2003. 6

Market Liquidity around Quarterly Earnings Announcements

Kazuhisa Otogawa

Market Liquidity around Quarterly Earnings Announcements:
Evidence from Japan
Kazuhisa Otogawa*

April 9, 2003

* Graduate School of Business Administration, Kobe University. I would like to thank participants at
the Japanese Association of Management Accounting (JAMA) Research Seminar in Tokyo for theirhelpful comments on this paper. I wish to acknowledge the financial support provided by aGrant-in-Aid for the Encouragement of Young Scientists 13730110 from the Ministry of Education,
Culture, Sports, Science, and Technology in Japan.
Correspondence: 2-1, Rokkodai, Nada, Kobe, Hyogo 657-8501 JAPAN. Tel/Fax: +81-78-803-6911.
E-mail: otogawa@rose.rokkodai.kobe-u.ac.jp0Market Liquidity around Quarterly Earnings Announcements:
Evidence from Japan

Abstracts
In Japan there has recently been a rapid increase in the number of firms disclosing quarterly
earnings. I investigate the information asymmetry and market liquidity around the quarterly earnings
announcements, by focusing on the bid-ask spreads and quoted depths. Prior theoretical research has
indicated that information asymmetry is exacerbated and market liquidity is reduced just before andat the point of public information disclosure, and that information asymmetry is improved andmarket liquidity is enhanced by disclosing public information. Using the transaction data of 121
firms that have implemented quarterly earnings reporting during 2001, I find that there are significant
decreases in daily bid-ask spreads and slight increases in daily depths during the period just after the
release of the quarterly earnings, which are consistent with the prediction based on prior theoreticalstudies. However, I do not find strong evidence that the spreads are wider and the depths lower
during the pre-announcement and announcement periods.

Key Words: Quarterly Earnings Announcements; Information Asymmetry; Market Liquidity;
Bid-Ask Spread; Quoted Depth
Data Availability: The data used in this study are publicly available from the sources indicated in
the text.

1

Market Liquidity around Quarterly Earnings Announcements:
Evidence from Japan

1. Introduction
In Japan there has recently been a rapid increase in the number of firms disclosing quarterly
earnings, mainly because in November 1999 the Tokyo Stock Exchange (TSE) organized a new
section named Mothers, in which small, newly-established companies could raise funds, andimposed a rule requiring that listed firms in this section report their earnings quarterly. Many firms
listed in the other sections also began voluntarily to release quarterly earnings, so that investors could
obtain information on their performance in a more timely matter.1 Furthermore, on June 27, 2002,
the TSE announced that all of the listed firms would be obligated to make quarterly reporting for the
fiscal years beginning after April 1, 2003.2 The purpose of this study is to examine the effectivenessof quarterly financial reporting, which has rapidly been becoming pervasive in the Japanese stock
market.
In the United States, quarterly earnings reporting has a forty-year history, since the American
Stock Exchange (ASE) first required listed firms to issue quarterly reports in 1962. For example,
Morse (1981) find that the most significant stock price changes and excess trading volume occur the
day prior to and the day of the quarterly earnings announcements in the Wall Street Journal.
McNichols and Manegold (1983) indicate that there is a significant reduction in the marginal

1

Based on the survey of TSE (2001), 139 Japanese firms released financial reports for the firstquarter of the fiscal year ending in March 2002. Among these firms, 98 were ones listed on the TSE,
36 on the over-the-counter market, and 5 on the other stock markets. It was also reported in the
Nihon Keizai Shimbun on September 9, 2002 that another 140 firms listed on the TSE newly
disclosed financial reports for the first quarter of the fiscal year ending in March 2003.
2
To be more precise, the TSE announced a plan that first mandates listed firms to concisely discloseeach quarter’s general conditions such as sales revenues, order backlogs, and increases or decreasesof assets and liabilities for the fiscal years beginning after April 1, 2003, and subsequently to file thequarterly condensed financial statements for the fiscal years beginning after April 1, 2004.
2

information content of annual earnings announcements following the introduction of quarterly
reporting. Landsman and Maydew (2002) find evidence of an increase in the informativeness ofquarterly earnings announcements over the past three decades, as measured by both abnormal
trading volume and abnormal return volatility.
Up to now, Japanese firms, in principle, have reported their earnings semi-annually. Several firms,
which have adopted U.S. GAAP for their consolidated financial statements, have only voluntarily
released quarterly earnings. Therefore, there has been little research that analyzed the information
content of quarterly earnings in the Japanese stock market. Otogawa (1999) examine the stock pricereaction to quarterly earnings announcements using 95 firm-quarter observations during the period
from 1987 to 1997.
In this study, I investigate the information asymmetry and market liquidity around quarterly
earnings announcements, measured by the percentage bid-ask spreads and quoted depths. Prior
theoretical research has indicated that information asymmetry is exacerbated and market liquidity is
reduced just before and at the point of public information disclosure, and that information asymmetry
is improved and market liquidity is enhanced by disclosing public information. Using the transaction
data of 121 TSE firms that have implemented quarterly earnings reporting during 2001, I find that
there are significant decreases in daily bid-ask spreads and slight increases in daily depths during theperiod just after the quarterly earnings are released, which are consistent with the prediction based on
the theoretical studies. However, I do not find strong evidence that the spreads are wider and depths
lower during the pre-announcement and announcement periods.
The remainder of the paper is organized as follows: in Section 2, I briefly survey earlier studies
and describe my hypotheses. In Section 3, I explain the sample selection, data, and researchmethodology. In Section 4, I present the empirical results, and Section 5 contains the conclusion.

2. Review of Prior Research and Research Hypotheses32-1. Financial Reporting and Information Asymmetry
There has been some theoretical research conducted on how earnings announcements affectinformation asymmetry.3 Assuming that costless public information is a perfect substitute for costly
private information concerning the return on a risky asset, Verrecchia (1982) shows that increasing
publicly available information decreases the amount of private information traders acquire on theirown. Diamond (1985) also demonstrates that releasing public information reduces the incentives forthe production of private information by traders, and that risk sharing is improved because the public
information makes traders’ beliefs more homogeneous and decreases the magnitude of the
speculative positions which informed traders take. One can think of the earnings information that acompany discloses as an example of publicly available information for investors trading its stocks.
Therefore, these analytical models lead to the following hypothesis:4
H1: Information asymmetry in the stock market is improved during the post-announcement
period after a firm releases earnings.
Kim and Verrecchia (1994) show that if investors have a different ability to process earnings
announcements, some traders capable of making informed judgments from public sources enjoy atemporary information advantage. Their model suggests information asymmetry at the date when an
earnings number is released, as follows:
H2: Information asymmetry in the stock market is exacerbated during the announcement period
during which a firm releases earnings.
Demski and Feltham (1994) demonstrate that there are some traders who are motivated to
privately acquire costly information in order to speculate on the forthcoming public disclosure undera certain condition. In the settings where traders with short-term investment horizons are allowed to

See Callahan, Lee, and Yohn (1997) for a more comprehensive literature survey.
Within the context of two complementary private signals, Lundholm (1991) indicates that as the
public information becomes more precise, fewer traders become informed, but the information gap
between informed and uninformed traders increases.
3

4

4

trade on their private information prior to a public disclosure, McNichols and Trueman (1994) showthat public disclosure stimulates investment in private information acquisition, and that an increase ineither the probability or the precision of a public disclosure gives informed traders an incentive toincrease the precision of their private information. Thus, these theoretical models, which predict thatsome traders’ private information search prior to the public disclosure exists, lead to the following
hypothesis:
H3: Information asymmetry in the stock market is exacerbated during the pre-announcement
period just before a firm releases earnings.
I test the three hypotheses on information asymmetry surrounding the earnings announcement
described above using data on Japanese firms that have initiated quarterly earnings reporting.

2-2. Information Asymmetry and Liquidity in the Stock Market
In the New York Stock Exchange (NYSE), exchange-designated specialists have affirmative
obligations to provide continuous liquidity to the market. Specialists offer simultaneous quotes toboth buy and sell. Glosten and Milgrom (1985) demonstrate that a specialist sets a higher ask priceand a lower bid price when the fraction of informed traders increases or their information becomes
better. That is, the bid-ask spread, defined as the difference between the ask price and bid price, isthought to measure the extent of information asymmetry among the market participants.
The trading mechanism on the TSE differs substantially from the one on the NYSE.5 The primarydifferences between the two systems are the absence of a designated liquidity-provider such as
specialists or market makers in the TSE.6 Within continuous double auction trading called the

See Lehmann and Modest (1994), and Hamao and Hasbrouck (1995) for the market
micro-structure of the TSE.
6
It is anecdotally argued that the self-trading department of stockbrokerage firm acts as amarket-maker in the TSE.
55

Zaraba, traders may submit limit orders or market orders.7 All liquidity is supplied by traders who
submit limit orders. The highest limit order to buy becomes the best bid price, and the lowest limit
order to sell becomes the best ask price. Therefore, the bid-ask spread, in this study, is defined as thedifference between the best ask price and the best bid price of all limit orders.
The market order to buy (sell) that arrives at the exchange is successively matched to the best ask(bid) limit order, and the trade is executed if the price change from the last trade satisfies prescribed
conditions set by the TSE, and if the depth at the quote is sufficient.8 Virtually all trades occurring
under the Zaraba mechanism are the result of market orders hitting limit orders or limit orders
crossing. Because market orders almost never cross, there are virtually no trades between the bid andask prices. Therefore, I do not compute the effective spread, which is defined as the difference
between the transaction price and the mid-point of the bid and ask quotes, but instead use the quoted
spread.
Prior research suggests that the bid-ask spread set by a specialist is comprised of the transaction
costs of processing orders, and the costs of holding a less than fully diversified portfolio, as well as
expected losses due to dealing with informed traders. On the TSE, stockbrokerage firms charge acommission for the provision of trading services, and order processing costs are unlikely to be
recovered by the bid-ask spreads. Because all traders are able to post limit orders, no one should beforced to maintain an excess inventory position. Leuz and Verrecchia (2000), which investigate
German firms included in the DAX 100 stock index, suggest that other spread components unrelated

7

TSE trading takes place in two different trading sessions. The morning session, called the Zemba,
begins at 9:00 A.M. and ends at 11:00 A.M., while the afternoon session, called the Goba, begins at
0:30 P.M. and ends at 3:00 P.M. Trade at the beginning of each session is initiated through asingle-price auction called the Itayose. After that, trades occur under the Zaraba mechanism until thesession closes, at which orders are also executed through the Itayose mechanism. Lehmann andModest (1994) report that 65 to 70 percent of total trading volume occurs under the Zaraba
mechanism for all firms regardless of their size decile.
8
If the price change exceeds maximums mandated by TSE, trading is temporarily halted toadvertise the need for additional liquidity and smooth quote adjustments between transactions.
6to information asymmetry are presumably less important in an order-driven market. As the TSE is anorder-driven market, I don’t attempt to partition the total quoted spread into these components.
Lee, Mucklow, and Ready (1993) point out that if the specialist believes the probability that sometraders possess superior information has increased, he could protect himself not only by increasing
the bid-ask spread, but also by decreasing the number of shares available to trade at each quoted
price. Therefore, I also focus on the quoted depth, which is measured as the number of shares quoted
at the best ask price plus the number of shares quoted at the best bid price, to comprehensively
understand information asymmetry in the stock market.
Furthermore, in the context of narrowing spread and increasing depth, traders can buy or sell large
numbers of shares that they want at low transaction costs. In contrast, in the context of widening
spread and decreasing depth, traders cannot buy or sell even small numbers of shares at the given
transaction costs. Bid-ask spread and quoted depth serve together as the proxy for market liquidity.
Because of this, I investigate the changes in information asymmetry and market liquidity around thequarterly earnings announcement using data on quoted spreads and depths.

2-3. Bid-Ask Spreads and Depths around the Earnings Announcements
Many researches have examined bid-ask spreads and depths around informational events such as
earnings announcements.9 For example, Morse and Ushman (1983) investigate bid-ask spreads over
21 days surrounding quarterly earnings announcements of 25 over-the-counter (OTC) firms between
1973 and 1976. They find no significant changes in bid-ask spreads around earnings announcements.
Venkatesh and Chiang (1986), using a random sample of 75 NYSE listed firms, examine bid-ask

9

See Callahan, Lee, and Yohn (1997) for a more comprehensive literature survey. As the literaturethat focus on the relation between other information events and bid-ask spreads, Conrad and Niden(1992) and Jennings (1994) examine the behavior in spreads around takeover announcements, while
Barclay and Smith (1988), Singh, Zaman, and Krishnamurti (1994), Wiggins (1994), and Miller and
McConnell (1995) investigate open market stock repurchases.
7

spreads just before earnings and dividend announcements. They find significant increases in bid-ask
spreads only before the second announcement that is preceded by another announcement in the priorthirty days. Lee, Mucklow, and Ready (1993) use intraday quotes data of 230 NYSE firms to analyzeboth bid-ask spreads and depths at the time of quarterly earnings announcements. They show thatbid-ask spreads widen, and depths drop, in advance of quarterly earnings announcements, and the
sharpest increases in bid-ask spreads occur in the half hour during which the earnings
announcements are made. Coller and Yohn (1997) investigate the relationship between management
earnings forecasts and bid-ask spreads. They report that forecasting firms have significantly larger
spreads than matched non-forecasting firms during the period prior to the release of the management
forecast, and that the spreads of forecasting firms temporarily increase in the day of and the day after
the management forecast. In addition, they report that there are no significant differences in spreads
between forecasting firms and non-forecasting firms during the nine days after the management
forecast. Affleck-Graves, Callahan, and Chipalkatti (2002) examine the bid-ask spreads aroundquarterly earnings announcements for 247 NASDAQ firms. They find a significant increase in theadverse selection component of the bid-ask spread on the day and the day before quarterly earnings
announcements for firms with less predictable earnings, but no changes for firms with morepredictable earnings.
There have also been several studies analyzing non-U.S. stock markets. Leuz and Verrecchia(2000) investigate German firms included in the DAX 100 stock index, and show that firms
switching to international reporting standards (IAS or U.S. GAAP) have significantly smaller
spreads than the firms following the German reporting standards. Acker, Stalker, and Tonks (2002)
use a sample of 195 U.K. firms on the London Stock Exchange (LSE) over the period from 1986 to
1994. They find that the bid-ask spreads start to decrease 15 days before the earnings announcements,
and remain at relatively narrow levels for up to 90 days after the announcements. In this study, I
examine changes in the quoted spread and depth around the quarterly earnings announcement, using8

a sample of the Japanese firms listed on the TSE.

3. Research Design
3-1. Sample and Data
I use the Nikkei Telecom 21 (similar to the Dow Jones News Retrieval Service in the U.S.) to
identify whether a firm have implemented quarterly financial reporting, and when the quarterly
earnings numbers were published in the Nihon Keizai Shimbun (the most popular Japanese financial
newspaper). Among more than 2,000 firms that were listed on the TSE during 2001, 121 firms
released quarterly earnings. This results in an initial sample of 484 firm-quarter observations. But
because some firms introduced quarterly earnings reporting in the middle of 2001, there are 18
observations that quarterly earnings announcement date are missing. I obtain the necessary data forthis study from the Nikkei Tick by Tick Data provided by the Nikkei Quick Information Technology
Co., Ltd.10 I also eliminate 81 observations that don’t have sufficient market data over the estimation
period due to thin transactions. Therefore, the final sample consists of 385 quarterly earnings
announcements.
Panel A of table 1 presents the sample distribution based on the Nikkei two-digit industrial codes.
More than 70% of the firms that have disclosed quarterly earnings are in the service, stockbrokerage,

10

The Nikkei Tick by Tick Data is basically the same database as one provided by the University ofMemphis’s Institute for the Study of Security Markets (ISSM). It reports all trades and quotes
originating from TSE or other stock exchanges. For each trade, it records time stamped to the nearest
minute, price, volume, and transaction codes. For each quote, it records time stamp, code indicating
bid or ask quotes, best bid or ask prices, number of shares quoted at either price, and quote codes.
Because my data have a coarser time stamp than ones on the ISSM tape, which has time stamp to thenearest second, there are a number of trades and quotes in the same time. Since they are numberedserially in the broadcasted order, I process the data in accordance with their serial numbers. Then
there are some types of quotes on the TSE. By excluding a warning quote (chui kehai) and a special
quote (tokubetsu kehai) that are issued when no quote is available or when the required price change
to execute a single market order would exceed the maximum allowable price variation, I use only
regular quotes (ippan kehai), which are constituted by limit orders some trader has submitted, tocompute the daily spread and depth.
9trading, or electrical equipment industries. Panel B indicates a sample distribution by the market
section. I exclude more observations on the Second and Mothers sections than on the First section,
because the stocks on the former sections are much less actively traded than the stocks on the latter
section.
----------------------Table 1-----------------------

3-2. Abnormal Spread and Depth Measures
To test the changes in information asymmetry and market liquidity around the quarterly earnings
announcements, I compute the abnormal spread and depth using a standard event study methodology.
First, at each quarterly earnings announcement date, I separately estimate the following equations (1)and (2) using Ordinary Least Squares (OLS). Equation (1) is the model with the bid-ask spread, andequation (2) is the model with the quoted depth, as the dependent variable. The parameter estimates
are derived using the data from day -150 to day -11 (i.e., the estimation period), where day 0 is thequarterly earnings announcement date. Because I require that market data for at least 100 days areavailable for estimating each model, 81 firm-quarters are excluded from the final sample, as
mentioned above.
ln(SPREADi,t) = α0 + α1 ln(TRANSi,t) + α2 ln(PRICEi,t) + α3 ln(VARi,t)+ α4 ln(MVARi,t) + εi,t(1)ln(DEPTHi,t) = β0 + β1 ln(TRANSi,t) + β2 ln(PRICEi,t) + β3 ln(VARi,t)+ β4 ln(MVARi,t) + µi,t

(2)

SPREADi,t is the daily average of percentage bid-ask spreads for firm i on day t. I measure thepercentage spread as the difference between the bid and ask prices in effect at the time of the10transaction deflated by the midpoint of the bid and ask prices.11 DEPTHi,t is the daily average of thequoted depths for firm i on day t. I define the quote depth as the number of shares quoted at the ask
price plus the number of shares quoted at the bid price in effect at the time of the transaction divided
by its round lot.12 TRANSi,t is the daily number of transactions for firm i on day t. PRICEi,t is theclosing price for firm i on day t. VARi,t is the proxy of volatility, measured as one plus the squared
percentage change in the closing price for firm i from day t-1 to day t. MVARi,t is the proxy ofmarket-wide volatility, calculated as one plus the squared percentage change in a popular market
index, Tokyo Stock Price Index (TOPIX), for firm i from day t-1 to day t. These independent
variables, TRANS, PRICE, VAR, and MVAR, are suggested to be the determinants of the bid-ask
spreads by many prior researches.13 But as there are few studies on depths, it is not very clear how
they vary among firms and over times. In this study, both the bid-ask spread and depth areconsidered to be the measures of information asymmetry and market liquidity. I choose the same
independent variables in the depth model as in the spread model. All variables are log-transformed.
Next, on each trading day in the event period (i.e., day -10 to day +10), I calculate the expected
spread and depth based on the estimated regression coefficients of equations (1) and (2), respectively.
The difference between the actual spread (depth) on each day in the event period and the expectedvalue computed in this manner is an estimate of the abnormal spread (depth). Under hypothesis H1, I
expect that the abnormal spread is significantly negative, and that the abnormal depth is significantly
positive during the post-announcement period. Under hypotheses H2 and H3, I predict that theabnormal spread is significantly positive, and that the abnormal depth is significantly negative during

11

I eliminate the opening and closing transactions of each trading session executed through asingle-price auction. Because stocks of Japanese firms generally have par value of ¥50, ¥500, or¥50,000, I use the percentage spread, not the amount spread, which is the difference between bid andask prices, to keep cross-sectional comparability.
12
The reason is because there are various round lots of 1,000, 100, or 1 shares in Japan. I use thedepth deflated by its round lot, to facilitate the cross-section comparison.
13
For example, see Callahan, Lee, and Yohn (1997, p.52, table 1).
11the announcement and pre-announcement periods. To infer statistical significance, I compute threetest statistics. The first is the t-statistic, computed using the cross-sectional standard deviation on each
event day. The second t-statistic is defined using the standard deviation estimated from thetime-series of average abnormal measures over the estimation period (Brown and Warner, 1985, p.7).
These parametric tests are for the null hypothesis in which the mean is zero. In contrast, the third is
the z-statistic based on the non-parametric binominal sign test for the null hypothesis in which themedian is zero.

4. Empirical Results
4-1. Descriptive Statistics
Table 2 reports the descriptive statistics for some characteristics of 121 firms in the initial sample
that have released their earnings quarterly. For reference, I also provide descriptive statistics foranother 1,882 firms that have not implemented quarterly financial reporting. For each firm, allvariables are the average value of at maximum 246 trading days during the period from January to
December 2001. While the non-quarterly reporting firms have a mean (median) daily percentage
spread of 1.48 (1.06) %, the quarterly reporting firms have a mean (median) spread of 1.23 (0.73) %.
The difference in mean (median) spreads across the two groups is significant with p = 0.0485 (p =0.0021) using a two-tailed t-test (Mann-Whitney-Wilcoxon test). The mean (median) quoted depthof the quarterly reporting firms are 24.1915 (12.4708) round lots, which are marginally higher than
one of the non-quarterly reporting firms at the significant level of 0.1218, using a
Mann-Whitney-Wilcoxon test. The quarterly reporting firms are also larger in size, are traded more
actively, and have a more volatile stock price, than the non-quarterly reporting firms.
----------------------Table 2-----------------------

12

It is not completely clear to me how these characteristics of sample firms affect the empiricalresults on information asymmetry and market liquidity around the quarterly earnings announcements.
However, Lang and Lundholm (1993) indicate that the disclosure practices of larger firm areevaluated more highly by financial analysts. Because quarterly reporting firms always take up
positive attitudes toward information disclosure, for reasons inclusive of the size factor, they might
keep information asymmetry among the market participants at a lower level, so that they have theirstocks traded more actively, at smaller bid-ask spreads, and with marginally higher quoted depths,
over time than the non-quarterly reporting firms.14 If so, the following results are potentially biased
against finding significant changes in spread and depth around the quarterly earnings announcementdate.

4-2. Bid-Ask Spreads
In this section, I examine the three hypotheses about information asymmetry and market liquidity
around the quarterly earnings announcements by focusing on the bid-ask spreads. Because priorstudies suggest numerous determinants of the bid-ask spread, I first estimate equation (1) to control
the effect of such determinants.15 Table 3 provides the descriptive statistics for the estimation resultsof the spread model. Generally, the coefficient on TRANS is significantly negative, suggesting thatthe more actively stocks are traded, the lower the bid-ask spreads are. PRICE also has a significantly
negative coefficient, that is, lower-priced stocks have higher spreads. The positive coefficients on
VAR and MVAR indicate that higher individual stock’s and market-wide volatilities are associatedwith wider spreads. The only coefficient on VAR is significant. These results are basically consistent
with prior research. The model has a moderate explanatory power; the mean (median) adjusted R2 is

14

The positive relationship between disclosure quality and market liquidity is demonstrated by
Welker (1995), Healy, Hutton, and Palepu (1999), and Heflin, Shaw, and Wild (2001).
15
Excluding the market-wide volatility (MVAR) from equation (1) does not materially alter the
results reported below.
130.2258 (0.1723).
----------------------Table 3----------------------Next, on each trading day in the event period, I compute the abnormal spread, defined as thedifference between the actual percentage spread and the expected one based on the estimatedcoefficients of equation (1). Panel A of table 4 presents the behavior in an abnormal spread around385 quarterly earnings announcement dates that are released by 121 firms listed on the TSE during
2001. During the period just after releasing the quarterly earnings, especially from day +2 to day +10,
both the mean and median abnormal spreads are significantly negative. These results vigorously
support hypothesis H1 that information asymmetry among the market participants is improved bypublic disclosure of earnings information. However, over the other period from day -10 to day +1,
the abnormal spreads are also negative, and statistically significant in most days. These findings
provide no support for hypotheses H2 and H3 that private information search and excellent
information processing by some traders deteriorate information asymmetry and market liquidity
during the pre-announcement and announcement periods.
----------------------Table 4----------------------Because up to now Japanese firms have been mandated to release their earnings semi-annually,
the earnings information newly disclosed by introducing quarterly financial reporting is only the
information from the first and third quarters. Because of this, I divide the sample into two groups inorder to conduct the above-mentioned analysis repeatedly. Panel B reports the results for the
sub-sample consisting of 183 firm-quarters that announce earnings in first or third quarters. During
the post-announcement period, the mean abnormal spreads are negative, but statistically significant

14only from day +7 on forward. The median spreads are significantly negative in most days. During
the pre-announcement and announcement periods, they are also significantly negative in some days.
Panel C provides the result for the sub-sample of 202 observations, including only second quarter(semi-annual) or fourth quarter (annual) earnings announcements, which have been the prevailingreporting system in Japan for many years. The mean and median abnormal spreads are consistently
negative and mostly significant at the conventional level. These results from both sub-samples arebasically the same as the results from the full sample, and support hypothesis H1, but not hypotheses
H2 and H3.

4-3. Quoted Depths
In this section, I focus on the quoted depths to examine the hypotheses about information
asymmetry and market liquidity around the quarterly earnings announcements. First, I estimate
equation (2), which has the same independent variables as the above spread model.16 Table 5 reports
the descriptive statistics for the estimation results of the depth model. Generally, the coefficient on
TRANS is significantly positive, showing that more actively traded stocks have larger quoted depths.
But PRICE, VAR, and MVAR have insignificant coefficients. As suggested by the mean (median)adjusted R2 of 0.1599 (0.1239), the depth model has rather less explanatory power than the spread
model.
----------------------Table 5----------------------Next, on each trading day in the event period, I compute the abnormal depth, defined as thedifference between the actual quoted depth and the expected one based on the estimated coefficients

16

Excluding the market-wide volatility (MVAR) from equation (2) does not materially alter the
results reported below.
15

of equation (2). Panel A of table 6 presents the behavior in abnormal depth around 385 quarterly
earnings announcement dates that are released by 121 firms listed on the TSE during 2001. The
result is not as clear as the result obtained with the bid-ask spreads. During the period just after
announcing quarterly earnings, the mean abnormal depth is positive, and statistically significant onlyin day +2. The median depths are not statistically significant. These results just weakly support
hypothesis H1, which predicts that accounting disclosure alleviates information asymmetry among
the market participants. Positive abnormal depths during the announcement period, from day -1 today +1, provide no support for hypothesis H2 that information asymmetry in the market isexacerbated by the traders’ differential information processing abilities. During the
pre-announcement period, the mean abnormal depths are not significantly different from zero. The
median depths are significantly negative in days -10. These findings provide just little support for
hypothesis H3 that private information searches by some traders deteriorate information asymmetry
and market liquidity during the pre-announcement period.
----------------------Table 6----------------------Next, I divide the sample into two groups to conduct the analysis mentioned above repeatedly.
Panel B reports the results for the sub-sample consisting of 183 firm-quarters that announce earnings
in first or third quarters. In days +6 and +8, the mean abnormal depths are significantly positive,
which are consistent with the prediction of hypothesis H1. In days -10 and -3, the median depths are
significantly negative, supporting hypothesis H3. Panel C provides the results for the sub-sample of
202 observations including only second quarter (semi-annual) or fourth quarter (annual) earnings
announcements. The positive mean depth in days 0 and +2, and the negative median depth in day -4
are only statistically significant. These results are not very consistent with the hypothesized changes
in information asymmetry and market liquidity around the quarterly earnings announcements.

16

5. Concluding Remarks
In Japan, there has recently been a rapid increase in the number of firms releasing their earnings
quarterly. The TSE decided that all of the listed firms would be mandated to implement quarterly
financial reporting after April 2003. I investigate from the viewpoint of the ex ante equity or equalityof opportunity in the capital markets suggested by Lev (1988). I first derive three hypotheses on thechanges in information asymmetry and market liquidity around the earnings announcement datebased on prior theoretical studies, and then use bid-ask spreads and quoted depths to test them.
During the period just after releasing quarterly earnings, the bid-ask spreads decrease significantly,
and the quoted depths increase slightly, which are consistent with the prediction that information
asymmetry among the market participants is improved by the public disclosure of accounting
information. During the announcement period, the findings that there are significant decreases inbid-ask spreads and moderate increases in quoted depths contradict the hypothesis that excellent
information processing by some traders deteriorates information asymmetry and market liquidity.
Over the period just before an earnings announcement, I find that the spreads lower significantly, andthat the depths decrease somewhat. The former finding provides no support for the hypothesis that
information asymmetry and market liquidity are exacerbated by some traders’ private information
search activities, but the latter provides very weak support for it.
Significant decreases in bid-ask spreads over the pre-announcement and announcement periods
are not consistent with the findings of Lee, Mucklow, and Ready (1993) for the U.S. stock market,
but are consistent with the findings of Acker, Stalker, and Tonks (2002) for the U.K. market. The
reason why spreads are reduced significantly before quarterly earnings are announced in theJapanese stock market is an open question that needs to be resolved in the future.
[2003.3.7 644]

17

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Research 17 (Summer): 217-229.

20

Table 1
Sample Distribution
Firms%
Observations
Panel A: By Industry
Foods
1
0.83
Chemicals
2
1.65
Rubber1
0.83
Ceramics2
1.65
Machinery
4
3.31
Electrical Equipment
17 14.05
Automobile
3
2.48
Precision Machinery4
3.31
Other Manufacturing1
0.83
Trading
18 14.88
Retail3
2.48
Stockbrokerage
19 15.70
Other Finance
5
4.13
Real Estate1
0.83
Air Transportation
1
0.83
Communications
3
2.48
Service36 29.75
Total
121 100.00
Panel B: By Market Section
First Section
73 60.33
Second Section
27 22.31
Mothers Section
21 17.36
Total
121 100.00

%

4
1.04
8
2.08
4
1.04
8
2.08
15
3.90
59 15.32
8
2.08
13
3.38
4
1.04
54 14.0312
3.12
75 19.48
14
3.64
2
0.52
4
1.04
6
1.56
95 24.68
385 100.00
276 71.69
61 15.84
48 12.47
385 100.00

21

Table 2
Characteristics of Quarterly Reporting Firms
Variable

MeanMedianStd. Dev.

t-statisticz-statistic

Panel A. Quarterly Reporting Firms
SPREAD

0.01230.00730.0120-1.9742-3.0759

DEPTH

24.1915 12.4708

43.7991-0.3650

1.5474

MVE

435.4

46.2

1027.24.15054.3539

TRANS

183.8

56.5

283.1

7.10135.1142

ABSRET

0.02710.02440.00987.24896.2664

Panel B. Non-Quarterly Reporting Firms
SPREAD

0.01480.01060.0132

DEPTH

29.65239.5857164.1556

MVE

150.1

22.3

710.0

TRANS

81.1

25.2

141.9

ABSRET
0.0218 0.0205
0.0077
Quarterly reporting firms are 121 firms in the initial sample thathave listed on the TSE during 2001, and that have released theirearnings quarterly. Non-quarterly reporting firms are another 1,882
firms that have listed on the TSE during 2001, but that have not
implemented quarterly financial reporting.
Variable definitions: SPREAD is the daily average ofpercentage bid-ask spreads, measured as the difference between thebid and ask prices in effect at the time of the transaction divided by the
midpoint of the bid and ask prices. DEPTH is the daily average ofquoted depths, defined as the number of shares quoted at the ask priceplus the number of shares quoted at the bid price in effect at the timeof the transaction divided by its round lot. MVE is the market value ofequity, computed as the closing price multiplied by the number ofshares issued (in billion yen). TRANS is the daily number oftransactions. ABSRET is the absolute percentage change in closing
price from the previous day. For each firm, all variables are the meanvalue over at maximum 246 trading days from January to December
2001.
The t-statistic is based on the parametric t-test for the null
hypothesis that the means of the two groups are the same. The
z-statistic is based on the non-parametric Mann-Whitney-Wilcoxon
test for the null hypothesis that the medians of the two groups are the
same.

22

Table 3
Descriptive Statistics for Ordinary Least Squares Estimation of the Spread Modelln(SPREADi,t) = α0 + α1 ln(TRANSi,t) + α2 ln(PRICEi,t) + α3 ln(VARi,t) + α4 ln(MVARi,t) + εi,tN

Mean

Observations

385

136.3013

8.3287

138

140

140

a0

385

-1.7235

6.3250-4.1906-1.3029

1.3383t-statistic385-1.2795

3.5878-2.9340-0.80280.7405a1

385-0.14890.1306-0.2382-0.1400-0.0604

t-statistic385-2.5084

2.1250-3.8638-2.4311-1.1048a2

385-0.40450.8342-0.8254-0.4586

0.0124t-statistic385-3.23938.7571-4.4450-2.0988

0.0510a3

385

40.901962.85099.748725.134451.7616t-statistic

385

2.04931.37081.15701.97162.8999a4

385

36.1541119.5377-17.7342

35.1246

94.4244385

0.55561.1907-0.2473

0.54601.3337385

0.22580.18390.10400.17230.2916t-statistic
2

adj. R

Std. Dev.

Q1

MedianQ3

F-statistic
385
32.7826
208.1063
4.92218.045315.0229
For each of 385 firm-quarters, the spread model is estimated using the data of at least 100
days over the estimation period from day -150 to day -11, where day 0 is the quarterly earnings
announcement date.
Variable definitions: SPREADi,t is the daily average of percentage bid-ask spreads for firm ion day t, measured as the difference between the bid and ask prices in effect at the time of thetransaction divided by the midpoint of the bid and ask prices. TRANSi,t is the daily number oftransactions for firm i on day t. PRICEi,t is the closing price for firm i on day t. VARi,t is the proxyof volatility, measured as one plus the squared percentage change in closing price for firm i fromday t-1 to day t. MVARi,t is the proxy of market-wide volatility, calculated as one plus the squared
percentage change in a market index, Tokyo Stock Price Index (TOPIX) for firm i from day t-1 today t. All variables are log-transformed. a0, a1, a2, a3, and a4 denote estimated coefficients α0, α1, α2,
α3, and α4, respectively.
Q1 and Q3 are the first and third quartiles of the distribution, respectively.

23

Table 4
The Behavior in Abnormal Spread around the Quarterly Earnings Announcement Date
Event Day N
Mean Median Std. Dev. Positive Negative t1-statistic t2-statistic
Panel A: Full Sample-10 372 -0.0558 -0.0187
0.3613170
202-2.9777-2.0328-9 378 -0.0297 -0.0356
0.4264161
217-1.3541-1.0822-8 378 -0.0696 -0.0613
0.3842147
231-3.5198-2.5350-7 372 -0.0212 -0.0470
0.3989159
213-1.0243-0.7720-6 375 -0.0666 -0.0551
0.3831156
219-3.3664-2.4268-5 373 -0.0647 -0.0479
0.4121152
221-3.0300-2.3562-4 373 -0.0599 -0.0456
0.3937154219-2.9376-2.1825-3 374 -0.0591 -0.0540
0.4468156
218-2.5562-2.1523-2 374 -0.0778 -0.0687
0.3384139
235-4.4458-2.8347-1 380 -0.0220 -0.0258
0.4083171
209-1.0492-0.8008
0 372 -0.0769 -0.0646
0.4037145
227-3.6748-2.8027
1 375 -0.0456 -0.0437
0.3987156219-2.2129-1.6603
2 375 -0.0544 -0.0727
0.3691141234-2.8554-1.9835
3 374 -0.0665 -0.0692
0.3738141233-3.4383-2.4222
4 375 -0.0662 -0.0605
0.3888142
233-3.2958-2.41125 380 -0.0575 -0.0559
0.3915152228-2.8653-2.0970
6 375 -0.0659 -0.0701
0.3995143
232-3.1953-2.4020
7 375 -0.0884 -0.0830
0.4018136
239-4.2602-3.2211
8 375 -0.1020 -0.1034
0.4096129
246-4.8214-3.7169
9 375 -0.0930 -0.0926
0.4579142233-3.9351-3.3906
10 380 -0.0926 -0.0764
0.3958148
232-4.5628-3.3759
Panel B: First or Third Quarter Earnings Announcements-10 178 -0.0563 -0.0165
0.354281
97-2.1218-1.7451-9 181 0.0020 -0.0109
0.437488
93
0.06190.0623-8 181 0.0026 -0.0378
0.385678
103
0.08960.0796-7 175 0.0050 -0.0548
0.368272
103
0.18040.1556-6 178 -0.0522 -0.0517
0.392376
102-1.7765-1.6182-5 178 -0.0785 -0.0504
0.435072
106-2.4083-2.4327-4 176 -0.0231 -0.0254
0.424979
97-0.7199-0.7143-3 178 -0.0355 -0.0571
0.432576
102-1.0942-1.0990-2 179 -0.0646 -0.0512
0.351276
103-2.4608-2.0014-1 181 -0.0054 -0.0257
0.429981100-0.1679-0.1663
0 172 -0.0576 -0.0392
0.437275
97-1.7278-1.7846
1 178 -0.0333 -0.0258
0.429381
97-1.0336-1.0304
2 178 -0.0217 -0.0398
0.377475
103-0.7671-0.67223 176 -0.0296 -0.0604
0.381569
107-1.0302-0.9178
4 180 -0.0434 -0.0337
0.426079
101-1.3662-1.3438
5 181 -0.0256 -0.0459
0.383881
100-0.8958-0.79166 180 -0.0372 -0.0563
0.401175
105-1.2438-1.1521
7 177 -0.0972 -0.0689
0.424769
108-3.0452-3.01158 180 -0.1083 -0.1153
0.428464
116-3.3912-3.3544
9 177 -0.0859 -0.1002
0.415370
107-2.7516-2.661210 180 -0.0903 -0.0411
0.414278
102-2.9247-2.7976z-statistic-1.6073-2.8289-4.2691-2.7479-3.2017-3.5209-3.3138-3.1542-4.9123-1.8981-4.1997-3.2017-4.7509-4.7055-4.6476-3.8474-4.5443-5.2673-5.9902-4.6476-4.2578-1.1243-0.2973-1.7839-2.2678-1.8738-2.4735-1.2814-1.8738-1.9433-1.3379-1.6012-1.1243-2.0237-2.7890-1.5652-1.3379-2.1615-2.8563-3.8013-2.7059-1.7143

24

Table 4 - continued
Event Day N
Mean Median Std. Dev. Positive Negative t1-statistic t2-statistic z-statistic
Panel C: Second or Fourth Quarter Earnings Announcements-10 194 -0.0553 -0.0297
0.368689
105-2.0886-1.6922-1.0769-9 197 -0.0588 -0.0655
0.415073
124-1.9897-1.8009-3.5624-8 197 -0.1358 -0.0971
0.371869
128-5.1278-4.1582-4.1323-7 197 -0.0445 -0.0397
0.423987
110-1.4722-1.3611-1.5674-6 197 -0.0796 -0.0577
0.375180
117-2.9775-2.4357-2.5649-5 195 -0.0520 -0.0411
0.390880
115-1.8582-1.5918-2.4348-4 197 -0.0928 -0.0600
0.361575
122-3.6024-2.8406-3.2774-3 196 -0.0805 -0.0501
0.459580
116-2.4523-2.4637-2.5000-2 195 -0.0899 -0.0953
0.326563
132-3.8440-2.7517-4.8696-1 199 -0.0371 -0.0260
0.388090
109-1.3481-1.1350-1.2760
0 200 -0.0935 -0.0930
0.372770
130-3.5485-2.8625-4.1719
1 197 -0.0567 -0.0690
0.369675
122-2.1522-1.7348-3.2774
2 197 -0.0840 -0.1026
0.359966
131-3.2759-2.5715-4.5598
3 198 -0.0992 -0.0824
0.364772
126-3.8276-3.0371-3.7665
4 195 -0.0872 -0.1024
0.350763
132-3.4718-2.6693-4.8696
5 199 -0.0866 -0.0690
0.397171
128-3.0778-2.6523-3.9697
6 195 -0.0924 -0.0994
0.397168
127-3.2504-2.8294-4.1535
7 198 -0.0805 -0.0890
0.381067
131-2.9729-2.4644-4.4772
8 195 -0.0962 -0.0858
0.392665130-3.4215-2.9447-4.5831
9 198 -0.0994 -0.0716
0.493772
126-2.8335-3.0435-3.7665
10 200 -0.0947 -0.0912
0.379470
130-3.5313-2.9001-4.1719
In panel A, the full sample consists of 385 firm-quarters that have listed on the TSE during 2001, and that
released quarterly earnings. The sample of panel B is composed of 183 firm-quarters that announced first or third
quarter earnings. The sample of panel C is made up of 202 firm-quarters that announced second quarter(semi-annual) or fourth quarter (annual) earnings.
The abnormal spread is defined as the difference between the actual percentage spread and the expected
spread. The actual spread is the daily average of the percentage bid-ask spreads, defined as the difference between
the ask and bid prices in effect at the time of the transaction deflated by the midpoint of the bid and ask prices. The
expected spread is based on the estimated coefficients of the log-linear equation (1) (see table 3 for detailed model
description and estimation specifications). At each firm-quarter, I separately estimate equation (1) for the data of atleast 100 days over the estimation period (day -150 to day -11) using Ordinary Least Squares. I use equation (1) toestimate the expected spread on each trading day in the event period (day -10 to day +10) inclusive of the quarterly
earnings announcement date.
Event Day represents the trading day relative to the quarterly earnings announcement.
The two t-statistics are based on the parametric t-test for the null hypothesis that the mean abnormal spread iszero. The first t-statistic is computed using the cross-sectional standard deviation on each event day. The second
t-statistic is defined using the standard deviation of the average abnormal spread estimated over the estimation
period. The z-statistic is based on the non-parametric binominal sign test for the null hypothesis that the medianabnormal spread is zero.

25

Table 5
Descriptive Statistics for Ordinary Least Squares Estimation of the Depth Modelln(DEPTHi,t) = β0 + β1 ln(TRANSi,t) + β2 ln(PRICEi,t) + β3 ln(VARi,t) + β4 ln(MVARi,t) + µi,tN

Mean

Observations

385

136.3013

8.3287

138

140

140

b0

385

0.21538.2239-2.07091.28753.9385t-statistic385

0.80153.3317-0.89360.64532.4701b1

385

0.26720.22440.13660.22850.3477t-statistic

385

3.46802.32201.9813

3.22314.6309b2

385

0.14441.0630-0.3258

0.00040.4597t-statistic

385-0.0380

3.2252-1.63860.00141.6057b3

385-19.8842

43.5145-29.8215-9.9695

1.5645t-statistic385-0.5851

1.2740-1.4383-0.65900.1641b4

385-5.3010130.3567-77.3678-5.322564.9890385-0.0484

1.1119-0.7680-0.06800.6221385

0.15990.14590.05530.12390.2321t-statistic
2

adj. R

Std. Dev.

Q1

MedianQ3

F-statistic
385
9.434912.3055
2.97415.876410.9611For each of 385 firm-quarters, the depth model is estimated using the data of at least 100
days over the estimation period from day -150 to day -11, where day 0 is the quarterly earnings
announcement date.
Variable definitions: DEPTHi,t is the daily average of quoted depths for firm i on day t,
measured as the number of shares quoted at the ask price plus the number of shares quoted at thebid price in effect at the time of the transaction divided by its round lot. TRANSi,t is the daily
number of transactions for firm i on day t. PRICEi,t is the closing price for firm i on day t. VARi,tis the proxy of volatility, measured as one plus the squared percentage change in closing pricefor firm i from day t-1 to day t. MVARi,t is the proxy of market-wide volatility, calculated as one
plus the squared percentage change in a market index, Tokyo Stock Price Index (TOPIX) for
firm i from day t-1 to day t. All variables are log-transformed. b0, b1, b2, b3, and b4 denoteestimated coefficients β0, β1, β2, β3, and β4, respectively.
Q1 and Q3 are the first and third quartiles of the distribution, respectively.

26

Table 6
The Behavior in Abnormal Depth around the Quarterly Earnings Announcement Date
Event Day N
Mean Median Std. Dev. Positive Negative t1-statistic t2-statistic
Panel A: Full Sample-10 372 -0.0224 -0.0535
0.4343155
217-0.9930-0.9035-9 378 -0.0072 -0.0250
0.4556176
202-0.3052-0.2889-8 378 0.0316 -0.0052
0.4156188
190
1.4786
1.2773-7 372 -0.0121 -0.0611
0.4589169
203-0.5067-0.4871-6 375 0.0132 -0.0412
0.4487169
206
0.57080.5344-5 373 -0.0158 -0.0149
0.4455182
191-0.6845-0.6380-4 373 -0.0102 -0.0264
0.4687175
198-0.4210-0.4128-3 374 -0.0107 -0.0500
0.4661169
205-0.4438-0.4322-2 374 0.0409 -0.0141
0.4664181
193
1.69711.6540-1 380 0.0150 -0.0265
0.4859185
1950.60060.60490 372 0.0760 0.0311
0.5603193
179
2.61653.0716
1 375 0.0556 0.0160
0.5018191
184
2.14532.2461
2 375 0.0519 0.0079
0.4880192
183
2.05832.09583 374 0.0185 -0.0229
0.4868184
190
0.73640.7491
4 375 0.0270 -0.0163
0.5132180
195
1.0191
1.09135 380 0.0225 -0.0280
0.4965178
202
0.88320.90906 375 0.0352 -0.0225
0.5065178
197
1.34641.42307 375 0.0408 0.0121
0.5182194
181
1.52631.6503
8 375 0.0418 0.0021
0.4808188
187
1.68301.6886
9 375 0.0002 -0.0222
0.4912179
196
0.00660.006810 380 0.0185 -0.0084
0.5019184
196
0.71670.7457
Panel B: First or Third Quarter Earnings Announcements-10 178 -0.0504 -0.0722
0.428464
114-1.5696-1.5798-9 181 -0.0075 -0.0382
0.452779
102-0.2240-0.2363-8 181 0.0424 0.0027
0.430392
89
1.32671.3301-7 175 0.0185 -0.0709
0.498180
95
0.49200.5807-6 178 0.0287 -0.0168
0.448483
95
0.85390.8997-5 178 -0.0228 -0.0524
0.496876
102-0.6133-0.7160-4 176 0.0156 0.0205
0.49119185
0.42260.4904-3 178 -0.0372 -0.0832
0.473173
105-1.0491-1.1662-2 179 0.0441 -0.0159
0.431885
94
1.36661.3826-1 181 0.0235 -0.0530
0.508586
95
0.6216
0.73660 172 0.0722 0.0005
0.633286
86
1.49552.2634
1 178 0.0697 -0.0012
0.560589
89
1.66022.18652 178 0.0173 -0.0320
0.529783
95
0.43480.54113 176 0.0078 -0.0791
0.500180
960.20720.24484 180 -0.0075 -0.0551
0.533077
103-0.1878-0.2339
5 181 0.0006 -0.0587
0.526078
103
0.01430.0175
6 180 0.0876 -0.0227
0.556087
93
2.11332.74527 177 0.0540 0.0164
0.547093
84
1.3123
1.69138 180 0.0810 0.0155
0.512794
86
2.11982.53929 177 0.0302 -0.0222
0.52558691
0.7647
0.9467
10 180 0.0331 0.0097
0.556892
880.7982
1.0385z-statistic-3.1627-1.2859-0.0514-1.7110-1.8590-0.4142-1.1391-1.8098-0.5688-0.46170.67400.30980.4131-0.2585-0.7230-1.1799-0.9295
0.61970.0000-0.8262-0.5643-3.6727-1.63520.1487-1.0583-0.8245-1.8738
0.3769-2.3235-0.5979-0.5946-0.0762-0.0750-0.8245-1.1307-1.8634-1.7839-0.37270.60130.5217-0.30070.223627

Table 6 - continued
Event Day N
Mean Median Std. Dev. Positive Negative t1-statistic t2-statistic z-statistic
Panel C: Second or Fourth Quarter Earnings Announcements-10 194 0.0034 -0.0226
0.439291
103
0.10680.1069-0.7898-9 197 -0.0068 -0.0088
0.459397100-0.2076-0.2156-0.1425-8 197 0.0217 -0.0088
0.402696
101
0.75540.6877-0.2850-7 197 -0.0392 -0.0562
0.420489
108-1.3093-1.2448-1.2824-6 197 -0.0008 -0.0625
0.449786
111-0.0236-0.0240-1.7099-5 195 -0.0094 0.0190
0.3941106
89-0.3315-0.2969
1.1458-4 197 -0.0333 -0.0423
0.447984
113-1.0442-1.0575-1.9949-3 196 0.0134 -0.0103
0.459696100
0.40740.4245-0.2143-2 195 0.0380 -0.0055
0.497296
99
1.06781.2067-0.1432-1 199 0.0072 -0.0129
0.465699100
0.21860.22900.00000 200 0.0793 0.0516
0.4907107
93
2.28512.51660.9192
1 197 0.0428 0.0242
0.4431102
95
1.3553
1.35800.4275
2 197 0.0831 0.0549
0.4461109
88
2.61592.63841.42493 198 0.0281 0.0263
0.4758104
940.83030.89100.6396
4 195 0.0588 0.0440
0.4934103
92
1.66491.86690.7161
5 199 0.0424 0.0035
0.4685100
99
1.27801.34710.0000
6 195 -0.0131 -0.0175
0.452191
104-0.4050-0.4162-0.8593
7 198 0.0291 0.0062
0.4921101
97
0.83260.92420.21328 195 0.0056 -0.0154
0.4477941010.17440.1775-0.4297
9 198 -0.0267 -0.0238
0.458193
105-0.8195-0.8468-0.7817
10 200 0.0052 -0.0262
0.447892
1080.16580.1666-1.0607
In panel A, the full sample consists of 385 firm-quarters that have listed on the TSE during 2001, and that
released quarterly earnings. The sample of panel B is composed of 183 firm-quarters that announced first or third
quarter earnings. The sample of panel C is made up of 202 firm-quarters that announced second quarter(semi-annual) or fourth quarter (annual) earnings.
The abnormal depth is defined as the difference between the actual quoted depth and the expected depth. The
actual depth is the daily average of the quoted depths, defined as the number of shares quoted at the ask price plus
the number of shares quoted at the bid price in effect at the time of the transaction divided by its round lot. The
expected depth is based on the estimated coefficients of the log-linear equation (2) (see table 5 for detailed model
description and estimation specifications). At each firm-quarter, I separately estimate equation (2) for the data of atleast 100 days over the estimation period (day -150 to day -11) using Ordinary Least Squares. I use equation (2) toestimate the expected depth on each trading day in the event period (day -10 to day +10) inclusive of the quarterly
earnings announcement date.
Event Day represents the trading day relative to the quarterly earnings announcement.
The two t-statistics are based on the parametric t-test for the null hypothesis that the mean abnormal depth iszero. The first t-statistic is computed using the cross-sectional standard deviation on each event day. The second
t-statistic is defined using the standard deviation of the average abnormal depth estimated over the estimation period.
The z-statistic is based on the non-parametric binominal sign test for the null hypothesis that the median abnormal
depth is zero.

28

Discussion Paper
No.
2002・1

AuthorNobuyuki Isagawa

2002・2

Nobuyuki Isagawa

2002・3Mahito Okura

2002・4

Elmer Sterken
Ichiro Tokutsu
Mahito Okura
Mahito Okura
Nobuyuki Isagawa
Koji Okubayashi
Toshinori Takashina

2002・5
2002・6
2002・7
2002・8

2002・9Hajime Shimizu

2002・10 Nobuyuki Isagawa
2002･11

Nobuyuki Isagawa

2002･12Kenji Kutsuna
Richard Smith

2002・13 Kunio Miyashita
2002・14 Hajime Shimizu
2002・15 Hajime Shimizu
2002・16 Koji Okubayashi
2002・17 Fumitoshi Mizutani
Shuji Uranishi
2002・18 Kazuhisa Otogawa
2002・19 Atsuo Takenaka
2002・20 Tsuneo Nakano

2002・21 Tsuneo Nakano
2002・22 Fumitoshi Mizutani
Shuji Uranishi
2002・23 Atsushi Takao
Mahito Okura
2002・24 Fumitoshi Mizutani
2002・25 Fumitoshi Mizutani
Takuya Urakami
Yasuyuki
Miyahara
2002・26
2002・27 Nobuyuki Isagawa
2002・28 Mitsutoshi Hirano

Title
Cross Holding of Shares, Unwinding Cross Holding of
Shares, and Managerial
Entrenchment
A Theory of Stock Price Behavior following Repurchase
Announcements
An Equilibrium Analysis of the Insurance Market
with Vertical Differentiation
What are the determinants of the number of bankrelations of Japanese firms?
Review Article：Adverse Selection in Insurance Market
Welfare Effect of Firm Size in Insurance Market
Does Investment Horison Affect Investment Strategy ?
Research Report of Careers and Employment Process ofWorkers over 60 years old :a Case of a Japnaese
Manufacturing Company
On the Existence of Tax Equilibrium : Incomplete Market
with Capital Income Tax
Cost of Financial Distress and Debt Restructuring :Debt Forgiveness and Equity-for-Debt Swap
Open-Market Repurchase Announcements, Actual
Repurchases, and Stock Price Behavior in Inefficient
Markets―revised version of No.2001･36―
Why Does Book Building Drive Out Auction Methodsof IPO Issuance?
Evidence and Implications from Japan
International Logistics and Modal Choice
Incomplete markets with capital income tax and public
goods
On the possibility of Pareto improving of tax-equilibrium
China-Japan Comparison of Work Organization
The Post Office vs. Parcel Delivery Companies:
Competition Effects on Costs and Productivity―revised version of No.2001･33―
Earnings Forecast and Earnings Management of JapaneseInitial Public Offerings Firms
The Classification of Foreign R&D Units
The Dutch East India Company and its Corporate
Governance―revised version of No.2000･40―
The British East India Company and its Corporate
Governance
Privatization Effects on TFP Growth and Capital
Adjustments
Some Notes on the Privatization of Postal Life Insurancein JapanPrivately Owned Railways’ Cost Function, Organization
Size and Ownership
A Private-Public Comaprison of Bus Service Operators
Principal-Multiagent Relationships with Costly
Monitoring
Unwinding of Cross Shareholding under Managerial
Entrenchment
Contingency Model for Personnel Grading System―Issues on Design and Management for Qualification
System and Job Grading System―

Date(in Japanese)

1／ 2002(in Japanese)

1／ 20022／20023／2002(in Japanese)(in Japanese)(in Japnaese)

3／20023／20023／20024／2002(in Japnaese)

4／2002(in Japnaese)

4／20025／20025／2002(in Japnaese)(in Japnaese)

6／20026／20026／20027／20027／20028／2002(in Japanese)(in Japanese)

8／20028／2002(in Japanese)

8／20028／2002(in Japanese)

9／20029／20029／2002
10／2002
10／2002(in Japanese)

11／2002

Discussion Paper
No.
Author
2002・29 Atsushi Takao
2002・30 Yasuhiro Shimizu
2002・31 Hideki Murakami

2002・32 Atsushi Takao

2002・33 Nobuyuki Isagawa
2002・34 Takuji Hara
2003・1 Katsuhiko Kokubu
2003・2 Kazuhiro Tanaka
Fumitoshi Mizutani
2003・3
Shuji Uranishi
Yang Jia Yin
2003・4
Koji Okubayashi
2003・5

Mitsutoshi Hirano

2003・6

Kazuhisa Otogawa

Title
On the Emergency Effect of the late FUKUZAWA,
Yukichi in Introducing of Modern Insurance into Japan
Amortization of Intangible Assets before Newark
Morning Ledger
An Economic Analysis of Duopolistic Competition
between Gulliver and Dwarf airlines:
The case of Japanese Domestic Air Markets
Simulation Model to Consider the Penetration of Modern
Insurance in Japan −Confirmation of Emergence andPhase Transition of New Japanese Risk-Bearing System
by Evolutional Economics
Mutual Shareholding and Unwinding of Mutual
Shareholding as Stockpile for Business Recovery
TLOs in Japan in the life science area : present and future
Environmental Accounting for Corporate Management
Embeddedness and Entrenchment of Managers
The Effects of Privatization on TFP Growth and Capital
Adjustments
Labour Turnover of Japan-Affiliated Companies inShanghai
Generation and Resolution of Asymmetric Information in
Human Resource Management –In the Cases of Job
Rotation in Two Retailers in JapanMarket Liquidity around Quarterly Earnings
Announcements(in Japanese)Date
11／2002(in Japanese)

11／2002
11／2002(in Japanese)

12／2002

12／2002(in Japanese)(in Japanese)(in Japanese)

12／2002
1／20032／20032／2003(in Japanese)

3／2003(in Japanese)

3／20033／2003