Price performance of common stock new issues

Journal of Financial Economics 2 (1975) 235-272.

Q North-Holland

Publishing Company

PRICE PERFORMANCE OF COMMON STOCK NEW ISSUES Roger

G. IBBOTSON*

Graduate School of Business, Unicersity of Chicago, Chicago, III. 60637, U.S.A. Received December 1974, revised version received May 1975 The paper studies both the initial and aftermarket performance (measured by risk-adjusted returns) on newly issued common stocks which were offered to the public during the 1960s. The results confirm that average initial performance is positive (11.4 percent), while the distribution of returns is skewed so that the subscriber of a single random new issue offering has about an equal chance for gain or loss. The results are generally consistent with aftermarket efficiency. Positive initial performance along with aftermarket efficiency indicate that new issue offerings are underpriced. The paper provides insights into this underpricing mystery, but does not solve it.

1. Introduction This paper studies the risk and performance (measured by risk-adjusted returns) on newly issued common stocks which were offered to the public for the first time during the period 1960 through 1969. The new issues studied are selected from underwritten offerings registered with the Securities and Exchange Commission (SEC). One objective is to measure the initial performance from the o&ring date until the date when a public market (aftermarket) is first established. A second objcctivc is to cxaminc the nftermnrkct performance to test for departures from market elhcicncy. If any incllicicncies arc uncovered in the aftermarket, investors can profit directly. If the initial performance is nonzero, profit opportunities may be erased by side payments. Nevertheless, knowledge of any irregularities should be of great interest to primary market participants. Numerous other investigators have studied unseasoned common stock public offerings with mixed results. The SEC (1963), Reilly and Hatfield (1969), Stickney (1970), McDonald and Fisher (1972), and Logue (1973) all find that initial performance is positive, whereas Stigler (1964) finds that initial performance is negative. Shaw (1971), in an analysis of the Canadian new issue market, *This paper is adapted from my Ph.D. thesis at the University of Chicago. I would like to especially thank Eugene Fama, my dissertation chairman. I also owe a great debt to the others who served at various times on my dissertation committee: Fischer Black, Nicholas Gonedes, Robert Hamada, Arthur La%. Merton Miller, Harry Roberts, and Myron Scholcs. In addition, helpful comments were given by Jeffrey Jaffe, Michael Jcnscn, Lawrence Fisher, James Lorie and an anonymous referee. The research reported here was funded by the Center for Research in Security Prices, University of Chicago.

236

R.G. ibbotson,

Price performance

of common

stock new issues

also finds negative initial performance. Purchases of new issues in the aftermarkets are only examined by Stickney and McDonald and Fisher. Stickney’s work does not test, but is consistent with, aftermarket efficiency. McDonald and Fisher also do not directly test aftermarket efficiency but do indicate that initial performance is unrelated to aftermarket performance. The works of Stigler, Reilly and Hatfield, Logue, and Shaw examine the performance from the offering date to the sale date after various holding periods. Shaw concludes that aftermarket new issue returns are abnormally low, while none of the other authors suggest any departures from aftermarket efficiency. In general, past research on new issues is difficult to interpret, since King (1966) and Fama (1973), among others, have demonstrated that returns from identical time periods are not independent events even after subtracting the overall market factor from the returns. Stigler, Reilly and Hatfield, Stickney, Shaw, Logue, and McDonald and Fisher all either draw more than one return from each calendar month or measure multiple month returns that overlap each other. These authors then make probability statements concerning their results that implicitly or explicitly assume independent observations. Even if these authors had recognized that their observations were not independent, the number of independent time periods used would probably be insufficient to give meaningful measures of the performance of new issues. While all of the previous research covers short periods relative to the present study, the paucity of independent observations is most acute in the work of Reilly and Hatfield (covering the periods December 1963 to August 1964 and January 1965 to June 1965), Stickney (cover_ing the year 1967) and McDonald and Fisher (covering the first quarter 1969). 2. Methodology 2.1. The data

This paper examines the risk and performance of new issues offered from January 1960 through December 1969. One offering is selected at random each month from the universe of unseasoned SEC registered offerings.’ Random selection of offerings within the month and selection of each observation from a separate calendar month eliminates a possible source of observational dependence that would be associated with drawing returns from identical time periods.2 ‘The universe of new issues and their initial offering quotes were obtained from a computer tape purchased from the Investment Bankers Association (IBA). which compiled the information in cooperation with the Investment Dealers Digest. The data were then compared with a book that the IBA and the Investment Dealers Digest have published, History of corporate finance for the decade (1972). ‘Fama (1965) has demonstrated that for New York Stock Exchange stock returns from separate chlendhr months are indcpcndent. Although no such research has dealt explicitly with the new issues market, the assumption that new issue returns from separate calendar months are uncorrelated is consistent with findings for other markets compiled in Cootner (1964).

R.G. Ibbotson, Price performance of common stock

new

issues

237

of offerings each month is shown in table 1. The new issues are generally traded in OTC markets. All prices are month-end bids,3 except for the initial offering price which is observed the day on which the offering takes place. The dimensions and composition of the total sample is illustrated in table 2. Table 3 shows the first year of the sample.

The total number

Table 1 Number of Securities and Exchange Commission (SEC) registered new issues underwritten each calendar month (1960-69)’ Months January February March April May June July August October November Totals

1960

1961

1962

1963

1964

1965

1966

1967

1968

1969

16 16 21 16 19 40 17 23 20 27 38 IG

11 27 25 27 42 29 29 50 37 53 53 52

40 31 50 74 40 5 6 7 17 7 II IO

2 5 7 8 8 10 6 7 8 8 8 6

10 4 2 11 12 8 5 11 8 8 8 10

6 7 13 24 13 8 8 8 17 11 20 11

5 4 9 16 10 13 8 5 1 5 5 3

2 4 4 12 8 5 7 12 9 1’ 1: II

15 14 21 18 28 23 30 24 29 53 5’ 6i

68 54 88 76 72 78 34 33 54 85 68 71

269

435

298

8’

97

146

84

100

368

771 --

“From this univcrsc of new issues, one ofTcring is selected at random each calendar month.

Each issue is followed for a period of up to sixty months. The numbers forming the triangle in table 3 rcfcr to the month of .~mot~irrg of each particular stock j during calendar month 1. Soasoning rcfcrs to the time elnpscd between the offering date and the observation date. For example, the first security selected in the sample (j = 1) was issued January Il. 1960. The return during the first month of seasoning is the return measured from January 11, 1960 to the last quote in January 1960. February 1960 is the second month of seasoning with the return measured from the end of January 1960 until the end of February 1960. Note from table 2 that in the case of issues offered after January 1967 the price series does not extend through the entire five years. Rather, the sample is truncated after 1971. ‘The monthly quotes were obtained from the Bank and Quotation Record (BQR), which in turn obtained its month-end quotes from the National Quotation Bureau ‘pink sheets’ or from listed exchanges. Since the pink sheets list several bids and asks (one from each market maker), the BQR takes the median bid price and then adds the mean spread between each bid and ask to determine the ask price for their quotes. Bid quotes tend to be more accurate than ask quotes since ask quotes often reflect a potential dealer short position. Some dealers arc reluctant to short OTC stocks which are unmarketable relative to NYSE stocks.

238

R.G. Ibborson. Price performance of common srock new issues

R.G. ibbotson. Price performance of common stock new issues

239

Table 3 Partial sample illustrating seasoning composition.’ Calendar month (I) 1960 Stock 0’)

1

2

3

6

7

8

9

10

11

12

1 2 3 4 5 6 7 8 9 10 11 12 -

1

2 1

3 4 5 6 2345678 1 234567 1 23456 1 2 1

7

8

9

10 9 8 7 6 5 4 3 2 1

11 10 9 8 7 6 5 4

12 11 10 9 8 7 6 5 4 3 2 1

4

5

345 234 1 2 12

3 1

: 1

--

‘The numbers in the above triangle represent the number of months seasoning n for each stockj during calendar month t. For cxamplc, the second stock selected for the sample (j = 2) will be in its third month of seasoning (n = 3) during the fourth calendar month (I = 4). In general, n = r-j+ I.

The monthly returns arc measured from bid to bid and adjusted for capital changes.4 Some bids were missing or deleted because of mergers, approaching bankruptcies, inactive trading markets, etc.’ A missing quote causes two adjacent returns to be missing from the sample. 2.2. The two-paramc’tcr Sharpe

(1964)

ntodd

and Lintncr (1965) propose a two-parameter

market equilibrium

‘All prices arc adjusted for dividends, stock dividends, splits, and other capital changes:as d&cd by Moody’s manuals (various issues). “If a company mcrgcd, the market value of whatever was reccivcd in exchange for a share is included in the sample, while subsequent quotes are deleted if the new issue is not the surviving company. In one attempt to eliminate large reporting errors from being input in this study, ask-to-bid ratios were used as a proxy for reporting error magnitude. Casual observation of the data revealed that high ask-to-bid ratios occur most frequently among low priced stocks. Based on the characteistics of the sample. any ratio greater than 8 was considered large enough to indicate an inaccurate quote. In order to include large price drops in the sample, the first quote Hith an ask-to-bid ratio greater than 3 was retained. When subsequent ask-to-bid ratios were greater than $, quotes were deleted since the inaccurate quotes tend to bias returns. For example, if a stock, quoted at 2-24 in one month, fell sharply SO that subsequent monthly quotes arbitrarily fluctuated between Q3 and &+, then the initial -94 pcrccnt return would remain in the sample, while alternating +lOO percent and -50 percent returns would bc deleted based on the j rule.

240

R.G. Ibbotson, Price performunce

of common stock new issues

model for pricing risky assets. The model can be expressed generalized form as

algebraically

in a

where E(aj) is the expected return on any assetj; E(K,) is the expected return on the market portfolio; E(y,) is interpreted as the expected return on any security whose return is uncorrelated with j?,; and

cov(Rj* Km) Pj =

a’(K,)’

The Sharpe-Lintner model explicitly states that the intercept term, E(*>,), is expected to be equal to the return on a riskless asset, R,. Black (1972) and others vary the underlying Sharpe-Lintner assumptions to develop models in which the intercept E(y,-,) is greater than R,. In this paper, it is not necessary for us to distinguish between these two versions of eq. (I). Rather, we make use of the empirical results of Black, Jensen, and Scholes (l972), and Fama and MacBeth (1973), which are consistent with a positive lincnr tradeoff between systematic risk, fl,, and expected security returns, E(aj), with no measure of risk other than b, aflecting expected returns E(Rj). A comprchcnsivc summary of the liternturc on the two-pnramctcr model can be found in Jensen (I 972). Fama (1973) shows that if the Sharpe-Lintncr model is derived from the assumption of multivariate normal asset returns, then a linear relationship exists between 8, and R,, with /?, = Cov (R,, &J/a2(R,,). Applying these results to the more gcnernlizcd asset pricing equilibrium model described in eq. (I), for which we assume that y,, is the minimum variance portfolio that is uncorrelatcd with 8,,,, a linear relationship exists bctwecn asset returns 8,, lo, and 8, which can bc expressed as

RJ= ~,+ll,,o70+/1,.,k+(;,,

(2)

where cov P/m

=

(RJ.

--

8,) =

/IJ,

aZ(RA

PJ.0 = and is the stochastic disturbance term for assetj. Rearranging eq. (2) into excess return form and making period returns by adding the subscript I, we have ‘?J

#J,,-PO.,)

=

a,+P,(R,.,-~0.,)+2J,,.

use of period-by-

R.G. Ibbotson, Price performonce

The conditional

expectation

of common stock new issues

241

of eq. (3) is

The market equilibrium model described by eq. (1) then says that aj = 0 for allj. Thus estimates of a, in eq. (3) provide measures of ‘abnormal performance’, given that (1) is the appropriate model of market equilibrium. We shall use estimates of a; to test the return performance of new issues. In order to utilize the two-parameter model described in eq. (3), it is necessary to have a measure of the two market factors, i?,,,,, and PO,,. This paper uses an equally weighted arithmetic average of the returns on the New York Stock Exchange (NYSE) stocks as a measure of k?,., and To., estimates derived from NYSE stocks in the Famn and MacBeth (1973) paper.6 As all but nine of the stocks in the sample were traded in over-the-counter (OTC) markets during the entire period of study, application of the 8,,, and lo., series to the new issues may cause a problem if OTC stocks behave differently from NYSE stocks. This problem will be discussed later in the paper.

2.3. Tire RATS model In the present paper, we measure the systematic risk of a portfolio that maintains a constant composition of security seasoning vver time. Measures of systcmntic risk for indilicidunl securities are not possible since there is no price scrics available prior to the offering and since the stability of the systematic risk is itself being examined as the issues become seasoned. Since we arc combining returns across tim and securities, the model is designated as RATS. In the simplest case, WC mcasurc the return each month for a one-stock portfolio that consists of a different stock each month. One-stock portfolio regressions are classified as (/r-n) (read )I dash n), The first n refers to the purchase of each new issue at the bqinning of month II after the offering and the second IZrefers to the sa1c of each issue at the crttl of month n after the offering. The following RATS regression model is formulated for the general class of one-stock portfolio regressions (n-n) :

(~j.n-70)= a,,+~~,,(~,,-70)+Pn,-1(~,.-~-Po,-~)+~j,n,

(4)

where is the month of seasoning, ; 1.n

is the return

which is held constant

of security j during

in each regression;

the nth month of seasoning;

6The Fama and McBeth estimates of _i,,., were calculated only through June 1968. Extensions of TO., through 1971 were obtained using their same procedures except that portfolio rankings were not updated after June 1968.

242 a,

Bn.0

R.G. Ibborson, Price performance

of common stock new issues

is the regression constant which is the average return in excess of the returns implied by the equilibrium relationship described in eq. (1) (z, will serve as a measure of abnormal performance); is the regression coefficient for the unlagged independent variable;

BIl.-l

is the regression month;

coefficient

&PO

are measured during the same calendar month as Rj., for the unlagged independent variable (8, -To), and measured in the previous calendar month for the lagged independent variable (&_1 --70,-,);

ej.m

is the stochastic seasoning.

disturbance

for the independent

variable

term for asset j during

lagged

the nth month

one

of

Due to inactive trading in many of the newly issued securities, month-end quotes may be old and therefore out of date. As a result, part of a stock’s actual return for any month may be reflected in the next month’s measured return.’ In order for the measured return 8,,” to be matched with the corresponding month’s R,,, and lo, the previous month’s 8, and y. have to be included in the model. The addition of the lagged independent variable does not substantially affect the statistical properties of the model and may reduce the residual variation. Since returns from the market portfolio are independent from month to month. eq. (4) does not exhibit multicollincnrity. The true beta, b,, can be shown to be approximately equal to the sum of the lagged and unlagged betas,

The source of the first year’s data elcmcnts for the particular regression thzif mcasurcs the systematic risk and performance of new issues during thcirfirsf month of seasoning (II = I) is illustrated in table 4. The elcmcnts of rcgrcssion (I- I) arc the one-stock portfolio excess returns, (Rj,,- yo), from each ol’fcring’s first month of seasoning. rcgrcsscd against both the same and previous calendar month market excess returns, C,R,,,- y,J. Note again that each data point for the RATS regression model is drawn from a separate calendar month, eliminating potential dependence arising from returns drawn from identical periods. The RATS model posited in eq. (4) has the unique advantage of allowing for the contingency that the sys!cmntic risk of new issues may change as the issues become seasoned, that is, for larger values of II. However, eq. (4) is not a direct transformation of the two-parameter model described in cq. (3). Unlike the exhibiting differing R ,., in eq. (3). the I?,,, in eq. (4) arc drawn from distributions systematic and unsystcmntic risks because a different securityj is in the portfolio ‘The lack of timeliness of quotes was examined by running the RATS regression model of variable. Preliminary results indicated that only the first lag is important.

eq. (4) including various lag terms in the independent

R.G. Ibbotson,

Price performance

243

of common stock new issues

Table 4 Illustration of one-stock portfolio that is composed of each new issue during its its tirst month of seasoning [regression (l-l)], partial layout of sample.’ Calendar month (r) 1960 Stock(j) 1 2 3 4 65

1

2

@

3

4

5

6

7

8

9

10

11

12

:

:: 2 0

:

4

:

!

9 8

10 9

: 0

‘: 02

: ;

4 ;

: ;

; ;

11 10 9 8 ;

12 11 10 9 ;

2

3 2 0

;

;:

;

: 0

4 3 2 0

’ 0 *

0

7 8 9 10 11 12

0

2 0

‘During every calendar month r, a new issuej enters the portfolio. At the end of the calendar month, the new issue is removed from the portfolio. The circled numbers represent the stocks by security and month which form the one-stock portfolio. The excess returns on the portfolio are the elcmcnts of the dependent variable (R, ..- PO)in cq. (4).

each month. Thus the true /?” in eq. (4) is not fixed but has ;1 diffcrcnt for each nssct j.

value, /I,,

Fortunately, we can apply the ‘random coeflicicnts’ model described in Theil (1971) and Zcllncr (1966). As long as the independent variable (&-f,J in cq. (4) is uncorrclatcd with the eq. (4) error term .!?,,“, the 8. nnd 8. in eq. (4) are unbiased estimators of the mean uj and /?, in eq. (3).* Thus, 67, and /I” estimate the mean performance and systematic risk for all securities j during their nth month of seasoning. The estimators are not minimum variance because the disturbances E,,, are heteroskedastic. In our case, the hcteroskedasticity is caused by the differing systematic risk p, and unsystematic risk a2(Cj,,) that correspond to the changing securities j in the portfolio.” %cc Zcllner (1966. especially p. 7, f.n. 5). Strictly speaking, the different values of the systematic risk /I, should also be drawn from distributions having the same mean. As the sample has been randomly selected, this last condition would not be violated unless the systcmatic risk of securities during their nth month of seasoning were calendar-time dependent. For a discussion ofcalendar-time depcndcnce, see lbbotson and Jaffe (1974). %uppose the true underlying relationship describing one-period returns on a security is a, = J%&+z,,

24-I

2.4.

R.G. Ibbotson,

The aggregated

RATS

Price per]ormance

of common stock new issues

nlodel

The RATS model is sufficient for measuring performance over separate months of seasoning n. However, in order to measure performance over holding periods r that are longer than one month (r > 1) and to insure that the observations will be independent of each other, a more sophisticated approach is necessary. The procedure used is to measure monthly returns for a portfolio consisting of r securities. Each security in the sample is held in the portfolio for r months. At the beginning of each calendar month, one stock is added to and one stock is sold from the portfolio so that the portfolio always consists of r securitieswithmonthsofseasoningn,n+l,. . .,n+r-I. The aggregated RATS model for any regression [(n)-(n + r - l)] (read n dash n + r - 1) can be described algebraically as follows:

0 p.n,r- Jo)= %,,+L,o c~~-~o>+~“,,,-,~(~,,-t--~,,-,,+e,,”,,, (5) where is the calendar month return of the r-stock portfolio p consisting of equal dollar weights in issues with months of seasoning n, n+ 1, . . . , n + r - 1 (the n and r are constant in each regression); &I. PO arc measured during the same calendar month as Rp,“., for the unlagged indcpcndcnt variable (I?,,,-yo) and in the previous month for the lagged independent variable (n,,,,_, - yo,_,); is the rcgrcssion constant which serves as a mcasurc of abnormal c!,I.I pcrformancc; is the rcgrcssion cocflicicnt for the unlagged indcpcndent variable; is the regression coelXcicnt for the lagged independent variable; is the regression disturbance for thepth portfolio. a p.n.r

To clarify cq. (5), we present an illustration. Suppose WC wished to measure the systematic risk and pcrformancc associated with buying stocks in each month on the offering date (n = 1) and selling them at the end of the sixth month of where /?I is the true beta of security j and 2, is the disturbance. estimate dilTerent from the true beta, our result becomes R,

Once we introduce

a beta

= Ii.R,+E,.

Setting the above two equations equal to each other and rearranging terms, the residual term ,!?, now encompasses both the dilTerence bctwccn the true /II and /I”, and the 2, of the particular security. The variance of E, can be expressed in three components, UW,)

= (8,-/i,)o,2(R,)+~22(~,)+u,~.

Since /?, and ol’(P,) differ across securities j, the residual terms E, are heteroskedastic. Fortunately, the hcteroskedasticity is likely to diminish when multistock portfolios are used, and we do so in section 2.4. A multistock portfolio with only one stock changing each calendar month is likely to have a far more stable beta, &,, and unsystematic risk, uz2(~& over time than a single stock portfolio that contains a dillizrent security j each calendar month.

R.G. Ibbotson, Price performance

of common stock new issues

245

seasoning (n+r1 = 6). Table 5 shows the source of the first seven input elements for regression (l-6). The elements of regression (l-6) are the six-stock portfolio excess returns (a p,n,,-TO) regressed against both the same calendar month’s and the ooemonth lagged calendar month’s market excess returns (B,,,-To). After a new issue is purchased on its offering date, it is held in the portfolio for six months, and then sold and replaced with another new issue purchased on its offering date. One new issue offering is purchased each month, and one six-month seasoned offering is sold each month, so that the portfolio return consists of the Table

5

Illustration of six-stock portfolio (denoted by italics) that is composed of each new issue during its first six months of seasoning [regression (l-6)], partial layout of sample.’ -_ Calendar

Stock 0’)

12345

1 2 3 4 5 6 7 8 9 IO I1 I’

1

2 1

345 2 3 1 2 1

4 3 2 1

------

month (I) 1960

6

7

8

9

10

11

12

6 5 4 3 2 I

7 6 5 4 3 2 1

8 7 6 5 4 3 2 I

9 8 7 6 5 4 3 2 I

10 9 8 7 6 5 4 3 2 I

11 10 9 8 7 6 5 4 3 2 I

I2 11 10 9 8 7 6 5 4 3 2 I

--

‘During every calendar month I a new issue j is purchased on its offering date and inserted into the portfolio p, The issue is then held until the end of its sixth month of seasoning. Each of the six stocksj in the portfolio p are held during their first, second, third, fourth, fifth, and sixth month of seasoning, respectively. Thus, the portfolio excess return (A,...,&) is the average of the six security excess returns measured during the same calendar month 1.

average of six security returns measured during the same calendar month but measured during the first, second, third, fourth, fifth, and sixth month of seasoning for the rcspcctivc securities. Note that the first observation is not drawn until June 1960, since this is the earliest calendar month in which the entire sixstock portfolio can be held. Combining the returns into portfolios serves to reduce the sampling errors in the parameter estimates. Due to the effects of diversification, the unsystematic risk in eq. (S), a2(EP,,,,) will be less than the unsystematic risk of eq. (4). a*(,!?,,“).

246

R.G. Ibbutson. Price performance of common stock new hues

3. Results The results presented in this section make use of the aggregated RATS model described in eq. (5). To simplify the analysis, the regressions are classified into four groups. Table 6 provides an index to the various regressions included in each group.” 3.1. Examination of initial performance We test the hypothesis that initial performance is positive. In principle, we would like to measure initial performance from offering date to first trade. However, because our data include only offering date prices and calendar monthend prices (as well as any capital adjustments), initial performance is measured by the first partial month performance from group I regression (l-l). This is an impure measure of initial performance since it includes up to one month’s aftermarket performance. Table Regression (L.,-70) . -.-

6

classifications,

= ~“.,+A.,.*(I?~-~“)+P”.~.-t(~~,-,-~0.-L)+21,.n.r.

__--_--_~__

__-_ Group I regressions

Group II regressions

Group 111 regressions

Group IV regressions

1.7,

13. . . ., 55

I

sclectcd

6

1’. -, . . 12. 24,. 60

_l--_-l-. n (beginning of month seasoning in which new issue was purchased)

I’9-v . 60

r (number of months securities held)

1

Regression classifications [(!I)-(n + r - I )I

. .*

-

_~ -

~----II

., 6. . .,

I-1.2-2,

l-6.7-12.

l-1, 1-2,

. . *, 60-60

. . ., 55-60

. . ., 1-6. l-12,

l-24,

selected

l-l, 2-6. 3-6.4-6, 5-6, 3-4

. . ., l-60

Group I regression (l-l) shown in table 7A indicates that first month pcrforof table 7B mance 8,,, is 11.4 pcrccnt with a r-statistic of 3.48. Examination reveals that the distribution of residuals does not closely resemble a normal distributive. Rather it is highly peaked and skewed toward the right (positive) with fat tails. Only 37 percent of the residuals from the first month regression ‘“Many of the group I regressions (where r = 1) contain a few missing elements resulting from missing or delsted quotes. Generally, group II-IV regressions do not contain missing elcmcnts. even though some of the portfolios contain less than r stocks due to the missing or delctcd quotes.

R.G. Ibbotson.

Price performance

of common stock new issues

247

are positive, while 58 percent are within one negative standard deviation from zero. Thus B,,, estimates only the mean performance, which is above the median performance. Table 7

(R,,.,,-M

Group I regression (l-1). = a~..+B..,.o(R,-,;o)+B..,.-l(r?,.-,-~~.-l)+E,...,.(n

B. Residual distribution, relative frequency of E,,.., .

A. Summary statistics 1-I

Unit normal

Coefficient S.E. t-statistic Coellicient S. E. t-statistic Coetficient S. E. t-statistic

0.114 0.033 3.481 2.178 0.699 3.116 0.082 0.704 0.084


>4.0

0.0089

0.0013 0.0228

> 3.0 > 2.0

0.0179 0.0179

Mean S.D. Mean S. D.

0.124 0.352 0.128 0.35 I

Regression

uI*, Bn.r.0 L-1 (&*.,,-Y,) P &I*. R’

0.066

D. W. S. E. of estimate Dcgrccs of freedom

I .946 0.340 109

_-..lpl_.

= 1.r = 1):

____ __~.._ ________.-__-I-

S.D.

l-1

0.0440 0.0919

1.5 to 1.oto

2.0 1.5

0.0357 0.0804

0.1498 0.1915

0.5 to 0.0 to

1.0 0.5

0.0714 O.lSI8

0.1915 0.1498

-0.5 to 0.0 -1.0 to -0.5

0.3571 0.2232

0.0919 0.0440 0.0”s o.Oz3 c 0.0001 -_-_---

-1.5 to - I .o -2.0 to - I.5 < -2.0 c -3.0 < -4.0 _.~---

0.0357 0.0179 0.0000 o.OOtN 0.0000

‘Regression n = I, r = I mcasurcs systematic risk and pcrformancc their first month of seasoning.

of new issues during

A listing of the sorted rcsidunls is shown in table 8. Note that since 8,., is 1I .4 percent, the individual initial performance (a,,,+ gP’,.,,,) is positive in 66 of the 112 cases. To test to see if \VC‘have better than an even chance of drawing a positive initial performance, WC compare the 66 successes with the number of successes predicted by 112 independent Bernoulli trials (112(1/2) = 56). Since the standard deviation of the 112 Bernoulli trials is d[(112)(1/2)(1-l/2)]

= 5.29,

the t-statistic is (66- 56)/5.29 = I .89, and it is not quite possible to reject at the 5 percent signilicance level the null hypothesis that we have only an even chance of observing a positive initial performance. We are more interested in discovering whether the mean initial performance d,,, is positive. As mentioned in section 2. eq. (3) and subsequently eq. (5) are

248

R.G. Ibbotson, Price performance

of common stock new issues

based on the assumption of multivariate normal asset returns. The unusual observed residual distribution is contrary to this assumption. In light of the unusual residual distribution, there is a potential danger in interpreting the alpha t-statistic of 3.48 as being drawn from a t distribution. If, however, the distribution of aggregated residuals approximates normality, our knowledge of normal distributions will help us to infer the probability of the 11.4 percent initial return being a random fluctuation. We therefore simulate the initial performance estimates by drawing from the observed residuals. Five hundred Table 8 Listing of 112 sorted residuals, I?,,‘,...,,from regression (l-l).’ 2.045 1.129 0.585 0.541 0.531 0.521 0.499 0.452 0.434 0.432 0.406 0.394 0.376 0.360

0.348 0.315 0.297 0.297 0.262 0.256 0.209 0.194 0.192 0.162 0.160 0.154 0.152 0.145

0.143 0.140 0.140 0.112 0.105 0.096 0.076 0.071 o.O‘t9 0.03s 0.014 0.007 -0.006 -0.024

- 0.028 - 0.029 -0.029 -0.034 -0.039 -0.041 -0.041 -0.043 -0.047 -0.049 - 0.049

- 0.066 - 0.067 -0.071 - 0.077 -0.081 - o.os2 -0.101 -0.108 -0.108 -0.113 -0.119

-0.126

-0.lS8

-0.258

-0.130

-0.204

-0.266

-0.131

-0.205

-0.268

-0.131

-0.214

-0.270

-0.138

-0.216

-0.299

-0.140

-0.219

-0.329

-0.142

-0.219

-0.339

-0.150

-0.221

-0.380

-0.151

-0.223

-0.407

-0.169

-0.226

-0.483

-0.173

-0.227

-0.499

-0.060

-0.121

-0.175

-0.242

-0.558

- 0.064

-0.125

-0.178

-0.244

-0.563

- 0.064

-0.125

-0.179

-0.246

-0.701

. ‘The^ 66 residuals to the left of the vertical lint rctlcct positive initial performance (SM.,+ &,...,) SlllCCct:n,r= 1I .4 pcrccnt. simulations of the residual mean arc calculated by drawing I12 residuals with repluccment from the regression (I-I) observed residuals. The results of sclcctcd sorted simulations are shown in table 9. Even though the distributions of residuals themselves are highly peaked and skewed to the right with fat tails, the simulated means closely rescmblc a normal distribution. Moreover, only the largest observation (13.8 percent) is greater than &,,, (I I .4 percent). Therefore, the simulations indicate that there is only one chance in 500 that an initial performance as great as il.4 percent would be observed conditional on zero initial performance with residuals distributed as in regression (l-l). Thus, we conclude that initial mean performance is positive. The measurement of initial performance may also be affected by the ten issues for which the first end of the calendar month quotes are identical to the offering prices. Each identical quote could bc the result of no change in price in a free market, an absence of trading during the period, or by stabilization practices

R.G. Ibbotson, Price performonce of common stock new issues

249

affecting the floating of new issues.” In either of the latter two cases, initial performance would not be reflected until the second calendar month of seasoning. However, a preliminary study that included these ten second-month returns in initial performance had a negligible effect on the results.” Table 9 Selected results from 500 sorted simulations of mean residuals E‘lzP_i~P.,$ I2 when drawn with replacement from regression (l-l).’

Observation number 1 2 3 4 5 10 15 20 25 :: 40 45 50 7s 100 125 150 175 200 225 250 ‘Mean of’ means

Simulated mean residual

Observation number

Simulated mean residual

- 0.089 - 0.086 -0.os5 - 0.078 -0.078 -0.061 - 0.056 -0.053 - 0.050 -0.049 - 0.047 -0.044 -0.043 -0.041 0.035 - 0.028 -0.024 - 0.0’0 -0.017 -0.013 -0.009 -0.005

500 499 49s 497 496 491 486 481 476 471 466 461 456 451 426 401 376 351 326 301 276 251

0.138 0.107 0.100 0.089 0.085 0.068 0.059 0.056 0.054 0.053 0.05 I 0.048 0.044 0.040 0.03 I 0.020 0.018 0.012 0.007 0.003 -0.001 -0.004

= -0.002;

standard deviation of means ~0.033.

“The Securities Act of 1934. Rule lOB7 (last amended in 1954) provides for stabilization policies through which the underwriting syndicate may provide market support known as ‘pegging’. In this case the syndicate may buy up stock in order to keep the market bid price at least equal to the fixed oflizring price for the fen days following the olfering date. “The second-month average performance,

of the ten issues which have first month-end quotes identical to offering prices is 7.5 percent. Relative to the standard errors of estimation, 7.5 percent is not very dilfcrent from the average performance in either regression (l-l) or (2-2). which are II.4 percent and 7.6 percent, respectively. Including the ten second-month performance estimates as first-month performance changes the performance of regression (l-l) to 12.1 percent, while leaving the performance of regression (2-2) at 7.6 prcent.

250

R.G. Ibbotson. Price performance of common stock new issues

The large magnitude of initial performance makes us suspect that it would be uncovered even with far simpler models. For example, the average monthly return of the market 8, during the period is only 0.6 percent. If we only look at K p.n.r or (&.,,,ii,,), we observe mean returns of 12.8 percent or 12.4 percent, respectively, compared with both having standard errors of 3.3 percent. Furthermore, the R-square of regression (l-l) is only 0.066, indicating that the betas explain very little of the variation of the dependent variable. Therefore, the finding that initial performance is positive is robust to almost any reasonable model formulation. This result is fortuitous in our case since we make an OTC application of 8, and To which are derived from NYSE stocks. In another study, Ibbotson and Jaffe (1974) use a,,,,,,-a, as a simple measure of performance. During the same time period, using the average firstmonth returns on all new issues (rather than one random new issue each month), they find that their average performances each month are positive in 97 out of the 120 months, with an overall average monthly performance of 18.5 percent per month. We have presented strong evidence that the mean initial performance is positive. We cannot conclusively determine whether the investor in a single random new issue has better than an even chance to make a profit. He does, however. draw from an extremely skewed and disperse distribution (the standard yO) is 35.2 percent )which gives him a higher likelihood of deviation of (R,,,.,an extrcmcly large positive performance than a correspondingly large negative performance. 3.2. Exatninalion of aftcrtttarkcr performance WC now cxaminc whether there arc dcparturcs from market cfliciency in the aftcrmarkct. In our search for dcparturcs we use all the regressions in groups I-IV that do not include purchases on the oILring (tz = I). If the aftermarket is etlicient, WC do not expect estimates of pcrformancc, bl,,,, to be significantly different from zero. Group I regression (2-2) gives us our first measure ofaftermarket performance. The second-month mean performance (a,,, for tz = 2, r = 1) is 7.6 percent with a I-statistic of I .879. Only 27 percent of the second-month residuals are positive, while 71 percent are within one negative standard deviation of zero. In light of the unusual distributions of residuals, the relatively low !-statistic, and the CJct that only 53 percent of the individual second performances (c2,,,+E,,“.,) are positive, the second-month pcrformancc taken by itself is not statistically significant. Examination of the remaining group I regressions (tz = 3,4, . . ., 60 and r = 1) in tables IO and II indicates that after the first and second months there are few large departures from cficiency. The alpha r-statistics have absolute values that are never greater than three and only grentcr than two in five out of

TO)

Mean S. D.

Coeficient S. E. r-statistic Coefficient S. E. r-statistic Coefikient S. E. r-statistic Mean S. D.

D. W. S. E. of estimate Degrees of freedom

RZ

Lr

(k,,..,-

L-l

LO

in.,

Regressions

0.076 0.011 1.879 2.035 0.902 2.256 - 0.707 0.881 - 0.80’ 0.087 0.427 0.091 0.431 0.030 2.024 0.421 107

7-Z 0.019 0.016 1.168 1.481 0.332 4.458 0.027 0.341 0.080 0.029 0.180 0.033 0.179 0.139 1.745 0.167 113

3-3 0.001

0.011 0.261 1.841 0.297 6.196 -0.861 0.303 -0.532 0.015 0.176 0.018 0.178 0.237 1.854 0.154 116

5-5

0.019 2.560 1.285 0.411 3.129 -0.378 0.408 - 0.927 0.055 0.213 0.059 0.214 0.065 2.174 0.206 113

43 0.050

___~___

0.024 0.015 1.586 1.546 0.310 4.978 0.144 0.310 0.464 0.036 0.175 0.089 0.174 0.175 1.974 0.159 114

6-6

0.017 -0.256 1.747 0.354 4.941 0.369 0.359 1.029 0.009 0.204 0.010 0.202 0.184 1.726 0.184 115

8-8

0.016 -0.289 1.600 0.332 4.813 0.302 0.328 0.920 0.008 0.188 0.010 0.191 0.173 1.843 0.171 116

-0.005

-_____

-0.001

7-7

Group I regressions [Or)-(n+r - l)] summary statistics, (I?,...,- ;‘”) = %r+B..,.dL-x)+B ..,,- ,(E7”._,-j;,,_,)+~~...,.

Table 10

0.015 0.281 1.947 0.324 6.007 0.535 0.317 1.688 0.024 0.191 0.025 0.191 0.262 1.710 0.164 115

0.004

9-9 0.010 0.015 0.638 1.215 0.306 3.966 -0.136 0.312 -0.435 0.02 1 0.166 0.033 0.166 0.106 1.541 0.157 114

IO-10

0.015 0.014 1.042 1.135 0.280 4.050 0.487 0.292 1.666 0.030 0.162 0.032 0.159 0.140 1.898 0.150 114

11-11

- 0.020 0.014 - 1.387 1.220 0.276 4.422 0.803 0.282 2.848 -0.005 0.169 -0.002 0.166 0.209 1.830 0.150 114

12-12

252

R.G. Ibbolson, Price performance

Group I regressions:

Plots of performance

of commonsrock

new issues

Table 11 measure z.,~ (left) and related r-statistics

(right).’

4.000 .

l .

2.000

.

.

.

.

0.000~

jy._j

-4.000

-0.050

0

12

‘Months of

24

seasoning

36

46

60

(n)* n = 1.2, . . ,, 60; r

=

1;

.

”

. -2.000

.

.

‘0

‘1l .

. .

. .

.j

12

.

l

l .*

. ’

.

I 0

I

. .

‘.

2,

36

46

60

regressions l-l, 2-2, . . ., 60-60.

the remaining 58 regressions. Thus, we cannot reject aftermarket effkiency from these single stock group I regressions. However the saucer-shaped plots in table 1I with generally positive performance the first year, negative pcrformance the next three years, and generally positive performance the last ycnr suggest a possible pattern in the data to be examined in the aggregate results. Next we cxaminc the group II regressions shown in tables I2 and 13. The group II regressions for six month holding periods (r = 6) indicate once again the saucer pattern in the data, However, obsctvc from table I2 that the nine periods that do not include purchase on the offering (the periods exclusive of rcgrcssion (l-6) include only two periods in which the absolute values of the alpha t-statistics arc grcatcr than two (-2.242 for regression (13-18) and - 2.1 I5 for regression (43-48)). For group II regressions, the incidence of alpha r-statistics with an absolute value greater than two is somewhat higher than we would expect if the residuals were normally distributed. Yet none of these alpha t-statistics are much greater than two. Although they are not prcscnted here, the distributions of residuals exhibited serious departures from normality, particularly in the first year of seasoning. Therefore, we cannot reject aftermarket efliciency from the group II regression results.’ ’ The reader may argue that we do not explicitly test for the saucer pattern in the results. Howcvcr, we have no theoretical reason to suggest such a pattern. Tests designed solely through ex post observation of the results are by their nature ad hoc. Finally, the group II regressions are thcmsclvcs pokverful tests since the sampling errors arc reduced by the six-stock portfolio returns. “Preliminary in group II.

r = 12 regressions yielded results similar to those of the r = 6 regressions

Bo)

‘These

!-statistics

-___-

o&I9 0.013 3.850 1.683 0.267 2.561 -0.266 0.269 -0.990 0.061 0.153 0.063 0.164 0.250 1.990 0.133 112

1-6

are designed to test if /I.,,,,,

Coefficient S. E. f-statistic Coefficient S. E. r-statistic’ Coefficient S. E. f-statistic Mean S. D. Mean S. D.

R’ D. W. S. E. of estimate Degrees of freedom

&.n.r

(L.,-

L-1

Pa.r.0

Regressions __~ . a...

&...,+

regressions

>

1.

-0.002 0.008 -0.207 1.483 0.154 3.143 0.4-16 0.155 2.878 0.012 0.112 0.013 0.119 0.499 1.690 0.080 112

7-13

Table 12

-0.016 0.007 -2.242 1.424 0.135 3.148 0.255 0.135 1.895 -0.006 0.107 -0.003 0.1 IO 0.520 2.239 0.071 112

-0.014 0.008 -1.7&I 1.341 0.159 2.140 0.278 0.160 1.738 0.001 0.116 0.001 0.114 0.411 2.075 0.089 112

19-24 -0.003 0.010 -0.859 1.156 0.172 0.911 0.230 0.171 1.344 0.008 0.120 0.010 0.122 0.302 2.250 0.100 111

25-30 -0.014 0.008 - 1.686 1.281 0.152 1.852 0.184 0.149 1.232 -0.002 0.113 0.000 0.113 0.414 2.269 0.086 105

31-36

statistics,

(I?,-~,)+~“,,,-,~~,.-,-~~.--l)+~~ip.”.r.

[(d-o-( + I - l)] summary

13-18

70) = a&,+/j..,.0

Group II

-0.005 0.007 -0.668 1.255 0.124 2.063 0.312 0.123 2.529 0.008 0.103 0.009 0.10-l 0.542 2.063 0.069 99

37-42

:

--____

0.019 0.009 -2.115 1.170 0.159 1.077 0.169 0.159 1.063 -0.009 0.412 -0.007 0.111 0.381 2.203 0.088 93

43-48

0.014 0.011 1.331 I .044 0.186 0.246 0.407 0.186 2.195 0.023 0.121 0.026 0.120 0.314 I.678 0.100 87

49-54

$fi z ‘i E; P I!

0.‘07 0.484 1.953 0.078 81 ~__

2

2 : $ n 5

.: b 2.

8

8

g s

0.927 1.127 0.148 0.860 0.451 0.148 0.017 3.057

0.008 0.009

55-60

0.109 0.020

--

P cl

R.G. Ibbotson, Price performance

254

Table Group

II regressions:

Plots

of performance

of common stock new issues 13

measure, a.., (left) and related f-statistics

0.100

(right).*

2.000 -

O.OQO

0.050

-

-

0.000

-2.000

-0.050

-

-4.000 0

‘Months 7-12,.

-

12

*I

of seasoning

36

(n).

46

11 = 1,7.

60

0

13, 19,25,31.37,43.49,

12

24

55;

36

46

r = 6; regressions

60

l-6,

. ., S-60.

The group III regressions in table 14 are designed to test if the initial performance disappears in the aftcrmnrket. If aftermarket prices still reflect the positive initial pcrformnncc. then any portfolios that include the purchase of n new issue on the offering each month should also rcflcct the positive performance. Note that the performance is positive for all of the r-stock portfolios (r = 1,2,3,4, 5, 6, I2,24, 36,48, GO). If the portfolios in the group III rcgrcssions arc held for more than one month, the gcomctric man might bc the more rclcvant mcasurc of pcrformancc. In table I5 WCcompute an cstimatc for the gcomctric mean over the r months that pcrformancc is seldom less each security is held. I4 As. the r month compounded than the Il.4 pcrccnt initial pcrformancc, thcrc is no evidence that the positive initial pcrformancc is cvcr erxcd in the aftermarket. Even more direct evidcncc that new issue performance is not erased in the aftcrmarkct is :tvailablc in Ibbotson and Jaffe (1974). They rcgrcss the secondmonth pcrformancc on the first-month pcrformancc. Since the slope coefficient is positive with a t-statistic of 2.43, their evidence strongly dernonstrntcs that initial pcrformnnce is not erased in the second month of seasoning. However, their evidence dots suggest possible departures from market efliciency in the early months of seasoning following the offering. “Markowitz (1959) dcmonstrntes that a good approximation of the expected natural log of the gcomctric mean G expressed in terms of the mean A and variance of the one-period returns u* is E(ln(l +G)) = In(l +A)!@‘/(I +A)‘). Markowitz then runs simulations to show that r-multipcriod very small downward biases as long as r is not extremely large.

compounded

returns

have only

- To)

t&an S. D.

CoeRicient S. E. f-statistic Coefficient S. E. r-statistic’ Coefficient S. E. f-statistic t&n

0.033 3.4Y1 2.178 o.s99 1.690 0.062 0.704 0.069 0.124 0.352 0.128 0.353 0.066 1.946 0.340 109

0.114

l-l

-- -- -_

3.01’ 1.s90 0.689 1.351 -0.405 0.663 -0.810 0.105 0.341 0.108 0.347 0.050 2.017 0.332 116

0.094 0.03 I

l-2

‘These r-statistics are designed to test if /?n.,.O > 1.

D. IV. S. E. of estimate Degrees of freedom

RI

LJ

&..,.

L-r

LO

&..r

Regressions 0.069 0.021 3.258 1.809 0.449 1x02 -0.333 0.452 -0.737 o.oso 0.240 0.083 0.246 0.109 1.987 0.226 115

l-3

0.017 3.694 1.701 0.367 1.917 -0.325 0.367 -0.885 0.075 0.199 0.078 0.205 0.145 1.975 0.184 114

0.064

l-4 0.052 0.015 3.446 1.727 0.315 2.314 -0.296 0.315 - 0.940 0.064 0.175 0.066 0.181 0.197 1.879 0.157 113

1-5 0.049 0.018 3.850 I .683 0.267 2.561 -0.266 0.269 - 0.990 0.061 0.153 0.063 0.160 0.250 I.990 0.133 112

l-6

Table 14 Group Ill regressions ((n)++rI)] summary statistics,_ G,....70) = ~...+B”.~.o(R-90)+81...-rtR.-*-~~.-l)+E,.”.r.

0.024 0.009 2.730 1.881 0.176 3.301 0.081 0.178 0.458 0.041 0.114 0.042 0.121 0.426 1.831 0.087 106

l-12

0.007 0.667 1.450 0.131 3.449 0.123 0.132 0.931 0.024 0.094 0.021 0.099 0.562 1.861 0.062 94

0.004

1-24

0.006 0.616 1.408 0.118 3.465 0.057 0.117 0.486 0.024 0.087 0.022 0.090 0.627 1.807 0.053 82

0.004

l-36

0.006 0.671 1.383 0.105 3.657 0.051 0.106 0.477 0.023 0.084 0.022 0.086 0.71 I 1.593 0.045 70

0.004

l-48

__-

0.007 0.005 1.351 1.367 0.099 3.718 0.078 0.100 0,779 0.025 0.082 0.024 0.087 0.765 1.467 0.040 58

l-60

RX.

2.56

Ibbotson. Price performance

of common stock new issues

Table 15 Compounded

geometric mean performance of issues purchased on offering date (n = 1) and held for months r.

%.,

Estimate of geometric mean”

r, multiple month compounded return.

3.48 3.01 3.26 3.69 3.45 3.85 2.73 0.67 0.62 0.67 1.35

6.7 4.8 4.7 4.9 4.1 4.1 2.0 0.2 0.3 0.3 0.G

11.4b 9.8 14.7 21.1 22.2 27.2 27.4 5.2 9.8 15.4 44.9

a..,. hlonths held r

es:imate of arithmetic monthly mean’

1 2 3 4 5 6 12 24 36 45 60 -

11.4 9.4 6.9 6.4 5.2 4.9 2.4 0.4 0.4 0.4 0.7

‘Percentage values. When r = I, tbc compounded return is just &I..,.

To complete our search for departures from aftermarket efficiency, wc focus on the group IV regressions which measure the aftermarket performance in the first six months following the offerings. When new issues are purchased at the beginning of the second month and held until the end of the sixth month of seasoning (regression (2-6)), t!rc performance 8,*, is 3.5 percent per month with a f-statistic of 3.123. Note that 57 percent of the residuals arc negative, while thcrc arc some very large positive residuals. Other aftcrtnarkct holding periods are measured by rcgrcssions(3-6) (4-G) (5-6), and (3-4). Note from table I6 that the estimates of alpha &,., for these periods (2.5 percent, 2.7 percent, 1.7 percent, and 3.4 percent) are also high relative to their standard errors with l-statistics (2.854, 2.786, 1.642. and 2.591). From table 17 observe that the distributions are again highly peaked, and skcwcd to the right with fat tails. As the performance L!?,.,is high, WC may have uncovered an inefiiciency in the first six months following the otfering. However, this is a borderline case, since given the skewness in the residual distributions, it is questionable whether the mean is a suficicnt mcnsurc of central tendency. If we have uncovered an inethciency, we now desire to know if it is of suflicient magnitude to cover transaction costs. The mean bid-ask spreads for the first six months ending quotes are 7.0 percent, 6.4 percent, 6.3 percent, 6.6 percent, 6.9 percent and 7.3 percent.‘” None of the above single month arithmetic mean “The OTC mnrhct is a negotiated market so that it is dilficult to determine vvhere actual trades would take place. Since the introduction of the National Association of Securities Dealers Automatic Quotation Syjtcm in 1971 (after the period of study), dealers have been rcquircd to make bid-ask markets good for at lcast 100 shares.

R.G. Ibbotson,

Price performance

of common stock new issues

Table Group (L.,-70)

257

16

IV regressions [(+o+rI)] summary = a,.,+8..,.o(l?n-Y’o)+B....-I(Rm._I-:0._,)+~~.~.,.

statistics,

-_ Regressions

I-1

L-r

(&...,-

0.114 0.033 3.481 2.178 0.699 1.690 O.Oh2 0.701 0.089 0. I24 0.35’ 0.1X 0.353 0.066 I .946 0.340 109

Coefficient S. E. r-statistic Coefficient S. E. t-statistic” Coefficient S. E. r-statistic Mean S.D. Mean S. D.

a..,

;fcJ

R P.“., R’ D. W. S. E. of estimate Degrees of freedom

‘Thcsc

t-statistics

arc designed

2-6

3-6

4-6

0.035 0.011 3.123 1.634 0.237 2.684 -0.287 0.237 -1.211 0.047 0.140 0.048 0.155 0.286 2.056 0.118 112

0.025 0.009 2.854 1.528 0.183 2.893 -0.1’9 0.18’ -0.710 0.037 0.115 0.039 0.121 0.374 2.053 0.09 I II?

0.027 0.010 2.786 1.5J8 0.203 2.708 -0.181 0.206 -0.881 0.039 0.125 0.041 0.133 0.330 2.186 0.102 112

to test if /?m.,,0 z-

Table Group

IV rcgrcssionx:

Frequency

5-6

3-4

0.017 0.01 I

I.642 1.631 0.216 2.921 -0.056 O”1 .__ -0’5’ 0:019 0.135 0.031 0.141 0.328 1.918 0.111 11’

0.034 0.013 2.591 1.413 0.274 1.519 - 0.227 0.274 -0.830 0.043 0.151 0.046 0.155 0.175 1.987 0.137 114

I.

17 distribution

of residuals.

-~“-~-._---_--._--._---

L?,‘,,..,. --.-

_._. -I_

Rcgrcssions Unit

normal

Standard deviations

1-I

---< 0.0001 0.0013 0.022s 0.0440 0.0919 O.I49Y 0.1915 0.1915 0.1498 0.0919 0.0-140 O.O”Y O.OZ
2-6

3-6

----___-__-

3-4

to I.0 to 0.5 to 0.0 to -0.5 -1.0 -1.5

O.OOR7 0.0174 0.0261 0.0348 0.0348 0.0957 0.2348 0.2957 0.2087 0.0435 0.0’61

o.cwO 0.017-l 0.0318 0.0609 0.0-135 0.0609 0.2522 O.“Gl 0.IoS-I 0.0696 0.0435

0.0087 0.0174 0.0435 0.017-l 0.0522 0.1130 0.1739 0.2870 0.2087 0.0783 0.0261

0.0087 0.0174 0.0435 0.0000 0.0957 0.0522 0.2609 0.2435 0.2087 0.05’2 0.0435

0.0085 0.0085 0.0256 0.0513 0.0427 0.085G 0.2137 0.2735 0.2051 0.0684 0.0171

< -3.0 -2.0 < -4.0

0.0000 o.wOO 0.0000

o.OOOo 0.0000

o.Oooo 0.0000 O.OCOO

0.0000 o.OOOo 0.0000

o.oOw 0.0000 o.OooO

0.0000 0.0085 0.0000

I.0 t0

0.5 0.0 -0.5 - 1.0 -1.sto -2.oto

5-6 ~____

0.0059 0.017’) 0.017’) 0.0357 0.0804 0.0714 0.1518 0.3571 0.2232 0.0357 0.0179

1.5to

>4.0 > 3.0 > 2.0 ‘0

4-G -.--.

i:s

258

R.G. Ibbotson, Price performance

of common stock new issues

performances are above this magnitude. In table 18, we compute an estimate for the geometric mean, compound the estimate over the r months that each security is held and subtract out transaction costs. Only regressions (2-6) and (3-6) have geometric mean compounded performance that are sufficient to cover transaction costs. Thus the results indicate that there are few, if any, departures from market efficiency in the aftermarket. 3.3. Examination of systematic risk and timeliness of quotes We have already noted that the aggregated RATS model described in eq. (5) explicitly allows for systematic risk of new issues to be different from the systematic risk of i?,, and for systematic risk of new issues to be seasoning dependent. We now examine the usefulness of these properties by testing two hypotheses. We first test to see if the systematic risk of new issues is greater than the systematic risk of the market portfolio. From section 2.3, the true beta b, is approximately equal to the sum of the lagged and unlagged beta. Note from the group I regressions that the unlaggcd betas /3,;,,0 plotted in table 19 are generally greater than one, whiic the lagged beta p..,,_l shown previously in tables 10 and I2 arc gcncrnily positive. In order to confirm that the systematic risks of new issues arc grcatcr than the systematic risks of the market portfolio, it is sufficient to dcrnonstratc that I),,.,.(, > I. WC thcrcforc examine the t-statistics measuring departures from /?n,r.O = I in the group II rcgrcssions. The group II rcgrcssions shown in table 20 rcvcal that rclativc to their standard errors the uniaggcd betas arc considerably larger than one for the first two years. Although statistical sigtiilicancc is not csrabiishcd in the remaining three years, it is noteworthy that ail the $n,,.O cocllicicnts arc grcalcr than enc. Thcsc results taken togcthcr conlirm that the average systematic risk of new issues is grcntcr than the risk of the market portfolio. The assertion that new issues exhibit higher than mnrkct systematic risk is intuitively appealing. In addition, new issues arc voiatilc stocks, and Fama and MacBcth (1973) have shown that mensurcs of systematic risk arc corrclatcd with measures of unsystematic risk. Next, wc test to see if systematic risk declines as the issues incrcasc their seasoning. Note from the group I regressions (table 19) that the uniaggcd betas lL.0 appear to decline with seasoning. The largest magcitudes arc observed in the first and second months with /?.,P,O equailing 2.178 and 2.03.5, respectively. The high first-month coeficient is particularly striking in that the estimator is downward biased (the raw first-month returns Rp,n,r do not reflect cntirc calendar month returns as do the y,, and 8, series). The group II (table 20) and group III (table 14) regressions also give evidence that the untagged betas fi.,,,0 decline with seasoning. In the group II regressions a decline is observed in seven of nine increases in seasoning, while in the group III

Z-6 3-6 4-6 5-6 3-t

--_--

3.5 2.5 2.7 1.7 3.4

Regression I(U)-ort r - 1)I

‘Percentage values.

G.P. estimate of arithmetic mean’

_ ~.

3.12 1.85 2.79 1.64 2.59

I-In., 2.9 2.1 2.1 1.1 2.5

Estimate of geometric mean’ 15.4 8.7 6.7 3.1 5.1

r, multiple month compounded return&

Table 18 geometric mean performance

_-- _~____

Compounded

_--

6.8 6.8 7.0 7.1 6.5

Mean bid-ask transaction costs for purchase in month n and sale in month (rr+r- 1)

after transaction costs.

8.6 1.9 -0.3 -4.9 - 1.4

Compounded performance after transaction costs’

R. G. Ibborson, Price perfirmance

260

of common stock new issues

Table 19 Plots of unlagged beta coefiicients &,.O (left), and related f-statistics (right).’

Group I regressions:

&OOO

6.000

l

--7---

-

l

:

!. 1 ~ I “I 1.

l. .

.

. -*-:;

4 000

i

..

.

.

_.

/

l

.

.

.

..

. .

.

2 000

.

’

j

.

*I .

.n

.’

. .

. 0 000

-2 000

_ 0

I2

24

16

48

(Ic

“Months of seasoning ()I), n = I, ‘7, . . ., GO; r = I ; regressions I-I. 2-2. . . ., GO-GO.

Group 11 rcgrcssions:

4 003

,000

rIL _-_-

.

2000--.-

. __-

--

c / --.-

,“.,rn

.-

(VL

0000

-I

000

29

~--

0

--

.-_-.

I

_.~--__i.__

/

I

12

24

-

__I J ._.’ I 1

<*c‘m”‘~

--+--

I

-_

fin,,,,, (Icft), and rclatcd f-statistics

I,1

. __.

yrml

,000

Table 20 Plots of unlaggcd beta coclkicnts (right).”

bnal~

.! -.--

I

36

I

.B

60

‘hlonths of seasoning ()I). n = I. 7. 13, 19. $5. 31, 37, 43.49. 55; r = 6; regressions 7-12,. . .) 55-60. These f-statistics arc dcsigncd to test if jIm.,.o > 1.

1-6,

R.G. Ibbotron, Price performance of common stock new issues

261

regressions, a decline is observed almost uniformly as the holding periods (r) are increased, indicating that the first month of seasoning has higher systematic risk than the remaining months tested. The decline in the unlagged beta Ijn.,,O can be tested directly by running two regressions (one each for groups I and II results) of the following form:

Bn.r.0

(6)

= A,+A,tiz+&,

where is the integer 1,2, . . ., 60 for group I regressions (60-60), and 1, 2, . . ., 12 for group II regressions (55-60) ;

(l-l), (2-2), . . .’ (l-6), (7-12), . . .’

are the coellicients

(n) - (n + r - 1);

from the group I and II regressions

is the regression

constant;

is the regression

slope coefficient;

is the stochastic

disturbance

term.

Table 21 Eq. (6) rcgrcssion results. Data input from Group I regressions Group II regressions

Number of obscrvntionr

60 I2

A2 (t-statistic) -0.010 (- 2.68) -0.056 (-5.35)

R2

0.21 0.82

The results from the two eq. (6) regressions are presented in table 21. Since the ;iz estimates are negative with large f-statistics, WC can conclude that unlagged beta /?n,r,O dcclincs with seasoning. The decline of systematic risk as issues are seasoned may not be reflected uniformly or cvcn in general across all the securities in the sample. For example, if some securities increased their systematic risk while others decreased their systematic risk, there would bc a tendency for the high risk issues to drop out higher cost of dealer inventories, etc. of the snmplc due to bankruptcies, Therefore, we can only conc!udc that systematic risk tends to drop for those issues that remain in the sample.

262

R.G. Ibbotson, Price performance of common stock new issues

4. Economic interpretation of the results The results indicate positive initial performance. Therefore, either the offering price is set too low or the investors systematically overvalue new issues at the end of the first month of seasoning. Since the results indicate few, if any, departures from efficiency in the aftermarket, positive initial performance can only be attributed to a downward bias in the offering price. We now discuss the strange phenomenon of the underpriced new issue of offering. The three groups of actors are the issuers, the underwriters, and the investors. We want to know why the offerings are underpriced and who, if anybody, wins and who, if anybody, loses. Underwriters are the intermediaries between the issuers (those needing the capital) and the investors (those supplying the capital). If a security were issued in an unregulated competitive market, it would be sold to investors for whatever price it could fetch. The purchasers of the issue would not expect to earn any abnormal returns. Furthermore, the issuing corporation would expect to receive the purchase price less any distribution and risk assumption costs incurred by the underwriters. The primary lcgnl requirement that could affect the initial performance of the issues is the constraint that new issues must be offered at a fixed price. This stems from the ‘Rules of Fair Practicc”6 and is implicit in most of the regulations described in the Securities Act of 1933 and the Securities and Exchange Act of 1934.” Under these rules it is necessary to set a maximum filing price two weeks in advance of the actual oRering, although the maximum Ming price can be adjusted in some cases. The price of the offering need not be set until immcdiatcly bcforc the offering. Once the offering is made it is possible for underwriters to break the syndicate; that is, sell the omering at lower than the fixed price that was set for the olrcring. However, in the case of strong demand it isr~of possible to sell any part of the issue above the fixed olTcring price. Once underwriters arc constrained to offer new issues at a fixed price, there are potcrtfiaf one-sided risks that may be borne. If the value of the new issue (the fixed price plus the initial performance) is grcntcr than the fixed price, the investor who purchases the offering earns a profit. On the other hand, if the value of the new issue is less than or equal to the fixed price, the new issue can only be sold to investors for its value. Underwritings are made on either a ‘firm commitment’ or ‘best efforts’ basis. ‘Vhc ‘Rules of Fair Practice’ are a set of mandatory standards set by the National Association of Security Dcalcrs, a national securities association registered under the Securities and Exchange Act of 1933. “In 1933 the Securities and Exchange Commission was established and empowered particularly with the Securities Act of 1933 and the Securities and Exchange Act of 1934. The former Act provides for disclosure and the prevention of fraud in distributing new issues. The latter Act purportedly restricts manipulation of the stocks in the aftermarket.

R.G. Ibbotson.

Price performance

of common stock new issues

263

In the case of firm commitment underwritings, the underwriter purchases all of the issue from the issuer and consequently bears all of the risks in selling the issue. The fixed offering price (to the investors) is equal to the underwriter’s purchase price (from the issuer) plus the underwriting spread.” In the case of best-efforts underwritings, the underwriter receives the underwriting spread to cover his costs, but the issuer bears the risks of selling the issue at the fixed price. In theory, the fixed-price mechanism can be circumvented. In firm commitment underwritings, if the spread were controllable by the underwriters, it would be in their interest to set the spread arbitrarily high by setting the offering price arbitrarily high. Similarly, in best-efforts underwritings, it would be in the interest of the issuers to instruct the underwriters to set the fixed price arbitrarily high. In either event, no stock would be purchased by investors at the fixed offering price causing the syndicate to break. Thus, the fixed-price mechanism would be circumvented, and the new issues would be sold for whatever price they would fetch in the free market. However, since few syndicates are broken,” we know that these methods of avoiding the fixed-price mechanism are not widely used. Although the methods are not explicitly illegal, they evidently are against the intent of the ‘Rules of Fair Practice’. Even if underwriters must price their oKerings at a fixed price that cannot in general be above the value of the offerings, there is apparently no law (either implicit or explicit) that prevents the fixed price from being set exactly equal to the value of the new issue. This would be accomplished if underwriters a&cd to see the demand schcdulcs of the investors as a condition of sale. In fact, this happens. Undcrwritcrs typically ask the purchasers to ‘circle’ (pledge to subscribe to) the issues at a certain price. Even though this pledge is not legally binding, no purchaser could disguise his demand curves for the issues over a reasonable period of time without giving up his access to the new issue market. Once WC assume that the fixed price is constrained so that it cannot be set aboce the new issue’s expcctcd value prior to the offering and cannot always be set exactly equal to the rcalizcd value of the orering, then the potential oncsided risk becomes a reality. ” The next best solution is to set the fixed oflering

‘“This spread typically allows for a management fee, an underwriting group spread, a selling group spread, risk assumption costs, and possibly an expense allowance. The spread is usually received in cash but may involve a certain percentage of the shares, certain rights or warrants, and/or other types of noncash remuneration. “See A history ofcorporate finance for the decade (1972). *“We can get a measure of the cost of the one-sided risk if we consider the new issue offering as an option being given to the investors enabling them to buy the issue at the fixed price. The cost of the one-sided risk is equal to the value of the option, which is given freely to investors. Assuming the fixed price is equal to the cxpectcd value of the issue prior to the offering date, and assuming the initial performance is normally distributed (with a standard deviation of 34.0 percent), then the Black and Scholcs (1973) model indicates an option value of 14.0 percent of the fu;cd price.

264

R.G. Ibbotson, Price performance

of common stock new issues

price equal to the new issue’s expected value. Strangely enough, we have not soIved the mystery of the empirically observed underpriced new issue offerings. Setting the fixed offering price below the expected value is clearly suboptimal even under the current assumptions. We now suggest a few scenarios that, even though they may not be very plausible, are at least consistent with the empirical findings. The underpricing of new issue offerings could be explained thus : (1) If regulations require underwriters to set the offering price below the expected value. (We have earlier indicated that implicit regulations may prevent underwriters from setting prices above the expected value. However, it appears very unlikely that regulations would even implicitly require underwriters to set the offering price befolv the expected value.) (2) If underpriced new issues ‘leave a good taste in investors’ mouths’ so that future underwritings from the same issuer could be sold at attractive prices. (Although this explanation is prevalent on Wall Street, it clearly violates an efficient market framework.) (3) If undcrwritcrs collude or individually exploit inexperienced issuers to favor investors. (Since the population of underwriters is very large,” one would expect competition among underwriters to eliminate exploitation possibilities.) (4) If firm commitment underwriting spreads do not include all of the risk assumption costs, so that the underwriter must underprice to minimize these risks. (Underwriters could rcccivc side paymcnis from investors that arc cqunl to the cost of the one-sidod risks.) (5) If through tradition, or some other arrangement, the underwriting process consists of underpricing olTcrings with full (or partial) compensation via side payments from investors to undcrwritcrs to issuers. (6) If the issuing corporation and underwriter pcrceivc that underpricing constitutes a form of insurance against legal suits. For example, errors in the prospectus may be less likely to result in legal suits when the stock’s initial performance is positive. In the author’s opinion, the mystery has not been solved. Although it is possible to conceive of scenarios that are consistent with new issue underpricing, each scenario either involves unknown legal constraints, needlessly complicated indirect compensation schemes, or irrational behavior. We now push ahead and analyze who, if anybody, wins and who, if anybody, loses from new issue underpricing. Ccteris paribus, investors would profit if they could purchase offerings at prices below their expected value. However, side payments from investors to

a’Sec A history of

corporate linancc for the decade (1972).

R.G. Ibborson. Price performance of common stock new issues

265

underwriters seem quite likely in that numerous new issues are oversubscribed.” In general, if investors were to request random new issues they would receive a disproportionate quantity of the undersubscribed issues relative to the oversubscribed issues. If an investor wants oversubscribed new issues, he may have to pay directly or, more likely, indirectly for them.” These payments could conceivably erase the entire abnormal returns available to investors. Side payments from underwriters to issuers could take various direct (which would be illegal) or indirect forms. For example, the underwriting spreads could be set artificially low so as not to cover the complete cost of the underwriting. In this way the issuer would receive the fair nef price for the offering since the underwriter’s anticipated loss by undercharging for this spread would be paid for by the side payment he receives from the investor. However, inasmuch as underwriter spreads are explicitly itemized and filed with the SEC, this form of indirect payment may be difficult to facilitate. Thus, we once again cannot form definitive conclusions. Investors may pay some or all of their profits back to the underwriters. Meanwhile, we can only imagine very indirect ways that underwriters might pay side payments to issuers. If there are any losses, they are probably incurred by the issuers. The gains, if any, would be somehow split up among underwriters and investors. 5. Conclusions

The results confirm that the mean initial performance of unseasoned new issues is positive. However, the distribution is peaked and positively skewed with fat tails. We cannot reject the hypothesis that an investor in a single random issue has an equal chance for a gain or loss. However, he does have a far higher likelihood of an extremely large positive performance than a correspondingly large negative performance. The results generally confirm that there are no departures from market efficiency in the aftermarket. The second through the sixth month of seasoning may have high performance, but few trading rules are profitable after allowance for transactions costs. Positive initial performance without departures from efficiency in the aftermarket suggests that new issue offerings are underpriced. No adequate explanation of the underpricing process is given. Furthermore, it is unclear whether ‘2There is evidence that many offerings are rationed. For example, according to the U.S. Securities and Exchange Commission (1963, p. 515), ‘It was not uncommon for underwriters to receive, prior to the effective date, public “indication of interest” for five times the number of shares available. Indeed, indications of interest received by the managing underwriters alone sometimes exceeded the total amount of the offering.’ “The existence of fixed minimum commissions and ‘soft dollars’ services (brokerage services which are paid for by directed commissions) illustrates that indirect payments are prevalent in the brokerage industry.

266

R.G. Ibborson. Price performance of common stock new issues

issuers actually suffer losses or whether they are somehow compensated by underwriters who in turn are compensated by investors. The results also showed that the systematic risks of new issues are greater than the systematic risk of the market, and the systematic risks of securities are not stable in that they drop as the issues become seasoned. However, the magnitude of the positive initial performance was large enough so that it would have been uncovered even had our models not allowed for these two factors.

158950 160390 161080 162780 163150 164910 163930 166811 168450 169200 170590 171080

173013 173740 173380 175550 178040 178520 181180 180290 182190 185920 186020 189440

2129160 3/24/60 4127160 5/25/60 6121160 7/25/a 8/30/60 9114160 IO/ 6160 1l/10/60 121 6160

l/ 5161 2113161 3/31/61 4/18/61 5124161 6/ 9161 7126161 8/30/61 9/21/61 10/17/61 ll/ 8/61 12/13/61

l/l l/60

SEC number

Date

Appendix

_

Pocket Books Inc. Wings and Wheels Express Inc. Shinn Industries Inc. Colonial Mortgage Service Co. Brown Fintube Co. Walter J. Schneider Corp. Denver Real Estate Investment Ass. Almar Rainwear Corp. Gilbert Youth Research Inc. Premier Albums Inc. Natpac Inc. Foote and Davies Inc.

Admiral Plastics Corp. Culligan Inc. Arcs Industries Inc. hletal Goods Corp. Smilen Food Stores Inc. Harvey Aluminum Inc. Reeves Broadcasting Development Corp. Allegheny Pepsi Cola Bottling Co. Vitramon Inc. American Foods Inc. Maj Leag Bowling and Recreation Inc. Anderson Laboratorrz Inc.

Name of issuer ______~

Table 22

z 900 1,678 600 8,000 720 504 600 475 1,609

15,600

600 1,897 375 1.500 1,000 17.063 1,500 1,000 1,035 501 1,350 1.013

(thousands)

Gross

Companies selected for sample.

600 85 150 100 122 120 800 120 65 120 100 165

150 136 100 100 200 750 300 200 104 167 150 150

Shares (thousands)

1;: 6:00 7.75 5.00 4.75 9.75

26.00 3.00 6.00 9.00 13.75

2Z.E 5:OO 5.00 10.00 3.00 9.00 6.75

4.00 14.00 3.75 15.00

Price per share (I)

268

R.G.Ibbotson, Price performonce

ofcommon

stock new issues

221990 224300 225270 225850 226930 227440 227140 229310

230640 227980 231550 232660 235090 236350 236540 238620 237350 238380 241130 240950

242300 243540 244560 246570 246790 249430 247150 250900 253360 254710 253650 256530

5/12/6-l 6123164 7/!5/64 E/12/64 9/!5/64 10/20/64 ll/ 5164 12123164

l/27/65 2/18/65 31 3165 4126165 5126165 6117165 71 7165 E/19/65 91 9165 101 7165 I l/16/65 121 E/65

l/20/66 21 9166 3122166 4128166 5112166 6120166 7119166 81 3166 9126166 1O/20/66 1!/30/66 12115166

Digitek Corp. Aristo Foods Inc. Computing and Software Inc. Mid-America Pipeline Co. Fine Organics Inc. Granite Equipment Leasing Corp. Sperte Drug Corp. Rover Shoe Co. Computax Service Inc. Visual Electronics Corp. Space Corp. Air California

George Philbrick Researchers Inc. Corn Tech Products Corp. Bet2 Laboratories Inc. Dickinson Electronic Corp. Shelby Williams Industries Inc. Henredon Furniture Industries Twenty Grand Marine Service Marion Laboratories Inc. University Computing Co. Miller Industries Inc. The Cyclotron Corp. Dynamics Research Corp.

Colonial Life and Accident Insurance The Alfred Hart Co. Loehmanns Inc. Gearhart-Owen Industries Inc. E. F. Johnron Co. Tracer Inc. Jack Winter Inc. Volkswagen Insurance Co.

480 1,000 660 8,279 1,376 1,200 2,400 326 1,170 1.702 1;268 2,500

1,075 1,313 7,393 1,381 1.723 5;094 5,160 3,940 1,127 551 l,ooO 1,879

3,150 1,080 2,520 1,001 3,733 2.145 2;514 8,727

80 100 110 453 275 240 300 130 60 180 130 250

50 150 359 120 160 304 300 187 250 110 100 150

238 135 210 200 250 110 200 727

6.00 10.00 6.00 18.29 5.00 5.00 8.00 2.51 19.50 9.46 9.75 10.00

21.50 8.75 20.59 11.51 10.77 16.75 17.02 21.02 4.51 5.01 10.00 12.53

14.74 8.00 12.00 5.00 14.93 19.50 12.57 12.00

Guenther Systems Inc. Kewaunee Scientific Equipment King Radio Corp. Private and Computer Schools Inc. Griffiths Electronics Inc. Medic-Home Developers Inc. Anathon Computer and Ed. Sys. Inc. Environmental Research Corp. Systems Associates Inc. Sanitas Service Corp. Patrick Plywood Enterprises Convenient Industries of America

270720 272600 273590 272000

275590 278810 280820 277500 281340 285680 281540 279360 294570 298820 299620 291990

l/31/68 2/l 5168 3/21/68 4/17/68 5116168 6/‘0/68 I/26/68 a/ s/as 9119168 10/l 7168 If/ 8168 121 3168

__-_

-___---

1,200 7,150 3,250 550 1,103 3,OOQ 1,050 660 950 1.485 3,375 3,506

1,200 500 13,680 7,200 2,160 1,020 330 4,800 1,050 2,518 1,050 3,000

Gross (thousands) -_.__ -_._______

Gilford Instrument Lab Inc. Gulf Aerospace Corp. W. W. Grainger Inc. Safe Flight Instrument Corp. Genl. Employment Enterprises Semtech Corp. Discon Corp. Computest Corp. Burgess-Manning Co. Frier Industries Inc. Sage Laboratories Inc. Scientific Control Corp.

257670 255720 259980 262480 262890 264240 265750 269570

Name of issuer

Table 22 (cont.)

I/ 3167 2/20/67 3/29/67 41 9167 51 4167 6/ 6167 I/l 9161 a/24/67 9/l 2161 I O/24/67 11/22/67 I 2/Z I 167

Date

SEC number -

__-______

110 105 300 150 110 100 165 250 234

286 250

200

100 125 750 360 180 120 110 3,ooo 100 265 100 400

Shares (thousands)

9.00 13.50 15.00

6.00 25.00 13.00 5.00 10.50 10.00 7.00 6.00 9.50

7.50

12.00 8.50 3.00 16.00 10.50 9.50 10.50

12.00 4.00 19.00 20.00

Price per share (S)

a q 2’ r* I!

j rp B

3 a’ B %

?J cl B g g .i

R.C. Ibborson. Price

performance

of common

stock MW issues

271

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272

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Stickney. C.P., Jr.. 1970. A study of the relationships of accounting principles and common stock prices of tirms going public, unpublished Ph.D. dissertation (Florida State University, Tallahassee). Stigler. G.J.. 1964. Public regulation of the security markets, Journal of Business 37. 117-142. The& H., 1971, Principles of econometrics (John Wiley. New York). Treynor, J.L., 1961, Toward a theory of market value of risk assets, unpublished manuscript. Zellner, A., 1966, On the aggregation problem: A new approach to a troublesome problem, Report 6628 (Center for Mathematical Studies in Business and Economics, University of Chicago).