Download Does Supply Curve Inelasticity Explain Abnormal Long

Does Supply Curve Inelasticity Explain Abnormal Long-Run
Returns Following Open Market Share Repurchases?
William McNally, Brian F. Smith and Thomas Barnes*
This Version: July 2003
Abstract
This paper uses a new database that provides details on individual repurchase trades. We
estimate that repurchase trades earn significant long-run abnormal returns. We partly
attribute the returns to the fact that open market repurchases permanently remove supply
from the market. In the presence of supply curve inelasticity this leads to an increase in the
equilibrium price of the stock. Consistent with this argument, we find that individual
repurchase trades have a significantly greater permanent price impact than matched ordinary
trades. We also show that firms exploit their insider information by buying on dips and at a
discount to the prices paid by outside investors. The public announcement of the trades does
not signal information to the market.
* McNally and Smith are at the Clarica Financial Services Research Centre, School of Business and Economics,
Wilfrid Laurier University. Barnes is at the Department of Accounting and Finance, Brock University. Smith is
the contacting author and can be contacted at the School of Business and Economics, Wilfrid Laurier
University, 75 University Avenue West, Waterloo, Ontario, Canada N2L 3C5. Phone: 519-884-0710 ext. 2953.
Fax: 519-884-0201. E-mail: [email protected] The authors acknowledge financial support from the Social
Sciences and Humanities Research Council of Canada. We appreciate the suggestions of an anonymous referee,
and participants at the Northern Finance Association 2002 annual meetings and at a University of Toronto
seminar. We also thank Catherine Hartung, Danielle Knox, Ron Leisti and James Sandhu for research
assistance. The usual disclaimer applies.
Does Supply Curve Inelasticity Explain Abnormal Long-Run
Returns Following Open Market Share Repurchases?
Abstract
This paper uses a new database that provides details on individual repurchase trades. We
estimate that repurchase trades earn significant long-run abnormal returns. We partly
attribute the returns to the fact that open market repurchases permanently remove supply
from the market. In the presence of supply curve inelasticity this leads to an increase in the
equilibrium price of the stock. Consistent with this argument, we find that individual
repurchase trades have a significantly greater permanent price impact than matched ordinary
trades. We also show that firms exploit their insider information by buying on dips and at a
discount to the prices paid by outside investors. The public announcement of the trades does
not signal information to the market.
Does Supply Curve Inelasticity Explain Abnormal Long-Run
Returns Following Open Market Share Repurchases?
Past studies of open market repurchases find significant abnormal long-run returns to a
strategy of buying following program announcements and attribute the returns to undervaluation
at the time of the announcement (Ikenberry, Lakonishok and Vermaelen (1995, 2000)). Using a
new transaction-level database, we estimate that the non-tendering shareholders earn abnormal
long-run returns from the repurchase trades themselves. We examine three alternative
explanations for the source of the returns: 1) supply curve inelasticity; 2) asymmetric
information—firms trade on their insider information; and 3) signaling—the mandatory public
announcement of firms’ repurchase trades conveys information to the market. The major
contribution of the paper is that we attribute part of the abnormal return to the fact that open
market repurchases permanently remove supply from the market. The idea that repurchases
remove supply and thereby raise equilibrium prices has been used to explain price changes
around Dutch auctions (Bagwell (1992)). This is the first paper to explore whether open market
repurchases have the same effect.
Our dataset allows much more extensive analysis of repurchases than previous studies,
including the analysis of market microstructure issues. Canadian repurchasing firms are required
by law to file insider trading reports that provide details (price, quantity and date) of repurchase
trades. Our detailed dataset includes 1,118 programs by 500 firms repurchasing nearly 1 billion
shares. By matching the insider trading records with transaction level data, we are able to
identify 62,658 specific repurchase trades. With this detailed transaction data we compare the
price impacts of repurchase trades with those of matched ordinary trades. We find a significantly
greater permanent price impact for repurchase trades. This result is consistent with removal of
supply in a market with an inelastic supply curve. In contrast, we do not find that purchases by
other insiders create a significant excess permanent price impact.
Another potential source for the abnormal performance of the repurchase trades is that
firms have an information advantage over other traders. If firms have insider information that
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allows them to identify periodic undervaluation, then they can buy strategically at those times
and earn higher returns than outside investors. If this is the case, then other traders should not be
able to replicate firms’ performance unless they can exactly copy the timing and magnitude of
firms’ trades. We find that firms buy on ‘dips.’ They pay lower prices than outside investors but
similar to the prices paid by other asymmetrically informed insiders. We measure the returns
earned by a strategy of mimicking repurchasing firms’ trades and find no abnormal performance
after adjusting for price impact. We conclude that part of firms’ abnormal returns derives from
their information advantage and that is why the returns cannot be replicated by outside investors.
If firms have asymmetric information about periodic undervaluation of their stock, then
the public announcement of their trades should act as a signal to the market. Past studies argue
that open market repurchase program announcements are signals, and find that abnormal returns
are related to information learned from the announcement (McNally (1999)). Similarly, the longrun abnormal returns may partially be due to information learned through the public
announcement of actual repurchases. Canadian regulations require mandatory disclosure of
repurchase trades. While we confirm that traders respond to the announcement of the initiation of
a repurchase program, we find no significant market reaction to the announcement of completed
repurchase trades. Thus, abnormal returns are not the result of information signaled by the
disclosure of trades.
This paper has four sections. Section I reviews the inelasticity, information asymmetry
and signaling hypotheses. Section II describes the institutional structure governing Canadian
repurchases and the data. Section III discusses test methods and results. Section IV presents
conclusions.
I. Explanations for Long-Run Rates of Returns
Published evidence of abnormal returns following repurchases (Ikenberry, Lakonishok
and Vermaelen (1995, 2000)) leaves two questions unanswered. First, are the abnormal returns
available to all investors who acquire shares of a repurchasing firm or just to the firm itself?
Second, what is the source of the abnormal returns? The first question is unanswered because
previous studies measure the return to a strategy of purchasing at the end of the month of the
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announcement and they do not adjust those hypothetical trades for price impact. In contrast, we
measure the return earned on the firm’s purchases, which reveals whether the repurchase
transfers wealth from tendering (selling) to non-tendering shareholders. We find that firms earn
abnormal returns on their actual trades, but we do not find that a realistic replication of the firm’s
trades earns abnormal returns after adjusting for price impact.
Past studies attribute the abnormal long-run returns to the general undervaluation of the
shares during the repurchase announcement period and a subsequent reversal to full-valuation
over a one or two year time frame. Those studies do not explore the specific events that drive the
increase in stock prices. We explore three alternative explanations for the long-run abnormal
returns: 1) repurchases increase stock prices because they remove supply; 2) repurchasing firms
have asymmetric information which allows them to buy strategically; and 3) the announcement
of actual repurchases signals information to the market. Each of these hypotheses is examined in
turn.
A.
Supply Curve Inelasticity
Bagwell (1992) argues that Dutch auction repurchases increase the equilibrium price
because they reduce the pool of investors and change the marginal shareholder to one with a
higher reservation price. Prices rise following these repurchases because the supply curve for
shares is inelastic. Open market repurchases are smaller than Dutch auctions but also
permanently reduce the pool of investors. By construction, open market repurchases remove
shareholders with the lowest valuation, since it is those investors who sell at the market. If the
supply curve for shares is inelastic, then open market repurchases should raise the equilibrium
price of the stock higher than it would have risen following an ordinary purchase. We refer to
this difference as the inelasticity effect of repurchases. The presence of an inelasticity effect
would explain why there are abnormal long-run rates of return following open market
repurchases.
Open market repurchases are smaller than Dutch auctions, but that does not mean that the
inelasticity effect is insignificant. Only if the supply curve is flat for trades the size of
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repurchases would there be no inelasticity effect.1 The mean repurchase trade size is 13,565
shares, four times larger than the average ordinary trade size. Bagwell (1992) finds in a study of
Dutch auctions that the supply curve is not flat but rather is more inelastic for smaller quantities
of shares repurchased. Based on the arc elasticity estimate in Table II of Bagwell (1992), a 2%
repurchase of shares should lead to a 1.8% increase in stock price. The relatively high inelasticity
in the smallest set of Dutch auctions leads us to expect that open market repurchases of
equivalent size will result in significant price impacts. While the cumulative impact of a 2%
purchase should be significant, we also expect that each individual transaction generates a price
impact.
The inelasticity effect for individual trades depends on the impact of the trade on the
marginal investor. A repurchase trade removes but does not replace the seller, whereas a regular
trade replaces the marginal seller with another investor. With a regular trade, the new holder of
the security will likely have a higher reservation price than the seller of the security. However,
the presence of the new shareholder will put competitive pressure on the reservation prices of the
other shareholders.
To illustrate this point, consider a stock with a marginal seller, Seller A, asking $10 for
her 3,000 shares and the next seller, Seller B, asking $10.10 for her 4,000 shares. If all of Seller
A’s shares are repurchased, the new reservation price is $10.10. Now consider the case where
Seller A’s shares are acquired for $10 in a regular trade and the buyer has a reservation price of
$10.10. The presence of this new shareholder (the buyer) puts competitive pressure on other
shareholders, and Seller B may lower her reservation price to say $10.05. In the case of a
liquidity-motivated buyer, such as an Index fund, the reservation price will be very close to the
purchase price, and so the supply curve will be largely unchanged by the transaction.
While there are many scenarios, the main point is that in a regular trade the buyer puts
competitive pressure on the remaining shareholders, but this does not occur in a repurchase
where there is no new shareholder. Thus, repurchase trades should be followed by a larger
1
Empirical research on the limit order book reveals an upward-sloping supply curve for quantities the size of
repurchases. See evidence from Biais, Hillion and Spatt (1995) for the Paris Bourse and from Goldstein and
Kavajecz (2000) for the New York Stock Exchange.
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increase in the equilibrium price compared to ordinary trades. This hypothesized difference
presents a means of testing for an inelasticity effect. If there is an inelasticity effect, then the
permanent price impact (change in mid-quotes) of repurchase trades should be greater than that
of equivalent ordinary trades (non-repurchase trades matched by characteristics).
B.
Asymmetric/Insider Information
An alternative explanation for the abnormal performance of the repurchase trades is that
there is asymmetric information between the firm and the market. If the firm has insider
information that allows it to identify periodic undervaluation, then it can buy strategically and
pay lower prices and earn higher returns than other traders. The firm’s performance ought to be
equivalent to that achieved by other insiders. Indeed, repurchases have been characterized by
Barclay and Smith (1988) and Ikenberry and Vermaelen (1996) as a substitute for direct insider
buying.2 If the firm has insider information, then outside investors should not be able to replicate
the firm’s performance unless it can exactly copy the timing and magnitude of the firm’s trades.
In this view, the repurchase program announcement does not necessarily indicate current
undervaluation, but indicates that the firm expects to identify periods when its shares trade below
their fair value. This view was first articulated by Ikenberry and Vermaelen (1996). In summary,
if the firm has insider information then: 1) the firm should earn abnormal long-run returns on its
purchases; 2) the firm should pay lower prices than outside traders; 3) repurchases and purchases
by other insiders should be substitutes; and 4) outside investors should not be able to replicate
the firm’s performance.
Do Firms Pay Lower Prices than Other Traders?
If firms have asymmetric information about their value, then they should be able to time
their purchases advantageously. Brockman and Chung (2001) study repurchases with data
summarized on a daily basis for 370 repurchase programs on the Hong Kong Stock Exchange
during the 1990s. They calculate the price paid on repurchases to be about 9% below that of
bootstrapped samples of random trades and attribute this discount to asymmetric information and
2
A proof of their substitutability can be obtained from the authors upon request.
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superior management timing. Contrary to Brockman and Chung (2001), Cook, Krigman and
Leach (2000) use a survey to collect trading data from 64 U.S. repurchase programs in 1993.
Their overall sample indicates that firms do not buy at cheap prices, but their NYSE subsample
exhibits some evidence of timing ability by firms.
In our study, we compare the prices paid by repurchasing firms in 802 programs to those
paid by other investors. We compute the price premium in several ways, one of which controls
for trade and market characteristics that may also explain the price premium.
Are Repurchases and Purchases by Insiders Substitutes?
Previous studies document that insiders are asymmetrically informed traders and earn
abnormal returns (Jaffe (1974), Finnerty (1976), Seyhun (1986), Rozeff and Zaman (1988) and
Lakonishok and Lee (2001)). A repurchase and an insider purchase are substitutes in the sense
that subsequent to either transaction the insider’s wealth varies directly with the stock price. If
they are substitutes, then we should observe that if insiders buy at a discount, so should firms.
The discount paid by insiders should be positively correlated with the discount paid by firms.
Finally, if they are substitutes, then insiders should not be selling their equity interest at the same
time firms are buying back shares.
Can Outside Investors Replicate Firms’ Performance?
If firms earn abnormal returns because they are insiders and the market is semi-strong
form efficient, then outside investors should not be able to replicate firms’ abnormal
performance. To test this hypothesis, we measure the returns to a strategy of mimicking firms’
actual repurchase trades as they are publicly announced. This strategy is the closest feasible
match to firms’ purchasing and should yield returns close to those earned by firms. In calculating
the returns to this hypothetical trading strategy, we account for the price impacts of the trades.3
C.
Signaling Hypothesis
Past models hypothesize that the announcement of a repurchase program is a signal that
conveys management’s knowledge of future earnings to the market (McNally (1999)). Those
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models predict a significant abnormal return following program announcements. A problem with
modeling the announcement as a signal is that the announcement is not binding. Given that it is
not a commitment, we hypothesize that the market conditions its response to the initial program
announcement and completes its reaction only when it observes the firm actually repurchasing.
In this case, we would also expect abnormal returns in response to announcements of actual
repurchases. These reactions may explain the abnormal long-run returns in the year following
repurchase program announcements. We test two implications of the signaling hypothesis: that
there will be a significant reaction to the program announcement and that there will be a
significant reaction to announcements of actual purchases.
II. Regulation of Open Market Repurchases and Data
Most repurchases in Canada are open market programs since fixed-price and Dutch
auctions are taxed disadvantageously. Open market repurchases are carried out through the
facilities of the Toronto Stock Exchange (TSX) and are subject to its general by-laws. In the case
of repurchase programs, the by-laws supersede the Ontario Securities Act (OSA), which
normally governs all securities transactions in the province. Regulations affect the initial
announcement of repurchase programs, execution of purchases and announcement of actual
purchases. We discuss each in turn.
A.
Initial Announcement of Repurchase Program
The TSX must approve all open market repurchase programs. The exchange refers to
such programs as “normal course issuer bids.” For each program, the Exchange limits company
repurchases to the greater of 5% of shares outstanding or 10% of public float over a 12-month
period. In contrast, U.S. open market repurchases can last more than one year and, on average,
U.S. firms target to repurchase 7% of their outstanding shares.4 Canadian companies must
publicly announce their repurchase programs.
3
We thank the anonymous referee for this suggestion.
4
See Vermaelen (1981) and Stephens and Weisbach (1998).
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B.
Execution of Repurchase Programs
The TSX has the following rules that regulate how repurchase programs are executed.
These rules are established to reduce possible market manipulation:
•
Repurchases can only begin two days after receiving approval from the TSX.
•
Repurchases over any 30 calendar days must not exceed 2% of the outstanding shares.
•
Purchases cannot be made at a price higher than the last independent trade of a board lot
of the shares.
•
Purchases must be made through a single broker.
•
Prearranged trades (also referred to as put-throughs on the TSX) in which the seller is an
insider are prohibited.
C.
Reporting of Repurchase Trades Required by OSC and TSX
The Ontario Securities Act (OSA) also affects how repurchase programs are disclosed
since the Act considers firms that repurchase their own shares to be insiders. As insiders, firms
must report their repurchases to the OSC within 10 days of the trade.5 They must report the date,
price and quantities of shares acquired. This information is subsequently reported by the OSC in
the weekly Ontario Securities Bulletin and maintained electronically by Micromedia Inc. on the
Insider Reporting Database.
The TSX requires that firms report their repurchases to the Exchange within 10 days of
each month in which the repurchases are made.6 For every repurchase program, the TSX Daily
Record publishes the prior month’s total repurchases, the cumulative repurchases to date, the
number of shares targeted, and the expiry date. This information is typically published on the
third Friday of each month.
5
OSA, 1994, Section 107(2). Until December 1999, the OSA had the same time requirements as the TSX for
reporting insider trades (within 10 days of the end of month of trade).
6
TSX Rule Book Appendix F, 6-501(8)
8
D.
Data
Our database of repurchases covers the period from January 1, 1987 to Dec 31, 2000 and
is constructed from the TSX Daily Record and the OSC Insider Reporting Database. From the
Daily Record, we identify 2,674 repurchase announcements by companies listed on the TSX. Of
these announcements, there are 661 programs in which the TSX Daily Record records no
repurchase activity. Thus, the TSX records only 2,013 active repurchase programs in which
1,431 million common shares were repurchased.
The OSC database includes only completed transactions, and so only records programs
where there are actual repurchases. To our knowledge, this is the first paper to employ the OSC
detailed transaction data.7 The OSC database has information on 1,118 programs which match
with the database of announcements from the TSX Daily Record. It is from this OSC data that
we draw individual repurchase trades for our analysis of excess price impacts. Of the 1,118
programs, 32 have no record of repurchase activity by the TSX. This leaves 1,086 programs by
500 firms (involving the repurchase of 909 million shares) with at least some repurchase activity
recorded by both the TSX and OSC.
To conduct the analysis of IRRs and price premiums across programs, we need to have a
complete set of trades for each program.8 Thus, for each of the 1,086 repurchase programs, we
compare the data from the OSC with that of the TSX. Programs are excluded from our analysis if
the total number of shares reported by the OSC is 25% less than or 25% greater than the total
listed in the TSX Daily Record. This removes 251 programs from the analysis. Finally, we
remove 23 programs where reported prices are not consistent with the actual trading range on the
reported trade date or where there are no securities price data at all. (Closing stock prices and
7
Since it is the first time the electronic OSC data are used in an academic study, we extensively screen them for
input errors. The following corrections are made: reposition decimal points in incorrectly recorded prices; adjust for
changes in firm and security names; adjust for stock splits; and remove the repurchase trades that were transacted on
U.S. exchanges (such trades constituted only 5.5% of the original sample).
8
We use the larger set of OSC records for the price impact analysis because in that analysis we do not need to have
the complete set of trades for each repurchase program. Price impact analysis is done on the trade rather than the
program level.
9
indices are from Canadian Financial Markets Research Centre (CFMRC) database, and trades
and quotes data are from the TSX.) This screening reduces the sample to 802 programs in which
706 million shares are repurchased.
The OSC database is smaller than the TSX database. This difference is due to noncompliance with OSC disclosure regulations. From discussions with the OSC, enforcement of
insider reporting rules is not a priority of the commission. However, compliance improves over
the sample period. In the final year of the sample, 2000, the OSC Insider Reporting Database
reports 83% of the number of shares reported by the TSX.
To determine whether the sample of 802 is representative of the population of active
repurchase programs, we compare various characteristics of the sample with the population of
2,045 active repurchase programs recorded in either or both of the TSX and OSC databases. The
characteristics we compare are: market capitalization, daily turnover, insider holdings, and the
distribution of firms across industries. We find no statistically significant difference between the
characteristics of the sample and population of repurchase programs.
III. Test Methods and Results
A.
Summary Statistics
Table 1 shows that repurchase activity on the Toronto Stock Exchange increases
markedly in recent years. From January 1987 to December 2000, a total of 706 million shares
worth $14.7 billion are bought back. The most active year is 1999 when there are 134 buyback
programs involving 191 million shares worth $4.4 billion.9
[Insert Table 1 About Here]
Overall, the completion rates of the repurchase programs are similar to those reported in
Ikenberry, Lakonishok and Vermaelen (2000). On average, over the whole time period, about
40% of the targeted amount of each repurchase program is bought back by companies. With the
exception of 1990-1992, the annual completion rate varies from 30% to 48%. The figures are
10
lower from 1990 to 1992 because of a recession in Canada over that period. The recession
lowered corporate cash flows, thereby constraining the ability of firms to repurchase shares as
per Stephens and Weisbach (1998).
The last two columns provide some evidence which suggests that repurchases provide
substantial liquidity to the market. Across all years, while repurchases represent only 2.02% of
shares outstanding, they constitute 12.25% of shares traded during the repurchase program
period. Shares repurchased as a percentage of all trading volume varies from 5.07% in 1987 to
18.33% in 2000. There is no significant trend in the intervening years. These figures suggest that
repurchases provide substantial liquidity to sellers in the market at the time of the buybacks. In
contrast, Brockman and Chung (2001) find that bid-ask spreads widen during repurchase periods,
and conclude that repurchases reduce liquidity.
B.
Abnormal Long-Run Rates of Return on Repurchase Trades
Our database of detailed repurchases allows us to calculate the internal rate of return
(IRR) on all of the purchases constituting the repurchase program and contrast it to the expected
CAPM return. The firm’s IRR is the rate that equates the future values of all repurchase trades
(plus accumulated dividends) with the market value of the acquired shares at the terminal date.
We use two terminal dates: the expiration date of the program and the first anniversary of the
expiration date. The benchmark for computing abnormal returns is the predicted return based on
the CAPM using a Dimson (1979) beta. The market return is the IRR of a set of purchases—
equivalent in value to the firm’s repurchases—of the market index (with dividends reinvested).
Table 2 reports the median internal rates of return of share repurchase programs. As
shown in Panel A, firms earn a median 12.57% annualized return.10 Over this period, the median
9
Because data are not available after December 2000, the figures for the year 2000 exclude shares repurchased after
that year. The totals for year 2000 programs are underestimated.
10
We also compute the means of the returns. Like the medians, the means are found to be higher for the repurchase
programs. However, because some repurchase programs had buying concentrated near the terminal date, the
annualized returns on these programs are very upward skewed (in some cases, annualized returns are over 1,000%).
11
abnormal return is 3.52%, which is significant at the 1% level. This abnormal return indicates
that the repurchase transfers wealth to non-selling shareholders. For the period ending one year
after the expiry date of the repurchase program, the median abnormal return is not significantly
different from zero. This result indicates that the outperformance is concentrated in the period of
the repurchase program.
[Insert Table 2 About Here]
Given that firms earn an abnormal return on their repurchase programs, an interesting
question is whether investors could replicate firms’ trades and also earn an abnormal return. If
the market is semi-strong form efficient and firms trade on insider information, then outside
investors should not be able to replicate firms’ abnormal performance. Outside investors face
two obstacles to replicating repurchase trades. First, firms trade anonymously and the public only
learns of the trades when they are published in either the TSX Daily Record or the OSC Bulletin.
On average, there is a four-week lag between the trade and its publication. Thus, it is very
unlikely that replication trades would occur at the same prices as firms paid. Second, firms buy
patiently whereas replication trades require greater immediacy so that they can be completed
soon after the repurchase trades. The immediacy of execution means that replication trades are
likely to create significant price impact and so reduce the profitability of copying the firm.
We measure the return to replicating each firm’s trades based on the OSC publication
dates.11 For each repurchase program, we compute the IRR for a set of purchases replicating the
firm’s published trades. We adjust the returns to account for price impact of both the purchases
and liquidation at the terminal dates. We estimate price impact betas using 30-minute time
intervals (equation (1) of Breen, Hodrick, and Korajczyk (2002)). We assume that the
hypothetical purchases are completely buyer-initiated and sales are seller-initiated.
Panels B and C of Table 2 show the internal rates of return from replicating firms’
purchases with and without price impact. Without an adjustment for price impact, the median
Given the high degree of skewness, the means are not useful in interpreting the aggregate data so they are not
reported.
11
We used the OSC Bulletin instead of the TSX Daily Record because the Bulletin is published more frequently and
contains more detailed transaction data.
12
abnormal return to the expiry date of the program is 2.48% which is significant but slightly lower
than the median firm’s return. The abnormal return to one year later is not significantly different
from zero. Panel C shows the return after adjusting for the price impact of the purchases and the
sales. The abnormal return to the expiry date is not significantly different from zero, which
shows that lags in execution and price impacts prevent replication of firms’ performance. The
fact that firms’ performance cannot be replicated suggests that firms act on insider information
and that the market is semi-strong form efficient.
C.
Tests of Supply Curve Inelasticity
We next examine whether supply curve inelasticity is an explanatory factor for the
abnormal rate of return on firms’ trades. We test for inelasticity by measuring whether the
permanent price impact of repurchase trades exceeds that of a matched sample of ordinary
trades. If the supply curve is inelastic, then the permanent price impact of repurchase trades
should be greater than that of equivalent ordinary trades (matched non-repurchase trades). The
process used to identify 62,658 individual repurchase trades from OSC and TSX databases is
described in Appendix I. We discuss in the following paragraphs: 1) the selection of equivalent
ordinary trades; 2) the estimation of the excess price impacts; and 3) the cross-sectional
regression of trade and repurchase program characteristics on excess price impacts.
Equivalent Ordinary Trades
The individual repurchase trades must be matched with equivalent ordinary trades in
order to estimate the excess price impact. Repurchase trades should be matched with trades that,
in the absence of inelasticity effects, should have the same permanent price impacts. The
following factors have been found to affect permanent price impact: insider ownership, firm size,
trade initiator, trade size, level of asymmetric information (Koski and Michaely (2000)),
liquidity, and order aggressiveness. There is no need to control for information conveyed by the
firm’s identity because repurchase trades are done anonymously (i.e., reported with a one-month
lag). To control for the first two factors we match repurchase trades with ordinary trades in the
same company. In order to control for trade initiator, we classify and match all trades as buyerinitiated, seller-initiated or neutral using the method developed by Lee and Ready (1991). We
13
find that 57.82% and 30.35% of repurchases are seller- and buyer-motivated, respectively.12
These results indicate that the repurchasing firms are net providers of liquidity to the market,
which is evidence that firms are value traders who are less aggressive than other buyers.
To control for trade size we require that the size of the matched trade be within 15% of
that of the repurchase trade. To control for the level of asymmetric information and liquidity we
choose matching trades that are proximate to the repurchase trade. The median matched trade
occurs within 20 hours of the repurchase trade (the maximum difference is five calendar days),
and so we are confident that the level of liquidity and the amount of information in the market
when the matched trade occurs is similar to the levels when the repurchase trade is executed.
Other than matching by trade initiator, it is difficult to control for order aggressiveness.
Breen, Hodrick and Korajczyk (2002) find that beyond trade size some of the most significant
determinants of price impact are factors related to aggressiveness: urgency of order execution,
whether the trader is a value investor, and whether the order is a limit order. Our data sources do
not allow us to measure these factors, and thus we must consider the potential bias from this
omission. Repurchasing firms are expected to be less aggressive than other buyers and so the
price impact of repurchase trades should be lower than the impact of the matched ordinary
trades, ceteris paribus. This will reduce the excess price impact and bias downwards our estimate
of price inelasticity.
Repurchasing firms are expected to be less aggressive than other buyers for two reasons.
First, repurchasing firms are patient—repurchases are not legally binding and firms have one
year in which to complete them. Firms are also more patient because of the TSX restriction on
buying at a price higher than the last board lot traded. Second, repurchasing firms are value
traders—they buy securities when they believe they are undervalued (Harris (2003)). That firms
12
Given the TSX prohibition on trades that occur at prices higher than the last independent trade of a board lot of
the shares, it is surprising that the proportion of seller-motivated repurchases isn’t higher. We examine whether
firms comply with this TSX rule and discover that in 11.6% of trades, firms repurchase at a price higher than that of
the last traded board lot of shares. Thus, the fact that one in eight repurchase trades do not comply with the ‘up-tick’
restriction decreases the proportion of seller-motivated repurchases.
14
are value traders is apparent from their timing ability documented in Section F and the fact that
firms buy shares at a significant discount relative to other traders.
Excess Permanent Price Impacts
Following the matching process described above, we are able to match 29,718 of the
individual OSC repurchase trades with ordinary trades.13 Table 3 reports the estimates of the raw
and excess permanent price impacts. Because the majority of repurchases are seller-initiated, it is
not surprising that the mean permanent price impacts in the periods 15 seconds, 1 minute and 30
minutes following the announcement are significantly negative.14 The raw permanent price
impact of the repurchases measured to the end of the trading day is significantly positive. This
suggests that firms have superior timing ability in their repurchases over the course of a trading
day.
[Insert Table 3 About Here]
The excess permanent price impact of the repurchases over the matched ordinary trades
is significantly positive for all four time periods following the trades. We do not distinguish
between buyer- and seller-initiated trades since in both cases the inelasticity of the supply curve
causes a positive excess permanent price impact. The mean excess permanent price impacts over
the 15 seconds and one minute immediately following the trade are 0.060% and 0.059%,
respectively. To the end of the trading day the excess permanent price impact is 0.136%. Given
that there is a median of 36 trades in each repurchase program, this suggests that over the course
13
Individual trades are extracted from approximately 85% of the 1,118 repurchase programs reported to the OSC.
The sample characteristics, including firm size and buying intensity, are not significantly different at the 5%
significance level between the subset and population of OSC-reported repurchases. The extraction process does not
appear to bias our sample characteristics.
14
Large sample sizes increase estimator precision and so yield large t-statistics. This increases the probability of
making a type I error, and researchers typically reduce the significance level of their test to account for this. Zellner
(1984) presents a method for determining an appropriate significance level for large samples using the posterior
odds ratio. Following his method, for a sample size of 2,000, a t-value of 3.74 is consistent with a 20:1 posterior
odds ratio.
15
of a repurchase program, the estimated aggregate impact of the inelasticity effect is 36 x 0.060%
= 2.16%.15
To further prove that repurchase trades have a different impact than ordinary trades, we
also analyze the excess permanent price impact of a set of insider purchases. Insider purchases
are similar to repurchases but they do not remove supply from the market. They are similar in
two respects: 1) they have an equivalent impact on the wealth of insiders; and 2) insiders should
have the same asymmetric information as the firm. The other insider purchases are obtained from
the OSC Bulletin and matched with TSE trades in the same manner as described for repurchases.
As shown in Table 3, the excess price impact of the other insider purchases is not significant.
None of the t-statistics are significant given the large sample size. Since we find a significant
excess price impact for the repurchases and not for the insiders, we attribute the results to the
supply curve inelasticity and not to any sort of information advantage firms have.
Cross-Sectional Analysis of Excess Permanent Price Impacts
To further explore the inelasticity effect, we test for factors that may explain crosssectional variation in the excess permanent price impact. The factors are: 1) shareholder
heterogeneity (due to asymmetric information); 2) liquidity; and 3) trade size.16 There is a greater
degree of asymmetric information in smaller firms (Vermaelen (1981)), which creates a higher
level of shareholder heterogeneity. The higher level of heterogeneity should lead to greater
inelasticity of supply, and so repurchases by smaller firms should induce larger permanent price
impacts. The markets for small firms are also on average more illiquid than the markets for large
firms’ shares. Following Amihud and Mendelson (1986), illiquidity should lead to greater supply
curve inelasticity. This is another reason why small firms should have greater excess permanent
price impacts.17
15
We use the 15 second price impact to eliminate confounding effects from multiple trades.
16
Hodrick (1999) identifies other reasons for greater price inelasticity: greater risk aversion, illiquidity and capital
gain lock-in. Proxies for those factors do not provide additional explanatory power in our analysis and so are
excluded for the sake of brevity.
17
We also try using relative trading volume as a measure of liquidity but it is not significant and the result is not
reported. Thus, the firm size variable more likely reflects shareholder heterogeneity than liquidity.
16
The results of the cross-sectional regression are reported in Table 4. The firm size
variable (log of market capitalization) is significant and negative for all time periods. This
indicates that smaller firms have larger excess permanent price impacts, suggesting that their
equity supply curves are more steeply sloped. This result is consistent with that of Bagwell’s
(1992) study of Dutch auction share repurchases.
[Insert Table 4 About Here]
The relationship between the excess permanent price impact and trade size involves two
offsetting effects. On one hand, the inelasticity effect should increase with trade size: a large
repurchase absorbs more of the available supply of shares and so moves the equilibrium price
further up the supply curve. On the other hand, this may be offset by the fact that repurchasing
firms are not expected to be as aggressive as other traders when they acquire large blocks of
shares. As noted above, this is especially the case with buyer-initiated repurchases because of the
TSX purchase price restriction. Because they are value traders, repurchasing firms are more
patient than other traders. They buy large blocks of shares only when the price impact is
expected to be equivalent to buying in small amounts. As a result, the excess permanent price
impact for repurchase trades may not rise as trade size increases (it may in fact shrink for buyerinitiated repurchases). The price impact related to inelasticity may be offset by the lower
aggressiveness of larger repurchase trades.
To empirically capture the different relationship between trade size and excess price
impact for buyer and seller-initiated trades, we include an interaction variable: Buyer*Trade
Size. Buyer = 1 if the trade is buyer-initiated and Buyer = 0 otherwise. Thus, the coefficient on
the Trade Size variable reflects the relationship for seller-initiated and neutral trades. The
coefficient on the interaction term indicates whether this relationship is different for buyerinitiated trades. Given the price restriction, we expect this coefficient to be negative.
As shown in Table 4, the coefficient on Trade Size is not significantly different from zero
using price impact measured at 15 seconds, 1 minute and 30 minutes following the trade. This
suggests that firms’ ability to manage price impact in large trades offsets the inelasticity effect
for seller-initiated and neutral trades; thus there is no significant relationship between excess
price impact and trade size. The significantly negative coefficient on the interaction term (Buyer
17
* Trade Size) for 15 seconds and 1 minute indicates that the relationship between excess price
impact and trade size is smaller for buyer-initiated trades than for seller-initiated and neutral
trades.
D.
Prices Paid by Repurchasing Firms
If firms have asymmetric information about their value, then they should be able to time
their purchases advantageously, and buy their shares at lower prices than uninformed traders. In
Table 5, we present three estimates of the premium that firms pay over uniformed traders. Each
premium is the difference between the volume weighted average price paid by the firm and an
estimate of the price that uninformed investors paid for shares over the same period. If firms pay
less, then the premium should be negative.
[Insert Table 5 About Here]
The first estimate of the average price paid by uninformed traders is simply the volume
weighted average price of all trades that are not repurchases during the buyback period. Panel A
of Table 5 shows the cross-sectional means and medians across the 802 repurchase programs.
The average firm paid 6.53% less than uninformed buyers and the median firm paid 4.31% less
(both values are significant at the 1% level). The second row of Panel A shows an alternative
estimate of the premium following Brockman and Chung (2001) with 1,000 bootstrap samples
for each program. The mean of the bootstrap premiums is –7.13% and the median is –6.02%.
These results are comparable to the first approach as well as to Brockman and Chung’s (2001)
results for Hong Kong repurchases.
The third estimate of the price paid by uninformed traders controls for market liquidity,
trade size, trade initiator and time of day by using only trades that have the same characteristics
as the repurchase trades. This approach uses only the OSC records that are matched with specific
TSX trades—the matching process is described in Appendix I. The price paid by firms in these
trades is compared to the price paid in non-repurchase transactions, selected according to the
following criteria: 1) they occur on a day with similar total volume (+/-25%) as the day on which
the repurchase transaction occurred; 2) they have the same trade size (+/-25%) as the repurchase
transaction; 3) they have the same type of trade initiator; and 4) they occur within one hour of the
18
time of day of the repurchase transaction. The eligible matching transactions are randomly
sampled, and a weighted average price is constructed. This procedure is repeated 1,000 times for
each repurchase program, and the resulting bootstrap average is referred to as the trade-by-trade
bootstrap premium.
Row 3 of Panel A reports the cross sectional means and medians of the trade-by-trade
bootstrap premium. The sample size is much smaller, since only about half of the OSC data were
successfully matched with TSX trade data, and not all of those had a sufficient number of
eligible matches according to criteria outlined above.18 The average premium is –4.53% and the
median premium is –2.93%, and both are significant at the 1% level. Firms pay less than other
investors even after controlling for market liquidity, trade size, trade initiator, and time of day.
Thus, we conclude that the discount is due to firms’ information advantage and resulting timing
ability.
Next, we look at cross-sectional variation in the premium. The premium is expected to
vary across both firm size and buying intensity (shares purchased as a proportion of trading
volume). Consistent with Vermaelen (1981), we suspect that large firms are more efficiently
priced than small firms because more analysts tend to follow large-capitalization stocks. Thus,
smaller firms should be able to buy at a bigger discount than larger firms. We also expect that
repurchase programs with more buying intensity should tend to pay a higher price premium. This
positive relationship stems from two sources: 1) the total price impact rises with trade size in the
presence of an upward-sloping supply curve; and 2) programs with greater buying intensity
involve more frequent repurchases and each repurchase trade generates an excess price impact.19
The discount paid by firms should be related to the discount paid by other insiders, since
repurchasing and insider buying are expected to be substitutes. Firms should buy at a large
discount when other insiders do. We investigate these relationships with the following crosssectional regression:
18
Trades were not included in the bootstrap analysis if there were fewer than 10 eligible matching trades.
19
These arguments assume that the average price paid by other investors is held constant. However, if the firm’s
purchasing raises the price paid by other investors in subsequent transactions, the premium may not increase with
greater buying intensity. Clearly, this is not the case as the premium does increase with greater buying intensity.
19
prem i = a 0 + a 1
# repurch i
+ a 2 ln MVi + a 3Other Insideri + e i
# traded i
(1)
where
= logarithm of ratio of the average repurchase price over the average price
premi
paid in all other trades during buyback program
# repurchi
= total number of shares repurchased
# tradedi
= total number of shares traded during the year of buyback program
Ln MVi
= logarithm of market capitalization
Other Insideri
= logarithm of ratio of the weighted average price paid by insiders (other than
the firm) over the weighted average price paid by outsiders.
As shown in Table 6, the coefficient on firm size is significant and negative. This
indicates that smaller firms have greater information asymmetry. The smallest decile of firms has
an average repurchase price premium of –15.16% and the largest size decile has an average price
premium of –1.16%. Table 6 also shows that buying intensity is positively related to the
repurchase premium, which is consistent with the upward sloping supply curve. The lowest
buying intensity decile of firms pays a premium of –15.67%, whereas firms in the highest decile
pay a premium of 2.49%. Finally, the repurchase premium is also positively related to the
premium paid by other insiders—firms buy at a low price when other insiders do.
[Insert Table 6 About Here]
The last result suggests that firms and insiders share a common information advantage
over other traders. This information advantage may be reduced by the first public disclosure of
their trades, resulting in: 1) fewer opportunities to buy at a discount; and 2) smaller discounts
when those opportunities arise. Thus, we might expect to see relatively less repurchasing
following public disclosure and smaller discounts (bigger premiums).
To investigate this issue, we measure the timing and concentration of repurchases during
the year of the program. A typically active repurchasing firm makes its first trade 21 (median)
20
days after announcing its repurchase program.20 The active trading period lasts 235 days. Over
that period, the typical firm spreads its trading out over 22 different trading days. On average, a
trade is revealed in the TSE Daily Record with a 34 day lag and in the OSC Bulletin with a 43
day lag. The first disclosure of the first trade typically occurs 29 days after the trade. This 29 day
period is the firm’s opportunity to trade anonymously and we call it the running period. The
running period constitutes 14% of firms’ active trading period, and during that period firms
execute 19% of their trades. The median number of shares purchased per day is 1,656 during the
running period, which is 182 shares per day larger than the median during the remaining active
period of the repurchase (the difference is significant at the 1% level). Thus, there is a tendency
for firms to front-load their purchasing. However, we test but do not find that the average (or
median) premium decreases after the running period. Thus, firms still find opportunities to
purchase at below-average prices after the running period, but they find fewer such
opportunities.
E.
Are Repurchases a Substitute for Insider Buying?
If repurchases are a substitute for insider buying, then both firms and other insiders
should buy at a discount and the discounts should be positively correlated. The correlation is
indeed positive as revealed by the positive coefficient on the Other Insider variable as discussed
in the previous section. Panel B of Table 5 reports three estimates of the premium paid by
insiders on their purchases. The three estimates use the same methods as used to compute the
premium paid by firms. When compared against the average prices paid in all other trades (row
one in Panel B), insiders buy at a price discount similar to the firms’. The estimates of the mean
(median) premium range from –4.57% (–2.51%) to –6.01% (4.01%) which is in the same range
as the estimates for the premium paid by firms. (All values are significant at the 1% level.)
If repurchases are a substitute for insider buying, then we should not observe that
insiders sell while firms purchase. During repurchase programs insiders acquire 141 million
20
The descriptive statistics reported in this paragraph refer only to firms where the first trade is publicly disclosed
before the last trade in a program is executed. 608 firms qualify as being typically active. The median excluded firm
traded only on one day.
21
shares through market purchases and exercise of options and sell 158 million shares. We analyze
whether insiders sell on the same days as their firm buys, and find that this occurs only 10% of
the time. Finally, we study the pattern of insider selling during the 12 months of the repurchase
and find that 61% of insider sales occur in the last four months of the year, whereas firms only
execute 19% of their buybacks over the same period. Thus, insider sales do not coincide with
repurchasing.
F.
A Test of the Signaling Hypothesis
We test the signaling hypothesis by analyzing whether there is an abnormal return
following program announcements and following announcements of actual shares repurchased.
In particular, we conduct a pooled cross-section time series analysis of daily abnormal returns
during share repurchase programs. To isolate the effect of announcements, we control for the
impact of the repurchase trades (as opposed to their announcement) as well as all public news
releases by firms. In particular, we include good and bad news dummies on each day when a
firm makes a press release. We gather 23,121 press releases for repurchasing firms during the
period from July 1995 to December 2000 from CANSTOCK, an electronic database of all public
newswire releases. CANSTOCK data are only available over that time period. The sample of
daily returns includes 99,299 observations covering 578 repurchase programs by 248 different
firms.
Abnormal returns are regressed against a set of dummy variables that are designed to
measure abnormal returns following key days during the repurchase year:
R i = X iβ + ε i
(2)
Where Ri is a vector of t daily abnormal stock returns for each repurchase program i.21 The
matrix, Xi, contains observations for explanatory variables for each day t for each repurchase
program i. The explanatory variables are as follows:
21
Expected returns are calculated from CAPM. Betas are estimated over the two years ending one year
prior to announcement. The daily call loan rate proxies for the risk free rate and we use the TSX 300 index as the
market proxy.
22
Ann
PreTrd
Trd
PostTrd
TSX
OSC
Good
Bad
= 1 if (Announcement Day) ≤ t ≤ (Announcement Day + 2)
= 1 if (Trade Day – 5) ≤ t < (Trade Day)
= 1 if t = Trade Day
= 1 if (Trade Day) < t ≤ (Trade Day+5)
= 1 if (TSX Record Publication Day) < t ≤ (TSX Record Publication Day+5) 22
= 1 if (OSC Bulletin Publication Day) < t ≤ (OSC Bulletin Publication Day+5)
= 1 if (Good News Day) ≤ t ≤ (Good News Day + 1)
= 1 if (Bad News Day) ≤ t ≤ (Bad News Day + 1)
The Announcement Day is the day that the firm publicly announces the repurchase
program. The Trade Day is the day of the share repurchase as recorded in the OSC Bulletin. The
TSX Record (OSC Bulletin) Publication Day is the day of the TSX (OSC) publication which
reports repurchase activity. The Good News (Bad News) Day is a day when there is a good (bad)
news press release. Good news press releases include the following: i) an earnings or dividend
increase; ii) a positive earnings revision; iii) a large contract win or order; or iv) a takeover offer.
Bad news press releases include the following: i) an earnings or dividend decrease; ii) an
earnings warning; or iii) a large loss of business.23
The results of the pooled regression are shown in Table 7. The regression controls for
differences across firms using the fixed-effects method. The coefficient on the Ann dummy is
positive and significant, indicating a positive abnormal return following program
announcements. This is consistent with the results of Ikenberry, Lakonishok and Vermaelen
(2000) who find a significant abnormal return with monthly data. While there is a significant
market reaction to the program announcement, there is no evidence of a significant reaction to
the publication of firms’ actual purchases. Neither of the coefficients on the TSX and OSC
dummy variables are significant. The market does not learn information from the announcements
of actual trades, which may be due to the fact that the announcements occur quite a long time
after the actual trades. We reject the hypothesis that the long-run abnormal return in the year
22
We use a five day window because the Daily Record and OSC Bulletin were mailed to many market participants;
thus the reaction to the publication of the information is expected to occur over an extended period.
23
We also try broader and narrower definitions of good and bad news but the results are the same as those reported.
23
following a repurchase announcement is due to the market’s reaction to the completion of the
repurchase signal.
[Insert Table 7 About Here]
The pooled regression provides additional evidence of firms’ strategic trade timing
ability. The coefficient on the PreTrd variable is negative indicating abnormal declines in the
stock price prior to repurchase trades, and the coefficient on the PostTrd variable is positive and
significant indicating abnormal gains after the trade. Firms are able to time their trades to take
advantage of short-run dips in the stock price. The pooled regression also shows a significant
abnormal decline on the trade day itself. While we might have expected a positive abnormal
return on the repurchase day to reflect price impact of firms’ purchases, we must be cognizant of
the fact that most repurchase trades are seller initiated, which puts downward pressure on the
price. The impact of the repurchase is to lessen the decline but not completely reverse it. Finally,
the good news variable is positive and significant, and the bad news variable is negative but not
significant.
IV. Conclusions
In this paper, we use a new database which provides price and quantity information about
repurchase trades. Firms repurchase shares in different amounts on different dates and so the
appropriate return measure to evaluate performance is the internal rate of return. The detailed
transaction data allow us to do this. Using data for 802 repurchase programs over the period
1987 to 2000, we estimate a median abnormal rate of return of 3.52%, which is clear evidence
that repurchases transfer wealth from tendering (e.g., selling) to non-tendering shareholders. We
examine whether the abnormal returns can be explained by the inelasticity effect, information
asymmetry or signaling hypotheses. Our analysis shows that abnormal returns can be attributed
to inelasticity effect and information asymmetry but not to signaling.
Open market repurchases permanently remove supply from the market. If the supply
curve is upward sloping, then removing supply increases the equilibrium price of the stock. This,
in turn, leads to abnormal stock returns. In support of this argument, we find that the permanent
price impacts of 29,718 repurchase trades are significantly higher than those of a matched
24
sample of ordinary trades. As further evidence, we find no significant excess price impacts to
purchases by other insiders.
We also attribute abnormal returns to firms’ use of insider information when timing their
repurchase trades. On average, they buy shares at an average discount of 6.53% to the price paid
by other buyers of the stock during the year of the repurchase program. We find that insiders buy
at similar discounts to firms and generally do not sell while firms are repurchasing shares. We
conclude that repurchases are substitutes for insider buying. We attribute the source of the
discount to the fact that firms buy on short-term dips in the stock price. We find no significant
abnormal returns (net of price impact) to a strategy of replicating firms’ trades subsequent to
their public disclosure. Thus, we conclude that the market is semi-strong efficient, and that
firms’ abnormal performance is based on insider knowledge of periodic undervaluation.
We find no evidence that abnormal returns result from signaling effects. In particular,
stocks show no significant response to publication of repurchase trades. We attribute the lack of
response to the long delay in public disclosure. We find that firms time their trades to take
advantage of short periods of undervaluation, and so the public disclosure of those trades 4-6
weeks later provides no useful information to outside investors. If the goal of public disclosure is
to reduce information asymmetry, then repurchase trades should be disclosed on a much more
timely basis to alert outside investors to the undervaluation.
25
Appendix I
In some of the analysis we need to identify which individual trades in the TSX Trade and
Quotes database correspond to repurchases reported in the OSC database. The OSC records have
two important features that make matching them with individual trades difficult. First, the OSC
records do not report the exact time of repurchase trades, which is problematic if there are
several trades of equivalent price and quantity on the same day. Second, the OSC sometimes
reports aggregated repurchase trades. For example, if Canadian National Railways bought 100 of
its shares at $39 in the morning and 100 shares at $37 in the afternoon, the OSC record might
show the firm buying 200 shares at $38. This complication means we have to consider all
possible combinations of trades on the Trade and Quote database that can comprise an OSC
record.
We wrote a computer program to determine all possible combinations of individual trades
that can comprise an OSC record. The program selects only cases in which there is a unique
match between an OSC record and a set of TSX trades. A unique match is the only combination
of trades that match the OSC record on either the OSC trade date or the four previous trading
days. We check the four previous trading days because some firms record the settlement date
rather than the actual trade date. Our search for unique matches is more extensive than that found
in Cook, Krigman and Leach (2000). Unlike Cook et al (2000), we do not limit the search to
combinations of 30 or fewer trades. We also do not stop searching for possible combinations if
we find only one combination using a particular number of trades. Of the 42,002 records in the
OSC database, this program finds that 19,280 of these can be uniquely matched with 62,658 TSX
trades.
26
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27
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28
Table 1
Summary of Repurchase Activity 1987 to 2000
This table shows the summary statistics for share repurchase programs of firms listed on the
TSX. The year of repurchase program is the year in which the program was announced. The
figures in the last three columns are averages across repurchase programs initiated during the
year. For programs announced after January 1, 2000, our database includes only repurchases
until December 31, 2000.
Number of
Share
Year of
Repurchase Repurchase
Programs
Program
1987
20
1988
21
1989
18
1990
15
1991
28
1992
33
1993
31
1994
44
1995
70
1996
65
1997
85
1998
118
1999
134
2000
120
Total/Avg
802
Shares
Shares
Aggregate
Aggregate
Repurchased Repurchased
Shares
Number of
Value of
as a %
as a %
Repurchased
Shares
Shares
of Shares
of Shares
as a %
Repurchased Repurchased
Traded
Outstanding
of Target
(in $ millions) (in millions)
$20.55
2.48
31.92
1.16
5.07
44.89
4.28
32.61
2.09
13.48
89.58
6.06
48.49
2.36
12.74
11.03
1.67
23.54
1.21
10.68
341.55
11.83
28.71
1.23
9.87
88.72
7.43
21.07
1.04
7.40
160.66
11.62
33.17
1.62
10.15
152.73
17.63
40.70
2.08
13.43
927.56
41.40
46.71
2.30
13.98
1,096.55
59.16
40.78
1.99
11.38
1,243.10
81.74
41.04
2.01
8.38
2,540.86
122.85
44.03
2.18
11.45
4,444.28
191.14
46.20
2.49
12.35
3,517.45
146.95
29.93
1.96
18.33
$14,679.49
706.26
38.97
2.02
12.25
29
Table 2
Abnormal Long-Run Rates of Return of Repurchase Programs
This table shows the summary statistics for the Internal Rate of Return (IRR) and the abnormal
rate of return calculated for each of the repurchase programs and for a strategy of replicating the
firms’ repurchases. The IRR is the return on the portfolio of repurchased shares (or replicated
repurchases) to two terminal dates: the expiry date of the program, and one year later. The
abnormal rate of return is computed as the excess over the predicted return based on the CAPM
using a Dimson (1979) beta. The market return is the IRR of a portfolio matching the size and
timing of the firm’s repurchases (or replicating purchases) but invested in the market index. The
p-values are from Wilcoxon signed rank test.
To
Expiry Date
Nobs
To 1 Year After
Expiry Date
Median
p-value
Nobs
Median
p-value
PANEL A: Repurchase Trades
Internal Rate of Return
706
12.57%
<0.0001
517
9.69%
<0.0001
Abnormal Return
704
3.52%
0.0002
516
0.06%
0.9457
PANEL B: Replication of Firms’ Repurchase Trades with No Price Impact
Internal Rate of Return
507
9.78%
<0.0001
312
9.39%
<0.0001
Abnormal Return
504
2.48%
0.0046
309
-2.96%
0.4114
PANEL C: Replication of Firms’ Repurchase Trades with Price Impact
Internal Rate of Return
507
1.95%
0.0004
312
7.03%
0.0016
Abnormal Return
504
-6.36%
0.9606
309
-5.50%
0.0522
30
Table 3
Excess Permanent Price Impacts During Repurchase Programs
Panel A compares the permanent price impact of repurchases versus a matched sample of
purchases in which firms are not the buyer. For each repurchase, we identify an ordinary trade of
the same stock that has the same characteristics (e.g., trade initiator, size and within +/- 5 days).
Panel B compares the permanent price impact of other insider purchases with those of outside
investors. Matching is done in a way similar to that for repurchase trades. The statistics shown in
the second through fourth columns are means. One asterisk indicates that the odds against the
null hypothesis of the mean equaling zero are greater than 20:1, using the posterior odds ratio.
For a sample size of 29,718, the t-critical value is 4.09 and for the sample size 4,037 the t-critical
value is 3.84.
Excess of Target
T-Statistic of
Matched
Time Following
Over Matched
Target Trade
Excess
Ordinary Trade
the Repurchase
Trade
PANEL A: Repurchase Trades (N=29,718)
15 seconds
-0.102*
-0.162*
0.060*
6.50
1 minute
-0.096*
-0.155*
0.059*
6.43
30 minutes
-0.048*
-0.131*
0.083*
7.59
To End of Day
0.056*
-0.080*
0.136*
8.89
PANEL B: Other Insider Purchases (N=4,037)
15 seconds
0.087
0.000
0.087
2.38
1 minute
0.080
-0.029
0.108
2.98
30 minutes
0.089
0.002
0.087
1.95
To End of Day
0.329*
0.247*
0.082
1.37
31
Table 4
Determinants of Excess Price Impacts of Individual Share Repurchases
This table shows the cross-sectional regression on excess permanent price impact of repurchase
trades. MV is the log of the market capitalization of the firm. Trade Size is the repurchase trade
volume divided by daily average trading volume over previous 3 months. Buyer*Trade Size is an
interaction term. Buyer=1 if the trade is buyer-initiated. One asterisk indicates that the odds
against the null hypothesis of the mean equaling zero are greater than 20:1, using the posterior
odds ratio. For a sample size of 29,448, the t-critical value is 4.09. All coefficients are multiplied
by 105. Standard errors are heteroscedasticity consistent. (T-values in parentheses.)
Predicted
Sign
Intercept
Time Following the Repurchase Trade
15 seconds
1 minute
30 minutes
To End
of Day
78.50
(6.64)*
76.10
(6.39)*
74.40
(5.95)*
88.10
(5.46)*
Ln MV
−
-3.59
(-6.73)*
-3.50
(-6.50)*
-3.31
(-5.82)*
-3.85
(-5.25)*
Trade Size
+
0.43
(0.73)
-0.07
(-0.11)
-0.83
(-1.10)
-4.10
(-3.57)
Buyer*Trade Size
−
-4.39
(-5.45)*
-4.08
(-4.80)*
-3.08
(-2.77)
-0.98
(-0.63)
29,448
29,448
29,448
29,448
0.30
0.29
0.18
0.16
Sample Size
Adjusted R-squared (%)
32
Table 5
Premium Paid (Discount) in Repurchase Programs
Panel A of this table reports various comparisons of the prices paid by firms in repurchase
programs versus the prices paid by other investors. The first row of Panel A shows the ratio of
the volume-weighted price paid by the company over the volume-weighted price paid by all
other investors in the 12-month repurchase program period. The second row of Panel A shows
the ratio based on the bootstrapped sampling technique of Brockman and Chung (2001). The
third row of Panel A shows the ratio based on a bootstrapped sampling technique but using a set
of individual trades matched by market liquidity, trade size, trade initiator and time of day.
Panels B shows comparable ratios for other insider purchases. One asterisk indicates statistical
significance at the 5% level.
Average
(%)
Median
(%)
No. of
repurchase
programs
Log of ratio of repurchase price to TSX average
-6.53*
-4.31*
802
Brockman and Chung (2001) replication
-7.13*
-6.02*
639
Trade-by-trade bootstrapped premium
-4.53*
-2.93*
389
Log of ratio of purchase price to TSX average
-5.53*
-3.40*
1,129
Brockman and Chung (2001) replication
-4.67*
-2.51*
1,027
Trade-by-trade bootstrapped premium
-6.01*
-4.01*
317
PANEL A: Repurchases
PANEL B: Other Insider Purchases
33
Table 6
Determinants of Price Premium (Discount) of Repurchase Programs
This table shows the results of a regression explaining variation in the average price paid in
repurchase programs. Premi equals the logarithm of the ratio of the average repurchase price over
the average price paid in all other trades (expressed in %) during buyback program i. # repurchi is
the total number of shares repurchased during buyback program i. # tradedi equals the total
number of shares traded during the year. MVi is the market capitalization of firm at end of month
just preceding repurchase program i, and OtherInsideri is the natural logarithm of the ratio of the
weighted average price paid by insiders (other than the firm) over the weighted average price
paid by outside investors during repurchase program i. Standard errors are heteroscedasticity
consistent. One asterisk indicates significance at the 5% level.
prem i = a 0 + a 1
# repurch i
+ a 2 ln MVi + a 3Other Insideri + e i
# traded i
Coefficient
T-Statistic
-33.38
-5.18*
#repurchi / # tradedi
0.27
4.42*
ln MVi
1.73
4.15*
Other Insideri
0.20
2.12*
Sample Size
798
Intercept
Adjusted R-squared
8.80%
34
Table 7
Pooled Cross-section Time Series Analysis of Daily Abnormal Returns in Repurchase Programs
This regression includes all repurchase programs of firms listed on the TSX from 1996 to 2000.
Daily abnormal returns are based on the CAPM. No intercept is reported because the estimation
is performed with a fixed-effects model to control for firm specific factors.
Ann
PreTrd
Trd
PostTrd
TSX
OSC
Good
Bad
= 1 if (Announcement Day) ≤ t ≤ (Announcement Day + 2)
= 1 if (Trade Day – 5) ≤ t < (Trade Day)
= 1 if t = Trade Day
= 1 if (Trade Day) < t ≤ (Trade Day+5)
= 1 if (TSX Record Publication Day) < t ≤ (TSX Record Publication Day+5)
= 1 if (OSC Bulletin Publication Day) < t ≤ (OSC Bulletin Publication Day+5)
= 1 if (Good News Day) ≤ t ≤ (Good News Day + 1)
= 1 if (Bad News Day) ≤ t ≤ (Bad News Day + 1)
Coefficents are multiplied by 104. One asterisk indicates that the odds against the null hypothesis
of the mean equaling zero are greater than 20:1, using the posterior odds ratio.
Coefficient Value
T-Statistic
Ann
66.66
5.33*
TSX
3.65
0.63
OSC
0.12
0.02
PreTrd
-20.50
-5.42*
Trd
-49.80
-11.08*
PostTrd
38.17
10.01*
Good
71.74
8.37*
Bad
-34.20
-1.79
Adjusted R-squared
0.32%
Number of Observations
99,298
35