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Impact and Value
Of Reverse Stock Splits
by
Mohsin Memon
An honors thesis submitted in partial fulfillment
of the requirements for the degree of
Bachelor of Science
Undergraduate College
Leonard N. Stern School of Business
New York University
May 2003
Professor Marti G. Subrahmanyam Professor Damodaran Faculty Adviser Thesis Advisor
Executive Summary:
Stock splits are examples of illusory changes because they should not affect the
value of the firm. In a reverse stock split, a firm consolidates its shares by a certain factor
and also increases its stock price by the same factor. As a result, the market
capitalization of the company does not change and therefore this should have no impact
on the value of the company. However, past research on forward stock splits has shown
that there is a positive market response on the date of announcement which can be
explained by an optimal trading range theory and positive information effects. On the
other hand, little research has been done on the impact of reverse stock splits because
they have not been a tool used frequently by corporate managers until recently. The
purpose of this study is to test the market response to reverse splits with a recent sample
and to explain what causes the abnormal returns if any exist.
There are many possible motives for companies to reverse split their stock. The
discretionary motivations can be to reduce registrar fees and shareholder mailing costs,
“squeeze” out shareholders, enhance image or improve marketability. Also, with the
current bear market after a period of extreme overvaluations, a non-discretionary
motivation to reverse split has become prominent. The NYSE and Nasdaq require a $1
price minimum to remain on their exchange and if a company slips below this level, it
will be in danger of being delisted. The fact that many companies have slipped below
that $1 level has led to many of them being forced to reverse split their stock to remain on
a major exchange.
In accordance with some of the research that has been done on reverse splits, I
believe that I will find that firms announcing reverse splits will show a statistically
significant decline in stock price on the day of the announcement. More specifically, I
hypothesis that firms which are forced to reverse split because of delisting fears will
perform relatively better than firms that chose to reverse split for discretionary purposes.
The reason I believe this is because I feel that the companies which are forced to reverse
split actually have the most to gain from the increased marketability since they will also
take away the fear of being delisted and no longer be considered “penny-stocks.”
Secondly, I hypothesis that companies which have negative earnings before a reverse
split will perform worse than companies with positive earnings. Companies which have
negative pre-split earnings will send a strong informational signal to investors that these
poor earnings are here to stay or else they would not have had to artificially raise their
prices.
After doing a descriptive analysis on my sample, I saw that most companies that
did reverse splits were on the Nasdaq and were trading at less than $1 signaling a non-
discretionary split. Sector and year analysis saw a decrease in reverse splits in the boom
period and a drastic increase in the last 2 years, especially in the technology sector.
In the daily and monthly returns around the announcement dates, I got statistically
significant negative returns on the announcement date indicating that reverse splits do
have some impact on value. I then ran a multiple regression on the announcement day
return with variables indicating discretionary or non-discretionary split, negative or
positive earnings per share two quarters before the announcement, split factor, size, and if
they are on the Nasdaq or NYSE.
Before I analyzed the results, I individually looked at three factors extensively.
The first, marketability, was analyzed through average split adjusted trading volumes
before and after the reverse split. Results showed a statistically significant increase in
volume which increases the liquidity and marketability of the stock. Also, I looked at the
price range of companies before and after the split and saw that most companies were
below a dollar before the split and above it after. However, the post-split price did not go
over the $5 threshold which many institutional investors do not look below, so it seemed
as though their main motivation was not as much for marketability but rather desperation
to stay on a major exchange.
Second, I looked at companies which were forced to reverse split (pre-split price
below $1) and those which did it for discretionary purposes (pre-split price above $1).
The results showed statistically significant negative abnormal returns for both, but
surprisingly a much higher negative return for non-discretionary companies. This can be
explained by the fact that a majority of non-discretionary companies actually end up
delisting anyways which means that their stock underperforms the market after the
reverse split. Investors read this as a sign that these companies are overvalued or
distressed and that their price is going to drop which causes the negative impact on the
announcement date.
For the next factor, I found that companies which had negative earnings prior to
the reverse split performed a lot worse than companies which had positive earnings -
however the latter still had statistically significant negative returns. The negative earning
companies send a strong signal that they are going to continue to perform poorly and are
therefore distressed.
Finally, I decided to test positive earning companies that reverse split for
discretionary reasons and actually got a slightly significant positive return on the
announcement date implying that once the two main negative factors are taken out, the
benefits of an increase in marketability can be seen.
The multiple regression results show that the non-discretionary factor drowns out
the effects of most of the other variables and is the major cause for the negative returns
on the announcement date.
In conclusion, an announcement of a reverse split causes a negative impact if the
company has either negative earnings prior to the announcement or is performed for non-
discretionary reasons. The investors read the announcement of a reverse split for these
companies as an indication of distress and overvaluation. Finally, a trading strategy can
be created if every stock that hits $1 on the Nasdaq is shorted because a good percentage
of them reverse split within 6 months and as indicated in my analysis, will be expected to
have highly negative returns on the announcement date.
INTRODUCTION:
Stock splits, forward and reverse, are examples of illusory changes to the financial
position of a firm. Illusory changes refer to accounting adjustments and window-dressing
techniques that, by themselves, have no impact on the firm’s future cash flows. On the
other hand, a real change is one that directly affects the earnings and risk factor of the
firm such as mergers and acquisitions, new product lines, and patent expirations. These
types of changes can be given estimated dollar values and can therefore affect the value
and share price of a firm.1
However, these definitions only hold true in a perfect markets environment with
perfectly divisible financial assets, homogenous investor expectations, and no transaction
costs. In reality we live in imperfect markets where trading and information
imperfections may cause stock prices to react to splits. Substantial research has been
done on the impact of forward splits but reverse splits have received little attention in the
past.
In a forward split, there is an increase in the number of a corporation's outstanding
shares, which in turn decreases the value of its stock. The market capitalization remains
the same because the factor to decrease the price is the same as the factor to increase
shares outstanding. For example, in a 2-for-1 stock split, each stockholder receives an
additional share for each share held, but the value of each share is cut in half: two shares
now equal the original value of one share before the split. Therefore, the proportional
ownership of shareholders remains the same.
1 Radcliffe, R.C. and Gillespie, W., (February 1979), “The Price Impact of Reverse Splits,” Financial Analysts Journal, 63-67
Even though shareholder wealth should technically remain the same after a split,
extensive research has proven otherwise. The consensus is that a forward split
announcement brings about a positive market response.2 There have been many
explanations for the positive stock market response such as the adjustment of the stock
price to a more attractive trading range.3 A second hypothesis explaining the abnormal
returns involves the reduction of information asymmetries. Most versions of this
argument explain that stock splits reduce information asymmetries either by directly
signaling good information that previously was privately known or simply by attracting
greater attention to the firm.4
On the other hand, not much is known about the effects of revere stock splits
because they simply have not been a tool frequently used by firms until the recent bear
market we are in today. In a reverse split, there is a decrease in the number of a
corporation's outstanding shares, which in turn increases the value of its stock. Once
again, the market capitalization remains the same because the factor to increase the price
is the same as the factor to decrease shares outstanding. This is another example of a
paper transaction where there should be no effect on shareholder wealth. However, the
little research that has been done in this field shows that there is an abnormal negative
response to companies when they announce a reverse stock split.5 The purpose of this
2 Fama, E., Fischer, M., Jensen, M., and Roll, R. (February 1969), “The adjustment of stock prices to new information,” International Economic Review, 1-21. 3 Lakonishok, J. and Lev, B. (September 1987), “Stock splits and stock dividends: Why, who, and when,” Journal of Finance, 913-932. 4 Brennan, M.J. and Copeland, T.E. (October 1988), “Stock splits, stock prices and transaction costs,” Journal of Finance and Economics, 83-101. Grinblatt, M.S., Masulis, R.W., and Titman, S. (December 1984), “The valuation effects of stock splits and stock dividends,” Journal of Financial Economics, 461-490. 5 Lamoureux, C.G. and Poon, P. (December 1987), “The market reaction to stock splits,” Journal of Finance, 1347-1370. Woolridge, J.R. and Chambers, D.R., (Autumn 1983), “Reverse splits and shareholder wealth,” Financial Management, 5-15.
paper is to test the market response to reverse splits with an up-to-date sample and to
explain what causes the abnormal returns if any exist.
MOTIVES:
There are many factors that might motivate firms to reverse split their stock. If
reverse splits had no impact on the value of the firm, then there would seem to be no
economic use for them by management. Since reverse splits do occur, especially in
recent times, corporate managers must believe otherwise.
A possible motivation for a reverse split might be to reduce registrar fees and
shareholder mailing costs. However, as Gillespie and Radcliffe (1979) explain, it is not
probable that the minimal future benefits from reverse splitting firms would in most cases
offset the immediate costs involved to undertake this action.6 As a result, this motivation
will not be given much credibility and thus not looked into further.
Reverse splits may also be used to eliminate enough shareholders to remove the
corporation from disclosure requirements. A reverse split provides a relatively simple
means of going private without making a tender offer and, depending upon the corporate
charter, without a shareholder vote. Large reverse splits can squeeze out small
shareholders since, in some states, shareholders are not permitted to own fractional
shares. We do not usually see this done for companies that are traded on the major
exchanges which are the only ones I am looking at in this sample, so this factor of
motivation will also not be analyzed further in this paper.
Next, and probably one of the more compelling motivations for reverse splits, is
to increase marketability. Share prices that are too low may affect marketability because
6 See footnote 1
they may be considered speculative, and therefore not attractive to investors, especially
institutional investors. Also, many institutional stock screens and quantitative models
ignore stocks that have a price below $5. Companies with such low prices do not give off
a good image because investors feel that there has to be a reason they are trading at such
poor prices. Gillespie and Seitz (1977) discovered image improvement to be the most
common motivation for reverse splits.7 If higher stock prices do enhance a firm’s image
or provide other benefits to a firm, then stock prices should be affected positively on the
announcement date.
Other increases in marketability can come from a reduction in transaction costs.
Since transaction costs are inversely related to share price, transaction costs (as a
percentage of stock price) should decrease after a reverse split.8 Other things remaining
the same, this decrease in cost should improve of the liquidity of the stock. Also, in the
U.S. a stock can not be bought on margin if it trades at less than $5 which can be a
serious disadvantage for investors. By raising share prices, reverse splits can improve the
margin eligibility, which, in turn enhances the liquidity of the stock.
So far all the motivations for reverse splits that have been described are for
discretionary purposes. However, a non-discretionary motivation which has become of
much more importance in recent times, is to artificially raise the stock price through a
reverse split in order to prevent the company stock from being delisted off a major
exchange. The NYSE and Nasdaq require for a company to remain on its exchange to
keep a stock price above $1. If a company fails to meet this requirement for more than
7 Gillespie, W. and Seitz, N., “Price Trends Following Reverse Stock Splits,” paper presented at Regional AIDS Meeting, 1977. 8 See footnote 4
30 days, or any of the other requirements, it will be delisted from the exchange.9 As a
result, its shares typically begin trading either on the OTC Bulletin Board, run and
loosely regulated by the Nasdaq, or the Pink Sheets, a barely regulated private quotation
service where companies aren’t required to file regular financial reports. These markets
are much less liquid because it is harder to match buyers with sellers and as a result, this
lack of marketability can further destroy a firm which must already be in trouble because
it was forced to delist off an exchange.
HYPOTHESIS DEVELOPMENT:
The increased threat and concern of delistment in recent times is a result of many
reasons. First of all, in the 1980s and 1990s the Nasdaq and NYSE exchanges eased
requirements to allow companies to enlist on their exchange because of major
competition between them to get business. Then in 1997, for fear of hurting its
reputation, the Nasdaq tightened its requirements to stay on its exchange. The
technology boom which followed allowed most companies to temporarily comply with
those requirements because of all the optimism and hype that caused incredibly high
valuations on those companies. However, when the market finally collapsed in 2000 into
the bear market we are in today, the tightening of those rules in 1997 really came into
affect. Many companies have seen there stock prices plummet during these tough times
to below the $1 threshold putting them in danger of being kicked off a major exchange.
As a result, a lot of these companies are trying to do whatever it takes to survive and
many are resorting to reverse stock splits.
9 Companies receive a warning after being below $1 for 30 days which gives them 90 days to bring the stock price above $1 for 10 consecutive days or else they are delisted (see appendix for list of requirements).
In accordance with some of the research that has been done on reverse splits, I
believe that I will find that firms announcing reverse splits will show a statistically
significant decline in stock price on the day of the announcement. This will show that the
negative information effects will outweigh the microstructure benefits that may arise
from a reverse split. More specifically, I will make the following two hypotheses:
(H1): Firms which are forced to reverse split because of delisting fears will perform
relatively better than firms that chose to reverse split for discretionary purposes.
(H2): Companies that have negative earnings before a reverse split will perform worse
than companies with positive earnings before the reverse split.
In the first hypothesis, I am assuming that the companies that are forced to reverse split
actually have the most to gain from the increased marketability because they will also
take away the fear of being delisted and no longer be considered a “penny-stock” As a
result, they should perform better than the companies that do it for discretionary
purposes. In the second hypothesis, I am assuming that companies which have negative
earnings before a reverse split will send a strong informational signal to investors that
these poor earnings are here to stay or else they would not have had to artificially raise
their prices. On the other hand, companies that have had positive earnings and then
perform reverse splits might be just trying to get an immediate increase in marketability
which should help the company. However, the artificial raising of the stock price might
still send a negative signal but it will not be as large because they were performing well
before the announcement.
DATA:
To get a sample of companies that performed reverse splits I did a search in
Factset by setting the split factor less than 0.5 for all companies from January 1998 to
December 2002. However, there was a problem because I couldn’t specify what
exchange the company should be on at a certain time, only what exchange it was
currently on. Therefore, if I limited my search to only companies on the three major
exchanges (AMEX, NYSE, and Nasdaq), I would only get a list comprised of companies
that performed reverse splits and are still being traded on one of the major exchanges
now, leaving out all delisted companies after reverse splits which is what I want to really
look at. As a result, I did a cross search on the list I got from Factset, which contained a
few thousand companies including ones currently traded on the OTC with the CRSP
database which has only companies that are or have been on the NYSE, AMEX, or
Nasdaq.10 If the company in my sample did not show up on the CRSP database, I
excluded it from my dataset which significantly cut down the original list of about 2,000
companies. I then eliminated any companies that were not trading 6 months before the
split because I wanted to examine pre-split earnings and stock returns. I also eliminated
companies on the AMEX because they delist companies on a case by case basis which
would hamper my analysis between discretionary and non-discretionary reverse splits.
Finally, any companies for which I could not get pertinent accounting data from
Compustat to conduct my analysis were also eliminated, and in the end, I was left with
211 companies in my dataset.
10 I could not search directly for companies that performed reverse splits on CRSP because of limitations through the WRDS account for NYU students.
Below is a table which divides up the data by S&P sectors and by years so we can
see if there is any trend in the annual number of reverse stock splits and if there are any
sectors worth noting.
Table 1: Sector and Year distribution of Reverse Stock Splits
1998 1999 2000 2001 2002 Total
Consumer Discretionary 7 10 5 6 9 37 16.28% 28.57% 20.00% 12.50% 15.00% 17.54% Consumer Staples 0 4 1 2 1 8 0.00% 11.43% 4.00% 4.17% 1.67% 3.79% Energy 8 2 2 0 1 13 18.60% 5.71% 8.00% 0.00% 1.67% 6.16% Financials 2 2 4 4 2 14 4.65% 5.71% 16.00% 8.33% 3.33% 6.64% Health Care 9 6 4 4 7 30 20.93% 17.14% 16.00% 8.33% 11.67% 14.22% Industrials 7 3 2 6 2 20 16.28% 8.57% 8.00% 12.50% 3.33% 9.48% Information Technology 6 7 4 23 27 67 13.95% 20.00% 16.00% 47.92% 45.00% 31.75% Materials 4 1 2 2 4 13 9.30% 2.86% 8.00% 4.17% 6.67% 6.16% Telecommunication Services 0 0 1 1 7 9 0.00% 0.00% 4.00% 2.08% 11.67% 4.27% Utilities 0 0 0 0 0 0 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Total 43 35 25 48 60 211 20.38% 16.59% 11.85% 22.75% 28.44% 100.00%
With the market in full gear during the late 1990s, the exchanges were battling to
get companies to enlist with them and many companies that should not have become
public did just that. Being the height of the technology boom and more specifically the
dot com bubble, many of these companies that should not have been public were
technology companies. As the bubble busted in 2000, many of these technology
companies were sent to the exits as fast as they had come in. As a result, you see less
reverse splits when the market was booming in 1999, and 2000 (there are relatively more
reverse splits in 1998 because the Nasdaq tightened their delisting policies at the time and
companies which weren’t able to catch the boom in time were booted as a result), and
gradually more splits in the latter years with 2002 having the most. Also, the
concentration of technology companies performing reverse splits has increased greatly
which makes timely sense as a result of the collapse of the technology sector.
Descriptive statistics on the sample are displayed in table 2. The average split
factor for a reverse split is 11.43, but that figure is skewed upward because of the few
companies which took on extremely large splits such as 200 to 1 which is the maximum
split in the sample. The median split factor is 5.0 which gives a better idea of what size
of reverse split most companies perform. The pre-split average price of the sample is
rather low at $1.43 exemplifying the point that low priced companies tend to do reverse
splits. The post split average price of $7.05 is interestingly above the $5 threshold which
most institutional investors do no look below, however the median is only $3.15
suggesting that most stocks do not try to reverse split for the purpose of getting over $5.
In terms of size, companies performing reverse splits indicated by their market cap are
only on average $68.3 million with a median of $12.9 million. This goes along with the
historical trend of smaller companies usually performing reverse splits but some larger
companies are taking on this strategy as well as can be seen by the maximum size of a
company in the sample being over $10 billion. Finally, as expected, there are a lot more
reverse splits done on the Nasdaq because of the amount of technology companies on that
exchange.
Table 2: Descriptive Statistics on Sample N Mean Median SE mean Min Max Sample Size 211 Split Factor 11.43 5 1.65 2 200 Pre-Split Price $1.43 $0.54 0.21 $0.01 $26.19 Post-Split Price $7.05 $3.15 0.82 $0.70 $99.58 Market Cap (millions) $68.30 $12.90 $49.50 $0.01 $10,405.60 NYSE 176 Nasdaq 35
ANALYSIS:
To analyze the impact of reverse splits on stock price, I looked at the –20 to +20
day period around the announcement date to see the impact of the news, with day zero
being the announcement date. Also, to look at a more long term perspective, I looked at
the –5 month to + 6 monthly returns around the split with the returns from month zero to
month one being the month of the announcement. As the dataset used in this study is a
very recent one, it will not be possible in this paper to analyze any longer term effects for
these companies. However, Desai and Jain did a study in 1997 and looked at a more
dated set of reverse splits (ranging from 1976-91) and analyzed the long run effects on
them. They found that companies which do reverse splits have an abnormal return in
their announcement period which is followed by even worse abnormal returns in the 3
years post split. So not only does the news of reverse split contain negative news
reducing shareholder wealth, the period after the split is followed by deteriorating
shareholder wealth.11
When looking at stock returns around the announcement date, it is important to
try and focus on firm specific returns or abnormal returns which exceed that of the
market. To get more specific and take into account any sector effects, I adjusted the
individual returns with that of its sector S&P index for the same time periods. As a result
the adjusted return was:
Radj = Rcomp - Rind
This will give us the abnormal stock returns of the individual companies which
will be analyzed around reverse split announcement dates for each company. The returns
should be randomly distributed around zero. Any statistically significant departures from
this pattern would imply that there is something special about the sample stocks.
(Please Turn Over)
11 Desai, H., Jain, P.C., (July 1997), “Long-Run Common Stock Returns Following Stock Splits and Reverse Splits,” The Journal of Business, 409-433
Table 3: Abnormal Daily Returns Around Reverse Stock Split
Day Abnormal Return Standard Error t-statistic -20 0.914 0.839 1.09 -19 0.344 0.828 0.42 -18 -0.302 0.748 -0.4 -17 -0.152 0.754 -0.2 -16 0.409 0.915 0.45 -15 -0.148 0.731 -0.2 -14 0.54 0.688 0.78 -13 -0.259 0.61 -0.42 -12 0.151 0.624 0.24 -11 -0.674 0.568 -1.19 -10 1.244 0.805 1.54 -9 -0.231 0.628 -0.37 -8 0.076 0.665 0.11 -7 -0.315 0.664 -0.47 -6 -0.243 0.775 -0.31 -5 1.35 1.36 1.72 -4 -0.657 0.607 -1.08 -3 -0.168 0.67 -0.25 -2 -0.645 0.613 -1.05 -1 -0.322 0.787 -0.41 0 -8.535 0.992 -8.61** 1 -0.342 0.944 -0.36 2 -0.557 0.866 -0.64 3 0.815 0.812 1 4 0.061 0.823 0.07 5 1.784 0.844 2.11* 6 -0.378 0.734 -0.51 7 -0.373 0.678 -0.55 8 -0.83 0.687 -1.21 9 -0.321 0.658 -0.49
10 0.516 0.634 0.81 11 0.249 0.688 0.36 12 0.249 0.669 0.37 13 -0.023 0.732 -0.03 14 0.145 0.67 0.22 15 0.879 0.881 1 16 -0.248 0.646 -0.38 17 -0.23 0.535 -0.43 18 -0.722 0.615 -1.17 19 -0.677 0.493 -1.37 20 -0.256 0.595 -0.43
* statistically significant at the 5-percent level ** statistically significant at the 1-percent level
Table 4: Abnormal Monthly Returns Around Reverse Stock Split
Month Abnormal Return Standard Error t-statistic
-5 1.89 3.87 0.49 -4 -2.44 2.69 -0.91 -3 -4.34 2.86 -1.52 -2 -3.1 2.14 -1.45 -1 -1.43 5.23 -0.27 0 -4.95 2.26 -2.63** 1 -11.51 2.81 -4.09** 2 -3.08 2.93 -1.05 3 2.74 2.59 1.06 4 -2.45 2.48 -0.99 5 3.22 2.08 1.52 6 -4.62 2.25 -2.05*
* statistically significant at the 5-percent level ** statistically significant at the 1-percent level
The average abnormal return on the announcement date is –8.54%, significant at
the 1-percent level, indicating that negative abnormal returns do occur at the
announcement of reverse splits. Looking at the monthly returns to see a longer term
effect, we find the month of the announcement to have abnormally negative and
statistically significant returns with a –11.51% return at the 1-percent level.12
Interestingly, the month prior to the announcement is significantly negative as well,
indicating that companies that perform reverse splits were performing a lot worse than
the market before they made their announcement. Even though I am not looking as far
long term as Desai and Prem did, my results do not indicate statistically negative returns
following the reverse split other than in month six. It seems as though all the information
is incorporated at the time of the reverse split and then the stock goes back to it normal
return pattern. It is important to note that I am only looking at a 6 month outlook and that
my sample size is reduced significantly because I had to eliminate companies from 12 Companies that did reverse splits from October 2002-December 2002 in this sample had to be left out because there +6 month information was not available at the time the data was collected in March 2002.
October through December 2002. The reduction in sample size for this longer term
analysis may reduce the accuracy and therefore statistical significance of abnormal
returns which may in fact exist.
EMPIRICAL TESTS AND RESULTS:
We analyze the significant abnormal negative return on the announcement date
using a multiple regression with the return on day zero being the dependent variable and
factors that could represent trading range and information effects as the independent
variables.
RET = BB0Nondiscretionary + B1B NegEPS + BB2SplitFactor + B3B Size + BB4NYSE + B5B Nas
For the non-discretionary variable, I used dummy variables with a 0 for
discretionary and 1 for non-discretionary. I also used a dummy variable for earnings per
share with a 0 for positive earnings two quarters before split announcement and a 1 for
negative earnings per share. For split factor I used the fractional value of the reverse split
and for size I used the market capitalization of the company. Finally, for the NYSE and
Nasdaq variables I used dummy variables with a 1 if the stock was on the exchange.
Before going into the results of this regression, I will individually analyze three key
factors which I feel are the most important to look at in explaining the negative returns:
Marketability, Discretionary vs. Non-Discretionary, and Negative Earnings Information.
Marketability:
As mentioned earlier, one of the main motives for companies to undergo reverse
stock splits is to increase the marketability of their stock. To determine if marketability
does in fact go up after a reverse split I will look at trading volume and price distributions
before and after the split.
For analyzing trading volume, I looked at split adjusted trading volume from 30
days prior to 30 days after the reverse split.13 As you can see in the graph below, there
was a spike in trading volume around announcement time and then the volume dropped a
little before leveling off at a range higher than before the split. The average trading
volume for the 30 days prior to the split was 62.9 thousand shares and 95.7 thousand
shares after (t-statistic of difference –5.88) indicating that the reverse split did increase
the marketability because more shares were being traded implying higher liquidity.
Trading Volume Around Reverse Stock Split
0.0020.0040.0060.0080.00
100.00120.00140.00160.00180.00200.00
-30-28-26-24-22-20-18-16-14-12-10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30
Days Around Split
Trad
ing
Volu
me
(thou
sand
s)
13 A split-adjusted trading volume lets us compare the volume before and after the split. To illustrate, consider a firm that reverse split its shares by the split ratio of 0.25. Suppose that 1000 shares and 400 shares were trading during the pre and post split periods, respectively. In this case, the volume measures are 1000 shares and 1600 shares (300/0.25) for the pre and post split periods, respectively.
The table below shows the pre and post split price ranges for the sample. Before
viewing the results, I expected that most companies would be trying to get above the $5
threshold to substantially increase their marketability. However, the results do not go in
line with those expectations but rather raise some interesting points. Most companies that
performed reverse splits were actually below $1 indicating that they were forced to
reverse split to get out of the threat of delistment. This can be confirmed by the post-split
price range in which most companies are above the $1 cutoff but surprisingly still under
$5. This further shows that these companies weren’t necessarily motivated by the need to
increase marketability but were rather forced to save themselves from being delisted.
Number Of Firms
P<=$1 $1<P>$5 $5<=P>=$10 P>=$10 Pre-Split 162 42 5 5 Post-Split 3 155 40 34
From the analysis on marketability, trading volume and price go up which shows that
marketability does in fact go up but the question arises if that is the main motivational
force.
Discretionary vs. Non-Discretionary:
To test my first hypothesis, I will classify reverse splits by companies that had a
pre-split price below or equal to $1 as non-discretionary because they faced the threat of
delistment and were forced to do so to stay on an exchange. On the other hand,
companies above $1 were considered to have performed reverse splits for discretionary
purposes. There may be a lot of companies close to $1 but slightly above it that did
reverse splits because of the threat of delistment but just to keep an accurate sample and
not to cut down the size of the discretionary sample too much, I kept a $1 cutoff.
Running a two-sample t-test to compare the announcement date results of the two
subsets, I surprisingly found a much greater statistically significant negative impact for
non-discretionary splits than discretionary ones.
Table 5: Discretionary vs. Non-Discretionary Two-Sample T-Test and CI N Mean (%) StDev SE Mean Non-Discretionary 162 -10.5 15.2 1.2 Discretionary 49 -2.11 8.71 1.2 Estimate for difference: -8.37
95% CI for difference: (-11.78, -4.95)
T-Test of difference = 0 (vs not =): T-Value = -4.85 P-Value = 0.000
What is interesting to note is that even though something causes companies that
are forced to reverse split to perform a lot worse than ones that do it for discretionary
purposes, companies that do it for discretionary purposes still have a statistically
significant negative return on announcement date. This means that there is also
something else that drives stocks to have abnormal returns on an announcement of a
reverse split.
To further try to understand why non-discretionary companies perform a lot
worse, I will look at the driving force which causes companies to be forced to reverse
split – delistment.
Out of my sample of 211 firms, 107 or 50.71% have already been delisted by
December 31, 2002. The average number of days before delisting after a reverse split
was 568 days which means all the companies that have done reverse splits after June 11,
2001 have not even reached the average duration before delisting. This means that this
percentage is negatively skewed and that the actual number will probably be a lot higher.
Now, separating between non-discretionary and discretionary companies, I find that
58.64% of non-discretionary have delisted by December 31, 2002 while only 24.48% of
discretionary companies. If we look at just companies that have done a reverse split
before June 11, 2001, we find an astonishing 78.72% of non-discretionary companies
have already delisted by December 31, 2002. This is telling us that companies reverse
split to artificially raise their price to prevent being delisted but their stock price still
drops to below $1 and they are forced to delist. Since their stock prices go down even
after the negative announcement date return, these stock are obviously either overvalued
or distressed. Management must know that the stock price is going to go down as a result
and they try to artificially raise the stock price with enough of a cushion so that it does
not drop below the $1 mark. However, as the results show, they have not been very
successful in keeping there companies on the major exchanges. These companies do not
belong there and are doing whatever they can out of desperation to stay on. Investors are
reading this when they see a non-discretionary reverse split and that is why they assign
such high negative returns to it on the announcement date.
Negative Earnings Information:
To test the second hypothesis, I will look at the earnings two quarters before the
reverse split for the firms in the sample. The reason I am not looking at earnings one
quarter before is because the results of those quarters were possibly not reported by the
time the reverse split was announced. As you can see in the table before, companies
which had negative earnings before a reverse split performed a lot worse than companies
with positive earnings. It is worth noting that the companies with positive earnings still
had a statistically significant negative return on announcement date.
Table 6: Positive vs. Negative EPS Two-Sample T-Test and CI: Pos -2Q, Neg -2Q
N Mean (%) StDev SE Mean Pos -2Q 58 -5.2 12.7 1.7 Neg -2Q 153 -12.1 20.5 1.7 Estimate for difference: 6.90
95% CI for difference: (2.25, 11.55) T-Test of difference = 0 (vs not =): T-Value = 2.93 P-Value = 0.004
The firms which already had negative earnings must be sending a stronger
negative signal to the market that their poor results will continue or else they would not
have tried to artificially raise their prices. The argument can also be made that positive
earning companies might be signaling a bad future because they also artificially raised
their prices but the signal is not as strong because they were not already reporting
negative returns.
Controlling for Negative Factors:
Now we have seen that non-discretionary and negative earnings cause a
substantial negative impact on the announcement date but their counterparts,
discretionary and positive earning companies each also have a much smaller, yet still
significant negative return on that day. I thought it would be interesting to see what the
results would be if we took out both negative factors and tested the returns on positive
earning companies that performed reverse splits. This screening of the data reduced the
sample to only 23 companies which hurt the accuracy and significance of the test.
However, interestingly enough, as you can see below the average return for these
companies on the announcement date was a positive 1.72% on a slightly less, but still
decently significant 90% confidence level. This means that two major factors that cause
negative returns have possibly been identified and that if they are removed, we can
actually see the positive impact of increased marketability of companies that announce
reverse splits.
Table 7: Pos EPS and Dis One-Sample T: PosEPS and Dis Test of mu = 0 vs mu not = 0 Variable N Mean StDev SE PosEPS and Dis 23 1.722 3.964 0.934 95.0% CI PosEPS and D ( -0.249, 3.693) T=1.84 P=0.083
MULTIPLE REGRESSION RESULTS:
When we run the multiple regression mentioned above to see what causes the
negative returns on the announcement day, we find that the only statistically significant
factor is if the company does it for non-discretionary purposes. I got a highly negative
coefficient significant at the 95% confidence level indicating that a non-discretionary
split accounts for the major part of the negative returns. All the other factors were
drowned out by this one except for the negative earnings factor which showed some
statistical significance at the 90% confidence level. For the negative earnings variable,
there was a negative coefficient indicating that negative earnings prior to announcement
are responsible for some of the negative effect. The R-squared for the regression was
rather low at 7.0% but that is normal in finance because of the correlations between all
the individual factors that you bring into the equation.
Table 8: Multiple Regression Regression Analysis: RET versus nondis, neg eps, factor, size, nyse, nas * nas is highly correlated with other X variables * nas has been removed from the equation The regression equation is RET = - 0.82 - 6.21 nondis - 4.29 neg eps - 0.0406 factor + 0.00049 size + 3.59 nyse Predictor Coef SE Coef T P Constant -0.818 2.461 -0.33 0.74 nondis -6.211 2.423 -2.56 0.011
neg eps -4.295 2.214 -1.94 0.054 factor -0.04064 0.04076 -1 0.32 size 0.000493 0.001355 0.36 0.716 nyse 3.594 2.623 1.37 0.172
S = 13.89 R-Sq = 9.2% R-Sq(adj) = 7.0%
CONCLUSION:
After running tests on my sample, I find that my first hypothesis was wrong
because I had thought non-discretionary companies would gain the most from an increase
in marketability and reduction of threat from delistment after a reverse split. As it turns
out, these companies performed the worse because, as shown by my results, they are
either overvalued or distressed when they reverse split and management is just trying to
save the company out of desperation. Investors are smart and read the announcement of
a reverse split from these types of companies as a signal that they are highly overvalued
or are distressed and will underperform the market in the future.
On the other hand, my second hypothesis seemed to show some truth as
companies with prior negative earnings sent a stronger negative signal to the market than
ones with positive earnings before a reverse split. Investors read that as a sign indicating
that poor earnings were going to continue and that the firm was probably distressed. As a
result, they assigned it a significantly high negative return on the announcement date.
Finally, I saw that the increase in marketability which we proved does occur was
drowned out by these two negative factors and if we remove the negative factors, we can
actually see the benefits of it with a slightly significant positive return on the
announcement day.
These findings also bring up an interesting thought on trading strategy. I looked
at a sample of 100 companies that hit $1 on the Nasdaq and found that 30% of them
performed reverse stock splits within 6 months of hitting $1. If you were to short every
stock that hits $1 on the Nasdaq, you could make an expected return of (.30) * (10.5) =
3.15%. The 10.5% is the average negative return on the announcement date for non-
discretionary companies which is essentially what we are looking at when we look for
stocks that hit $1. You could also possibly short all non-discretionary companies once
they reverse split because my research has show that most of them tend to delist meaning
their stock price drops after the reverse split.
It is also important to note that my analysis is a very time-specific one. We have
seen a tremendous boom followed by a bust which has caused many companies to be
forced to reverse split to survive. Many of them probably would not even have been on a
major exchange if it wasn’t for the ridiculous overvaluations in the late 90s and therefore
this data sample is very skewed to those types of companies. Also, if the Nasdaq decides
to ease their delisting requirements which they are considering, it could drastically effect
the negative returns that I got on the announcement day since much of it was due to the
information from companies being forced to reverse split.
Appendix 1: NYSE Suspension and Delisting Guidelines
Appendix 2: Nasdaq Suspension and Delisting Guidelines
Figure 1: Adjusted Daily Returns Around Reverse Stock Split
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Daily Return Around Reverse Split Date
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