Electronic copy available at: http://ssrn.com/abstract=1473942
The Cost of Illiquidity:
Evidence from After-Hours Trading
Brian Walkup
University of Florida
September 9, 2009
Abstract
I use after-hours trading (post-close and pre-open) to examine the cost of finding liquidity in an
illiquid market. Using a large sample of after-hours trades from the three major U.S. stock
exchanges I determine the amount of price reversal that occurs when liquidity returns at the open
of normal trading hours. The size of the reversal is statistically and economically significant
with approximately 40%-65% of the after-hours price change reversing at the time of the
opening trade for the next trading day. However, during after-hours sessions with significantly
increased trading this reversal shrinks considerably, even becoming a momentum effect in
certain conditions. These days of heavy trading likely represent days in which an information
event has occurred outside of regular trading hours and therefore a price reversal would not be
expected as the price is reacting to the new information. This study suggests that those looking
for a large amount of liquidity in an illiquid market (such as the after-hours market) are forced to
pay a large premium for the liquidity.
Electronic copy available at: http://ssrn.com/abstract=1473942
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
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Introduction
The three major U.S. stock markets (New York Stock Exchange, Nasdaq, and American
Stock Exchange) all operate from 9:30am to 4:00pm on trading days. Outside of these normal
hours of operations information is still revealed and trades can still occur. However, the after-
hours market doesn’t come close to matching the liquidity available while the major exchanges
are open. Due to the lack of liquidity, those making trades during the after-hours sessions pay a
high liquidity premium to execute a trade.
This paper looks at the size of the price reversal/momentum when the market opens for
trading after there has been a price movement during the after-hours session. Due to the lack of
liquidity available after-hours, when liquidity is needed in one direction trades will have to be
executed at prices further and further away from the closing price of the prior day in order to be
able to find the liquidity to fulfill the orders. If the change in the price over the after-hours
session is mostly the result of a significantly larger liquidity premium outside of regular trading
hours, then we should expect to see a reversion back towards the original closing price from the
previous trading day when the market opens at 9:30am. However, if the change in price is the
result of new information (whether public or short-lived private information) being priced, then
we should not expect to see a price reversion.
I look at a large sample of stocks from all three U.S. exchanges and use trade-by-trade data
from the Trade and Quote database (TAQ). After-hours returns are calculated as well as the
stock’s price change from the last after-hours trade to the open price once the market opens for
trading. Multiple regressions are used to look at the impact of after-hours returns on the opening
price at the beginning of the next trading day as well as the price movement during the first hour
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
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of the trading day. Control variables include firm size, sign of the after-hours return, whether or
not there was a significant increase in after-hours trading during that session, whether or not
there was a single large trade that dominated the after-hours trading, and whether or not the after-
hours session took place over a weekend.
There are multiple hypothesis that can be formed regarding how the after-hours price change
of a stock could impact the opening price for the next trading day. Many of the trades made
outside of regular trading hours are likely to be liquidity based such as funds re-balancing. They
also could be based on new information being revealed publicly while the markets are closed,
such as an after-hours earnings announcement. It is also likely that many of the trades executed
after-hours are based on short-lived private information. If the prices are being shifted due to
liquidity demands, we should see a reversal due to the increased cost of finding liquidity after-
hours. However, if the trades are information based it is not likely that we will see this reversal
as there is information driving the price in a direction.
The results of this paper support the hypothesis that there is a significant increase in the cost
of trading associated with the illiquidity of the after-hours market. I show that returns that occur
outside of trading hours tend to reverse themselves at the open of trading the next trading day.
This is likely the effect of a high cost of demanding liquidity in the after-hours market.
However, if there is a high probability that new information was revealed (proxied by an increase
in after-hours trading of more than two standard deviations) then the reversal essentially
disappears.
The magnitude of the reversal is quite significant. If after-hours trading volume for a stock
during an after-hours session falls within the normal range (not more than a two standard
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deviation increase in trading volume) then approximately 40-65% of the after-hours price change
is reversed immediately upon the opening of regular trading hours. The reversal is statistically
stronger for small market capitalization stocks (approximately 7.7% larger reversal than large
market capitalization stocks), during after-hour sessions that occur over weekends
(approximately 6.6% larger reversal than non-weekend after-hours sessions), and during after-
hours session with negative after-hours returns (approximately 12.4% larger reversal than during
positive after-hours sessions).
The rest of the paper is organized as follows: In Section II I give an overview of the existing
literature on the microstructure of the after-hours market. Section III gives the details of the data
selection. Section IV discusses the findings of the paper. Finally, Section V concludes the paper
with a brief discussion of potential extensions of the paper.
I. Overview of Existing After-Hours Literature
Much of the early literature regarding after-hours trading dealt with stocks that were listed on
at least one stock market outside of the U.S. as well as being listed on one of the major U.S.
exchanges. For example, Neumark, Tinsley, and Tosini (1991) found that price changes on the
U.S. exchanges were adequately incorporated the next day in the international markets, but the
opposite wasn’t always the case. However, after-hours trading has come a long way since these
early articles and trading jointly listed stocks on an alternative exchange is no longer the only
manner of trading a stock after-hours. After-hours trading began in 1975 but was limited to only
institutional investors and large block trades. It wasn’t until 1999 that regular investors were
allowed to trade outside of the normal 9:30am – 4pm trading day. Due to this fundamental
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
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change, I will focus on the more modern strand of the literature which looks at the after-hours
market since the rule change in 1999.
One of the most important papers in the current after-hours literature is Barclay and
Hendershott (2003). This paper is not only important because of its overall findings, but also
because it has the most comprehensive summary statistics concerning after-hours trading. They
show a clear picture of after-hours trading relative to regular trading hours. The data used by
Barclay and Hendershott contains all after-hours trades and quotes for Nasdaq-listed stocks for
212 trading days during 2000. They show that these stocks average around 25,000 after-hours
trades per day. This represents almost 4% of the daily total trading volume on average.
Throughout their study they focus on the 250 highest-volume stocks from their sample, which
they show represents about 75% of all after-hours trading. Barclay and Hendershott show in
Figure 1 of their paper that after-hours trading is strongest directly before the open and after the
close of regular trading hours. It also shows that volatility follows the same pattern, but with a
much less severe drop-off during after-hours trading. The main finding of Barclay and
Hendershott (2003) is that the amount of information on a per-trade basis during after-hours
trading is significantly higher than during regular trading hours. Therefore, even though the
volume of trading is significantly lower, there is still strong price discovery outside of regular
trading hours.
Barclay and Hendershott also make some other interesting observations about after-hours
trading. First, they argue that the lack of popularity of after-hours trading likely stems from their
finding that there is a higher probability of information-based trades on a per-trade basis outside
of regular hours. Smaller liquidity traders prefer to try and trade together to minimize the
likelihood of trading against informed traders and are therefore better off pooling together during
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
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regular trading hours when the per trade likelihood of informed trading is lower and trading costs
are smaller. They also touch on how the different characteristics of after-hours trading could
affect whether or not a firm releases earnings announcement during regular trading hours or
after-hours. In their paper they claim, “The noisier stock prices and less efficient price discovery
after hours could affect firms’ decisions about the timing of their public announcements, such as
earning announcements. Announcements made after hours are likely to generate greater
volatility and larger price reversals than are announcements made during the trading day.”
(Barclay and Hendershott, 2003, p. 1070) The idea of after-hours trading affecting firms’
decisions on public announcements has generated some interest in recent years including Greene
and Watts (1996), Bagnoli et al (2006), and others.
In Barclay and Hendershott (2004) the authors look at after-hours trading and its effect on
market microstructure characteristics. They look specifically at how the lack of trading outside
of normal trading hours affects trading costs through bid-ask spreads. Their results are
consistent with what should be expected. The lack of liquidity in the after-hours market results
in higher trading costs. Both quoted and effective spreads increase significantly outside of
normal trading hours. The percentage effective half spread moves from an average of
approximately 0.17% during the trading day to approximately 0.6% after-hours. They also find
that spreads become significantly larger for stocks with lower trading volume. Barclay and
Hendershott then break the bid-ask spread down into its three fundamental components:
inventory holding costs, order processing costs, and adverse selection costs (as found in Stoll,
1989). They find that the adverse selection component of the spread is 15 times larger during the
pre-open than during normal trading hours and 7 times larger during the post-close than during
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
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normal trading hours. They sum up why they feel after-hours trading will never grow much
beyond its current low level of trading with the following thoughts:
“The magnitude of the liquidity externalities suggest that exchanges have little
incentive to expand their trading hours due to competitive pressure. Despite the
wide spreads, profit opportunities for dealers to provide liquidity appear limited
and the high adverse selection and low trading activity make monitoring the
market costly. The wide spreads should discourage investors from trading after
hours unless they have very high liquidity demands or short-lived private
information. Finally, the investor protections, for example, warnings of high
trading costs and volatility, currently employed by brokers and regulators should
be continued.” (Barclay and Hendershott, 2004, p. 709)
There are relatively few other papers that look at the current after-hours trading market. One
such paper that does is Zdorovtsov (2003). Zdorovtsov looks mostly at the volatility over the
after-hours period and considers the private information hypothesis and the public information
hypothesis. One of the main findings of the paper is that a large amount of trading volume in the
pre-open period coincides with more volatility in overnight returns and less volatility during
regular trading hours. According to the author this represents a shift in the price discovery
toward the pre-open hours. Another important finding of the paper is that the greater the flow of
public information after hours the greater the after-hours volatility (and the same is true for
during normal trading hours). Finally, Zdorovstov finds evidence (as in prior studies) that
information releases outside of trading hours are of greater economic significance than
information releases during trading hours.
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II. Data Selection and Variable Definition
I use transaction level TAQ data for all three U.S. exchanges from January 1, 2006 to
December 31, 2006. All of the stocks traded on all three exchanges are sorted by exchange and
then placed into deciles based on annual trading volume. Standard screens are used to eliminate
REITs, trusts and holding groups. A random sample of 50 stocks is selected from deciles four
through ten for each exchange, leaving a sample of just over 1,000 firms. Deciles one through
three are eliminated due to their very low frequency of after-hours trades (similar to Barclay and
Hendershot, 2003). All penny stocks (stocks traded at any point during the year for less than $5)
are eliminated from the sample. This step is taken to ensure that the after-hour returns are not
being caused in large part by the bid-ask bounce and the fact that there is almost no liquidity for
these stocks in the after-hours market. This is more likely to be the case for stocks with low
prices. The remaining sample consists of 617 firms. Prior to calculating after-hours returns all
prices are adjusted for splits and dividends.
I calculate the after-hours return as:
/
represents the after-hours return for firm i on day t, represents the
price of the last after-hours trade prior to the market opening for firm i on day t, and is
the closing price for firm i on day t-1. Out of a potential 155,484 after-hours returns (617 firms *
252 trading days) there are 140,997 days that I am able to calculate an after-hours return (not all
firms have non-zero after-hours trading every-day and one day per firm is lost in order to be able
to calculate an overnight return). Summary statistics for the complete sample of after-hours
returns are shown in Table 1.
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The dependent variable in my regressions represents the change in price from the last
after-hours return to the opening price when regular trading resumes at 9:30am the next trading
day. It is calculated as follows:
/
Where is the dependent variable representing the change in price for firm i on
day t from the last after-hours trade executed to the opening price at 9:30am when the exchange
opens for trading. represents the price of the stock for firm i when the market opens for
trading on day t and is the price of the last after-hours trade for firm i on day t.
Control variables used in regressions include:
SmallMarketCap: Dummy variable that equals 1 if the stock is in MarketCap deciles 1, 2,
or 3; and 0 otherwise
o MarketCap: Average shares outstanding for January 2006 times average share
price for January 2006
SmallMarketCapInteraction: SmallMarketCap * AHreturn
AHnegativeDum: Dummy variable that is 1 if AHreturn < 0; and 0 otherwise
AHnegativeInteraction: AHnegativeDum * AHreturn
LargeNumberOfTradesDum: Dummy variable that equals 1 if there was more than a 2
standard deviation increase in the number of trades during that after-hours trading session
relative to the mean number of trades during all after-hours trading sessions for that stock
during the year 2006; and 0 otherwise
LargeNumberOfTradesInteraction: LargeNumberOfTradesDum * AHreturn
OneLargeTradeDum: dummy variable which equals 1 if there is a single trade during that
after-hours session larger than the mean after-hours trade size for that stock plus 2
standard deviations; and 0 otherwise
OneLargeTradeInteraction: OneLargeTradeDum * AHreturn
WeekendDum: dummy variable which equals 1 if the after-hours session is from Friday
after 4pm to Monday at 9:30am; and 0 otherwise
WeekendInteraction: WeekendDum * AHreturn
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
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One distinct way I look at the data for a robustness check is by eliminating trades with
after-hours price movement close to 0%. It is likely that in many of these cases there is very
little need for liquidity after-hours. There may be only a few trades executed while the
exchanges are closed and therefore the price remains relatively close to the closing price from
the prior day. In these cases a price reversal wouldn’t necessarily be expected. This could affect
the model. Therefore I remove these observations from the sample to see if the results of the
model are affected.
Another robustness check that I utilize is to re-run the regressions looking at longer
period returns. The dependant variable is changed from the very short time interval of
ReturnOpen to time intervals of 5 minutes, 15 minutes, 30 minutes, and 1 hour from the opening
of trade. This allows me to see whether or not the reversal is maintained as regular trading
continues through the early morning trading. These returns are calculated as follows:
Return5Min = /
Return15Min = /
Return30Min = /
Return1Hour = /
I start by eliminating any days in which the after-hours return is less than . The
remaining dataset consists of 54,445 days with after-hours returns greater than 0.25% or less than
-0.25%. I do the same procedure again cutting the dataset into after-hours returns greater than
0.5% or less than -0.5% which consists of 33,666 observations. This is once again done using
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
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1% as the cutoff (16,015 observations) and 2% as the cutoff (5,678 observations). Summary
statistics for each of these cuts are shown in Table 2.
III. Results
A. Full Sample Results
For the initial set of results I utilized my entire sample of 142,371 after-hours sessions from
617 firms. OLS regressions are run with ReturnOpen as the dependent variable. First I use only
AHreturn as the explanatory variable. From there other explanatory variables are added. The
initial assumptions on signs would be as follows (No prediction will be made on dummy
variables since the effect is likely to be opposite on positive AHreturns and negative AHreturns.
Therefore, the sign is ambiguous.):
AHreturn : Negative
o The illiquidity of the after-hours market is expected to cause a reversal of
prices for the open of trading. Since a reversal is expected the sign should be
negative.
SmallMarketCapInteraction: Negative
o If the company associated with the stock has a small market cap then it is
likely that the after-hours market for the shares of the company’s stock would
be even more illiquid causing a larger reversal. Therefore the coefficient is
expected to be negative.
AHnegativeDumInteraction : No prediction
o No prediction is made on the interaction term between AHnegativeDum and
AHreturn. This simply allows the slope of the reversal relative to the after-
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hours return to be different for negative after-hours returns than positive after-
hours returns. No prediction is going to be made about the direction of this
difference in slope.
LargeNumberOfTradesInteraction : Positive
o If there is a significant increase in the number of trades being executed during
the after-hours trading session then it is more likely that an information event
has occurred. In the event of information being released outside of trading
hours, then the price is being adjusted for the new information and we
therefore should not expect as large of a reversal (and possibly even some
momentum rather than reversal). Any reversal that would normally be found
(which would have a negative sign) would need to be offset, therefore making
the expectation on LargeNumberOfTradesDum positive assuming a net
reversal is found in the regression outside of the LargeNumberOfTradesDum
variable.
OneLargeTradeInteraction : No prediction
o In the case that there is a single large trade during an after-hours session the
prediction could go either way. A claim could be made that there is a high
probability that a single large trade during an after-hours session could be
inside information based. In this case the prediction would depend on how
short-lived the information is. If it is extremely short-lived and therefore
becomes public by the opening of trading then we should see no reversal and
therefore a positive sign on OneLargeTradeInteraction. However, if it is not
revealed until after the opening than it can be treated as a liquidity trade and
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should result in more reversal, therefore giving it a negative sign. The
argument could also be made that if there is only one single large trade then it
is likely liquidity based. The argument could be that if it was based on public
information there would likely be other large trades, while if it was inside
information it would likely be split into a series of small trades. Therefore a
single large trade would be liquidity based and result in increased reversal
giving OneLargeTradeInteraction a negative sign.
WeekendInteraction : No prediction
o No prediction is being made about the impact of the after-hours trading
session falling on a weekend (Friday close of regular trading to Monday open
of regular trading).
The results for the regressions on the full sample are shown in Table 3. All of the
independent variables theoretically signed have the predicted signs and are statistically
significant at the 99% significance level. Figure 1 shows the expected amount of reversal given
differing after-hour returns. It is quite evident from Figure 1, as well as from Table 3, that the
most important determinant in deciding if a large reversal will take place is whether or not there
is large number of trades (greater than 2 standard deviation increase from the mean number of
trades). Given that the variable representing a large number of trades should be a good signal of
some form of public information event these results are quite consistent with the lack of liquidity
and high cost of finding liquidity during after-hours trading story. If the trading levels are
normal, a very significant portion of the price change during the after-hours session is
immediately reversed upon the opening of regular trading hours at 9:30am the next morning.
Approximately 40-65% (depending upon factors such as whether or not the firm is a small
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
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market cap firm, whether or not the after-hours return was negative, etc) of the after-hours price
movement can be explained as simply an additional cost of liquidity during an illiquid market
given that it is immediately reversed once normal liquidity resumes. If there is an information
event then liquidity becomes less of an issue and the reversal effect becomes much less
significant as the price is being moved closer to the true value given the new information.
The after-hours return variable alone is extremely statistically significant and shows that
approximately 44% of after-hours price movement is reversed if there is positive price
movement with approximately an additional 12% reversal if the after-hours return is negative
(giving a reversal of 56%). A potential explanation for negative after-hours returns experiencing
a larger reversal is that those being forced to sell for liquidity during the after-hours sessions are
likely in more of a “must-sell” mode than those buying are in a “must-buy” mode and therefore
are willing to pay higher premiums to find the liquidity. The other key variables (the interaction
terms) also come through as statistically significant. As predicted, small market capitalization
firms tend to experience larger reversals as liquidity is harder to find. The coefficient on the
SmallMarketCapInteraction shows an expected 7.7% larger reversal for small market cap firms.
A stock having a single large trade during the after-hours session results in approximately a 9.5%
smaller reversal. The reversal effect is approximately 6.6% stronger following a weekend.
B. Restricted Sample Results – After-Hour Return Cutoffs
A large portion of the observations have very little after-hours price movement. In fact, over
60% of the observations have price changes of less than 0.25% during the after-hours session. In
these cases it is likely that there wasn’t much need for liquidity outside of the regular trading
hours. If there are only a few trades made and the price has very little movement, it becomes
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less likely that we will see a significant reversal when the market opens at 9:30am and regular
liquidity resumes. These observations could affect the model. Therefore, I rerun the regressions
after making restrictions on the size of the after-hours price movement to determine if the results
are significantly affected.
The first step taken is to eliminate all observations during which the after-hours return is less
than the absolute value of 0.25%. The results of these regressions can be found in the first
column of Table 4 (also shown in Figure 2). After removing approximately 60% of the
observations which were clustered around an after-hours price change of 0% the results of the
regressions have not changed much. The magnitude of the price reversal is still around 40%-
65% of the after-hours price change. The explanatory variables all remain of the same sign and
nearly the same magnitude. The t-statistics fall due to the significantly decreased number of
observations. However, the explanatory variables all remain extremely significant statistically.
The adjusted R2 of the model increases as it is now able to explain a larger amount of the
variation in the reversal.
I then continue to reduce the observations clustered near an after-hours price movement of
0% from the model by eliminating all observations for which the after-hours return is less than
the absolute value of 0.5%. The results for these regressions are shown in the second column of
Table 4 and can be seen in Figure 3. Once again the magnitude of the results is relatively
unchanged while the statistical significance of the model and the independent variables stay very
high. This same procedure is repeated again using the absolute value of 1% as the cutoff for
AHreturn (results in the third column of Table 4 and shown in Figure 4) and once more for 2%
as the cutoff for AHreturn (results in the fourth column of Table 4 and shown in Figure 5). The
magnitude continues to be relatively unchanged as the sample size is reduced and the clustered
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observations with very little movement are peeled away. Despite the shrinking sample size the
statistical and economic significance remain large. From comparing all of the models utilizing
different cutoffs, it appears that the clustering around an after-hours price change of 0% does not
significantly affect the results of running the regression on the whole sample. Regardless of
whether the regression is run on the full sample or a restricted sample, it still remains evident that
there is a large price reversal of around 40-65% conditional on there not being abnormally high
trading.
C. Longer Time-Length Returns: Return5Min, Return15Min, Return30Min, Return1Hour
As another robustness check, the time-length of the return is expanded from simply the
change between the last after-hours trade and the opening trade of the next trading day. I look at
5-minute returns and 1-hour returns (15 and 30 minute returns also used with similar results but
excluded from the paper to avoid overkill). The 5-minute return regression results are available
in Table 5 and the 1-hour returns regression results are available in Table 6. The expected
amount of reversal given differing after-hours returns are available in Figures 6 and 7 for the 5-
minute returns and 1-hour returns, respectively. The results from these regressions show that the
magnitude of the reversal remains relatively unchanged as the regular trading hours take place
the morning after the after-hours price change. As was the case with the earlier regressions, even
after 5 minutes or 1 hour the magnitude of reversal is still approximately unchanged with
approximately 40-60% of the after-hours price change being reversed if there is not a large
amount of trading. It is also still the case that a significant increase in the amount of trading
results in this reversal decreasing significantly, and even becoming a slight momentum effect
depending on other factors. These results show that is not simply the opening trade that
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experiences this reversal. Instead, the reversal is more permanent and continues as trading picks
up throughout the morning.
IV. Conclusion
This paper demonstrates the importance and magnitude of the costs associated with trading in
an illiquid market. When traders are forced to find liquidity when there isn’t much available,
they can tend to have a strong impact on the price until the liquidity returns to normal levels.
The after-hours market is a perfect testing ground for this impact. The liquidity found in the
after-hours market is substantially less than the liquidity found during regular trading hours.
Over a short period of time the liquidity is restored (at 9:30am when the markets open) and we
would expect to see a reversal of the price changes that occurred after-hours if the prices were
being mostly driven by liquidity demands. However, in the cases where the price is being moved
by information rather than liquidity demands, we would expect this reversal to become much less
significant and potentially go all the way to zero or become a momentum effect.
I look at a large sample of after-hours trading and calculate the return from the close of
trading the previous trading day until the last after-hours trade. I then calculate the change in
price from the last after-hours trade to the opening price when trading resumes the next trading
day. Using this data, as well as other explanatory variables, I find that there is a significant
reversal of the magnitude of 40%-65% when the regular trading hours begin and high liquidity
returns. This reversal becomes much smaller and, depending on other variables, can even
become a slight momentum effect when there is a significant increase in the amount of after-
hours trading. This increase in trading has a high probability of signaling an information event.
Therefore the significant lessening of the reversal effect, and even potential momentum effect, is
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expected given that the price is moving during the after-hours session in response to the new
information. The price is becoming more efficient and a reversal would not be needed when
regular trading hours resume the next trading day.
My results would tend to imply that there are abnormal potential profits to be made by being
one of the traders providing liquidity during the after-hours sessions. This is in contrast to the
results of Barclay and Hendershott (2004) where they claim that the dollar profit per share is the
same after-hours as it is during the day. They look at the bid/ask spread and break it down into
its fundamental components and find that the profit from the spread is approximately the same
after-hours as it is during the trading day. I believe that it would be worthwhile to look into this
further with my results to identify whether there are excess profits to be made by providing
liquidity after-hours relative to providing liquidity during the trading day.
Another possible extension to my paper would be to identify which observations are linked to
the release of new information being revealed outside of regular trading hours. By identifying
instances linked to information events, such as quarterly earnings announcements, being made
outside of regular trading hours, I could more efficiently test the exact reversal for non-
information event after-hours sessions verse information event after-hours sessions. However,
given that it is impossible to precisely identify private information events, I would not be able to
determine the impact that private information events have on the reversal/momentum of after-
hours returns once regular trading hours resume.
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Crash Hangovers.” The Journal of Finance. Vol 46 No 1. pp 159-178.
Patell, James and Mark Wolfson. 1982. “Good News, Bad News, and the Intraday Timing of
Corporate Disclosures.” The Accounting Review. Vol 57 No 3. pp 509-527.
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
- 19 -
Penman, Stephen. 1987. “The Distribution of Earnings News Over Time and Seasonalities in
Aggregate Stock Returns.” Journal of Financial Economics. Vol 18 No 2. pp 199-228.
Stoll, Hans R. 1989. “Inferring the Components of the Bid-Ask Spread: Theory and Empirical
Tests.” Journal of Finance. Vol. 44 No 1. pp 115-134.
Zdorovtsov, Vladimir. Dec 2003 version. University of South Carolina Working Paper. “Firm-
Specific News, Extended-Hours Trading and Variances over Trading and Nontrading
Periods.”
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
- 20 -
Table 1. Summary Statistics for Whole Sample
This table shows summary statistics for the entire sample of after-hours sessions.
ReturnOpen is calculated as / . AHreturn is calculated
as / where represents the price of the last after-hours trade prior to the
market opening for firm i on day t, and is the closing price for firm i on day t-1. SmallMarketCap is a dummy
variable which equals 1 if the stock is in MarketCap deciles 4, 5, or 6 and 0; otherwise. AHnegativeDum is a
dummy variable that equals 1 if AHreturn < 0; and 0 otherise. LargeNumberOfTradesDum is a dummy variable
which equals 1 if there was more than a 2 standard deviation increase in the number of trades during that after-hours
trading session relative to the mean number of trades during all after-hours trading sessions for that stock during the
year 2006; and 0 otherwise. OneLargeTradeDum is a dummy variable which equals 1 if there is a single trade
during that after-hours session larger than the mean after-hours trade size for that stock plus 2 standard deviations;
and 0 otherwise. WeekendDum is a dummy variable which equals 1 if the after-hours session is from Friday after
4pm to Monday at 9:30am; and 0 otherwise.
Entire Sample of After-Hour Returns
Variable Observations Mean
Percent of Variable
Equal to 1
Standard
Deviation
Ahreturn 140997 0.043% 1.20%
ReturnOpen 140997 0.003% 1.00%
Return5Min 127550 0.007% 1.14%
Return1Hour 140997 -0.018% 1.54%
SmallMarketCapDum 140997 2.105%
AHnegativeDum 140997 41.732%
LargeNumberOfTradesDum 140997 2.394%
OneLargeTradeDum 140997 11.444%
WeekendDum 140997 21.505%
Trade Size (in shares) 2372080 4742.6
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
- 21 -
Table 2. Summary Statistics for Restricted Samples
This table shows summary statistics for the restricted samples of after-hours sessions.
ReturnOpen is calculated as / . AHreturn is calculated
as / where represents the price of the last after-hours trade prior to the
market opening for firm i on day t, and is the closing price for firm i on day t-1. SmallMarketCap is a dummy
variable which equals 1 if the stock is in MarketCap deciles 4, 5, or 6and 0 otherwise. AHnegativeDum is a dummy
variable that equals 1 if AHreturn < 0 and 0 otherise. LargeNumberOfTradesDum is a dummy variable which
equals 1 if there was more than a 2 standard deviation increase in the number of trades during that after-hours
trading session relative to the mean number of trades during all after-hours trading sessions for that stock during the
year 2006; and 0 otherwise. OneLargeTradeDum is a dummy variable which equals 1 if there is a single trade
during that after-hours session larger than the mean after-hours trade size for that stock plus 2 standard deviations;
and 0 otherwise. WeekendDum is a dummy variable which equals 1 if the after-hours session is from Friday after
4pm to Monday at 9:30am; and 0 otherwise.
Panel A : AbsValue(Ahreturn) > 0.25%
Variable Observations Mean
Percent of Variable
Equal to 1
Standard
Deviation
Ahreturn 54445 0.100% 1.93%
ReturnOpen 54445 -0.005% 1.34%
Return5Min 49265 0.006% 1.53%
Return1Hour 54445 -0.040% 1.93%
SmallMarketCapDum 54445 3.014%
AHnegativeDum 54445 47.182%
LargeNumberOfTradesDum 54445 4.186%
OneLargeTradeDum 54445 11.801%
WeekendDum 54445 21.99%
Panel B : AbsValue(Ahreturn) > 0.5%
Variable Observations Mean
Percent of Variable
Equal to 1
Standard
Deviation
Ahreturn 33666 0.158% 2.44%
ReturnOpen 33666 -0.020% 1.58%
Return5Min 30530 0.013% 1.17%
Return1Hour 33666 -0.035% 1.66%
SmallMarketCapDum 33666 3.327%
AHnegativeDum 33666 45.925%
LargeNumberOfTradesDum 33666 5.861%
OneLargeTradeDum 33666 12.057%
WeekendDum 33666 22.16%
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
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Panel C : AbsValue(Ahreturn) > 1%
Variable Observations Mean
Percent of Variable
Equal to 1
Standard
Deviation
Ahreturn 16015 0.295% 3.44%
ReturnOpen 16015 -0.051% 2.08%
Return5Min 14489 0.013% 1.17%
Return1Hour 16015 -0.049% 1.96%
SmallMarketCapDum 16015 3.928%
AHnegativeDum 16015 43.809%
LargeNumberOfTradesDum 16015 9.996%
OneLargeTradeDum 16015 12.182%
WeekendDum 16015 22.44%
Panel D : AbsValue(Ahreturn) > 2%
Variable Observations Mean
Percent of Variable
Equal to 1
Standard
Deviation
Ahreturn 5678 0.547% 5.46%
ReturnOpen 5678 -0.079% 3.02%
Return5Min 5065 0.027% 1.53%
Return1Hour 5678 -0.059% 2.51%
SmallMarketCapDum 5678 4.914%
AHnegativeDum 5678 42.515%
LargeNumberOfTradesDum 5678 19.954%
OneLargeTradeDum 5678 12.011%
WeekendDum 5678 22.31%
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
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Table 3. Regression Results for Whole Sample
This table shows regression results for the entire sample of after-hours sessions.
The dependent variable in each regression is ReturnOpen calculated as:
/
AHreturn is calculated as / .where represents the price of the last after-
hours trade prior to the market opening for firm i on day t, and is the closing price for firm i on day t-1.
SmallMarketCap is a dummy variable which equals 1 if the stock is in MarketCap deciles 4, 5, or 6 and 0 otherwise.
SmallMarketCapInteraction is calculated as SmallMarketCap times AHreturn.AHnegativeDum is a dummy variable
that equals 1 if AHreturn < 0 and 0 otherise. AHnegativeInteraction is calculated as AHnegativeDum times
AHreturn. LargeNumberOfTradesDum is a dummy variable which equals 1 if there was more than a 2 standard
deviation increase in the number of trades during that after-hours trading session relative to the mean number of
trades during all after-hours trading sessions for that stock during the year 2006; and 0 otherwise.
LargeNumberOfTradesInteraction is calculated as LargeNumberOfTrades * Ahreturn. OneLargeTradeDum is a
dummy variable which equals 1 if there is a single trade during that after-hours session larger than the mean after-
hours trade size for that stock plus 2 standard deviations; and 0 otherwise.. OneLargeTradeInteraction is calculated
as OneLargeTradeDum * Ahreturn. WeekendDum is a dummy variable which equals 1 if the after-hours session is
from Friday after 4pm to Monday at 9:30am; and 0 otherwise. WeekendInteraction is calculated as WeekendDummy
* Ahreturn.
T-statistics are given in parenthesis. * represents statistical significance at the 90% confidence level. ** represents
statistical significance at the 95% confidence level. *** represents statistical significance at the 99% confidence
level.
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
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Observations : Full Sample
Dependent Variable: ReturnOpen
Indep. Variable Expected
Sign
Intercept N/A 0.00244
(0.65)
AHreturn Negative -0.44156***
(-107.98)
SmallMarketCapDum N/A 0.01538***
(2.81)
SmallMarketCapInteraction Negative -0.07706***
(-19.97)
AHnegativeDum N/A 0.00714
(1.39)
AHnegativeInteraction N/A -0.12381***
(-29.03)
LargeNumberOfTradesDum N/A -0.12227***
(-7.81)
LargeNumberOfTradesInteraction Positive 0.49613***
(123.94)
OneLargeTradeDum N/A -0.00578
(-0.82)
OneLargeTradeInteraction N/A 0.09533***
(11.91)
WeekendDum N/A -0.04388***
(-7.96)
WeekendInteraction N/A -0.06584***
(-14.48)
N 140997
Adjusted R2 0.2572
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
- 25 -
Table 4. Regression Results for Restricted Samples
This table shows regression results for the restricted samples of after-hours sessions.
The dependent variable in each regression is ReturnOpen calculated as:
/
AHreturn is calculated as / where represents the price of the last after-hours trade prior to the market opening for firm i
on day t, and is the closing price for firm i on day t-1. SmallMarketCap is a dummy variable which equals 1 if the stock is in MarketCap deciles 4, 5, or 6
and 0 otherwise. SmallMarketCapInteraction is calculated as SmallMarketCap times AHreturn.AHnegativeDum is a dummy variable that equals 1 if AHreturn <
0 and 0 otherise. AHnegativeInteraction is calculated as AHnegativeDum times AHreturn. LargeNumberOfTradesDum is a dummy variable which equals 1 if
there was more than a 2 standard deviation increase in the number of trades during that after-hours trading session relative to the mean number of trades during
all after-hours trading sessions for that stock during the year 2006; and 0 otherwise. LargeNumberOfTradesInteraction is calculated as LargeNumberOfTrades
* Ahreturn. OneLargeTradeDum is a dummy variable which equals 1 if there is a single trade during that after-hours session larger than the mean after-hours
trade size for that stock plus 2 standard deviations; and 0 otherwise. OneLargeTradeInteraction is calculated as OneLargeTradeDum * Ahreturn.
WeekendDummy is a dummy variable which equals 1 if the after-hours session is from Friday after 4pm to Monday at 9:30am; and 0 otherwise.
WeekendInteraction is calculated as WeekendDummy * Ahreturn.
T-statistics are given in parenthesis. * represents statistical significance at the 90% confidence level. ** represents statistical significance at the 95% confidence
level. *** represents statistical significance at the 99% confidence level.
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
- 26 -
Indep. Variable Expected
Sign 0.25% 0.5% 1% 2%
Intercept N/A -0.04514*** -0.08850*** -0.16078*** -0.20791***
(-4.92) (-6.20) (-5.63) (-2.72)
AHreturn Negative -0.41784*** -0.40157*** -0.38018*** -0.37570***
(-69.78) (-53.59) (-34.90) (-19.88)
SmallMarketCapDum N/A 0.02526** 0.03318** 0.06533** 0.15455**
(2.46) (2.23) (2.41) (2.33)
SmallMarketCapInteraction Negative -0.08104*** -0.08462*** -0.08972*** -0.08715***
(-16.40) (-14.68) (-11.81) (-7.41)
AHnegativeDum N/A 0.06392*** 0.11836*** 0.19927*** 0.10143
(5.20) (6.00) (4.84) (0.89)
AHnegativeInteraction N/A -0.14362*** -0.15390*** -0.16758*** -0.19125***
(-23.51) (-20.39) (-15.59) (-10.45)
LargeNumberOfTradesDum N/A -0.22817*** -0.26907*** -0.33419*** -0.47862***
(-9.17) (-8.58) (-7.25) (-5.66)
LargeNumberOfTradesInteraction Positive 0.48640*** 0.47908*** 0.47073*** 0.47662***
(89.47) (73.23) (52.73) (33.82)
OneLargeTradeDum N/A -0.01021 -0.01296 -0.01020 0.02573
(-0.71) (-0.61) (-0.25) (0.24)
OneLargeTradeInteraction N/A 0.09540*** 0.09422*** 0.09095*** 0.09620***
(9.32) (7.83) (5.59) (3.57)
WeekendDum N/A -0.05603*** -0.06172*** -0.07352** -0.05715
(-5.01) (-3.76) (-2.41) (0.76)
WeekendInteraction N/A -0.06486*** -0.06498*** -0.06873*** -0.08094***
(-11.18) (-9.60) (-7.70) (-5.84)
N 54445 33666 16015 5678
Adjusted R2 0.3556 0.3937 0.4286 0.4362
Cutoff: AbsValue(Ahreturn) >
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
- 27 -
Table 5. Regression Results for 5-Minute Returns
This table shows regression results for the restricted samples of after-hours sessions.
The dependent variable in each regression is Return5Min calculated as:
Return5Min = /
AHreturn is calculated as / where represents the price of the last after-hours trade prior to the market opening for firm i
on day t, and is the closing price for firm i on day t-1. SmallMarketCap is a dummy variable which equals 1 if the stock is in MarketCap deciles 4, 5, or 6
and 0 otherwise. SmallMarketCapInteraction is calculated as SmallMarketCap times AHreturn.AHnegativeDum is a dummy variable that equals 1 if AHreturn <
0 and 0 otherise. AHnegativeInteraction is calculated as AHnegativeDum times AHreturn. LargeNumberOfTradesDum is a dummy variable which equals 1 if
there was more than a 2 standard deviation increase in the number of trades during that after-hours trading session relative to the mean number of trades during
all after-hours trading sessions for that stock during the year 2006; and 0 otherwise. LargeNumberOfTradesInteraction is calculated as LargeNumberOfTrades
* Ahreturn. OneLargeTradeDum is a dummy variable which equals 1 if there is a single trade during that after-hours session larger than the mean after-hours
trade size for that stock plus 2 standard deviations; and 0 otherwise. OneLargeTradeInteraction is calculated as OneLargeTradeDum * Ahreturn.
WeekendDummy is a dummy variable which equals 1 if the after-hours session is from Friday after 4pm to Monday at 9:30am; and 0 otherwise.
WeekendInteraction is calculated as WeekendDummy * Ahreturn.
T-statistics are given in parenthesis. * represents statistical significance at the 90% confidence level. ** represents statistical significance at the 95% confidence
level. *** represents statistical significance at the 99% confidence level.
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
- 28 -
Indep. Variable Expected
Sign Whole Sample 0.25% 0.5% 1% 2%
Intercept N/A 0.00189 -0.03578*** -0.06529*** -0.12026*** -0.14741*
(0.39) (2.94) (-3.44) (-3.50) (-1.69)
AHreturn Negative -0.41509*** -0.39637*** -0.38539*** -0.36899*** -0.37045***
(-78.00) (-50.00) (-38.66) (-28.15) (-17.14)
SmallMarketCapDum N/A 0.01751** 0.02862** 0.03703* 0.03015 0.09529
(2.46) (2.10) (1.87) (0.92) (1.25)
SmallMarketCapInteraction Negative -0.06194*** -0.06543*** -0.06764*** -0.07354*** -0.06674***
(-12.33) (-10.00) (-8.82) (-8.05) (-4.96)
AHnegativeDum N/A 0.00933 0.04671*** 0.07873*** 0.12044** -0.03033
(1.39) (2.87) (3.00) (2.43) (-0.23)
AHnegativeInteraction N/A -0.12538*** -0.14375*** -0.15241*** -0.16649*** -0.18704***
(-22.59) (-17.77) (-15.18) (-12.87) (-8.94)
LargeNumberOfTradesDum N/A -0.11061*** -0.20559*** -0.24934*** -0.29131*** -0.40400***
(-5.43) (-6.24) (-5.98) (-5.25) (-4.18)
LargeNumberOfTradesInteraction Positive 0.48391*** 0.47748*** 0.47362*** 0.46964*** 0.47738***
(92.89) (66.34) (54.41) (43.72) (29.62)
OneLargeTradeDum N/A -0.01355 -0.01709 -0.01966 -0.00934 0.01139
(-1.48) (-0.89) (-0.69) (-0.19) (0.09)
OneLargeTradeInteraction N/A 0.09762*** 0.09703*** 0.09565*** 0.09431*** 0.09981***
(9.37) (7.16) (5.98) (4.82) (3.24)
WeekendDum N/A -0.03982*** -0.05130*** -0.05245** -0.03740 0.05407
(-5.55) (-3.46 (-2.40) (-1.02) (0.5321)
WeekendInteraction N/A -0.07141*** -0.07073*** -0.07233*** -0.07703*** -0.09364***
(-12.07) (-9.21) (-8.03) (-7.17) (-5.91)
N 140997 54445 33666 16015 5678
Adjusted R2 0.1538 0.2184 0.2455 0.3154 0.3457
Restriction
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
- 29 -
Table 6. Regression Results for 1-Hour Returns
This table shows regression results for the restricted samples of after-hours sessions.
The dependent variable in each regression is Return5Min calculated as:
Return1Hour = /
AHreturn is calculated as / where represents the price of the last after-hours trade prior to the market opening for firm i
on day t, and is the closing price for firm i on day t-1. SmallMarketCap is a dummy variable which equals 1 if the stock is in MarketCap deciles 4, 5, or 6
and 0 otherwise. SmallMarketCapInteraction is calculated as SmallMarketCap times AHreturn.AHnegativeDum is a dummy variable that equals 1 if AHreturn <
0 and 0 otherise. AHnegativeInteraction is calculated as AHnegativeDum times AHreturn. LargeNumberOfTradesDum is a dummy variable which equals 1 if
there was more than a 2 standard deviation increase in the number of trades during that after-hours trading session relative to the mean number of trades during
all after-hours trading sessions for that stock during the year 2006; and 0 otherwise. LargeNumberOfTradesInteraction is calculated as LargeNumberOfTrades
* Ahreturn. OneLargeTradeDum is a dummy variable which equals 1 if there is a single trade during that after-hours session larger than the mean after-hours
trade size for that stock plus 2 standard deviations; and 0 otherwise. OneLargeTradeInteraction is calculated as OneLargeTradeDum * Ahreturn.
WeekendDummy is a dummy variable which equals 1 if the after-hours session is from Friday after 4pm to Monday at 9:30am; and 0 otherwise.
WeekendInteraction is calculated as WeekendDummy * Ahreturn.
T-statistics are given in parenthesis. * represents statistical significance at the 90% confidence level. ** represents statistical significance at the 95% confidence
level. *** represents statistical significance at the 99% confidence level.
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
- 30 -
Indep. Variable Expected
Sign Whole Sample 0.25% 0.5% 1% 2%
Intercept N/A -0.03035*** -0.09640*** -0.13824*** -0.18056*** -0.11415
(-4.58) (-6.18) (-5.86) (-4.01) (-1.03)
AHreturn Negative -0.44718*** -0.41519*** -0.40280*** -0.39158*** -0.40652***
(-61.75) (-40.82) (-32.56) (-22.82) (-14.75)
SmallMarketCapDum N/A 0.00517 0.03441** 0.05382** 0.07530* 0.12433
(0.53) (1.97) (2.19) (1.76) (1.28)
SmallMarketCapInteraction Negative -0.03497*** -0.04036*** -0.04222*** -0.04474*** -0.03348*
(-5.12) (-4.81) (-4.44) (-3.74) (-1.95)
AHnegativeDum N/A 0.05829*** 0.12342*** 0.15544*** 0.13168** -0.25736
(6.39) (5.91) (4.78) (2.03) (-1.56)
AHnegativeInteraction N/A -0.10446*** -0.13492*** -0.14634*** -0.16340*** -0.19205***
(-13.83) (-13.00) (-11.74) (-9.65) (-7.20)
LargeNumberOfTradesDum N/A -0.05045* -0.20656*** -0.25922*** -0.30842*** -0.45649***
(-1.82) (-4.89) (-5.01) (-4.25) (-3.70)
LargeNumberOfTradesInteraction Positive 0.49766*** 0.48580*** 0.48185*** 0.48117*** 0.49676***
(70.21) (52.61) (44.61) (34.21) (24.18)
OneLargeTradeDum N/A -0.01329 -0.00617 -0.00838 -0.00331 0.06638
(-1.06) (-0.25) (-0.24) (-0.05) (0.42)
OneLargeTradeInteraction N/A 0.08334*** 0.08227*** 0.08277*** 0.07141*** 0.05542
(5.88) (4.73) (4.17) (2.79) (1.41)
WeekendDum N/A -0.05314*** -0.08677*** -0.07066*** -0.0481 0.01745
(-5.45) (-4.56) (-2.61) (-1.00) (0.16)
WeekendInteraction N/A -0.09320*** -0.09125*** -0.09319*** -0.10308*** -0.12413***
(-11.58) (-9.26) (-8.34) (-7.33) (-6.14)
N 140997 54445 33666 16015 5678
Adjusted R2 0.0990 0.1591 0.1889 0.2240 0.2545
Restriction
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
- 31 -
Figure 1. Opening Trade Return for the Whole Sample
This figure shows ReturnOpen relative to AHreturn for the observations such that AbsValue(AHreturn) > 2%. The blue lines are conditional on SmallMarketCap
being equal to 1. The dashed lines are conditional on LargeNumberOfTradesDum being equal to 1. OneLargeTradeDummy, OneLargeTradeInteraction,
WeekendDummy, and WeekendInteraction are all held constant at 0.
-6
-4
-2
0
2
4
6
8
-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10
Retu
rn fr
om la
st A
H t
rade
to
Ope
ning
Tra
de (%
)
After-Hours Return (%)
Opening Trade Return:Small vs Large Market Caps
Normal Trading vs High Trading
Small Market Cap - high trading
Large Market Cap - high trading
Small Market Cap - normal trading
Large Market Cap - normal trading
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
- 32 -
Figure 2. Opening Trade Return for AbsValue(AHreturn) > 0.25%
This figure shows ReturnOpen relative to AHreturn for the observations such that AbsValue(AHreturn) > 2%. The blue lines are conditional on SmallMarketCap
being equal to 1. The dashed lines are conditional on LargeNumberOfTradesDum being equal to 1. OneLargeTradeDummy, OneLargeTradeInteraction,
WeekendDummy, and WeekendInteraction are all held constant at 0.
-6
-4
-2
0
2
4
6
8
-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10
Re
turn
fro
m la
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H t
rad
e t
o O
pe
nin
g Tr
ade
(%
)
After-Hours Return (%)
Opening Trade Return:Small vs Large Market Caps
Normal Trading vs High Trading
Small Market Cap - high trading
Large Market Cap - high trading
Small Market Cap - normal trading
Large Market Cap - normal trading
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
- 33 -
Figure 3. Opening Trade Return for AbsValue(AHreturn) > 0.5%
This figure shows ReturnOpen relative to AHreturn for the observations such that AbsValue(AHreturn) > 2%. The blue lines are conditional on SmallMarketCap
being equal to 1. The dashed lines are conditional on LargeNumberOfTradesDum being equal to 1. OneLargeTradeDummy, OneLargeTradeInteraction,
WeekendDummy, and WeekendInteraction are all held constant at 0.
-6
-4
-2
0
2
4
6
8
-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10
Re
turn
fro
m la
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H t
rad
e t
o O
pe
nin
g Tr
ade
(%
)
After-Hours Return (%)
Opening Trade Return:Small vs Large Market Caps
Normal Trading vs High Trading
Small Market Cap - high trading
Large Market Cap - high trading
Small Market Cap - normal trading
Large Market Cap - normal trading
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
- 34 -
Figure 4. Opening Trade Return for AbsValue(AHreturn) > 1%
This figure shows ReturnOpen relative to AHreturn for the observations such that AbsValue(AHreturn) > 2%. The blue lines are conditional on SmallMarketCap
being equal to 1. The dashed lines are conditional on LargeNumberOfTradesDum being equal to 1. OneLargeTradeDummy, OneLargeTradeInteraction,
WeekendDummy, and WeekendInteraction are all held constant at 0.
-6
-4
-2
0
2
4
6
8
-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10
Re
turn
fro
m la
st A
H t
rad
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o O
pe
nin
g Tr
ade
(%
)
After-Hours Return (%)
Opening Trade Return:Small vs Large Market Caps
Normal Trading vs High Trading
Small Market Cap - high trading
Large Market Cap - high trading
Small Market Cap - normal trading
Large Market Cap - normal trading
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
- 35 -
Figure 5. Opening Trade Return for AbsValue(AHreturn) > 2%
This figure shows ReturnOpen relative to AHreturn for the observations such that AbsValue(AHreturn) > 2%. The blue lines are conditional on SmallMarketCap
being equal to 1. The dashed lines are conditional on LargeNumberOfTradesDum being equal to 1. OneLargeTradeDummy, OneLargeTradeInteraction,
WeekendDummy, and WeekendInteraction are all held constant at 0.
-6
-4
-2
0
2
4
6
8
-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10
Re
turn
fro
m la
st A
H t
rad
e t
o O
pe
nin
g Tr
ade
(%
)
After-Hours Return (%)
Opening Trade Return:Small vs Large Market Caps
Normal Trading vs High Trading
Small Market Cap - high trading
Large Market Cap - high trading
Small Market Cap - normal trading
Large Market Cap - normal trading
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
- 36 -
Figure 6. 5 Minute Return for the Whole Sample
This figure shows Return5Min relative to AHreturn for the observations such that AbsValue(AHreturn) > 2%. The blue lines are conditional on SmallMarketCap
being equal to 1. The dashed lines are conditional on LargeNumberOfTradesDum being equal to 1. OneLargeTradeDummy, OneLargeTradeInteraction,
WeekendDummy, and WeekendInteraction are all held constant at 0.
-6
-4
-2
0
2
4
6
8
-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10
Re
turn
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o O
pe
nin
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(%
)
After-Hours Return (%)
5-Minute Return:Small vs Large Market Caps
Normal Trading vs High Trading
Small Market Cap - high trading
Large Market Cap - high trading
Small Market Cap - normal trading
Large Market Cap - normal trading
The Cost of Illiquidity: Evidence from After-Hours Trading Walkup
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Figure 7. 1 Hour Return for the Whole Sample
This figure shows Return1Hour relative to AHreturn for the observations such that AbsValue(AHreturn) > 2%. The blue lines are conditional on
SmallMarketCap being equal to 1. The dashed lines are conditional on LargeNumberOfTradesDum being equal to 1. OneLargeTradeDummy,
OneLargeTradeInteraction, WeekendDummy, and WeekendInteraction are all held constant at 0.
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-4
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0
2
4
6
8
-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10
Re
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ade
(%
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After-Hours Return (%)
1 Hour Return:Small vs Large Market Caps
Normal Trading vs High Trading
Small Market Cap - high trading
Large Market Cap - high trading
Small Market Cap - normal trading
Large Market Cap - normal trading