The long-run stock performance of preferred stock issuers

Review of Financial Economics 15 (2006) 237–250

www.elsevier.com/locate/econbase

The long-run stock performance of preferred stock issuers

John S. Howe a, Hongbok Lee b,Ta College of Business, University of Missouri, Columbia, MO 65211-2600, United States

b College of Business and Technology, Western Illinois University, Stipes Hall 426, 1 University Circle, Macomb,

IL 61455, United States

Received 18 November 2004; received in revised form 15 March 2005; accepted 1 August 2005

Available online 12 October 2005

Abstract

We examine the long-run common stock performance of preferred stock issuers. We find that significant

abnormal underperformance is present only for 1 year after the issue. For the longer term we do not find

consistently significant abnormal performance. This result contrasts with substantial underperformance of common

equity and debt issuers during the 3 or 5 years post-issue. The better long-run performance of preferred issuers

relative to common equity and debt issuers is driven primarily by financial firms’ motivation to issue preferred

stock to satisfy regulatory requirements of capital adequacy.

D 2005 Elsevier Inc. All rights reserved.

JEL classification: G12; G 14

Keywords: Preferred stock issuers; Long-run common stock performance; Capital adequacy requirement

1. Introduction

According to the annual Compustat database as of the end of 1999, 20% of NYSE listed firms, 15%

of AMEX listed firms, and 17% of Nasdaq listed firms have preferred stock in their capital structure, and

those firms raised $325 billion through preferred stock offerings and $606 billion through seasoned

equity offerings during 1985–1999 (Bajaj, Mazumdar, & Sarin, 2002).

Despite its importance in corporate financing, relatively little research has been done on preferred

stock. That research has focused on short-term valuation effects (e.g., Mikkelson & Partch, 1986; Linn

1058-3300/$ -

doi:10.1016/j.r

T Correspond

E-mail add

see front matter D 2005 Elsevier Inc. All rights reserved.

fe.2005.08.002

ing author. Tel.: +1 309 298 1545; fax: +1 309 298 2198.

ress: [email protected] (H. Lee).

mailto:[email protected]

http://dx.doi.org/10.1016/j.rfe.2005.08.002

J.S. Howe, H. Lee / Review of Financial Economics 15 (2006) 237–250238

& Pinegar, 1988; Irvine & Rosenfeld, 2000) and the motivation and characteristics of preferred issuers

(e.g., Fooladi & Roberts, 1986; Houston & Houston, 1990; Ely, Houston, & Houston, 2002). Our

paper empirically investigates the long-run common stock performance of preferred stock issuing

firms.

To investigate the long-run performance of preferred issuers, we analyze 586 preferred stock issues

over the period 1991–2000. We collect our data from the Compact Disclosure New Issues database.

Noting the unsettled debate over the measurement of long-run abnormal stock returns, we use three

calendar-time portfolio models as our primary tools to gauge long-term common stock performance after

the issuance of preferred stock. These are the Fama and French (1993) three-factor model, the Mitchell

and Stafford (2000) adjusted intercept approach, and the Fama and French four-factor model. In addition

to the calendar-time portfolio approach, for completeness we provide the traditional buy-and-hold

abnormal returns (BHARs) method. We estimate long-run abnormal returns for 1-, 2- and 3-year post-

issue horizons.

When we use equally weighted returns in the three calendar-time portfolio models, we find that for the

1-year post-issue horizon, preferred stock issuers consistently underperform. For the longer investment

horizons (2 and 3 years after the issuance of preferred stock), the three calendar-time portfolio models do

not generate consistent abnormal performance. When we use value-weighted returns, no calendar-time

portfolio approach detects abnormal performance for any investment horizon. The lack of abnormal

performance that we find when we use value-weighted portfolios reflects small firms driving the

abnormal performance of the preferred issuers for the 1-year post-issue horizon.

Our study demonstrates that the underperformance of preferred stock issuers is transient and confined

to small firms. Relative to the long-term performance of common stock and debt issuers, our sample of

preferred issuers shows better long-run performance. Most studies on the long-run performance of

common stock and debt issuers report substantial underperformance during the 3 or 5 years post-issue.

The literature proposes that management’s attempt to take advantage of bwindows of opportunityQ isassociated with the significant long-run underperformance of common stock and debt issuers.

We attribute the disparity in the long-run performance between preferred issuers and common equity

and debt issuers to a different motivation. In our sample, financial firms are the most active issuers of

preferred stock—40% of the issues in our sample are from financial firms. Our investigation by industry

(financial firms, industrial firms, and utilities) finds that financial firms do not underperform for any

investment horizon under any model. We note that financial firms use preferred stock as a means of

satisfying capital adequacy requirements.

We find that abnormal underperformance is confined to the industrial and utility firms with

underperformance that is only temporary. These nonfinancial firms have poor profitability and high debt

ratios relative to financial firms, and seem to use preferred stock to take advantage of the distinct

characteristics of preferred stock relative to other types of securities.

2. Motives for issuing preferred stock

Preferred stock is a hybrid security, both similar and dissimilar to common equity and debt. Since

preferred stock does not affect the ownership control of existing common shareholders, it is an attractive

financing tool for companies that want to avoid dilution of current shareholder interests. Preferred stock

is also less risky than debt for the issuers. Thus, companies that cannot afford to commit to a fixed

J.S. Howe, H. Lee / Review of Financial Economics 15 (2006) 237–250 239

contractual obligation and want to avoid dilution of current shareholder interests may choose to issue

preferred stock.

The issuance of preferred stock might also be motivated by regulatory considerations in the case of

financial institutions. Callahan, Shaw, and Terando (2001) investigate why firms issue non-voting,

non-convertible preferred stock over other securities and show that the regulatory requirements of

capital adequacy influence the choice by banks to issue preferred stock. They provide evidence that

banks issue preferred stock to increase their relative core capital levels. If regulatory considerations are

the dominant motivation behind the offering of preferred stock, then no abnormal behavior of common

stock price should be detected. We investigate the common stock performance of the preferred issuers,

and try to reconcile the motives for preferred issuance and the long-run stock performance of preferred

issuers.

3. Data

We use the Compact Disclosure New Issues database to identify firms that issue preferred stock

during the period 1991–2000. Initially, we find 1376 preferred stock issues whose issue date of the final

prospectus appears in the Compact Disclosure New Issues database. For these issues we search the

Compact Disclosure SEC database using the bDisclosure company numberQ to find a Committee on

Uniform Securities Identification Procedures (CUSIP) number for each preferred issuer. There are 859

issues with CUSIP numbers in the Compact Disclosure SEC database. We use the CUSIP numbers to

screen for issuing firms that appear in the Compustat database and the Center for Research in Security

Prices (CRSP) database. We eliminate 273 issues for which data on Compustat and CRSP are not

available. The remaining 586 issues constitute our final sample.

Panel (A) of Table 1 reports the annual distribution of preferred stock issues from 1991 to 2000. In our

sample, preferred stock issuance is most active in 1993, with 123 issues. 1995 shows the lowest level of

preferred stock issuance, with only 25 issues. Calendar-time clustering in the preferred issuance activity

is evident in our sample. The segmentation of the sample by industry in panel (B), which is based on the

two-digit SIC codes of the preferred issuers, shows that financial firms are the most frequent issuers

(40% of the sample), followed by industrial firms (37%), and utilities (24%).

Table 2 reports the financial characteristics of preferred stock issuers. This table confirms the earlier

research that shows that the profitability of preferred issuers is tenuous (e.g., Lee & Figlewicz, 1999;

Pons-Sanz, Zuta, Ofer, Ravid, & Venezia, 2004). The mean return on assets (ROA) and net profit margin

of preferred issuers are negative (�0.7% and �11.7%), although the median values are positive. The

mean times-interest-earned ratio is also negative (�0.2) while the median is positive (2). The mean long-

term debt-to-assets ratio and total debt-to-assets ratio for the preferred issuers are 26.3% and 36%,

respectively.

Industry comparisons show that financial firms are the soundest financially, and industrial firms are

the least sound. All three profitability ratios measured by ROA, ROE, and net profit margin for

financial firms suggest that these firms are financially sound, but those ratios for industrial firms are

much weaker. In particular, the mean net profit margin is 9.5% for the financial firms and �47.2%for the industrial firms. Financial firms show the highest mean interest coverage ratio (3.8), and

industrial firms show the lowest value (�3.8). Financial firms also show much lower mean long-term

debt ratio (9.2%) than do industrial firms (38%) and utilities (35.4%). The nonparametric Kruskal–

Table 1

Panel A: Annual distribution of preferred stock issues over the period 1991–2000

Year Issues

1991 64

1992 107

1993 123

1994 47

1995 25

1996 42

1997 37

1998 64

1999 46

2000 31

Total 586

Panel B: Preferred stock issues by industry

Industry Number of issues

Financial firms 232 (40%)

Industrial firms 215 (37%)

Utilities 139 (24%)

Total 586 (100%)

Panel (A) reports annual preferred stock issues during the period 1991–2000. We screen the new issues of preferred stocks that

we collect from the Compact Disclosure New Issues database by the availability of company data on Compustat and CRSP.

Panel (B) shows preferred stock issues by industry. We categorize preferred issuers into three industries defined by the two-digit

SIC codes of the preferred issuers: financial firms with 60–64 and 67; utilities with 49; industrial firms with all other codes.

Table 2

Financial characteristics for preferred issuers over the period 1991–2000

Item (sample size) Full sample (586) Financial firms (232) Industrial firms (215) Utilities (139)

(1) ROA (%) Mean �0.7 1.1 �5.1 3.4

Median 1.0 0.9 �0.9 3.6

(2) ROE (%) Mean 12.9 12.9 14.1 11.2

Median 11.9 14.4 1.5 12.3

(3) Net profit margin (%) Mean �11.7 9.5 �47.2 9.4

Median 7.1 9.1 �1.6 10.4

(4) Times interest earned Mean �0.2 3.8 �3.8 2.8

Median 2.0 2.0 0.9 2.8

(5) Long-term debt to assets (%) Mean 26.3 9.2 38.0 35.4

Median 25.9 6.1 33.9 34.1

(6) Total debt to assets (%) Mean 36.0 25.5 44.1 40.2

Median 35.1 19.0 37.9 39.1

The table describes the financial characteristics of the preferred stock issuing firms prior to the offering. We provide both mean

and median values. (1) Return on assets (ROA) equals net income (Compustat annual data item 172) divided by total assets (item

6). (2) Return on equity (ROE) equals net income (Compustat annual data item 172) divided by common equity (item 60). (3) Net

profit margin equals net income (Compustat annual data item 172) divided by sales (item 12). (4) Times interest earned equals

[pretax income (Compustat annual data item 170) plus interest expense (item 15)] divided by interest expense (item 15). (5)

Long-term debt to assets equals long-term debt (Compustat annual data item 9) divided by total assets (item 6). (6) Total debt to

assets equals [long-term debt (Compustat annual data item 9) plus current debt (item 34)] divided by total assets (item 6).



Wallis H-tests of the differences in the financial characteristics of preferred issuers in different

industries confirm that financial firms, industrial firms, and utilities are significantly different in all

items at the 1% level. For all six financial characteristics, the Chi-square ranges from 89.3 to 276.2

with p-values less than 0.0001.

In measuring long-run performance, we follow the practice of earlier studies in screening our sample

(e.g., Spiess & Affleck-Graves, 1999). To reduce the effects of dependence in our statistical tests, we

choose our sample of preferred issues such that there is no overlap during the 3-year post-offering

windows for repeat issues. Therefore, once a firm offers preferred stock, that firm cannot reenter the

sample until 3 years after the issue date. We use the CRSP daily and monthly return files to compute

long-run common stock returns.

4. Research methods

We measure the long-run performance of preferred issuers for 1-, 2-, and 3-year post-issue horizons.

To mitigate the possible econometric problems arising from the use of longer horizons, we choose to use

a maximum 3-year period.

We use three calendar-time portfolio methods: the Fama and French (1993) three-factor model, the

Mitchell and Stafford (2000) adjusted intercept approach, and the Fama and French four-factor model.

Mitchell and Stafford argue that unreliable statistical inference attributable to the cross-sectional

correlations in event firm returns is the most serious problem with the BHAR approach. To avoid the

drawbacks of the traditional BHAR approach in measuring the long-run stock performance, we use the

calendar-time portfolio methods as our primary tools. Nonetheless, for completeness we also provide the

results from the BHAR approach.

4.1. Fama and French three-factor model

In Table 1, our sample shows calendar-time clustering in event firms by the number of yearly

preferred stock issues. The Fama and French (1993) calendar-time portfolio regression accounts for the

cross-sectional correlations of the individual event firm return by forming an event portfolio for each

period. Each month, we construct portfolios (both equally and value-weighted) containing all sample

firms that issued preferred shares during the [c�h, c�1] prior period, where c is the calendar month

and h is the investment horizon of interest (h=12, 24, and 36 months). We follow Mitchell and Safford

(2000) by requiring a minimum of ten firms in the event portfolio. We implement monthly rebalancing

of portfolios to add new preferred issuers and to drop preferred issuers that reach the end of the

investment horizon. We regress the portfolio excess returns on the three Fama and French factors:1

Rp;t � Rf ;t ¼ aþ b Rm;t � Rf ;t

� �þ sSMBt þ hHMLt þ et ð1Þ

where Rp,t is the month t return on the preferred stock issuing firm portfolio; Rf,t is the month t risk-free

rate (1-month Treasury bill rate); Rm,t is the month t market return; SMBt is the difference between the

average return on the small-stock portfolios and the average return on the big-stock portfolios in month t;

1Fama and French (1993) give details of the construction of these factors and Kenneth French provides these data in his Web site, http://

mba.tuck.dartmouth.edu/pages/faculty/ken.french/index.html (go to DATA LIBRARY).

http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/index.html

http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/index.html


HMLt is the difference between the average return on the high book-to-market portfolios and the average

return on the low book-to-market portfolios in month t.

We assume that the model adequately describes returns, so that the intercept, a, measures the average

monthly abnormal return on the portfolio of preferred issuers, which is zero under the null hypothesis of

no abnormal performance. A negative intercept indicates that after we control for market, size, and

book-to-market factors in returns, a sample portfolio performs worse than expected. The estimated

average monthly abnormal return (a) translates into N-year abnormal return, which we compute as

(1+a)12N�1.

In addition to an ordinary least squares (OLS) test, to account for the heteroskedastic residuals that

may be caused by the variation in the number of preferred issuers included in the different months’

portfolio (Fama, 1998, p. 299), we also implement a weighted least squares (WLS) test using the square

root of the number of preferred issuers in the monthly portfolio as weights. Table 3 presents the

regression results using Fama and French three-factor model.

4.2. Mitchell and Stafford adjusted intercept approach

Both Fama and French (1993) and Mitchell and Safford (2000) show that the three-factor model does

not perfectly describe the cross-section of expected returns, particularly for small and low book-to-

market firms. To address the pricing deficiency of the Fama and French three-factor model, Mitchell and

Stafford suggest an adjusted intercept approach. They compute the adjusted intercept as the difference

between the originally estimated intercept from the Fama and French regression of the event firms and

an expected intercept, which they estimate as the mean of intercepts from 1000 calendar-time portfolio

regressions with randomly selected non-event firms that are in the same size/book-to-market group as the

event firms. They use expected intercept as the null to calculate a new t-statistic:

t ¼ aa � E aað Þss

ð2Þ

where a is the intercept estimate from the Fama and French three-factor regression of the event firms;

E(a) is the expected intercept estimated with non-event firms; s is the intercept standard error estimates

from the Fama and French three-factor regression of the event firms. Table 4 provides the analysis of

long-run abnormal returns using the Mitchell and Stafford approach.

4.3. Fama and French four-factor model

Since the market may see the issuing of any security as exploiting pre-issue overvaluation

opportunities (Spiess & Affleck-Graves, 1999), price momentum may relate to post-issue returns.

Incorporating a momentum factor into the Fama and French three-factor model disentangles momentum

and security issuance effects.


� �þ sSMBt þ hHMLt þmUMDt þ et ð3Þ

where UMDt is a month t momentum factor computed as the average return on two high-prior-return

portfolios minus the average return on two low-prior-return portfolios (we obtain UMD from Kenneth

French’s website); everything else is the same as in the three-factor model. After we control for the

effects of the four pre-specified factors, the intercept of the four-factor model provides a measure of

abnormal returns. Table 5 presents the regression results from the four-factor model.

Table 3

Post-issue abnormal returns using Fama and French three-factor model

Portfolio

weighting

Model

estimated

Horizon=1 year Horizon=2 years Horizon=3 years

Intercept p-value Adjusted

R2


R2


R2

Panel A: Full sample

No. obs.=116 months No. obs.=116 months No. obs.=116 months

EQ OLS �0.0065 0.0013*** 0.7969 �0.0039 0.0183** 0.8447 �0.0026 0.0889* 0.8707

WLS �0.0062 0.0022*** 0.8006 �0.0041 0.0112** 0.8444 �0.0029 0.0458** 0.8679

VW OLS �0.0029 0.4372 0.6840 �0.0004 0.8833 0.7437 0.0028 0.2867 0.7312

WLS �0.0036 0.3484 0.6918 �0.0008 0.7207 0.7489 0.0025 0.2927 0.7344

Panel B: Subsamples by industry

Financial firms No. obs.=75 months No. obs.=112 months No. obs.=115 months

EQ OLS �0.0036 0.3736 0.6552 �0.0001 0.9698 0.7109 �0.0004 0.8832 0.7405

WLS �0.0028 0.4834 0.6631 �0.0001 0.9667 0.7068 �0.0001 0.9794 0.7319

VW OLS �0.0043 0.5769 0.6903 �0.0027 0.5583 0.7226 �0.0011 0.7792 0.7601

WLS �0.0056 0.4669 0.6962 �0.0027 0.5682 0.7218 �0.0008 0.8359 0.7528

Industrial firms No. obs.=92 months No. obs.=109 months No. obs.=109 months

EQ OLS �0.0138 0.0074*** 0.6593 �0.0095 0.0101** 0.6966 �0.0056 0.0598* 0.7612

WLS �0.0122 0.0110** 0.6418 �0.0089 0.0107** 0.6929 �0.0059 0.0415** 0.7592

VW OLS �0.0038 0.5543 0.5139 0.0034 0.5112 0.5231 0.0066 0.2102 0.4953

WLS �0.0027 0.6624 0.4862 0.0035 0.4693 0.5341 0.0059 0.2196 0.5175

Utilities No. obs.=38 months No. obs.=73 months No. obs.=93 months

EQ OLS �0.0098 0.0831* 0.3096 0.0003 0.9494 0.2937 0.0011 0.7521 0.3162

WLS �0.0096 0.0714* 0.3214 �0.0012 0.7599 0.3081 �0.0003 0.9389 0.3373

VW OLS �0.0120 0.0297** 0.3865 �0.0002 0.9639 0.2124 0.0014 0.7218 0.2230

WLS �0.0116 0.0255** 0.3981 �0.0018 0.6662 0.2271 �0.0001 0.9701 0.2450

We estimate abnormal returns for 1-, 2-, and 3-year horizons after preferred stock issuance. Each month, we compute equal- and

value-weighted (monthly rebalanced) calendar-time portfolio returns for all firms that issued preferred stock in the previous 12,

24, or 36 calendar months. We implement the following time-series regression based on the Fama and French (1993) three-

factor model:


� �þ sSMBt þ hHMLt þ et ðT:3Þ

where Rp,t is the month t return on the preferred stock issuing firm portfolio; Rf ,t is the month t risk free rate (1-month Treasury

bill rate); Rm ,t is the month t market return; SMBt is the month t return difference between a small- and large-stock portfolio;

HMLt is the month t return difference between a high book-to-market portfolio and a low book-to-market portfolio. In this

framework, the intercept, a, measures the average monthly abnormal return on the portfolio of preferred issuers, which is zero

under the null hypothesis of no abnormal performance. We exclude calendar months with less than ten observations in the event

portfolio. EQ denotes an equally weighted portfolio and VW represents a value-weighted portfolio. In addition to the ordinary

least squares (OLS) test, to account for the heteroskedastic residuals that may be caused by the variation in the number of

preferred issuers in the different months’ portfolios, we also execute the weighted least squares (WLS) test, using the square

root of the number of preferred issuers in the portfolio for each month as weights. We compute p-values using White’s (1980)

heteroskedasticity-robust standard errors. The asterisks *, **, and *** indicate significance at the 10%, 5%, and 1% levels,

respectively.


Table 4

Post-issue abnormal returns using Mitchell and Stafford approach

Portfolio

weighting


Adjusted

intercept

p-value Adjusted

intercept

p-value Adjusted

intercept

p-value


EQ �0.0052 0.0105** �0.0030 0.0669* �0.0018 0.2306

VW �0.0033 0.3797 �0.0009 0.7101 0.0024 0.3673


Financial firms EQ �0.0030 0.4570 0.0010 0.7300 0.0009 0.7413

VW �0.0044 0.5643 �0.0016 0.7293 �0.0001 0.9857

Industrials firms EQ �0.0119 0.0201** �0.0087 0.0182** �0.0053 0.0731*

VW �0.0045 0.4765 0.0034 0.5209 0.0060 0.2532

Utilities EQ �0.0112 0.0491** �0.0001 0.9771 0.0010 0.7889

VW �0.0135 0.0157** �0.0006 0.8894 0.0008 0.8531

The table shows the adjusted intercept estimates and p-values using the Mitchell and Stafford (2000) method. We compute the

adjusted intercept as the difference between the originally estimated intercept from the Fama and French regression of the

sample firms and an expected intercept, which we estimate as the mean of intercepts from 1000 calendar-time portfolio

regressions with randomly selected non-issuing firms that are in the same size/book-to-market group as the sample firms. We

exclude calendar months with less than ten observations in the event portfolio. EQ denotes an equally weighted portfolio and

VW represents a value-weighted portfolio. The asterisks *, **, and *** indicate significance at the 10%, 5%, and 1% levels,

respectively.


4.4. Long-term buy-and-hold abnormal returns

For completeness, we also examine post-issue BHARs following the method outlined in Barber and

Lyon (1997), Loughran and Ritter (1995), and Spiess and Affleck-Graves (1999). We estimate BHARs

as follows:

BHARi ¼YTi

t¼start1þ Ritð Þ �

YTit¼start

1þ Rctð Þ ð4Þ

where Rit (Rct) is the return on the common stock of the preferred issuer (control firm) on the tth day

after the issue; start is the date of the preferred stock’s issue; Ti is the number of days from the offering

date to the end of holding period (1, 2, and 3 years). The average buy-and-hold abnormal return is:

Average BHAR ¼ 1

N

� � XNi¼1

BHARi ð5Þ

where N is the number of firms in the sample.

In calculating the buy-and-hold abnormal returns, we consider two benchmarks of post-issue

performance: an industry/size matched benchmark and an industry/size/book-to-market matched

benchmark. For the industry/size matching scheme, we first segment firms into three industry categories

based on SIC codes. Then, from the group of firms that have not publicly sold common stock, preferred

stock, and debt during the 5 years prior to the issue date of preferred issuers, we select the firm with the

market capitalization closest to that of the preferred issuer as the matching firm. For the industry/size/

Table 5

Post-issue abnormal returns using a four-factor model

Portfolio

weighting

Model

estimated



R2


R2


R2


No. obs.=116 months No. obs.=116 months No. obs.=116 months

EQ OLS �0.0055 0.0086*** 0.7982 �0.0020 0.2448 0.8550 �0.0019 0.2477 0.8710

WLS �0.0053 0.0123** 0.8015 �0.0023 0.1592 0.8538 �0.0023 0.1336 0.8680

VW OLS �0.0025 0.4796 0.6815 �0.0009 0.7119 0.7420 0.0008 0.7502 0.7366

WLS �0.0029 0.4120 0.6899 �0.0014 0.5306 0.7474 0.0005 0.8320 0.7422


Financial Firms No. obs.=75 months No. obs.=112 months No. obs.=115 months

EQ OLS �0.0043 0.3219 0.6511 �0.0009 0.7446 0.7096 �0.0005 0.8428 0.7381

WLS �0.0035 0.4166 0.6591 �0.0009 0.7488 0.7054 �0.0003 0.9036 0.7296

VW OLS �0.0023 0.7381 0.6888 �0.0005 0.9026 0.7254 0.0007 0.8665 0.7621

WLS �0.0033 0.6324 0.6958 �0.0006 0.8910 0.7242 0.0008 0.8487 0.7541

Industrial firms No. obs.=92 months No. obs.=109 months No. obs.=109 months

EQ OLS �0.0124 0.0324** 0.6574 �0.0048 0.2077 0.7241 �0.0036 0.2700 0.7651

WLS �0.0107 0.0413** 0.6408 �0.0046 0.1895 0.7200 �0.0040 0.1921 0.7635

VW OLS �0.0076 0.2521 0.5205 �0.0004 0.9289 0.5352 0.0006 0.9097 0.5296

WLS �0.0050 0.4454 0.4870 0.0002 0.9671 0.5445 0.0004 0.9416 0.5522

Utilities No. obs.=38 months No. obs.=73 months No. obs.=93 months

EQ OLS �0.0113 0.0575* 0.3096 0.0011 0.8255 0.2862 0.0008 0.8402 0.3087

WLS �0.0115 0.0376** 0.3346 �0.0010 0.8196 0.2981 �0.0011 0.7844 0.3330

VW OLS �0.0125 0.0410** 0.3697 0.0003 0.9492 0.2019 �0.0003 0.9499 0.2240

WLS �0.0125 0.0278** 0.3868 �0.0019 0.6992 0.2158 �0.0022 0.6235 0.2530

We estimate abnormal returns for 1-, 2-, and 3-year horizons after preferred stock issuance. Each month, we compute equal- and

value-weighted (monthly rebalanced) calendar-time portfolio returns for all firms that issued preferred stock in the previous 12,

24, or 36 calendar months. We estimate the following four-factor time-series regression:


� �þ sSMBt þ hHMLt þmUMDt þ et ðT:5Þ

where Rp,t is the month t return on the preferred stock issuing-firm portfolio; Rf ,t is the month t risk free rate (1-month Treasury

bill rate); Rm,t is the month t market return; SMBt is the month t return difference between a small- and large-stock portfolios;

HMLt is the month t return difference between a high book-to-market portfolio and a low book to-market portfolio; UMDt is

the month t momentum factor, which we compute as the average return on two high-prior-return portfolios minus the average

return on two low-prior-return portfolios. In this framework, the intercept, a, measures the average monthly abnormal return on

the portfolio of preferred issuers, which is zero under the null hypothesis of no abnormal performance. We exclude calendar

months with less than ten observations in the event portfolio. EQ denotes an equally weighted portfolio and VW represents a

value-weighted portfolio. In addition to the ordinary least squares (OLS) test, to account for the heteroskedastic residuals that

may be caused by the variation in the number of preferred issuers included in the different months’ portfolios, we also execute

the weighted least squares (WLS) test, using the square root of the number of preferred issuers in the portfolio for each month as

weights. We compute p-values using White’s (1980) heteroskedasticity-robust standard errors. The asterisks *, **, and ***

indicate significance at the 10%, 5%, and 1% levels, respectively.


Table 6

Post-issue buy-and-hold abnormal returns

Matching scheme Horizon=1 year Horizon=2 years Horizon=3 years

Mean Median Mean Median Mean Median


Ind/Size �0.0473[0.1100]

�0.0332[0.0726]*

�0.0111[0.8327]

0.0191

[0.8733]

0.0166

[0.8208]

0.0589

[0.8191]

Ind/Size/BM �0.0428[0.1487]

�0.0557[0.0443]**

�0.0166[0.7716]

0.0288

[0.4786]

0.0019

[0.9816]

0.0191

[0.9916]


Financial firms Ind/Size 0.0285

[0.4443]

�0.0056[0.7239]

0.0697

[0.1581]

0.0439

[0.1141]

0.1198

[0.0530]*

0.1424

[0.0358]**

Ind/Size/BM �0.0426[0.2637]

�0.0654[0.1474]

�0.0033[0.9482]

0.0372

[0.9370]

�0.0005[0.9941]

0.0010

[0.7690]

Industrial firms Ind/Size �0.1329[0.0214]**

�0.1649[0.0169]**

�0.1079[0.3272]

�0.1559[0.0620]*

�0.1291[0.4065]

�0.2647[0.0260]**

Ind/Size/BM �0.0550[0.3519]

�0.0646[0.3097]

�0.0370[0.7635]

�0.0914[0.2363]

�0.0714[0.6994]

�0.0763[0.2294]

Utilities Ind/Size 0.0043

[0.8959]

�0.0205[0.9043]

0.0565

[0.2301]

0.0940

[0.0596]*

0.1531

[0.0320]**

0.2401

[0.0110]**

Ind/Size/BM �0.0177[0.5922]

�0.0477[0.1113]

0.0027

[0.9607]

0.1044

[0.3190]

0.1587

[0.0310]**

0.2361

[0.0050]***

The table shows mean and median buy-and-hold abnormal returns (BHARs) for 1, 2, and 3 year(s) after the issuance of

preferred stock. We calculate BHARs by subtracting the holding-period return of the control benchmark from the holding-

period return of the corresponding preferred stock issuing firm. In our matching scheme of Ind/Size we use the criteria of

industry and size. In our matching scheme of Ind/Size/BM our matching design is by industry, size and book-to-market ratio.

The asterisks *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively, using two-tailed paired t-tests for

the differences in means and two-tailed Wilcoxon signed-rank tests for the differences in the probability distributions between

preferred issuers and matching firms. P-values are shown in brackets under each parameter.


book-to-market matching design, we use the same set of non-issuers as the first matching scheme, and

follow the method suggested in Spiess and Affleck-Graves (1995, 1999). We choose a control firm for

each preferred issuer such that we minimize the sum of the absolute percentage difference in the sizes

and the book-to-market ratios between the preferred issuer and the non-issuers from the same industry.

Table 6 provides mean and median BHARs for our sample of preferred issuers.

5. Findings and interpretation

5.1. Analysis of the full sample

Panels (A) in Tables 3, 4, and 5 summarize the results for the full sample from the calendar-time

portfolio models. The three calendar-time portfolio methods are consistent in showing a significant

abnormal underperformance at the 5% level or better for the 1-year investment horizon when we use

equally weighted returns. For longer post-issue horizons, the three methods conflict in detecting

abnormal performance. We find a consistent abnormal performance using the Fama and French (1993)


three-factor model (panel (A), Table 3) for all investment horizons, 1, 2, and 3 year(s) after the issuance

of preferred stock. The Mitchell and Stafford (2000) approach (panel (A), Table 4) does not detect

abnormal performance for the 3-year post-issue horizon, and the four-factor model (panel (A), Table 5)

also suggests that the issuers’ abnormal performance for the 2- and 3-year horizons is insignificant.

In all three calendar-time portfolio models with equally weighted returns, the statistical significance of

preferred issuers’ abnormal performance declines as the investment horizon gets longer. The abnormal

returns from the Fama and French (1993) three-factor model are significant at the 1%, 5%, and 10%

levels for 1-, 2-, and 3-year post-issue horizons. The Mitchell and Stafford (2000) approach identifies

abnormal performance for 1 and 2 years after preferred stock issuance at the 5% and 10% levels. The

abnormal returns disappear 3 years after the issue. The four-factor model finds a significant abnormal

performance for the 1-year post-issue horizon at the 5% level, but fails to identify significant abnormal

returns at conventional levels for the 2- and 3-year horizons.

When we use value-weighted returns, no model shows abnormal performance for any investment

horizon, from which we infer that small firms are driving the underperformance during the first year

after preferred issuance. Fama (1998, p. 296), Loughran and Ritter (2000, p. 377), and Spiess and

Affleck-Graves (1999, p. 58) have special comments on the issue of portfolio weighting schemes for

asset pricing models. Fama argues that the bad-model problem that plagues all the common asset-

pricing models can explain why reliably negative intercepts with equally weighted portfolios turn out to

be indistinguishable from zero when value-weighted portfolios are used. Loughran and Ritter argue that

the Fama and French three-factor model using value-weighted returns tends to underestimate abnormal

performance when managerial actions involving cash flows, such as equity issues and share

repurchases, are being studied. In their simulations they find that value-weighted three-factor

regressions pick up only about half of the abnormal returns that are present when each firm is equally

weighted.

In Table 6, panel (A) provides post-issue buy-and-hold abnormal returns (BHARs) for the 1-, 2-, and

3-year post-issue horizons. Consistent with the results from the calendar-time portfolio models, we find

that for the 1-year post-issue horizon, preferred issuers significantly underperform their peers matched

by industry/size and by industry/size/book-to-market. The 1-year median BHAR of �5.57% from

industry/size/book-to-market matching is comparable to the abnormal return of �53 basis points per

month from the four-factor model (panel (A) of Table 5, WLS equally weighted portfolios), which

translates into a 12-month abnormal return of �6.18% (= (1�0.0053)12�1). For the 2-, and 3-year

post-issue horizons, we do not find abnormal returns for the preferred issuers under the BHAR approach.

This result is consistent with the results from the four-factor model.

5.2. Analysis of the subsamples by industry

We present the results for the industry-segmented samples under the calendar-time portfolio approach

in panels (B) of Tables 3, 4, and 5. We see that abnormal performance is confined to the industrial and

utility firms. Financial firms do not underperform for any investment horizon under any model. Similar

to the case of the full sample, only for the 1-year post-issue horizon do industrial firms and utilities

consistently show significant abnormal returns for all three calendar-time portfolio approaches. As with

the full sample in which only the equally weighted return metric detects abnormal performance,

industrial firms show abnormal performance only for the equally weighted portfolios. In contrast to the

total sample, utility firms’ abnormal performance is robust to the portfolio weighting schemes.


In Table 6, panel (B), the results from the BHAR approach are partially consistent with the results

from the calendar-time portfolio models. For the 1-year post-issue horizon, industrial issuers

significantly underperform their peers matched by industry/size. The 1-year mean BHAR of

�13.29% is comparable to the abnormal return of �124 basis points per month from the four-factor

model (panel (B) of Table 5, OLS equally weighted portfolios), which translates into 12-month abnormal

return of �13.91% (=(1�0.0124)12�1). The BHAR approach fails to find abnormal performance for

financial firms and utilities for the 1-year post-issue horizon.

5.3. Interpretation

Our analysis uncovers weak evidence of underperformance of preferred stock issuers. The

underperformance is transient and confined to nonfinancial firms. Relative to the long-run performance

of common stock and debt issuers, our sample of preferred stock issuers show better long-run

performance. Most studies of the long-run performance of common stock and debt issuers report

substantial underperformance during the 3 and 5 years post-issue.

The literature on the long-run performance of common stock and debt issuers associates substantial

underperformance of the issuers with management’s attempt to take advantage of bwindows of

opportunity.Q Ritter (1991) and Loughran and Ritter (1995) argue that firms take advantage of the

transitory windows of opportunity by conducting IPOs or SEOs when, on average, their firms’ stock is

substantially overvalued. Spiess and Affleck-Graves (1999) argue that overvalued firms are likely to

issue securities of any type, and that debt offerings, like equity offerings, signal overvaluation of the

issuer.

We attribute the disparity in the long-run performance between preferred issuers and common equity

and debt issuers to a different motivation behind these firms’ security issuance. In our sample, the most

active issuers of preferred stock are financial firms (40% of the issues) for which we find no abnormal

underperformance. Financial firms use preferred stock as means of satisfying capital adequacy

requirements (Callahan et al., 2001).

We see that abnormal underperformance is confined to industrial and utility firms and that their

underperformance is short-lived. These nonfinancial firms have poor profitability and high debt ratios

relative to financial firms, and seem to use preferred stock to take advantage of the distinct characteristics

of preferred stock relative to other types of securities. Underreaction to the news contained in the

announcement of preferred issuance could contribute to the transient underperformance of nonfinancial

preferred issuers.

According to the capital adequacy requirements for depository institutions in the United States based on

the Basel Accord of 1988, noncumulative perpetual preferred stock is considered as Tier 1 (core) capital,

and cumulative perpetual preferred stock and preferred stock with limited life are counted as Tier 2

(supplementary) capital.2 Callahan et al. (2001) show that the regulatory requirements of capital adequacy

influence the choice by banks to issue preferred stock and provide evidence that banks issue preferred

stock to increase their relative core capital levels. We believe that this distinct motive of financial firms, the

most active issuers of preferred stock in our sample, is the primary driver behind the relatively better long-

run performance of preferred stock issuers compared with the common stock and debt issuers.

2For the details of capital adequacy regulation, see Gardner, Mills, and Cooperman (2005) and Kidwell, Blackwell, Whidbee, and Peterson

(2006).


6. Conclusion

We examine the long-run common stock performance of preferred stock issuers and link the

motivation for preferred stock issuance and the long-run performance of preferred stock issuers. We use

three calendar-time portfolio models and the traditional buy-and-hold abnormal returns approach to

analyze the common stock price behavior for a sample of 586 preferred stock issues over the period 1991

to 2000.

We find that when we use equally weighted portfolios, preferred stock issuers show a significant

abnormal underperformance only for the 1-year post-issue horizon. For the longer investment

horizons (2 and 3 years after the issuance of preferred stock) we do not find consistently significant

abnormal performance under the three calendar-time portfolio models. Even the 1-year post-issue

underperformance disappears when we use value-weighted portfolios, from which we infer that small

firms are driving the underperformance. Industrial segmentation of the sample detects short-lived

abnormal underperformance for industrial firms and utilities, but no abnormal performance for

financial firms.

Most studies on the long-run performance of common stock and debt issuers report substantial

underperformance during the 3 to 5 years post-issue. The literature proposes that management’s attempt

to take advantage of temporary overvaluation is associated with the long-run underperformance of

common stock and debt issuers. We believe that the long-run performance difference between preferred

issuers and common equity and debt issuers is attributable to the different motivation behind the security

issuance. Financial firms, which are the most active issuers of preferred stock in our sample, use

preferred stock as a way to satisfy the regulatory requirements for capital adequacy. We believe that this

distinct motive of financial firms is the primary driver behind the relatively better long-run performance

of preferred stock issuers compared with the common stock and debt issuers.

References

Bajaj, M., Mazumdar, S. C., & Sarin, A. (2002). The costs of issuing preferred stock. Journal of Financial Research, 25(4),

577–592.

Barber, B. M., & Lyon, J. D. (1997). Detecting long-run abnormal stock returns: The empirical power and specification of test

statistics. Journal of Financial Economics, 43, 341–372.

Callahan, C. M., Shaw, W. H., & Terando, W. D. (2001). Tax and regulatory motivations for issuing non-voting, non-

convertible preferred stock. Journal of Accounting Research, 39(3), 463–480.

Ely, D. P., Houston, A. L., & Houston, C. O. (2002). Taxes and the choice of issuing preferred stock vs. debt. Journal of the

American Taxation Association, 24(1), 29–45.

Fama, E. F. (1998). Market efficiency, long-term returns, and behavioral finance. Journal of Financial Economics, 49,

283–306.

Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics,

33, 3–56.

Fooladi, I. J., & Roberts, G. S. (1986). On preferred stock. Journal of Financial Research, 9(4), 319–324.

Gardner, M. J., Mills, D. L., & Cooperman, E. S. (2005).Managing financial institutions (9th edition). Thomson/South-Western.

Houston, A. L., & Houston, C. O. (1990, Autumn). Financing with preferred stock. Financial Management, 42–54.

Irvine, P., & Rosenfeld, J. (2000, Summer). Raising capital using monthly income preferred stock: Market reaction and

implications for capital structure theory. Financial Management, 5–20.

Kidwell, D. S., Blackwell, D. W., Whidbee, D. A., & Peterson, R. L. (2006). Financial institutions, markets, and money

(9th edition). John Wiley & Sons, Inc.


Lee, H. W., & Figlewicz, R. E. (1999). Characteristics of firms that issue convertible debt versus convertible preferred stock.

Quarterly Review of Economics and Finance, 39, 547–563.

Linn, S. C., & Pinegar, J. M. (1988). The effect of issuing preferred stock on common and preferred stockholder wealth. Journal

of Financial Economics, 22, 155–184.

Loughran, T., & Ritter, J. R. (1995). The new issues puzzle. Journal of Finance, 50(1), 23–51.

Loughran, T., & Ritter, J. R. (2000). Uniformly least powerful tests of market efficiency. Journal of Financial Economics, 55,

361–389.

Mikkelson, W. H., & Partch, M. M. (1986). Valuation effects of security offerings and the issuance process. Journal of

Financial Economics, 15, 31–60.

Mitchell, M. L., & Stafford, E. (2000). Managerial decisions and long-term stock price performance. Journal of Business, 73(3),

287–329.

Pons-Sanz, V., Zuta, S., Ofer, A. R., Ravid, S. A., & Venezia, I. (2004). When are preferred shares preferred? Theory and

empirical evidence (Working paper).

Ritter, J. R. (1991). The long-run performance of initial public offering. Journal of Finance, 44(1), 4–27.

Spiess, D. K., & Affleck-Graves, J. (1995). Underperformance in long-run stock returns following seasoned equity offerings.

Journal of Financial Economics, 38, 243–267.

Spiess, D. K., & Affleck-Graves, J. (1999). The long-run performance of stock returns following debt offerings. Journal of

Financial Economics, 54, 45–73.

White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity.

Econometrica, 48, 817–838.

Documents

The long-run stock performance of preferred stock issuers