http://www.altmanzscoreplus.com/sites/default/files/papers/equity.pdf
The Equity Performance of Firms Emerging from Bankruptcy
by
Allan C. Eberhart*
The McDonough School of Business
Georgetown University
Washington, D.C. 20057
(202) 687-3784
eberhara@gunet.georgetown.edu
Edward I. Altman
Stern School of Business
New York University
New York, NY 10012
(212) 998-0709
ealtman@stern.nyu.edu
Reena Aggarwal
The McDonough School of Business
Georgetown University
Washington, D.C. 20057
(202) 687-3784
November 1998
Forthcoming in Journal of Finance
________
*We received helpful comments from Edie Hotchkiss, Lisa Fairchild, René Stulz, an anonymous referee and
seminar participants at the Hong Kong University of Science and Technology, IBC Conference, University of
North Carolina at Chapel Hill and the University of British Columbia. We would like to thank the Georgetown
University Capital Markets Research Center for providing support. Aggarwal and Eberhart received support
from a Georgetown University Summer Research Grant. Eberhart also received support from a Goldman,
Sachs Fellowship and worked on parts of this paper as a Visiting Assistant Professor at the New York
University Stern School of Business. Aggarwal worked on parts of this paper as an Academic Scholar at the
Securities and Exchange Commission. We thank Christopher McHugh of New Generation Research (Boston,
MA) for generously supplying part of the data for this study and our research assistants for excellent research
assistance.
The Equity Performance of Firms Emerging from Bankruptcy
Abstract
This study assesses the stock return performance of 131 firms emerging from Chapter 11. Using differing
estimates of expected returns, we consistently find evidence of large, positive excess returns in 200 days of
returns following emergence. We also examine the reaction of our sample firms’ equity returns to their earnings
announcements after emergence from Chapter 11. The positive and significant reactions suggest that our results
are driven by the market’s expectational errors, not mismeasurement of risk. The results provide an interesting
contrast, but not a contradiction, to previous work that has documented poor operating performance for firms
emerging from Chapter 11.
1
The Equity Performance of Firms Emerging from Bankruptcy
With large corporate bankruptcies being commonplace during the late 1980s and early 1990s, there
has been a notable increase in the number of firms emerging from bankruptcy (Altman (1993)). When firms
emerge from bankruptcy, they often cancel the old stock and distribute an entirely new issue of common stock.
The stocks of firms emerging from a Chapter 11 bankruptcy are often called “orphan” equities among
practitioners and there have been reports in the popular press about spectacular returns in this market. For
example, as Sandler (1991, p. C1) states:
While initial public offerings have been grabbing all the glory, there’s a shadow
market for new stocks that is doing nicely too. It’s where people trade shares of
companies coming out of bankruptcy or reorganization.
In recent months, some investors have made 50% to 100% on their money by
trading the new shares of Republic Health, Southland Corp. and Maxicare Health Plans
after those companies finished reorganizing their business.
The primary purpose of this paper is to test the efficiency of the market for stocks of firms emerging
from Chapter 11. Our sample includes 131 firms emerging from Chapter 11 between 1980 and 1993 and we
test whether the long-term–i.e., first 200 days of returns after emergence–average cumulative abnormal returns
(ACARs) are significantly different from zero. We find significant ACARs that–depending on how the
expected returns are estimated–have a lower bound of 24.6 percent (the median CARs, though lower, are also
positive and significant).1
We investigate several explanations for these findings. Since our tests are joint tests of efficiency and
the model we use to estimate expected returns, our results may reflect a mismeasurement of the stocks’
riskiness rather than an inefficient market. The results’ robustness with respect to different ways of estimating
expected returns casts doubt on this explanation, however.
We also examine the reaction of our sample firms to their earnings announcements after emergence.
La Porta, Lakonishok, Shleifer and Vishny (1995) argue that the positive excess returns on “value” stocks are
due to expectational errors made by the market. Consistent with this assertion, they find that value stocks have
2
unexpectedly good earnings as shown by the positive abnormal returns around their earnings announcements.
For our sample, the average and median excess returns are positive and significant around the sample firms’
earnings announcements, providing more evidence that our results are driven by expectational errors made by
the market, not a mismeasurement of risk.
We also analyze cross-sectional differences in the returns. Specifically, we examine the firms’ stock
prices upon emergence, changes in their primary line of business, whether the firm had a pre-packaged
bankruptcy and the willingness of institutional investors to accept only equity in the reorganized firm (in
exchange for their old claims).
Low price stocks often have higher transaction costs and may have higher estimation risks than
captured by our estimates of expected returns.2 We find no evidence, however, that our positive excess returns
are concentrated in small price stocks.
Firms that change their primary line of business in bankruptcy may also have higher estimation risks
because the historical information on the firm is less helpful in predicting the firm’s future performance. Our
results, though, show no consistent difference in returns between firms that change their primary line of
business and those that do not.
Because of their shorter duration, prepackaged bankruptcies may have risk characteristics that differ
from the non-prepackaged bankruptcies. However, we find no consistent evidence of a significant relation
between returns and a dummy variable equal to one if the firm had a prepackaged bankruptcy and zero
otherwise.
Finally, Brown, James and Mooradian (1993) argue that the acceptance of equity in a reorganized firm
by informed investors, such as banks, conveys favorable private information. We find some evidence that when
institutional investors accept only equity (including warrants) in exchange for their claims, the long-term
returns are higher.3
Our results are of broad interest for two main reasons. First, they cast doubt on the informational
3
efficiency of this market and are consistent with recent studies documenting long-term abnormal returns (e.g.,
Loughran and Ritter (1995), Spiess and Affleck-Graves (1995)). Second, the results provide an interesting
contrast, but not a contradiction, to prior work that suggests the Chapter 11 process does not efficiently screen
out economically inefficient firms (e.g., Hotchkiss (1995)). Our results suggest that, although these firms may
not achieve strong operating performance, their performance is better than the market expected at the time they
emerged from Chapter 11. Most firms emerging from bankruptcy, however, do not emerge with stock trading
on the NYSE/AMEX or Nasdaq and the sample in Hotchkiss includes some of these firms. Therefore, direct
comparisons with the sample in Hotchkiss must be tempered by this caveat.
A brief review of the bankruptcy process and related literature is presented in the next section. The data
and methods are discussed in Section II. The empirical results are presented in Section III and the summary
in Section IV.
I. The Bankruptcy Process and Related Work
Often, as noted earlier, when the formerly bankrupt firm emerges as a public company the old stock
is canceled and new stock is issued. If the value of the debt claims exceeds the value of the firm and the
absolute priority rule (APR) is followed, then the old shareholders’ claim is worthless. In approximately 75
percent of corporate bankruptcy cases, however, the APR is violated (e.g., Eberhart, Moore and Roenfeldt
(1990), Weiss (1990)). Nevertheless, Altman and Eberhart (1994) show that, on average, higher seniority still
implies higher payoffs upon emergence from bankruptcy. Creditors usually receive part of their payoff as new
stock in the firm, frequently giving them majority ownership.
During the bankruptcy process, the estimate of the firm’s going concern value that will be used to set
the payoffs to each class of claimants is debated. Depending on its priority, each class of claimants has an
incentive to present a biased estimate of the firm value. It is in the interest of junior claimants to argue for
upwardly biased estimates of firm value because this increases the proportion of the firm value they receive.
Conversely, senior claimants–who are often the institutional investors–usually push for a lower estimate of
4
firm value so that they can retain a greater portion of the firm and reap the rewards if the firm’s subsequent
equity value is higher than would be expected given the riskiness of the stock. Perhaps most important is the
bias of management; they have an incentive to value the firm above its liquidation value (to maintain their jobs)
but below its true value, assuming its true value is above the estimate of its liquidation value. Therefore, if the
market is persuaded by the manager’s forecast, the post-emergence stock performance of the firm will seem
superior relative to the equilibrium expected returns and the manager’s performance will look abnormally good.
Hotchkiss (1995) documents the operating performance of firms emerging from bankruptcy that filed
for Chapter 11 between October 1979 and September 1988. Overall, she finds the median operating
performance to be positive. More than 40 percent of the firms, however, continue to experience operating losses
in the three years after emergence and 32 percent subsequently file for bankruptcy again or restructure their
debt. Moreover, the median industry-adjusted operating performance is negative.
More recent evidence by Alderson and Betker (1996) suggests that the operating performance of firms
is abnormally positive following emergence from Chapter 11. They examine 89 firms emerging between 1983
and 1993. In contrast to the focus by Hotchkiss (1995) on accounting measures of performance, they focus on
the total cash flows provided by the firm. They report that the total cash flow returns for their sample are
significantly higher than the returns on the S&P 500 index.
In summary, the results in Hotchkiss (1995) suggest that the bankruptcy code is biased toward letting
economically inefficient, or poorly restructured, firms reorganize instead of liquidating. Alderson and Betker
argue that total cash flow measures and comparisons to the alternative of liquidation are better means of
assessing the success of firms emerging from Chapter 11. By their metrics, the Chapter 11 process looks more
efficient.4 Though the focus of this paper is on the efficiency of the stock market, our results are indirectly
supportive of Alderson and Betker (1996).
5
II. Data and Methods
Our primary source of information on firms emerging from bankruptcy is New Generation Research
(Boston, MA). New Generation is a firm that specializes in collecting bankruptcy data. Because New
Generation’s list of firms emerging from bankruptcy becomes more thorough in the 1990s, we construct our
sample in two phases.
The first phase is for a list of firms, provided by New Generation, that file and complete a Chapter 11
bankruptcy between January 1980 and December 1989. We supplement this list with a search on the Dow
Jones News Retrieval using the key words “bankruptcy” and “emerge.” There are 350 firms in this sample.
For the second phase, we use a more comprehensive list provided by New Generation. This list contains 196
firms that emerge from Chapter 11 between January 1990 and December 1993, bringing the total sample to
546 firms.
Among the 546 firms, 131 emerge with equity trading on the NYSE, AMEX or Nasdaq.5 When the
firms emerge from bankruptcy, 71 begin trading on the Nasdaq, 37 on the NYSE and 23 on the AMEX; 76
of the stocks trade throughout the bankruptcy process. Though we cannot rule out the possibility that our
sample is less than the population, we are confident that we have assembled the vast majority of firms.6
The average closing price on the first day of trading (post-emergence day 0) following emergence is
$6.32 and the median is $3.75. Similar to other studies (e.g., Altman (1993)), we find that the average time
spent in bankruptcy (measured, in our case, from the bankruptcy announcement date through the first trading
date after emergence) is close to two years with an average of 22.39 months and a median of 20.17 months.
There are 78 firms for which we have some information provided by New Generation on the payoffs
to each claimant in the formerly bankrupt firm. Over the past several years, New Generation has gathered
information on the payoffs from disclosure statements, discussions with attorneys, and other sources. With this
information, we can distinguish between cases where institutional investors accept only equity (including
warrants) in the newly emerged firm and cases where they demand another form of payment; 10 firms had their
6
institutional investors accept only equity.
A. Definition of the First Trading Date
Because the emergence procedure varies across firms, so does the appropriate starting point for our
efficiency tests. For example, as mentioned earlier, 76 of the sample firms’ stocks trade throughout the Chapter
11 period. The stock may trade up to the day the new stock is issued and the old stock is then canceled.
Alternatively, additional shares may or may not be issued and the “new” stock often trades under the old name.
If the old stock is canceled and new stock is issued, then the first trading date is simply the first day the new
stock trades following emergence. If additional stock is issued, then the first trading day is the first day the
“new” stock (i.e., with the additional shares) trades following emergence. If no new stock is issued, then the
first trading date is defined as the emergence date for the firm (recall that the first return day is for the second
day of trading). Our sources for the emergence dates include New Generation, Capital Changes Reporter, Wall
Street Journal Index (if we do not have information from the Dow Jones News Retrieval), and Bloomberg.
There are only two firms where we know the shareholders retain their shares in the old firm and no
additional stock is issued. As noted above, the other two categories are where the shareholders retain their
shares and additional stock is issued to pay the debtholders or the old stock is canceled and new stock is issued.
The difference between these two categories is not substantive; the old shareholders can have their ownership
diluted equally by retaining their shares and having the firm issue additional stock to the old debtholders or by
having the firm cancel the old stock and giving the old shareholders a fraction of the new stock.
The Center for Research in Security Prices (CRSP) does not always pick up the stock when it first
begins trading. So, we hand-collect data from the Standard and Poor’s Daily Stock Price Record (SPDSPR)
for the 28 firms where the first trading date in the SPDSPR precedes the first trading date on CRSP. The
reason for this gap is that all these firms begin trading on a “when-issued” basis (i.e., trading of stock before
it is issued). When-issued trading begins after the reorganization plan is confirmed. The exchanges and Nasdaq
allow when-issued trading when they are certain the shares will be mailed out by the firm and it will be possible
7
to do settlement shortly afterwards.7 Therefore, though there can be some liquidity and settlement day
differences between when-issued and “regular” stock trading (e.g., Lamoureux and Wansley (1989)), the first
trading date can be for when-issued or regular trading, whichever comes first.8 To check if the 28 firms with
SPDSPR prices (preceding the CRSP prices) perform differently from the other 103 firms, we compare the
average and median excess returns of the two subsamples over the 200-day period and they are insignificantly
different.
B. Estimation of Expected Returns
Our primary method of estimating expected returns is to use matched firms.9 For each sample firm,
we choose a matched firm that has the same primary 2-digit SIC code as the sample firm and is closest in
equity capitalization as of the first trading date for the sample firm. We call this sample the size and industry
matched (SIM) sample.
We also match firms in the same industry by size and book-to-market ratios. First, we form size deciles
within the 2-digit primary SIC code for each sample firm, where size is defined above. Next, we choose the firm
in the same size decile as the sample firm that has the closest book-to-market ratio. Seven of the matched firms
delist during the 200-day period following emergence from Chapter 11 for our sample firms. In these cases,
we fill in the remaining days with the next closest matched firm (where the matching is done as of the first
trading day for the sample firm).
Because our sample firms have often undergone dramatic restructurings, their book values reported
before their emergence cannot be used. Therefore, we use the book values reported in the first annual report
following emergence;10 for the sake of consistency, we use book values for the matched firms as reported in
their first annual reports following the emergence dates for the sample firms. We call this the book-to-market,
size and industry matched (BMSIM) sample. Because six of our sample firms do not report book values during
the 200-day period following emergence, these firms are not included in the sample. As a robustness check, we
compute the median book-to-market ratio for our sample firms and match firms to these six firms using this
8
ACAR ’ 1
N
jN
i’1
A T
t’1
(1 % rit) & 1 & 1
N
jN
i’1
A T
t’1
(1 % E(rit)) & 1 ’ 1
N
jN
i’1
CARi (1)
WR ’ jN
i’1
k 200
t’1
(1 % rit)
k 200
t’1
(1 % E(rit))
N (2)
median ratio. The excess returns with this full sample are qualitatively very similar to those reported below.
Finally, as an additional robustness check, we use the market model to estimate expected returns with
the NYSE/AMEX and Nasdaq value-weighted indices as the market returns. We estimate the market model
parameters over day 201 through day 274.
C. Efficiency Tests
Our first efficiency test is the well-known test of whether the average cumulative abnormal return
(ACAR) is significantly different from zero. The ACAR tests whether the average actual return equals the
average expected rate of return.
where
rit = actual rate of return for stock i on day t,
E(rit) = expected rate of return for stock i on day t (see Section II.B),
T = number of days in event period,
N = number of stocks
CARi =cumulative abnormal return for stock i.
We also compute a closely related measure of abnormal performance called the wealth relative (WR)
(e.g., Ritter (1991)):
A WR greater than one implies that the sample firms earned abnormal profits and a WR less than one implies
abnormal losses.
D. Cross-Sectional Tests
9
Ri
’ $0
% $1E(Ri) % $2Pi0
% $3SICCHi
% $4PREPACKi
% $5ISTKDUMi
% ,i (3)
Recall that firms with low stock prices may have higher returns because of estimation risk (e.g., Barry
and Brown (1984)) or transaction costs. Firms that change their primary 2-digit SIC code may have greater
estimation risk because the historical information on the firm is less helpful in predicting the firm’s future
performance and prepackaged bankruptcies may have different risk characteristics from the more lengthy nonprepackaged
bankruptcies. Finally, the willingness of institutional investors to accept only equity in the new
firm–in exchange for their old claim–may portend good future performance that is not fully reflected in the
stock price upon emergence.
We use the four variables described above (that are known at the close of the first trading day upon
emergence from Chapter 11) and the estimate of expected returns in our cross-sectional tests,
where
Ri = compounded actual rate of return for stock i (J(1+rit)-1),
E(Ri) = compounded expected rate of return for stock i (J(1+E(rit))-1),
Pi0 = (log of) price of stock i at the close of the first trading day upon emergence from
Chapter 11 (day 0),
SICCHi = dummy variable equal to one if firm changes its primary 2-digit SIC code during the
bankruptcy process, zero otherwise.
PREPACKi = dummy variable equal to one if the firm’s Chapter 11 filing is a prepackaged
bankruptcy, zero otherwise.11
ISTKDUMi = dummy variable equal to one if institutional investors accept only equity in the
emerging firm (in exchange for their old claim), zero otherwise.
E. Earnings Announcement Tests
There are 99 firms with at least one earnings announcement during the 200-day period following
emergence. To check if this subsample is biased toward the better performing firms, we compute the long- term
10
excess returns for the 32 firms without an earnings announcement and they do not have a significantly lower
ACAR and median CAR than the stocks with at least one earnings announcement. On average, there are 2.6
earnings announcements for each firm with an announcement.
For the earnings announcement tests, the (compounded) CARs–using the matched firms–are computed
over the 21-day period surrounding the announcement (-10 to +10; where 0 is the earnings announcement date).
The CARs are computed for up to four earnings announcements over the 200-day period for each firm that had
an announcement.
The ACARs are computed two ways. First, we assume independence among CARs computed for the
same firm and average all the CARs; we call this the “All Firm Announcement Effects” sample. Second, we
average the CARs for each firm with multiple announcements and use this average to compute the ACAR; this
method assumes that CARs from the same firm are perfectly correlated and we call this the “Average Firm
Announcement Effects” sample. We also compute median CARs for both samples.
III. Empirical Results
The ACAR results are presented in Table I. For the first two days of returns following emergence–
post-emergence period (1, 2)–the ACAR ranges from 3.0 percent to 3.8 percent but the statistical significance
is weak. Moreover, the median CARs are smaller (0 percent to 0.3 percent) and insignificant.
The results become unambiguous when the post-emergence period is extended to day 200. Under every
method of estimating expected returns, the ACARs are large, positive and significant (from 24.6 percent to
138.8 percent). Though lower, the median CARs are also positive and significant (from 5.1 percent to 8.4
percent). The wealth relatives are greater than unity every time.
Table II shows the excess returns around the earnings announcements. In each case, the ACAR is
large, positive and significant. The median CARs are also positive and significant, though the median CAR
is marginally significant for the “All Firm Announcement Effects” sample using the SIM matched firm sample.
These results suggest that the market is surprised by the performance of our sample firms over the 200-day
11
period following emergence.
The cross-sectional results are shown in Table III (the standard errors are corrected using White’s
(1980) method). For the first two return days, there is no variable that consistently explains the cross-sectional
differences in returns; therefore, the excess returns do not appear to be concentrated in stocks with higher
estimation risks or transaction costs. Because our primary method of estimating expected returns is to use a
matched firm of similar size to the sample firm, the transaction costs and estimation risks for these matched
firms are likely to be similar anyway.
The variable ISTKDUMi is positive but only marginally significant. With the 200-day return
regressions, ISTKDUMi is positive and significant with the BMSIM sample. On the other hand, with the SIM
sample, this variable–though positive–is not significant. Therefore, we find mixed evidence that the willingness
of institutional investors to accept only equity in exchange for their old claims on the formerly bankrupt firm
portends abnormally good long-term performance that is not fully reflected in the stock prices upon emergence.
More generally, we find no consistent evidence that any of the other variables that may be associated with risks
or transaction costs not fully captured in our expected return estimates explain our long-term excess returns.12
IV. Summary and Conclusions
We investigate the efficiency of the market for stocks of firms emerging from bankruptcy. We find
weak evidence of positive excess returns in the short-term and strong evidence of positive excess returns in the
long term. Specifically, over the first 200 days of returns after emergence, the ACAR varies from 24.6 percent
to 138.8 percent depending on how the expected returns are estimated. The median CARs, though lower, are
significant and range from 5.1 to 8.4 percent.
Transaction costs or risk-characteristics not captured in our expected return estimates could explain
the results. We investigate these possibilities using differing estimates of expected returns and checking for
whether other risk or transaction cost proxies explain the excess returns. We continue to find excess returns
12
after conducting these investigations. There is some evidence, however, that the willingness of institutional
investors to accept only equity (in exchange for their old claims on the formerly bankrupt firm) in the newly
emerged firm is positively associated with long-term excess returns. This result suggests the type of securities
accepted by these informed investors may reflect information on the stock’s intrinsic value that is not fully
reflected in the stock price upon emergence from Chapter 11.
We also find the average and median excess returns are positive when our sample firms make their
earnings announcements. These results are consistent with La Porta, Lakonishok, Shleifer and Vishny (1995)
and suggest that our findings are the result of the market being surprised by the post-emergence performance
of our sample firms.
In summary, our results cast doubt on the informational efficiency of this market. The results also
present an interesting contrast, but not a contradiction, to the poor operating results of firms emerging from
bankruptcy as reported in previous work. Our results suggest that, although these firms may not do well in their
post-Chapter 11 accounting performance, they appear to do better than the market had expected at the time of
emergence from Chapter 11.
13
Table I
Average Cumulative Abnormal Returns
Average cumulative abnormal returns (ACARs) are computed for the sample of 131 firms emerging from
Chapter 11 from 1980 through 1993. Post-emergence day 0 is defined as the first trading day upon emergence
from Chapter 11. The size and industry matched (SIM) sample is the sample with matching firms that have
the same 2-digit SIC code as the formerly bankrupt firms and are closest in size (e.g., equity capitalization).
The book-to-market, size and industry-matched (BMSIM) sample is the sample with matching firms that have
the same 2-digit SIC code as the formerly bankrupt firm, are within the same (industry) size decile, and are
closest in the book-to-market ratio. The market model adjusted returns are based on alpha and beta coefficients
estimated in the (201, 274) interval using the NYSE/AMEX market index and the Nasdaq index. The ACAR
and median cumulative abnormal return (CAR) are based on daily compounded returns. The Wealth Relative
is the average of the daily compounded actual rate of return divided by the daily compounded expected rate of
return. P-values are in parentheses.
Matched
Event Period Firm Sample ACAR Wealth Relative Median CAR
(1, 2) SIM 0.038C
(0.059)
1.038 0.000
(0.184)
(1, 200) SIM 0.246A
(0.004)
1.249 0.063B
(0.025)
(1, 2) BMSIM 0.030
(0.150)
1.030 0.000
(0.671)
(1, 200) BMSIM 0.600B
(0.050)
1.603 0.084B
(0.022)
(1, 2) Mkt. Model
(NYSE/AMEX)
0.033
(0.112)
1.033 0.002
(0.112)
(1, 200) Mkt. Model
(NYSE/AMEX)
1.385B
(0.016)
2.384 0.072A
(0.009)
(1, 2) Mkt. Model
(Nasdaq)
0.033
(0.114)
1.033 0.003
(0.497)
(1, 200) Mkt. Model
(Nasdaq)
1.388B
(0.028)
2.387 0.051B
(0.013)
A Significantly different from zero at the 1-percent level.
B Significantly different from zero at the 5-percent level.
C Significantly different from zero at the 10-percent level.
14
Table II
Earnings Announcement Tests
Average cumulative average returns (ACARs) are calculated around earnings announcement dates. The
(compounded) cumulative abnormal returns (CARs)–using the matched firms–are computed over the 21-day
period surrounding the announcement (-10 to +10; where 0 is the earnings announcement date). The CARs are
computed for up to 4 earnings announcements over a 200-day period for each firm that had an announcement.
The ACARs are computed two ways. First, we assume independence among CARs computed for the same
firm; we call this the “All Firm Announcement Effects” sample. Second, we average the CARs for each firm
with multiple announcements and use this average to compute the average CAR across firms; this method
assumes that CARs from the same firm are perfectly correlated and we call this the “Average Firm
Announcement Effects” sample. The size and industry matched (SIM) sample is the sample with matching
firms that have the same 2-digit SIC code as the formerly bankrupt firms and are closest in size (e.g., equity
capitalization). The book-to-market, size and industry-matched (BMSIM) sample is the sample with matching
firms that have the same 2-digit SIC code as the formerly bankrupt firm, are within the same (industry) size
decile, and are closest in the book-to-market ratio. P-values are in parentheses.
Sample
Matched
Firm Sample ACAR Median CAR
All Firm
Ann.Effects
SIM 0.068B
(0.043)
0.009
(0.136)
All Firm
Ann.Effects
BMSIM 0.079A
(0.010)
0.023A
(0.004)
Ave. Firm
Ann.Effects
SIM 0.045C
(0.100)
0.026C
(0.095)
Ave. Firm
Ann.Effects
BMSIM 0.062B
(0.013)
0.032A
(0.003)
A Significantly different from zero at the 1-percent level.
B Significantly different from zero at the 5-percent level.
C Significantly different from zero at the 10-percent level.
15
Ri
’ $0
% $1E(Ri) % $2Pi0
% $3SICCHi
% $4PREPACKi
% ,i
Ri
’ $0
% $1E(Ri) % $2Pi0
% $3SICCHi
% $4PREPACKi
% $5ISTKDUMi
% ,i
Table III
Cross-Sectional Tests
Regression estimates of the models,
where Ri is the compounded rate of return for firm i; E(Ri) is the compounded expected rate of return for firm
i; Pi0 is the log of the closing price on day 0 for firm i; SICCHi is a dummy variable that equals one if the firm
changes its primary 2-digit SIC code during the bankruptcy process, zero otherwise; PREPACKi is a dummy
variable that equals one if the firm’s Chapter 11 is a prepackaged bankruptcy, zero otherwise; ISTKDUMi is
a dummy variable equal to one if institutional investors accept only equity (including warrants) in the firm
emerging from bankruptcy, zero otherwise. The size and industry matched (SIM) sample–in Panels A through
D–is the sample with matching firms that have the same 2-digit SIC code as the formerly bankrupt firms and
are closest in size (e.g., equity capitalization). The book-to-market, size and industry-matched (BMSIM)
sample–Panels E through H–is the sample with matching firms that have the same 2-digit SIC code as the
formerly bankrupt firm, are within the same (industry) size decile, and are closest in the book-to-market ratio.
The p-values of the coefficient estimates are shown in parentheses. (1, 2) is for the first two return days
following emergence from Chapter 11; (1, 200) is for the first two hundred returns days following emergence.
SIM BMSIM
A B C D E F G H
Variable (1, 2) (1, 2) (1, 200) (1, 200) (1, 2) (1, 2) (1, 200) (1, 200)
Intercept 0.036
(0.261)
-0.041
(0.297)
0.227
(0.103)
0.331
(0.144)
0.036
(0.260)
-0.036
(0.328)
0.326C
(0.066)
0.381
(0.192)
E(Ri) 0.287B
(0.016)
-0.068A
(0.000)
0.295A
(0.000)
0.359B
(0.030)
0.572
(0.162)
0.566
(0.169)
0.429C
(0.036)
0.588
(0.192)
Pi0 -0.020
(0.222)
0.009
(0.617)
-0.091
(0.209)
-0.095
(0.346)
-0.020
(0.206)
0.010
(0.540)
-0.121
(0.158)
-0.121
(0.337)
PREPACKi
0.169B
(0.026)
-0.088
(0.140)
0.045
(0.770)
0.233
(0.312)
0.160B
(0.031)
-0.108C
(0.080)
0.035
(0.824)
0.215
(0.582)
SICCHi -0.095B
(0.017)
0.097C
(0.072)
0.163
(0.305)
-0.188
(0.276)
-0.106A
(0.008)
0.094C
(0.075)
0.111
(0.590)
-0.235
(0.224)
ISTKDUMi
0.115
(0.249)
0.147
(0.704)
0.089
(0.360)
0.406C
(0.034)
Adj. R2 0.083 0.088 0.118 0.107 0.118 0.107 0.060 0.104
A Significantly different from zero at the 1-percent level.
B Significantly different from zero at the 5-percent level.
C Significantly different from zero at the 10-percent level.
16
REFERENCES
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19, 58-67.
Alderson, Michael J. and Brian L. Betker, 1996, Assessing postbankruptcy performance: An analysis of
reorganized firms’ cash flows, Working paper, Saint Louis University.
Altman, Edward I., 1991, Distressed Securities (Probus Publishing Company, Chicago, Illinois).
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Altman, Edward I. and Allan C. Eberhart, 1994, Do seniority provisions protect bondholders’ investments?,
Journal of Portfolio Management 20, 67-75.
Andrade, Gregor and Steven N. Kaplan, forthcoming, How costly is financial (not economic) distress?
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Banz, Rolf W., 1981, The relationship between return and market value of common stock, Journal of
Financial Economics 9, 3-18.
Barber, Brad M. and John D. Lyon, 1997, Detecting long-run abnormal stock returns: The empirical power
and specification of test statistics, Journal of Financial Economics 43, 341-372.
Barry, Christopher B. and Stephen J. Brown, 1984, Differential information and the small firm effect,
Journal of Financial Economics 13, 283-294.
Betker, Brian L., 1995, An empirical examination of prepackaged bankruptcy, Financial Management 24,
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Brown, David T., Christopher M. James and Robert M. Mooradian, 1993, The information content of
exchange offers made by distressed firms, Journal of Financial Economics 33, 93-118.
Chatterjee, Sris, Upinder S. Dhillon and Gabriel G. Ramirez, Resolution of financial distress: Debt
restructurings via Chapter 11, prepackaged bankruptcies, and workouts, Financial Management 25,
5-18.
17
Dharan, Bala G. and David L. Ikenberry, 1995, The long-run negative drift of post-listing stock returns,
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the absolute priority rule in bankruptcy proceedings, Journal of Finance 45, 1457-1469.
Eberhart, Allan C. and Richard J. Sweeney, 1992, Does the bond market predict bankruptcy settlements?,
Journal of Finance 47, 943-980.
Field, Laura C., 1997, Is institutional investment in initial public offerings related to the long-run
performance of these firms?, Working paper, Pennsylvania State University.
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firms, Journal of Finance, 52, 161-197.
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Ritter, Jay R., 1991, The long-run performance of initial public offerings, Journal of Finance 46, 3-48.
Sandler, Linda, 1991, Post-bankruptcy shares: next big play?, Wall Street Journal, May 16.
Shumway, Tyler, The delisting bias in CRSP data, Journal of Finance, 327-340.
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18
1.The emergence of a firm from bankruptcy is loosely analogous to an IPO. In contrast to our long-term
positive excess returns, Aggarwal and Rivoli (1990) and Ritter (1991) report long-term negative excess
returns for IPOs. Field (1997) finds that IPOs with larger institutional holdings do not underperform a
control sample in the long run, ceteris paribus.
2.Barry and Brown (1984) argue that small firms have higher estimation risk and this explains much,
though not all, of the small-firm effect identified by Banz (1981). For our sample, the correlation between
the log of price at emergence and the log of equity capitalization at emergence is .73.
3.Brown, James and Mooradian (1993) focus on the valuation effects around offer announcements.
Therefore, they do not explicitly predict that the market fails to fully account for this information in the
stock price after it is publicly known. Nevertheless, their model provides a useful motivation for our test of
the market’s ability to efficiently incorporate this information.
4.See Gilson (1997) for some additional evidence on the efficiency of Chapter 11. Andrade and Kaplan
(1997) also examine 20 stocks of firms emerging from bankruptcy or financial distress and find that they
perform abnormally well after emergence.
5.Two firms in our sample stop trading during the 200 days of returns following emergence. As a
robustness check, we assume that these stocks are worthless on the last trading day and find qualitatively
similar results to those reported below (see Shumway (1997) for a discussion of the delisting bias in CRSP
data).
6.Hotchkiss (1995) has an overall sample that is larger than our sample but, in an earlier version of her
issued in exchange for pre-petition debt, Journal of Fixed Income 4, 49-59.
Weiss, Lawrence A., 1990, Bankruptcy costs and violation of claims priority, Journal of Financial
Economics 27, 285-314.
White, H., 1980, A heteroskedasticity-consistent covariance matrix estimator and a direct test for
heteroskedasticity, Econometrica 48, 817-838.
Endnotes
19
paper, she reports that only 41 of the firms in her sample have sufficient data on CRSP (Center for
Research in Security Prices) to compute returns for the first year following bankruptcy. Moreover,
Alderson and Betker (1996) require some market data for their tests and their sample size is 89 firms (we
have 126 firms over the 1983-93 period covered in the Alderson and Betker sample).
7.The stock is listed when it first begins trading, whether on a when-issued or “regular” basis. For an
analysis of the listing effect, see Dharan and Ikenberry (1995). Our sample differs substantially from the
sample in Dharan and Ikenberry because our firms typically have restructured their operating and financial
structure in a way that firms do not do when they just change their listing. Moreover, many firms in our
sample trade continuously and do not change their listing.
8.In one case (Maxicare Health Plans, Inc.), the Capital Changes Reporter states the firm began trading on
a when-issued basis on December 19, 1990 at $4 per share. However, the SPDSPR and CRSP do not note
any trading until April 30, 1991 and this is the date we use. The price on April 30 was $8.875. Therefore,
if the Capital Changes Reporter is correct, then we have biased downward our estimate of the excess
returns.
9.Spiess and Affleck-Graves (1995) employ the use of matched firms in their study of the performance of
stocks subsequent to seasoned equity offerings. Barber and Lyon (1997) also recommend the use of
matched firms.
10.Because of this estimation problem, we perform this test merely as a robustness check.
11.We have 25 prepackaged bankruptcies. The median time in Chapter 11 for our prepackaged
bankruptcies is 7.237 months and 22.83 for our non-prepackaged bankruptcies (recall that we measure
time in Chapter 11 from the bankruptcy announcement date through the first trading date). The samples in
Betker (1995) and Chatterjee, Dhillon and Ramirez (1996) are helpful in identifying which of our sample
firms are prepackaged bankruptcies.
12.To check further whether our long-term positive excess returns are concentrated among low price
stocks, we compute the 200-day average and median excess returns (with the SIM and BMSIM sample) for
20
stocks with a first trading day price of $4 or less and for stocks with a price of more than $4; the average
and median excess returns for the low price stocks are not significantly higher than for the high price
stocks.