Department of Economics and Finance
Working Paper: 2011014
November 2011
Stock Split Decisions: A Synthesis of Theory and Evidence
http://www.cb.cityu.edu.hk/EF/research/research/workingpapers
Yan He, Junbo Wang
Abstract
This paper reviews various studies of forward and reverse stock splits in the areas of motives for splits,
split practices, split effects on firm value, and changes in market activities around splits. It focuses on
three hypotheses and their extended evidence. As our analysis shows, the optimal price/tick hypothesis is
widely supported and applied; the signaling hypothesis is supported by limited empirical results; and the
procedure/structure hypothesis, backed up by some evidence, complements the first and second
hypotheses.
© 2011 by Junbo Wang. All rights reserved. Short sections of text, not to exceed two paragraphs, may be
quoted without explicit permission provided that full credit, including © notice, is given to the source.
Stock Split Decisions: A Synthesis of Theory and Evidence
Yan He
School of Business
Indiana University Southeast
New Albany, Indiana, U.S.A.
Email: [email protected]
Junbo Wang
Department of Economics and Finance
City University of Hong Kong
Tat Chee Avenue, Kowloon tong, Hong Kong
Email: [email protected]
July 21, 2011
Abstract
This paper reviews various studies of forward and reverse stock splits in the areas of
motives for splits, split practices, split effects on firm value, and changes in market
activities around splits. It focuses on three hypotheses and their extended evidence. As
our analysis shows, the optimal price/tick hypothesis is widely supported and applied; the
signaling hypothesis is supported by limited empirical results; and the procedure/structure
hypothesis, backed up by some evidence, complements the first and second hypotheses.
JEL Classification: G10
Key words: stock split, forward split, reverse split, optimal price, optimal tick,
signaling, market structure
Stock Split Decisions: A Synthesis of Theory and Evidence
I. Introduction
Recently, a stock split event captured the attention of the business world. In
January 2010, Berkshire Hathaway declared a 50-for-1 split in its Class B stock shares in
order to acquire a railroad company.1 Such an event, together with the mounting research
findings on stock splits during the 1990s and 2000s, rekindles the interest on stock splits
for decision makers and practitioners such as corporate financial managers, equity
investors, dealers/traders, and regulators.
Most existing studies focus on forward splits because these are far more common
than reverse splits. A forward split allows one share to split into a number of shares,
resulting in more shares but a lower price per share. Financial instruments other than
stocks, such as mutual funds, closed-end funds, and exchange-traded funds (ETFs), can
also split into more shares. A reverse split combines several shares into one share,
resulting in a higher price per share and fewer shares outstanding. For purposes of
studying the effects of splits, a “split event” is said to start with the announcement of the
intention to split. The actual split occurs about two months later when the stock price and
the number of shares are adjusted accordingly. Thus, the “announcement day” and the
“ex-split day” are two important events separated by about 52 days (French and Foster,
2002). Usually, the pre-split period is defined as the time period before the announcement
1
The split, which occurred before Berkshire Hathaway bought Burlington Northern Santa Fe, reduced the
B-share price of Berkshire Hathaway from $3,381 to $67 in order to match the price of Burlington shares
(see Section 2.1.7 of this paper).
1
day; the in-between period comprises the announcement day to the ex-split day; and the
post-split period is the time period following the ex-split day.
Researchers have observed and analyzed various corporate and market activities
before, during, and after splits. They have explored issues such as the motives for splits,
split practices in relation to motives, splits’ effect on firm value, and changes in market
activities around splits. This paper provides a review and summary of stock split
literature and addresses the following questions:

Why do firms split their stocks? Is the rationale to lower share price or to signal good
news? Do other corporate events such as mergers and acquisitions (M&As) and
seasoned equity offerings (SEOs) or external factors such as a change in market
regulation affect the split decision? What makes a fund or an American Depository
Receipt (ADR) split its shares?

Do split practices such as the frequency of splits, the split factor, and signal
credibility relate to the split motives? If so, how?

Does a split event affect firm value? Does the positive abnormal return upon a split
announcement fully reflect good news? Are the announcement effects the same for
stocks with option trading as for stocks without option trading? Will a split enlarge
the investor base? Do the cash flows (dividends and earnings) actually increase after a
split?

How does a split event affect various aspects of trading in the market? Is the market
more or less liquid after a split? Does a split affect bid-ask spread, depth of trading,
and trading volume? Will a split influence return volatility, limit order trading, the
2
number of small trades, price clustering, the profits of market makers, short interests,
and information asymmetry?
In answer to the questions above, current literature offers various explanations.
This paper analyzes the three major hypotheses of existing theories: optimal price/tick,
signaling, and procedure/structure. The optimal price/tick hypothesis claims that splits
return the stock price and the relative tick size to their own optimal range. The signaling
hypothesis argues that splits reveal information about firms’ future performance. The
procedure/structure hypothesis explains how a particular feature/structure/rule can cause
a certain phenomenon in relation to splits. In all, these theories help illustrate the
empirical findings with respect to split motives, split practices, the effect of splits on firm
value, and changes in market activities around splits. Our study is largely in line with the
existing literature involving stock splits and other distributions (see, for example, Baker,
Phillips, and Powell, 1995; Kiymaz, 2009; Michayluk, 2009; Baker, Singleton, and Veit,
2011). The contribution of our study lies in two areas. First, we focus solely on splits,
providing updated and extensive evidence for each of the three major hypotheses.
Second, our analysis shows that while the signaling hypothesis is not as well supported as
we thought, the optimal price/tick hypothesis and the procedure/structure hypothesis are
founded on abundant empirical evidence.
In this paper, we categorize the existing studies according to three major
hypotheses. Specifically, we classify each empirical issue as either supporting or contrary
evidence for a hypothesis. Supporting evidence is defined as an empirical issue that
entirely supports a hypothesis. Contrary evidence is either an empirical issue that entirely
3
contradicts a hypothesis, or a self-conflicting issue that has results both for and against a
hypothesis. We find that the optimal price/tick hypothesis is widely and strongly
supported by empirical results. The signaling hypothesis is less strongly supported. The
procedure/structure hypothesis, backed up by some studies, complements the optimal
price/tick and the signaling hypotheses.
This paper is organized as follows. Section II presents the optimal price/tick
hypothesis and extended evidence. Section III analyzes the signaling hypothesis and
extended evidence. Section IV discusses the procedure/structure hypothesis and extended
evidence. Section V concludes the paper.
II. The Optimal Price/Tick Hypothesis and Extended Evidence
Most of the stocks in the U.S. equity markets trade at a price between $10 and
$200. The minimum price movement (i.e., the tick size) in the NYSE and Nasdaq
markets today is $0.01. Between 1997 and 2000 the minimum tick size was 1/16 of a
dollar whereas before 1997 it was 1/8 of a dollar.
The optimal price/tick hypothesis states that for a given stock both the price and
the relative tick size have an optimal range. Here, relative tick size is defined as the
minimum price movement divided by the stock price. For firms with a price too high and
a relative tick size too low, a split event may help lower the price and increase the relative
tick size to the optimal level. For firms with a price too low and a relative tick size too
high, a reverse split may help move the price and tick back to optimal. In terms of price
levels, forward splitting firms and reverse splitting firms differ dramatically. For instance,
the average share price of forward splitting firms in the United States is about $50 before
4
splits and $28 after splits (Koski, 1998), while firms that execute reverse splits have an
average pre-split price of $1.21 per share (Koski, 2007).
The optimal price/tick hypothesis is a widely accepted and applied theory.
Sections 2.1, 2.2, and 2.3 analyze important findings in relation to this hypothesis. Table
1 provides a summary of these findings as well as information about the author(s), the
year of publication, and the characteristics of the sample. Specifically, Panel A of Table 1
presents the supporting evidence for the optimal price hypothesis; Panel B, the supporting
evidence for the optimal tick hypothesis; and Panel C, the contrary evidence for the
optimal price/tick hypothesis.
[Insert Table 1 about here.]
2.1. Supporting evidence for the optimal price hypothesis
2.1.1. Stock price variations
Although prices vary considerably across stocks, the average price for all stocks
in a market tends to be stable. According to Angel (1997), the median U.S. stock price is
about $40, a typical London stock price is about £5 ($7.50), a typical Hong Kong stock
price is about HK$22 ($2), and a typical U.S. initial public offering (IPO) is priced at
about $10. Moreover, from 1943 to 1994, the average NYSE share price remained almost
the same (ranging from $32 to $31), in spite of the fact that the S&P 500 Composite
Index increased over 15 times during the same period. Therefore, an optimal trading
range does seem to exist for the stock price of a given firm. This view is further analyzed
and strengthened in a value creation framework by Dyl and Elliot (2006). They explain
the substantial variation in the prices of common stocks in the U.S. markets and conclude
5
that a firm not only targets a particular stock price range, but also manages its price level
(by using splits, for example) in order to increase its firm value.
2.1.2. Price before and after splits
Lakonishok and Lev (1987) compare stock prices in two samples: splitting firms
and non-splitting firms. They analyze monthly stock prices five years before and five
years after the month of a split announcement. During the four to five years before the
split, the average prices of the two samples are quite close. However, within four years
before the split, the prices of splitting firms become significantly higher than the prices of
non-splitting firms as the date of the split announcement approaches. During the postsplit period, the average price gap between the two samples quickly narrows, and, in the
fourth month after the split announcement, vanishes. Thereafter, the average prices of the
two samples are almost identical during one to five years subsequent to the split. Hence,
when the price of a firm has risen to a high level, a split event tends to happen in order to
adjust the price to an acceptable or normal level.
2.1.3. Split factor and frequency
Lakonishok and Lev (1987) study the size of a split (i.e., the split factor) and
conclude that the motivation for stock splits is to return the price to a level that is
consistent with that of other firms in the industry and with market averages. They find
that the larger the deviation of a firm’s stock price from the industry and market-wide
average, the greater the split factor. Huang, Liano, Manakyan, and Pan (2008) examine
the frequency of splits. A firm in the frequent split group is defined as one with three or
more splits announced in a five-year period. During the period 1967 to 2000, about 18%
6
of splits are classified as frequent, while the rest are classified as infrequent. Results show
that frequent splits are consistent with the trading range hypothesis (rather than the
signaling hypothesis).
2.1.4. Investor base before and after splits
Practitioners have long claimed that splits broaden a firm’s shareholder base by
increasing the number of investors. A firm may attempt to select a trading range for its
share price that enlarges the firm’s investor base. An increase in the size of the firm’s
investor base may improve analysts’ awareness of the firm and lead to an increase in the
market value of the firm. Brennan and Hughes (1991) document a positive relationship
between the change in the number of analysts following a split and the split factor,
implying that splits attract analysts’ attention. According to Maloney and Mulherin
(1992) and Mukherji, Kim, and Walker (1997), the number of shareholders increases
after a stock split. As Dyl and Elliot (2006) report, the increase in the number of
shareholders of splitting firms is 59% greater than that of non-splitting firms during the
first four post-split years. Further, Maloney and Mulherin (1992), Powell and Baker
(1993/1994), and Dennis and Strickland (2003) find that institutional ownership increases
after splits.2
2.1.5. ADR split
Muscarella and Vetsuypens (1996) examine cases in which ADRs split in the
U.S., whereas the home-country stocks underlying the ADRs do not. Their results support
2
According to Dennis and Strickland (2003), the largest post-split increase in institutional ownership
occurs for firms that have the lowest institutional ownership before the split. In addition, the level of presplit institutional ownership is negatively related to the change in liquidity, and is also negatively related
to the post-split abnormal return.
7
the optimal price hypothesis rather than the signaling hypothesis. If a firm wants to signal
good news, it will split the home-country stock as well as the ADR. Since only the ADRs
split, the purpose of the split is to return the ADR price to an optimal range. Also, there
are no abnormal changes in post-split earnings for firms that split their ADRs.
2.1.6. Fund split 3
Since funds represent an aggregation of firms, various kinds of news from
individual firms are diversified away. Thus, the signaling hypothesis does not apply here.
Fund splits give rise to higher asset value, a larger investor base, positive abnormal stock
return, and higher liquidity. Hence, fund splits support the optimal price hypothesis.
Specifically, Fernando, Krishnamurthy, and Spindt (1999), who explore splits of openend mutual fund shares, find significant increases in net assets and in number of
shareholders after splits. Thus, splits enhance the marketability of mutual funds. Datar
and Dubofsky (1999) study the split announcement effect of closed-end funds. Compared
with individual firms, closed-end funds react no differently to split announcements in
terms of positive abnormal return. Dennis (2003) investigates the liquidity of an ETF
(i.e., the Nasdaq-100 tracking stock that has a 2-for-1 split). Although the post-split
relative bid-ask spread is higher, and the daily turnover is unchanged, frequency, share
volume, and dollar-volume of small trades all increase after the split, indicating that
splitting improves liquidity for small trades.
3
Here “fund” includes open-end funds, closed-end funds, and exchange-traded funds.
8
2.1.7. Split before an M&A
Splits occurring before M&As are intended to make the stock prices of the
acquiring firms more attractive to the acquired firms’ shareholders; that is, they restore
the stock price to an optimal range. For example, before Berkshire Hathaway bought
Burlington Northern Santa Fe, its B shares experienced a 50-for-1 split, reducing the Bshare price of Berkshire Hathaway from $3,381 to $67. Such a 50-for-1 split in
Berkshire’s Class B shares facilitated Burlington shareholders exchanging their stocks for
Berkshire’s. Further, Guo, Liu, and Song (2008) report that acquiring firms are more
likely than non-acquiring firms to split their stocks before making acquisition
announcements, especially when acquisitions are financed by stock and when the deal is
large.
2.1.8. Split before an SEO
Like splits preceding acquisitions, splits occurring before SEOs are intended to
make the stock prices of the equity-issuing firms more attractive to potential investors.
D’Mello, Tawatnuntachai, and Yaman (2003) point out that a split lowers the stock price,
makes the subsequent SEO more marketable to individual investors, and increases the
investor base. Thus, relative to firms that conduct an SEO only, firms that split their stock
shares and then issue stocks sell new shares at a higher price and raise more capital.
2.2. Supporting evidence for the optimal tick hypothesis
2.2.1. Relative tick size variations
Equity markets throughout the world use either a single absolute tick size or a tick
size that is a step function of share price. The absolute tick size approach applies to most
9
markets, including the U.S. markets.4 The London Stock Exchange and the Irish Stock
Exchange have no formal rules, but most stocks trade in penny and, in a few instances,
half-pennies. The step function approach is applied in Tokyo and Hong Kong. At the
Tokyo Stock Exchange, a typical stock under ¥1,000 has a tick size of ¥1; at ¥1,000, the
tick size jumps to ¥10; and at ¥10,000, the tick size jumps to ¥100. Hong Kong has the
most extreme version of a step function, with 10 different tick sizes. Overall, for markets
using either the absolute tick or the step function approach, the relative tick size (i.e., the
tick size divided by the stock price) seems remarkably consistent across countries, with a
median of 25.9 basis points (the median in the U.S. is 33 basis points). Additionally, the
ratio of bid-ask spread to tick size is also consistent, with a median of 3.7 (1.0 in the
U.S.). Therefore, an optimal range of relative tick size may exist for trading in a given
firm’s stock (Angel, 1997). One motivation for splits may be to increase the relative tick
size to desired levels because a larger tick size may result in more profitable marketmaking.
2.2.2. Clustering before and after splits
When the absolute tick size in dollars is held constant, the larger the stock price,
the higher the rounding frequencies on “0”s and “5”s, reducing the negotiation costs for
transactions (see Harris, 1991). A forward split leads to a lower stock price, while the
absolute tick size in dollars remains the same. Thus, the clustering on “0”s and “5”s is
expected to decrease after splits in relation to a bigger relative tick size. As French and
4
According to Angel (1997), the convention of 1/8 of a dollar as the tick size on the NYSE dates back to
1915, when the NYSE switched from quoting prices as a percentage of par value to quoting in dollars. Prior
to 1915, the minimum price variation had been 1/8 of a percent, a practice that dates back at least as far as
1817 when NYSE trading was formalized. The 1/8 of a dollar tick size lasted until 1997 in the U.S.
markets, when tick size was reduced to 1/16 of a dollar. In 2000, tick size was further reduced to a penny.
10
Foster (2002) show, post-split clustering is lower than pre-split clustering for NYSE,
AMEX, and NASDAQ stocks. Moreover, these results remain valid for both the $1/8tick-size period and the $1/16-tick-size period.
2.2.3. Limit orders before and after splits
Limit orders tend to increase as the relative tick size becomes larger. As Angel
(1997) finds, limit orders on the NYSE are used less frequently in stocks with a smaller
relative tick size. Since the relative tick size increases after splits, limit orders tend to
increase. Easley, O’Hara, and Saar (2001) document an increase in the number of
executed limit orders after splits, though this effect is overshadowed by the increase in
the costs of executing market orders due to the larger percentage spreads.
2.2.4. Profits to market makers before and after splits
Due to the bigger relative tick size after splits, the percentage bid-ask spread
increases, trading errors reduce, and negotiation costs diminish. On the one hand, postsplit transactions become more costly to investors due to larger percentage bid-ask
spreads.5 On the other hand, they become more profitable to market makers/brokers by
lowering the costs of market making, increasing the incentive of market makers to
provide inside quotes, and increasing dealers’ revenues. Schultz (2000) finds that the
percentage effective spread increases after splits, whereas the percentage of error trades
declines following splits. Gray, Smith, and Whaley (2003) document bigger revenues for
5
The percentage bid-ask spread increases following stock splits. See Conroy, Harris, and Benet (1990);
Schultz (2000); Dennis (2003); and Gray, Smith, and Whaley (2003).
11
market makers after splits.6 Their results show that the average daily revenue is $24,360
before the announcement of the split and $34,330 after the split, an increase of 40.9%.
Thus, stock splits appear to generate considerable additional revenue for market makers.
2.2.5. Small investors/trades before and after splits
According to the broker promotion argument, the increase in relative bid-ask
spread after a split induces brokers to promote splitting stocks to small investors. Thus, a
positive cross-sectional relation may exist between changes in the spread and changes in
the frequency of small trades around the ex-split dates. Furthermore, this relation may be
attenuated subsequent to decimalization (i.e., the tick size reduced to one penny). In line
with the broker promotion argument, Kadapakkam, Krishnamurthy, and Tse (2005) show
that during the $l/8-tick-size period, the relative spread increases significantly after the
ex-split day, the average buy order size decreases, the frequency of small transactions
increases, and the abnormal returns around the ex-split day are positive and significant.
During the decimal pricing period, these changes are smaller in magnitude, and the
abnormal returns around the ex-split day are not significant. Baixauli (2007) finds
significant abnormal returns around the ex-split day for split factors greater than 2 and
attributes the abnormal returns to an increase in the number of small investors.
2.2.6. Volatility before and after splits
For forward splits, the volatility of daily stock returns increases by an average of
35% subsequent to ex-split days (Ohlson and Penman, 1985). This increase occurs as a
6
They introduce a measure of market-making revenue as the volume-weighted effective spread on a
particular day times the number of shares traded during the day, i.e., the product of one-half of the volumeweighted effective spread and the daily trading volume in shares. Here, one-half of the effective bid/ask
spread can be interpreted as either the investor’s trading cost per share or the market maker’s revenue per
share.
12
jump on the ex-split day, and the new higher level of return volatility persists over one
year. There is no evidence of a gradual increase in volatility before the ex-split day.
Further, Dravid (1987) extends the volatility studies to all types of stock distributions,
including smaller splits and stock dividends; Sheikh (1989) documents the ex-date
increase in implied return variances for stocks with options; Koski (1998) shows that
variance increases after splits even with control of bid-ask spread and price discreteness;
and Kryzanowski and Zhang (1996) report similar volatility behavior for stocks traded on
the Toronto Stock Exchange. For reverse splits, the daily return volatility decreases by
25% after ex-split days (Koski, 2007). The explanations for the volatility changes due to
forward or reverse splits are largely related to the following issues within the framework
of the optimal tick hypothesis: the increase in relative tick size or percentage bid-ask
spread after forward splits, the increase in trades or small trades after forward splits, and
the decrease in relative tick size or percentage bid-ask spread after reverse splits.
First, the increases in relative tick size and relative bid-ask spread have limited
power in explaining the increase in volatility after forward splits. Dubofsky (1991)
observes the volatility change around splits on both the AMEX and the NYSE. For the
AMEX stocks, post-split volatility increases when daily returns are used to compute
volatility, but such an increase disappears when using weekly returns. Since weekly
returns do not contain much price discreteness and bid-ask bounce effects, the volatility
does not change after splits. Thus, the increase in daily return volatility on the AMEX can
13
be attributed to market microstructure factors. For the NYSE stocks, however, post-split
volatility always increases, regardless of whether daily or weekly returns are computed.7
Second, the increase in trades or small trades may help explain the volatility
increase after forward splits. As Lamoureux and Poon (1987) point out, splits give rise to
increases in both the number of transactions and the number of shares traded, thereby
increasing the volatility of the price series. According to Chen and Wu (2009), small
trades increase significantly after splits, and the increase in return volatility is strongly
related to the increase in small trades.8 Moreover, the results are robust to different
measures of trading activity and return volatility.
Third, decreases in relative tick size and relative bid-ask spread may partially
explain the decrease in volatility after reverse splits. Koski (2007) shows that market
microstructure factors may affect volatility, especially for lower priced stocks. Based on
observed daily returns, volatility decreases by 25% after reverse splits. Controlling for
bid–ask bounce, volatility still decreases for stocks with prices above $5.00. However, for
stocks priced below $2.00, volatility increases slightly. The portion of observed volatility
attributable to microstructure effects declines as the stock price increases and as the
relative tick size decreases. Thus, for stocks with high prices, microstructure effects may
7
Some studies find that tick size or bid-ask spread has no power in explaining the volatility increase.
Ohlson and Penman (1985) test price discreteness as a cause of post-split variance increase by computing
the percent of stocks with variance increases by share price level. They find that the portion of stocks with
variance increases does not increase monotonically as price level drops. Koski (1998) removes the effect of
bid-ask bounce by computing bid-to-bid (and ask-to-ask) daily (and weekly) returns and finds that postsplit variance still increases. French and Foster (2002) document that daily return variances increase
significantly following stock splits and that the results are generally unaffected by the 1997 tick size
reduction from 1/8 to 1/16 of a dollar.
8
Here small trades are defined as orders with a number of transacted shares less than or equal to 500
shares.
14
not be responsible for the change in volatility after reverse splits; for stocks with low
prices, microstructure effects may help explain the decrease in volatility.
2.3. Contrary evidence regarding the optimal price/tick hypothesis
2.3.1. Liquidity before and after splits
Greater liquidity may arise in certain price ranges than in others. If splits are to
restore the price/tick to an optimal range, they may give rise to more liquid markets for
trading stocks. However, existing studies present confounding empirical results.
Therefore, whether market liquidity enhances or worsens after splits is still unclear.
According to the liquidity improvement argument, forward splits lead to a lower
stock price per share, an enlarged equity ownership base, an increased number of small
trades (particularly small buy orders submitted by individuals), and a more liquid market
(Baker and Gallagher, 1980; Baker and Powell, 1993; Muscarella and Vetsuypens, 1996).
Also, Lin, Singh, and Yu (2009) support the argument for post-split liquidity
improvement by examining trading continuity, using daily data during 1975 to 2004.9
They find that the incidence of no trading decreases and that market liquidity improves
following splits, implying a decline in latent trading costs and a reduced cost of equity
capital. Furthermore, the post-split improvements in liquidity are correlated with the presplit announcement returns, suggesting nontrivial economic benefits. As for reverse
splits, although they lead to a higher price per share, they may also improve liquidity.
9
Trading continuity reflects liquidity, whereas trading discontinuity or non-trading reflects illiquidity. The
degree of trading discontinuity for each stock is measured as the standardized turnover-adjusted number of
days with zero trading volume over the prior 12 months.
15
Han (1995) finds a decrease in bid-ask spread, an increase in trading volume, and a
reduction in the number of non-trading days after reverse splits.
According to the liquidity reduction argument, percentage bid-ask spreads or
transaction costs increase and trading volume decreases after splits. For the larger
percentage bid-ask spread or smaller depth, Lin, Singh, and Yu (2009) report that both
Roll’s (1984) spread and the Gibbs estimate of Roll’s spread increase significantly
following the splits, and Gray, Smith, and Whaley (2003) show that stock splits adversely
affect the trading quality that incorporates both spread and depth.10 For the reduced
trading volume, Copeland (1979), Murray (1985), and Lamoureux and Poon (1987)
report a decrease in dollar trading volume after splits, and Lakonishok and Lev (1987)
document both a pre-split abnormal increase in volume and a post-split decrease in
volume.11
III. The Signaling Hypothesis and Extended Evidence
The signaling hypothesis argues that a firm’s split announcement conveys inside
information about the firm’s future performance to outside investors. A forward split
reveals good news, while a reverse split reveals bad news. Unlike the optimal price/tick
hypothesis, however, the signaling hypothesis is supported by only a limited number of
10
Gray, Smith, and Whaley (2003) introduce a market quality index measure that is the average depth on
one side divided by the product of the percentage bid-ask spread and the split adjustment. The higher the
index, the more liquid the market is. Their results show that the quality index falls from 8.19 in the preannouncement period to 5.16 in the post-split period, a decrease of 37.1%.
11
Lakonishok and Lev (1987) use a turnover rate as a measure for volume, calculated as the monthly
number of shares traded relative to the number of shares outstanding at the same date for a given stock.
From five years up to one year before the announcement, the average turnover rates of the test and control
samples were almost identical. Significant differences in turnover rates between the split and control
samples appear twelve months before the split announcement and, in particular, eight months before it.
These differences peak in the split announcement month and vanish by the second month following the
split announcement (i.e., around the ex-split day).
16
findings. Section 3.1 presents the supporting evidence and Section 3.2 shows the contrary
evidence. Table 2 presents a summary of the evidence supplemented by information
about the author(s), year of publication, and sample characteristics.
[Insert Table 2 about here.]
3.1. Supporting evidence for the signaling hypothesis
3.1.1. Split announcement effect
For forward splits, Grinblatt, Masulis, and Titman (1984) document that an
announcement of a stock split generates a positive abnormal return of about 3% and may
thus signal good news about the firm’s future performance. Brennan and Copeland
(1988) use the number of shares that will be outstanding after a split as a signal to explain
the announcement effect. Szewczyk and Tsetsekos (1993) demonstrate an inverse
relationship between managerial ownership and abnormal announcement returns. Arbel
and Swanson (1993) find that the magnitude of the announcement effect is greater for
information-poor stocks than information-rich stocks, where information richness is
measured by the number of analysts making annual estimates of firm earnings. For
reverse splits, Woolridge and Chambers (1983) show that the market reacts unfavorably
to reverse-split announcements, implying that the announcement of a reverse split sends
out a signal of bad news. Peterson and Peterson (1992) report that discretionary reverse
splits are associated with negative announcement effects, where discretionary reverse
splits are defined as reverse splits initiated by the informed party (i.e., management)
rather than the uninformed party (e.g., an exchange).
17
3.1.2. Infrequent split
According to Huang, Liano, Manakyan, and Pan (2008), about 82% of splits
between 1967 and 2000 are classified as infrequent splits.12 For these infrequent splitters,
the announcement effect is significantly related to the split factor, dividend yield, and
firm size. Thus, a split event, which happens rarely for a firm, may signal to outside
investors a firm’s good performance in the future.
3.1.3. Split factor
The size of the split (or split factor) may convey information about future
performance. McNichols and Dravid (1990) point out that earnings forecast errors
measure management's private information. They find that the difference between actual
and forecasted earnings following a split tends to be directly related to the size of the split
factor. So, firms may choose their split factors to signal management’s private
information about future earnings. Conroy and Harris (1999) examine split factors, split
announcement returns, and revisions of analysts’ earnings forecasts. They find that a
firm’s past history of splits plays a crucial role in the design and effect of current splits.
Most of the time, current splits are seemingly designed to return the stock price to the
level achieved after the last split. However, if a split factor is designed to achieve an even
lower price than the last split, both investors and analysts interpret this as a signal of
especially positive information. Thus, the current split factor relative to the last split (or
the expected level of share price after a split) plays an important information role.
12
A firm in the infrequent stock split group is a firm with two or fewer splits announced in five years, and a
firm in the frequent stock split group is a firm with more than two splits announced in five years.
18
3.1.4. Credibility of split signal
The split procedure itself does not cause any change in the total wealth of each
investor or the firm. Instead, it signals something about the firm’s future cash flows and
performance. To make the signal credible, costs must be associated with the signal.
Otherwise, firms that do not expect good performance in the future can easily split their
shares to manipulate their stock prices. As the retained earnings argument posits, a firm
that chooses to account for its stock share distribution by voluntarily reducing retained
earnings is presumed to be signaling management's confidence in its future earnings
(Grinblatt, Masulis, and Titman, 1984; Rankine and Stice, 1997).13 Bechmann and
Raaballe (2007) support the argument of retained earnings by investigating stock splits on
the Copenhagen Stock Exchange (CSE). They find that the announcement effect of stock
splits is closely related to the change in a firm’s dividend payout policy. When a split
announcement proceeds without an increase in total cash dividends, no significant
announcement effect is observed. This is because the retained earnings are unchanged,
and the signal revealed by the announcement is not linked with any cost. In contrast,
when a split is announced together with an increase in total cash dividends, the signal is
costly to the firm and credible to outside investors. In this case, a highly significant
abnormal return of 3.51% is observed at the split announcement.
13
Crawford, Franz, and Lobo (2005), however, criticize the retained earnings argument. They point out that
the findings in support of the retained earnings argument can be attributed to specification and
measurement choices that bias the results in favor of the argument. Support for the argument becomes
weaker when the sources of this bias are removed.
19
3.1.5. Split of stocks with options
Abnormal positive returns at the split announcement tend to be significantly lower
for optioned as opposed to non-optioned stocks. Chern, Tandon, Yu, and Webb (2008)
find that abnormal returns are significantly lower for NYSE/AMEX optioned stocks than
for non-optioned stocks, after controlling for market returns, capitalization, book-tomarket ratio, and trading volume. Their findings are consistent with the explanation that
prices of optioned stocks embody more information, thus diminishing the information
impact of the stock split announcement. Therefore, split announcements do reveal inside
information to outside investors. The signaling effect is stronger for stocks without
options than for stocks with options.
3.2. Contrary evidence regarding the signaling hypothesis
3.2.1. Post-split earnings and dividends
If forward splits signal good news about future cash flows, post-split earnings and
dividends should increase. This view is supported by most previous studies on earnings
and dividends, but questioned by some recent findings.
The supporting evidence regarding post-split earnings and dividends is illustrated
as follows. Lakonishok and Lev (1987) analyze growth in earnings and cash dividends
five years before and five years after the month of announcement. They find that splitting
firms enjoy unusually favorable earnings performance during the pre-split period relative
to similar, non-splitting firms. The above-normal earnings growth of splitting firms
persists in the first post-split year although the test-control difference is considerably
smaller than that in the pre-announcement years. The pre-announcement data indicate
20
that the dividend growth rates of splitting firms are higher than those of control firms. But
the differences in the dividend growth rates between the test and control samples are
substantially smaller than those of the earnings growth rates. For the 5-year period
following the split announcement, dividend growth for the test sample is higher than for
the control sample. All in all, earnings growth tends to stabilize subsequent to the
abnormal pre-split growth, and cash dividends prospects tend to improve after splits.
Pilotte and Manuel (1996) report that when firms split their stock multiple times, the
abnormal return at the announcement of the second split is directly proportional to the
earnings surprise following the first split. Tawatnuntachai and D’Mello (2002) study the
industry response to a firm’s split announcement. Their results show positive and
significant abnormal returns for non-splitting firms in the industry at the announcement
of a firm’s split. Also, these non-splitting firms’ earnings increase significantly and the
earnings changes are positively related to the stock price reactions. Thus, splits may also
signal good news about the future performance of the industry.
Some recent studies on post-split dividends and earnings challenge the signaling
view. Nayak and Prabhala (2001) investigate whether splits signal information about
future dividends; that is, whether the positive abnormal return around splits can be
attributed to the implied promise of higher dividends in the future. They examine
dividend-paying firms and non-dividend-paying firms and develop econometric methods
that obtain the part of value effects due to dividend information. Results show that a large
portion (46%) of valuation effects around splits cannot be attributed to dividend
information. Huang, Liano, and Pan (2006) examine whether splits contain information
21
about future profitability, measured as future earnings change, future earnings, or future
abnormal earnings. Little evidence is found that splits are positively related to future
profitability. Rather, splits are in general negatively related to profitability in years
subsequent to the split announcement, except for dividend-paying firms with a split factor
less than 0.5. The conclusion is that splits are not useful signals of a firm’s future
earnings prospects.
3.2.2. Post-split stock return
If forward splits reveal good news about firms’ future performance, then the postsplit abnormal stock return should be positive and significant, and the opposite should be
true for reverse splits. This view is supported by plenty of studies on stock returns, but
criticized in some recent findings.
The supporting evidence regarding post-split stock returns follows. Ikenberry,
Rankine, and Stice (1996) document higher post-split stock returns for splitting firms
than for non-splitting firms, based on the data from 1975-1990. Desai and Jain (1997)
study the long term post-split return for both forward and reverse splits, based on data
from 1976 to 1991. For forward splits, while the average abnormal return of the
announcement month is about 7.1%, the 1-year and 3-year buy-and-hold abnormal
returns after the announcement month are 7% and 12%, respectively. For reverse splits,
while the average abnormal return of the announcement month is -4.6%, the 1-year and
3-year abnormal returns after the announcement month are -11% and -34%, respectively.
The positive drift after forward splits and the negative drift after reverse splits imply that
the market under-reacts to both forward and reverse split announcements during the
22
announcement month. In line with the argument of market under-reaction to split news,
Ikenberry and Ramnath (2002) report a drift of 9% abnormal return in the year following
a split announcement and find that splitting firms have a low propensity to experience a
contraction in future earnings, based on data from the period 1988 to 1997. They also
mention market under-reaction for other self-selected corporate events such as reverse
splits, spin-offs, dividends, equity issuance, and mergers. Finally, Kim, Klein, and
Rosenfeld (2008) examine the long-run performance for firms with reverse splits during
the sample period 1962 to 2001. They find significant negative abnormal returns over the
3-year period after the month of a reverse split. Martell and Webb (2008) state that in the
three to five months following reverse splits, the performance of reverse-splitting stocks
in poor market conditions is less negative than in good market conditions. Overall, the
above-referenced supporting evidence suggests informational inefficiency; that is, the
market tends to under-react to split news at the announcements.
Some studies on post-split returns confront the signaling view and argue for
market efficiency. Byun and Rozeff (2003) measure the post-split performance of a large
stock sample over a long period (i.e., 12,747 stock splits from 1927 to 1996). The authors
use two different methods to measure abnormal returns: first, size and book-to-market
reference portfolios with bootstrapping, and, second, calendar-time abnormal returns
combined with factor models. For splits 25% or larger, neither method finds post-split
returns significantly different from zero. Thus, the evidence of market inefficiency with
respect to splits is neither pervasive nor compelling. In other words, stock splits are not
followed by abnormally positive returns and investors do not systematically under-react
23
to stock splits at the announcements. Boehme and Danielsen (2007) explore the
relationship between stock splits and subsequent long-term returns during the period
1950 to 2000. They find that firms do not exhibit positive long-term post-split returns;
that is, significant positive returns after the announcement day do not persist after the
actual day of the stock split. Hwang, Keswani, and Shackleton (2008) examine the longrun reaction to split announcements by differentiating anticipated announcements from
surprise announcements. Credibility explains why a post-split performance gap exists
between predicted and unanticipated splits. Firms that announce anticipated splits enjoy
much stronger performance before their announcement. The good news that they want to
convey through their splitting decision is viewed credibly. Thus, the market reacts
efficiently to an anticipated split announcement and not much drift is observed later. In
contrast, firms that announce surprise splits have lower credibility. This translates into an
under-reaction to announcements at first and, later, a pronounced positive drift.
3.2.3. Information asymmetry before and after splits
According to the signaling hypothesis, firms split their stock shares to reveal
inside information about future performance to outside investors; in other words, a stock
split serves to reduce information asymmetry between insiders and outsiders. However,
studies find either no change or an increase in information asymmetry after splits,
contradicting the signaling hypothesis. Desai, Nimalendran, and Venkataraman (1998)
examine bid-ask spread and its components before and after splits, based on Nasdaq
stocks during the years 1983 to 1990. They use both the bid-to-bid daily prices and the
George, Kaul, and Nimalendran (1991) method to decompose the bid-ask spread. Results
24
show that the percentage spread, the order processing component, and the adverse
information component all increase after splits. Easley, O’Hara, and Saar (2001) find no
evidence consistent with the hypothesis that stock splits reduce information asymmetry.
They show that after the split, both uninformed and informed trading activities increase.
D’Mello, Tawatnuntachai, and Yaman (2003) compare firms that conduct stock splits and
then SEOs with firms that conduct SEOs only. The authors find no difference in equity
announcement and issue period returns between the split-and-then-SEO firms and the
SEO-only firms, suggesting that firms do not split to reveal information or to reduce
adverse information.
3.2.4. Short interest before and after splits
If forward splits signal positive information about firms’ future performance, then
short interest is expected to decline at the split announcement. However, such a view is
not backed up by empirical findings. Kadiyala and Vetsuypens (2002) examine the
change in short interest in relation to splits during the period 1990 to 1994. Contrary to
the signaling hypothesis, their results show that short interest does not decline around
splits and that the change in short interest has considerable variation across different
firms.
IV. The Procedure/Structure Hypothesis and Extended Evidence
Although the optimal price/tick hypothesis and the signaling hypothesis are two
popular theories, they cannot explain all empirical findings related to splits. Thus, a third
hypothesis emerges: the procedure/structure hypothesis. It explores the features of the
split procedure, the market structure of trading around splits, and the regulatory rules that
25
affect splits. This hypothesis examines how a particular feature/structure/rule can cause a
certain empirical phenomenon in relation to splits. The hypothesis provides systematic
explanations for the following phenomena: positive return between the announcement
day and the ex-split day, negative return on the record day, positive return on the ex-split
day, larger percentage bid-ask spread after splits, higher volatility after the ex-split day,
and
split
due
to
price
deregulation.
Among
the
evidence
supporting
the
procedure/structure hypothesis, three findings (positive return on the ex-split day, higher
volatility after the ex-split day, and split due to price deregulation) also back up the
optimal price/tick hypothesis. Additionally, one finding (positive return between the
announcement day and the ex-split day) also confirms the signaling hypothesis. Table 3
provides a summary of the above-mentioned issues as well as information about
author(s), year of publication, and sample characteristics.
[Insert Table 3 about here.]
4.1. Supporting evidence for the procedure/structure hypothesis
4.1.1. Positive return between the announcement day and the ex-split day
As the signaling hypothesis posits, a firm’s announcement of a forward split
conveys good news to the market, and its stock price responds positively on the
announcement day. However, incorporation of the good news seems slow, and a positive
abnormal return between the announcement day and the ex-split day is observed. This
positive “drift” can be explained by the procedure/structure hypothesis. As Boehme and
Danielsen (2007) point out, the abnormal return is primarily confined to the period
between the announcement day and the ex-split day, and there is no evidence of any
26
multi-year drift. Thus, the drift pattern between the announcement day and the ex-split
day is inconsistent with a behavioral-based under-reaction explanation. More likely,
market frictions cause the short-term delay in price response to new information.14 In
addition, results show that the price delay is correlated with the positive abnormal return
between the announcement day and the ex-split day.
4.1.2. Negative return on the record day
Nayar and Rozeff (2001) report a negative abnormal stock return of about 1%, on
average, occurring near the record days of stock splits. This negative return is mainly due
to the trading inconvenience associated with the record day process, a phenomenon
consistent with the procedure/structure hypothesis. According to Nayar and Rozeff
(2001), a split event involves all the following days: (1) announcement/declaration day;
(2) record day; (3) payment day, (4) the business day after that, ex-split day; (5) the due
bill redemption day (three business days after the payment day); and (6) the next business
day, the settlement day of the when-issued shares. Figure 1 illustrates the relevant days
around a split event. If a trader buys shares before the record day, new shares are sent
directly to the trader by the company on the payment day. If a transaction happens after
the record day and before the ex-split day, the seller is obligated to remit the new shares,
when received, to the buyer (or the broker of the buyer). The due bill provides the legal
documentation of this obligation. On the ex-split day, the new stock replaces the un-split
stock in trading. The due bill redemption day is the last day by which the new stock must
14
The market friction measure, price delay, is based on Hou and Moskowitz (2005): market frictions impair
the speed with which new information is incorporated into the securities’ post-announcement prices, and
for most stocks, market frictions are resolved in less than one month.
27
be delivered to the buyer. Therefore, the trading inconvenience arises mainly from a
specific procedure: all trading of the old stock between the record day and the ex-split
day occurs in un-split shares with attached due bills signed by the seller. Because of the
inconvenience, the price of un-split shares usually drops around the record day.
[Insert Figure 1 about here.]
4.1.3. Positive return on the ex-split day
The ex-split day is the day when the actual split takes place. If the market is
efficient, no price effect would be expected to be observed on this day as no revelation of
information is associated with this event. However, empirical studies typically show a
significantly positive abnormal return on the ex-day of splitting stocks. According to the
optimal tick hypothesis, this positive abnormal return is related to the increase in small
trades due to the broker promotion argument (see section 2.2.5). In line with the
procedure/structure hypothesis, however, the explanations for this positive return are
mainly based on the tax effect, the market microstructure effect, and the record-dayinconvenience effect. First, Lamoureux and Poon (1987) offer explanations based on the
tax effect. They argue that the lower stock price after a split may attract more investors
who prefer capital gain; hence, clientele shifting may occur. Therefore, the positive return
on the ex-split day is not a reflection of market valuation. Rather, it is due to the
clientele-shifting-related price pressure. Second, Maloney and Mulherin (1992) provide
explanations based on the market microstructure effect. They find that the ex-day return
is dominated by an asymmetric increase in the ask price compared to the bid. In the 11
trading days after the split execution, trades of splitting stocks tend to congregate at ask
28
prices. The results imply a temporary increase in buy orders around the ex-split day. This
order flow imbalance induces an above average number of reported closing prices at the
ask, and this phenomenon is responsible for a major fraction of the ex-day abnormal
return. In other words, the positive return on the ex-split day is due to the order-flowimbalance-related price pressure, and the source of this pressure resides in the increase in
both the shareholder base and the institutional investors. Third, Nayar and Rozeff (2001)
give explanations based on the record-day-inconvenience effect. That is, the abnormal
positive returns on the ex-split days arise in part from the abnormally low prices of unsplit shares caused by the trading inconvenience around the record days. As their results
show, the more negative the return on the record day, the more positive the return on the
ex-split day.
4.1.4. Higher percentage bid-ask spread after splits
As the stock price declines after forward splits, the relative tick size and the
percentage bid-ask spread increase. Thus, the higher percentage spread may simply result
from the spread-setting function of market makers. Huang and Weingartner (2000) study
the relationship between the bid-ask spread and other trading variables before and after
splits. The bid-ask spread is regressed against price, volatility, volume, and the number of
trades, and the coefficients before splits are compared with those after splits. Results
show that the intercept and slope coefficients are the same before and after splits. Thus,
when a firm splits its shares to an optimal price range, market makers regard it as a nonevent and do not change their spread-setting behavior. Since the percentage spread and
the price are negatively related, the higher percentage spread simply corresponds to the
29
lower price after splits, based on the same spread-setting function. Thus, the higher
percentage spread after splits may only reflect the consistent spread-setting behavior in a
lower price environment, rather than worsened liquidity or market quality.
4.1.5. Higher volatility after the ex-split day
As noted in Section 2.2.6, the optimal tick hypothesis has already provided some
explanations for the higher volatility subsequent to the ex-split day. Here, the
procedure/structure hypothesis helps further explain the volatility issue based on a
specific feature of splits: when-issued trading. As Angel, Brooks, and Mathew (2004)
point out, the higher volatility occurring after the ex-split day follows a period of lower
volatility during the when-issued trading preceding the ex-split day. This artificial
increase accounts for the unexplained portion of the greater volatility at the ex-split day.
When-issued trading takes place over a short period from the record day to the ex-split
day, wherein a firm may trade when-issued shares at the post-split price level. The
introduction of when-issued (when, as, and if issued) trading provides an opportunity for
traders to elect one of two markets for trades: the un-split shares trading at one price
level, or the when-issued shares trading at the post-split price level. The introduction of
lower priced, when-issued shares attracts small-volume traders and separates the market
into two trading sets. When measuring the volatility of shares before the split, volatility is
lower for both the un-split shares and the when-issued shares as compared with matching
firms that do not trade when-issued shares. After the split, the small-volume traders
return to trading in the regular way with a single price level, and the volatility measure
increases accordingly.
30
4.1.6. Split due to price deregulation
During the 1990s and 2000s, some equity markets such as Switzerland and Japan
loosened their regulations on the legal minimum par value for each share of stock. As the
market structure changes (i.e., the minimum par value is reduced), firms tend to split their
stock shares to get to a new optimal price range and attract small investors. This finding
supports both the optimal price hypothesis and the procedure/structure hypothesis. Kunz
and Rosa-Majhensek (2008) examine a group of splits in Switzerland occurring within
one year after the legal minimum par value reductions in 1992 and 2001. Each sample
stock has to have at least one share class at the legal minimum par value before the
change in the regulation. The results—no significant post-split abnormal returns observed
in either the short or long term for the sample group—show that the splits occurred
mainly in reaction to the deregulation in minimum par value rather than to signal future
performance. Greenwood (2009) investigates the split bubble caused by deregulations in
Japan during the late 1990s and early 2000s.15 Before the deregulations, more than 95%
of the splits in Japan were in ratios of 1.3-for-1 or less, and the average split ratio in 1995
was 1.15-for-1. After the deregulations, split ratios greater than or equal to 2-for-1
became more prevalent, and the average split ratio in 2004 was about 10-for-1. Thus, it
follows that firms split their shares to return the price to a new optimal level as a response
to the change in regulatory requirements.
15
According to Greenwood (2009), two deregulation events made it easier for Japanese firms to split. First,
on October 1, 1999, the Tokyo Stock Exchange (TSE) changed the rules governing brokerage
commissions, which had been set at fixed rates for small transactions. Following the deregulation, severe
price competition among online brokers lowered trading fees by as much as 90%. Second, the law requiring
net assets per share to remain above 50,000 Yen was repealed in 2001, allowing firms to split to lower
prices. Therefore, in response to the two deregulations, some firms began splitting at higher ratios, with the
intention of improving liquidity and attracting small investors.
31
V. Conclusions
The literature offers various explanations for stock splits. This paper investigates
the three major hypotheses (optimal price/tick, signaling, and procedure/structure)
advanced to explain the phenomena surrounding stock splits. Based on our review and
analysis of numerous studies published over the past several decades, the optimal
price/tick hypothesis and the procedure/structure hypothesis appear largely supported by
empirical findings, but research on the signaling hypothesis offers inconclusive results.
Theoretical and empirical studies on stock splits provide some insightful
guidelines for corporate decision makers, investors, traders, and regulators in the areas of
motives for splits, split practices, split effects on firm value, and changes in market
activities around splits. The major findings in each area follow.

Split incentive. The main motivation for stock splits is to return the share price or the
relative tick to an optimal range. In a manner analogous to stocks, a fund or an ADR
may also split its shares to return the price to an optimal level. Corporate events, such
as M&As and SEOs, may be related to a decision to split, and a split tends to occur
before these events in order to adjust the share price. Stock splits may also intend to
signal the good news about firms’ future performance, but this view is challenged by
some findings on post-split earnings, dividends, stock return, information asymmetry,
and short interests. Finally, external factors, such as a change in market regulation,
may affect the decision to split at the aggregate level and cause a wave of split events.

Split practices. Split practices are related to various split incentives. Findings on
frequency of split and split factor back up both the optimal price hypothesis and the
32
signaling hypothesis. That is, a firm’s choices with respect to the number of times it
splits its shares and the split factor each time reflect a motivation to return the price to
the optimal level and to signal the good news about future performance. Findings on
signal credibility support the signaling hypothesis. That is, the cost to a firm, such as
the increase in total cash dividends associated with a split, makes the signal credible.

Split effects on firm value. A split event influences firm value in several ways. The
share price tends to increase upon a split announcement. The investor base tends to
become larger after a split, which may help increase firm value. When there is option
trading in a stock, however, the price effect of a split announcement is reduced.

Changes in market activities around splits. A split event affects various aspects of
trading in the market. The bid-ask spread in percentage terms tends to increase, and
the depth tends to diminish. Further, return volatility increases on the ex-split day,
limit order trading tends to increase after splits, the number of small trades may
increase, price clustering may decline, and the profits of market makers may increase.
Short interests and information asymmetry appear not much affected by splits. Some
specific features of processing the split, such as the record day and the ex-split day,
may cause temporary price effects in the market, but they are different from the
valuation effect at the announcements of splits.
Given all the above findings, two puzzles remain. First, in terms of split effects on
firm value, it is unclear whether post-split dividends and earnings actually increase or
decrease and whether post-split abnormal return exists in the long term. Second, in terms
of split effects on market activities, uncertainty persists with respect to whether liquidity
33
improves or deteriorates after splits. These two puzzles offer opportunity for future
studies.
34
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Costs,” Journal of Empirical Finance 10, 271-303.
Greenwood, R., 2009, “Trading Restrictions and Stock Prices,” Review of Financial
Studies 22, 509-539.
Grinblatt, M., R. Masulis, and S. Titman, 1984, “The Valuation Effects of Stock Splits
and Stock Dividends,” Journal of Financial Economics 13, 461-490.
Guo, S., M.H. Liu, and W. Song, 2008, “Stock Splits as a Manipulation Tool: Evidence
from Mergers and Acquisitions,” Financial Management 37, 695-712.
Han, K.C., 1995, “The Effects of Reverse Splits on the Liquidity of the Stock,” Journal
of Financial and Quantitative Analysis 30, 159-169.
36
Harris, L.E., 1991, “Stock Price Clustering and Discreteness,” Review of Financial
Studies 4, 389-415.
Hou, K. and T. Moskowitz, 2005, “Market Frictions, Price Delay, and the Cross-Section
of Expected Returns,” Review of Financial Studies 18, 981–1020.
Huang, G., K. Liano, H. Manakyan, and M. Pan, 2008, “The Information Content of
Multiple Stock Splits,” The Financial Review 43, 543-567.
Huang, G., K. Liano, and M. Pan, 2006, “Do Stock Splits Signal Future Profitability?”
Review of Quantitative Finance and Accounting 26, 347-367.
Huang, R.D. and H.M. Weingartner, 2000, “Do Market Makers Suffer from Splitting
Headaches?” Journal of Financial Services Research 17, 105-126.
Hwang, S., A. Keswani, and M.B. Shackleton, 2008, “Surprise vs. Anticipated
Information Announcements: Are Prices Affected Differently? An Investigation in
the Context of Stock Splits,” Journal of Banking and Finance 32, 643-653.
Ikenberry, D.L. and S. Ramnath, 2002, “Underreaction to Self-Selected News Events:
The Case of Stock Splits,” Review of Financial Studies 15, 489-526.
Ikenberry, D., G. Rankine, and E. Stice, 1996, “What Do Stock Splits Really Signal?”
Journal of Financial and Quantitative Analysis 31, 357-375.
Kadapakkam, P., S. Krishnamurthy, and Y. Tse, 2005, “Stock Splits, Broker Promotion,
and Decimalization,” Journal of Financial and Quantitative Analysis 40, 873-895.
Kadiyala, P. and M.R. Vetsuypens, 2002, “Are Stock Splits Credible Signals? Evidence
from Short-Interest Data,” Financial Management 31, 31-50.
Kim, S., A. Klein, and J. Rosenfeld, 2008, “Return Performance Surrounding Reverse
Stock Splits: Can Investors Profit?” Financial Management 37, 173-192.
Kiymaz, H., 2009, “Stock Splits, Stock Dividends, and Dividend Reinvestment Plans,” in
H. Kent Baker (Ed.), Dividends and Dividend Policy, 385-403. Hoboken, NJ: John
Wiley & Sons.
Koski, J.L., 1998, “Measurement Effects and the Variance of Returns after Stock Splits
and Stock Dividends,” Review of Financial Studies 11, 143-162.
Koski, J.L., 2007, “Does Volatility Decrease after Reverse Stock Splits?” Journal of
Financial Research 30, 217-235.
Kryzanowski, L. and H. Zhang, 1996, “Trading Patterns of Small and Large Traders
around Stock Split Ex-Dates,” Journal of Financial Research 19, 75-90.
Kunz, R.M. and S. Rosa-Majhensek, 2008, “Stock Splits in Switzerland: To Signal or
Not to Signal?” Financial Management 37, 193-226.
Lakonishok, J. and B. Lev, 1987, “Stock Splits and Stock Dividends: Why, Who, and
When,” Journal of Finance 62, 913-932.
Lamoureux, C. and P. Poon, 1987, “The Market Reaction to Splits,” Journal of Finance
62, 1347-1370.
Lin, J., A.K. Singh, and W. Yu, 2009, “Stock Splits, Trading Continuity, and the Cost of
Equity Capital,” Journal of Financial Economics 93, 474-489.
Maloney, M. and H. Mulherin, 1992, “The Effects of Splitting on the Ex: A
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Martell, T.F. and G.P. Webb, 2008, “The Performance of Stocks that are Reverse Split,”
Review of Quantitative Finance and Accounting 30, 253-279.
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Mukherji, S., Y. Kim, and M. Walker, 1997, “The Effect of Stock Splits on the
Ownership Structure of Firms,” Journal of Corporate Finance 3, 167-188.
Murray, D., 1985, “Further Evidence on the Liquidity Effects of Stock Splits and Stock
Dividends,” Journal of Financial Research 8, 59-67.
Muscarella, C. and M. Vetsuypens, 1996, “Stock Splits: Signaling or Liquidity? The Case
of ADR ‘Solo-Splits’,” Journal of Financial Economics 42, 3-26.
Nayak, S. and N.R. Prabhala, 2001, “Disentangling the Dividend Information in Splits: A
Decomposition Using Conditional Event-Study Methods,” The Review of Financial
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Nayar, N. and M.S. Rozeff, 2001, “Record Date, When-Issued, and Ex-Date Effects in
Stock Splits,” Journal of Financial and Quantitative Analysis 36, 119-139.
Ohlson, J.A. and S.H. Penman, 1985, “Volatility Increases Subsequent to Stock Splits:
An Empirical Aberration,” Journal of Financial Economics 14, 251-266.
Peterson, D.R. and P.P. Peterson, 1992, “A Further Understanding of Stock Distributions:
The Case of Reverse Stock Splits,” Journal of Financial Research 15: 189-205.
Pilotte, E. and T. Manuel, 1996, “The Market’s Response to Recurring Events: The Case
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Powell, G.E. and H.K. Baker, 1993/1994, “The Effects of Stock Splits on the Ownership
Mix of a Firm,” Review of Financial Economics 3, 70-88.
Rankine, G. and E.K. Stice, 1997, “The Market Reaction to the Choice of Accounting
Method for Stock Splits and Large Stock Dividends,” Journal of Financial and
Quantitative Analysis 32, 161–182.
Roll, R., 1984, “A Simple Implicit Measure of the Effective Bid-Ask Spread in an
Efficient Market,” Journal of Finance 39, 1127–1139.
Schultz, P., 2000, “Stock Splits, Tick Size, and Sponsorship,” Journal of Finance 55,
429-450.
Sheikh, A.M., 1989, “Stock Splits, Volatility Increases, and Implied Volatilities,” Journal
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Szewczyk, S.H. and G.P. Tsetsekos, 1993, “The Effect of Managerial Ownership on
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Tawatnuntachai, O. and R. D'Mello, 2002, “Intra-Industry Reactions to Stock Split
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Financial Management 12, 5-15.
38
Table 1. Evidence Related to the Optimal Price/Tick Hypothesis
This table presents both supporting and contrary evidence in relation to the optimal price/tick hypothesis, as
well as information about author(s), year, and sample. It also provides the section number in the text where
the evidence is discussed. Panel A presents the supporting evidence for the optimal price hypothesis; Panel
B, the supporting evidence for the optimal tick hypothesis; and Panel C, the contrary evidence for the
optimal price/tick hypothesis.
Panel A. Supporting evidence for the optimal price hypothesis
Evidence
Author(s), Year, and Sample
Section
Stock price variations
(The stock price of a firm has its optimal
range.)
Angel (1997): 2,517 stocks from various
countries in January 1994; NYSE stocks
during 1924-1994
Dyl and Elliot (2006): CRSP firms during
1976-2001
2.1.1
Price before and after splits
(Splitting firms have higher price levels
before splits than non-splitting firms, and
similar price levels after splits. Thus, splits
are to return the prices to normal levels.)
Lakonishok and Lev (1987): CRSP firms with
splits during 1963-1982, leading to a total
of 1,015 splits
2.1.2
Split factor and frequency
(Larger split factors and higher split
frequencies are to return the deviated prices
to the normal range.)
Lakonishok and Lev (1987): CRSP firms with
splits during 1963-1982, leading to a total
of 1,015 splits
Huang, Liano, Manakyan, and Pan (2008):
CRSP firms with splits during 1967-2000,
leading to a total of 3,253 splits
2.1.3
Investor base before and after splits
(A firm selects a price range that enlarges
the firm’s investor base.)
Brennan and Hughes (1991): CRSP and
I/B/E/S firms with splits during 19761987
Maloney and Mulherin (1992): CRSP Nasdaq
firms with splits during 1985-1989,
leading to a total of 446 splits
Mukherji, Kim, and Walker (1997): NYSE and
AMEX firms with splits during 19841988, leading to 168 splits
Dyl and Elliot (2006): CRSP firms with splits
during four years following 1976, 1981,
1986, 1991, and 1996
Powell and Baker (1993/1994): CRSP firms
with splits during 1982-1989, leading to a
total of 527 splits by 481 firms
Dennis and Strickland (2003): CRSP firms
with splits during 1990-1993
2.1.4
(Continued)
39
Table 1 continued.
Panel A. Supporting evidence for the optimal price hypothesis (continued)
ADR split
(ADRs’ solo-splits in the U.S. are to return
the prices to an optimal range.)
Muscarella and Vetsuypens (1996): CRSP
ADRs with splits during 1962-1993,
leading to a total of 143 splits of foreign
stocks and/or ADRs
2.1.5
Fund split
(Fund splits are to return fund prices to an
optimal range and improve liquidity.)
Fernando, Krishnamurthy, and Spindt (1999):
194 open-end funds with splits during
1978-1993
Datar and Dubofsky (1999): closed-end funds
with splits during 1962-1995
Dennis (2003): the Nasdaq-100 Tracking stock
with a 2-for-1 split during 1999-2000
2.1.6
Split before an M&A
(Acquiring firms may split their stock
shares before M&As to make their stock
prices more attractive.)
Guo, Liu, and Song (2008): 4,782 acquisitions
during 1980-2003
2.1.7
Split before an SEO
(Splits before SEOs are to make the stock
prices of the equity-issuing firms more
attractive.)
D’Mello, Tawatnuntachai, and Yaman (2003):
2,190 primary seasoned equity issues
during 1980-1995
2.1.8
Panel B. Supporting evidence for the optimal tick hypothesis
Relative tick size variations
(An optimal range of relative tick size exists
for trading a firm’s stock.)
Angel (1997): 2,517 stocks from various
countries in January 1994
2.2.1
Clustering before and after splits
(Price clustering decreases after splits in
relation to a bigger relative tick size.)
French and Foster (2002): CRSP firms with
splits during 1996-1998, leading to a total
of 1,590 splits
2.2.2
Limit orders before and after splits
(The number of limit orders increases after
splits in relation to a bigger relative tick
size.)
Easley, O’Hara, and Saar (2001): 72 NYSE
firms with splits in 1995
2.2.3
Profits to market makers before and after
splits
(Profits to market makers increase after
splits due to a bigger relative tick size.)
Schultz (2000): CRSP firms with splits during
1993-1994, leading to a total of 235 splits
Gray, Smith, and Whaley (2003): CRSP firms
with splits during 1993-1996, leading to a
total of 1,109 splits
2.2.4
(Continued)
40
Table 1 continued.
Panel B. Supporting evidence for the optimal tick hypothesis (continued)
Small investors/trades before and after
splits
(Brokers tend to promote stocks to small
investors after splits due to bigger relative
tick size and bigger relative bid-ask spread.)
Kadapakkam, Krishnamurthy, and Tse (2005):
CRSP NYSE and Nasdaq firms with
splits during three periods (1995-1996,
1998-1999, and 2001-2002)
Baixauli (2007): Spanish stocks with splits
during 1994-2004
2.2.5
Volatility before and after splits
(For forward splits, volatility increases
subsequent to ex-split days due to bigger
relative tick size as well as other factors,
and vice verse for reverse splits.)
Ohlson and Penman (1985): CRSP NYSE
firms with splits during 1962-1981,
leading to a total of 1,257 splits
Dravid (1987): CRSP firms with splits during
1962-1981
Sheikh (1989): 83 stocks with options that split
between 1976 and 1983
Koski (1998): NYSE firms with splits during
1987-1989, leading to a total of 317 splits
Kryzanowski and Zhang (1996): stocks splits
on Toronto Stock Exchange during 19831989
Koski (2007): CRSP Nasdaq firms with reverse
splits during 1993-2002, leading to a total
of 758 reverse splits
Dubofsky (1991): CRSP NYSE and AMEX
firms with splits during 1962-1987,
leading to a total of 2,552 splits
Lamoureux and Poon (1987): CRSP firms with
forward or reverse splits during 19621985, leading to 213 forward splits and 49
reverse splits
Chen and Wu (2009): 86 CRSP firms with
splits during 1997-1998
2.2.6
(Continued)
41
Table 1 continued.
Panel C. Contrary evidence for the optimal price/tick hypothesis
Liquidity before and after splits
(For the hypothesis: forward and reverse
splits restore the price/tick to an optimal
range and improve liquidity.)
For the hypothesis:
Baker and Gallagher (1980): survey study for
stock splits in 1978
Baker and Powell (1993): survey study for
stock splits in 1987-1990
Muscarella and Vetsuypens (1996): CRSP
ADRs with splits during 1962-1993,
leading to a total of 143 splits of foreign
stocks and/or ADRs
Lin, Singh, and Yu (2009): CRSP firms with
splits during 1975-2004, leading to a total
of 3,721 splits
Han (1995): CRSP firms with reverse splits
during 1963-1990, leading to a total of
136 firms
(Against the hypothesis: liquidity
diminishes after splits since the percentage
bid-ask spreads become larger, the depth
becomes smaller, and the trading volume
declines.)
Against the hypothesis:
Lin, Singh, and Yu (2009): CRSP firms with
splits during 1975-2004, leading to a total
of 3,721 splits
Gray, Smith, and Whaley (2003): CRSP firms
with splits during 1993-1996, leading to a
total of 1,109 splits
Copeland (1979): 25 NYSE firms with splits
during 1963-1974
Murray (1985): 118 COMPUSTAT firms with
splits during 1972-1977
Lamoureux and Poon (1987): CRSP firms with
forward or reverse splits during 19621985, leading to 213 forward splits and 49
reverse splits
Lakonishok and Lev (1987): CRSP firms with
splits during 1963-1982, leading to a total
of 1,015 splits
2.3.1
42
Table 2. Evidence Related to the Signaling Hypothesis
This table presents both supporting and contrary evidence in relation to the signaling hypothesis, as well as
information about author(s), year, and sample. It also provides the section number in the text where the
evidence is discussed. Panel A presents the supporting evidence for the signaling hypothesis; Panel B, the
contrary evidence for the signaling hypothesis.
Panel A. Supporting evidence for the signaling hypothesis
Evidence
Author(s), Year, and Sample
Section
Split announcement effect
(A forward split announcement generates a
positive abnormal return and signals good
news, and vice verse for a reverse split
announcement.)
Grinblatt, Masulis, and Titman (1984): CRSP
firms with splits during 1967-1976,
leading to a total of 1,140 splits
Brennan and Copeland (1988): 967 stock splits
during 1967-1976
Szewczyk and Tsetsekos (1993): 175 stock
splits during 1972-1986
Arbel and Swanson (1993): 105 pure split
announcements during 1984-1987
Woolridge and Chambers (1983): CRSP NYSE
and AMEX firms with reverse splits
during 1962-1981
Peterson and Peterson (1992): CRSP firms
with reverse splits during 1962-1989,
leading to a total of 483 reverse splits
3.1.1
Infrequent split
(A split that happens infrequently for a firm
may signal good news.)
Huang, Liano, Manakyan, and Pan (2008):
CRSP firms with splits during 1967-2000,
leading to a total of 3,253 splits
3.1.2
Split factor
(Split factors reveal information about
future performance.)
McNichols and Dravid (1990): CRSP NYSE
and AMEX firms with splits during 19761983
Conroy and Harris (1999): NYSE firms with
splits during 1925-1996; and CRSP
NYSE firms with splits during 1963-1996
3.1.3
Credibility of split signal
(A split announcement together with a
voluntary reduction in retained earnings
makes the signal credible.)
Grinblatt, Masulis, and Titman (1984): CRSP
firms with splits during 1967-1976,
leading to a total of 1,140 splits
Rankine and Stice (1997): CRSP NYSE firms
with splits in 1983, 1985, 1987, and 1989
Bechmann and Raaballe (2007): stock splits in
Denmark during 1995-2002
3.1.4
Split of stocks with options
(The signaling effect at the split
announcement is stronger for stocks without
options than for stocks with options.)
Chern, Tandon, Yu, and Webb (2008): CRSP
stocks with splits and with options during
1976-2004
3.1.5
(Continued)
43
Table 2 continued.
Panel B. Contrary evidence for the signaling hypothesis
Post-split earnings and dividends
(For the hypothesis: forward splits signal
good news, and the post-split earnings and
dividends increase.)
For the hypothesis:
Lakonishok and Lev (1987): CRSP firms with
splits during 1963-1982, leading to a total
of 1,015 splits
Pilotte and Manuel (1996): CRSP NYSE and
AMEX firms with splits during 19701988, leading to a total of 2,159 splits by
776 firms
Tawatnuntachai and D’Mello (2002): CRSP
firms with splits during 1986-1995,
leading to a total of 327 splits
(Against the hypothesis: splits are not useful
signals of the post-split dividends and
earnings.)
Against the hypothesis:
Nayak and Prabhala (2001): CRSP firms with
splits during 1985-1994, leading to a total
of 1,597 splits
Huang, Liano, and Pan (2006): CRSP firms
with splits during 1963-1998, leading to a
total of 6,417 splits
Post-split stock return
(For the hypothesis: forward splits signal
good news, and the post-split abnormal
stock return is positive. The opposite is true
for reverse splits.)
For the hypothesis:
Ikenberry, Rankine, and Stice (1996):
COMPUSTAT NYSE and ASE firms
with splits during 1975-1990, leading to a
total of 1,275 two-for-one splits
Desai and Jain (1997): CRSP and
COMPUSTAT firms with forward or
reverse splits during 1976-1991, leading
to a total of 5,596 forward splits and 76
reverse splits
Ikenberry and Ramnath (2002): I/B/E/S and
CRSP firms with splits during 1988-1997,
leading to a total of 3,028 splits
Kim, Klein, and Rosenfeld (2008): CRSP firms
with reverse splits during 1962-2001,
leading to a total of 1,612 reverse splits
Martell and Webb (2008): CRSP firms with
reverse splits during 1972-2003, leading
to a total of 1,668 reverse splits
(Against the hypothesis: the post-split
abnormal return is insignificant.)
Against the hypothesis:
Byun and Rozeff (2003): CRSP firms with
splits during 1927-1996
Boehme and Danielsen (2007): CRSP firms
with splits in 2002; CRSP firms with
splits during 1950-2000, leading to a total
of 6,106 split events
Hwang, Keswani, and Shackleton (2008):
CRSP firms with splits during 1962-2003
3.2.1
3.2.2
(Continued)
44
Table 2 continued.
Panel B. Contrary evidence for the signaling hypothesis (continued)
Information asymmetry before and after
splits
(Against the hypothesis: information
asymmetry does not diminish after splits.)
Against the hypothesis:
Desai, Nimalendran, and Venkataraman
(1998): 366 splits announced by 341
CRSP Nasdaq firms during 1983-1990
Easley, O’Hara, and Saar (2001): 72 NYSE
firms with splits in 1995
D’Mello, Tawatnuntachai, and Yaman (2003):
2,190 primary seasoned equity issues
during 1980-1995
3.2.3
Short interest before and after splits
(Against the hypothesis: short interest does
not decline after splits.)
Against the hypothesis:
Kadiyala and Vetsuypens (2002): 296 CRSP
NYSE firms with splits during 1990-1994
3.2.4
45
Table 3. Evidence Related to the Procedure/Structure Hypothesis
This table presents supporting evidence in relation to the procedure/structure hypothesis, as well as
information about author(s), year, and sample. It also provides the section number in the text where the
evidence is discussed.
Evidence
Author(s), Year, and Sample
Section
Positive return between the announcement
& ex-split days**
(Market frictions cause the short-term delay
in price response.)
Boehme and Danielsen (2007): CRSP firms
with splits in 2002; CRSP firms with
splits during 1950-2000, leading to a
total of 6,106 split events
4.1.1
Negative return on the record day
(The negative return on the record day is
mainly due to the trading inconvenience
associated with the record day process.)
Nayar and Rozeff (2001): CRSP firms with
splits during 1985-1993, leading to
3,336 splits in NYSE/ASE firms and
1,244 splits in Nasdaq firms
4.1.2
Positive return on the ex-split day*
(The positive return on the ex-split day is
related to the tax effect, the market
microstructure effect, and the record-dayinconvenience effect.)
Lamoureux and Poon (1987): CRSP firms
with forward or reverse splits during
1962-1985, leading to 213 forward
splits and 49 reverse splits
Maloney and Mulherin (1992): CRSP
Nasdaq firms with splits during 19851989, leading to a total of 446 splits
Nayar and Rozeff (2001): CRSP firms with
splits during 1985-1993, leading to
3,336 splits in NYSE/ASE firms and
1,244 splits in Nasdaq firms
4.1.3
Higher percentage bid-ask spread after
splits
(The higher percentage bid-ask spread after
splits may result from consistent spreadsetting behavior in a lower price
environment.)
Huang and Weingartner (2000): 179 CRSP
NYSE stocks with splits in 1992
4.1.4
Higher volatility after the ex-split day*
(The higher volatility after the ex-split day
is related to the when-issued trading.)
Angel, Brooks, and Mathew (2004): 198
NYSE firms with splits during 19891992
4.1.5
Split due to price deregulation*
(Due to deregulation in the minimum par
value, firms tend to split their stock shares
to get to a new optimal price range.)
Kunz and Rosa-Majhensek (2008): 80 stock
splits by 64 firms in Switzerland during
1992-2001
Greenwood (2009): 2,094 stock splits in
Japan during 1995-2005
4.1.6
*:
**:
the evidence also supports the optimal price/tick hypothesis.
the evidence also supports the signaling hypothesis.
46
Figure 1. Important Days around a Split Event
This figure displays two important days around a split event: the announcement day and the ex-split day. In addition, it also presents several other significant
days around a split event.
About two months
Announcement day
Ex-split day
Record
day
Payment
day
47
Due bill
redemption
day
Settlement
day