment Review, (Winter):35–39.

Chung, R.; Kryzanowski, L. and Rakita, I. 2000. The relationship betweenoverallotment options, underwriting fees and price stabilization forCanadian IPO’s. Multinational Finance Journal 4 (March/June):5–34.

Ellis, K.; Michaely, R. and O’Hara, M. 2000. When the underwriter is themarket maker: An examination of trading in the IPO aftermarket. TheJournal of Finance 55:1030–1074.

George, T. J.; Kaul, G. and Nimalendran, M. 1991. Estimation of the bid-askspread and its components: A new approach. Review of Financial Studies4:623–656.

Glascock, J. L.; Hughes, W. T. and Varshney, S. B. 1998. Analysis of REITIPO’s using a market microstructure approach: Anomalous behavior of assetstructure. The Journal of Real Estate Finance and Economics 16:243–256.

Glosten, L. R. and Harris, L. E. 1988. Estimating the components of the bid-askspread. Journal of Financial Economics 21:123–142.

Goldstein, M. and Kavajecz, A. 2000. Eighths, sixteenths, and market depth:Changes in tick size and liquidity provision on the NYSE. Journal ofFinancial Economics 56:125–149.

Harris, L. E. 1994. Minimum price variations, discrete bid-ask spreads, andquotations sizes. Review of Financial Studies 7:149–178.

Hegde, P. and Miller, R. E. 1989. Market-making in initial public offerings ofcommon stocks: An empirical analysis. Journal of Financial andQuantitative Analysis 24:75–90.

Huang, R. D. and Stoll, H. R. 1997. The components of the bid-ask spread: Ageneral approach. Review of Financial Studies 10:995–1034.

Lee, C. and Ready, M. 1991. Inferring trade direction from intraday data. TheJournal of Finance 46:733–746.

Nandha, M. S. and Sawyer, K. R. 2002. Ex-ante uncertainty in initial publicofferings: The Indian market. Finance India 16:961–976.

Porter, D. C. and Weaver, D. G. 1997. Tick size and market quality. FinancialManagement 26:4 (Winter):5–26.

Stoll, H. R. 1989. Inferring the components of the bid-ask spread: Theory andempirical tests. The Journal of Finance 44:115–134.

Documents

The Behavior of Prices, Trades and Spreads for Canadian IPO’s€¦ · positive number of traded shares and have trade-by-trade returns less TABLE 1. IPO’s By Year Year IPO’s