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Managerial FinanceEmerald Article: Bank profit warnings and signaling

Dave Jackson, Jeff Madura

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To cite this document: Dave Jackson, Jeff Madura, (2004),"Bank profit warnings and signaling", Managerial Finance, Vol. 30 Iss: 9

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Bank Profit Warnings and Signalingby Dave Jackson, University of Texas - Pan American and Jeff Madura, Florida AtlanticUniversity

Key Words: Bank Profit Warnings, Bank Signaling

Abstract

Bank profit warnings represent a milder form of negative news than a bank failure. Yet,they may contain signals about a bank or its rivals because the information is transmittedwhen the bank believes that the market is overly optimistic about its future earnings.Thus, the profit warning serves as a means by which insiders of the bank can reduce theasymmetric information between the banks insiders and its investors. We find that banks

experience negative valuation effects in response to their profit warnings. The banksprofit warnings result in significant negative valuation effects for its corresponding rivalbanks, which implies that the warning carries valuable information about banking indus-try conditions. However, the effects on rivals are attenuated since the passage of Regula-tion Fair Disclosure (RFD). This implies that investors may be relying on moretransparent sources of information about individual banks rather than relying on onebanks warning as a signal about other banks. Furthermore, bank regulations may allowfor more transparent communication by banks than that of nonbank firms.

Introduction

Several studies have documented how the information about an impending failure of abank cannot only affect the bank, but its rivals also. Yet, other news such as a profit warn-

ing may contain valuable information even though it does not signal failure. A milderform of negative news is a bank profit warning, which reflects the banks adjustment toexpected earnings in the prevailing quarter, and possibly beyond the quarter. A profitwarning may contain useful information, because it represents the banks effort to correctthe prevailing market expectations of its future earnings. Since the bank has informationabout its operations that is not available to the market, it should be more accurate than themarket. Thus, its adjustment to the earnings should reduce asymmetric information, andtherefore cause negative signals about the issuing bank and perhaps about banking indus-try conditions.

Our objective is to determine whether the bank profit warnings are priced by themarket. Specifically, we attempt to (1) determine if the banks that issue profit warningsare affected, (2) compare the effects on banks versus non-bank firms, and (3) determinewhether a profit warning contains a signal about bank rivals. We find that banks that issueprofit warnings experience a strong negative share price response. Second, the effects ofprofit warnings by banks are less pronounced than what has been found for non-banks.Third, a banks profit warnings causes significant negative valuation effects for its corre-sponding rival banks.

Contagion Effects

Studies have examined the impact on other commercial banks after a particular bank (orbanks) announces negative news such as a substantial loss or bank failure. A bankruptcy

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announcement provides negative information about a firms profitability and future cash

flow, which may not have been anticipated by the markets. Although each announcementis firm specific, investors may infer that other commercial banks will be subject to similarprofitability or cash flow concerns as regulators may have failed to react to internal warn-ing signs. Investors may therefore revise their expectations of other banks even thoughthe announcement did not directly relate to them. Thus, a negative announcement by onecommercial bank can be contagious to others.

Lang and Stulz (1992) establish a theoretical basis for understanding contagion andcompetitive effects within an industry. They hypothesize that the more similar a companyis to the bankrupt company, the greater the possibility of negative effects. In addition,similar firms with higher leverage will be more negatively impacted because those firmshave a greater probability of bankruptcy. The relatively large deposit portfolios of com-mercial banks compared to their capital base cause commercial banks to be highly lever-

aged. Hence, commercial bank stocks may demonstrate greater contagion effects thanfirms from less highly leveraged industries. On the other hand, investors may view com-mercial banks as more highly regulated and hence a profit warning may induce a smallercontagion effect than that for non-banking firms.

Aharony and Swary (1996) suggest that the contagion effect from bank failures isthe primary reason for bank regulation. Potential negative contagion effects of bankrupt-cies in the banking industry will be more disruptive than in other economic sectors. Thefailure of a single bank, especially a large one, may cause the public to lose confidence inthe banking system and cause a run. However, if the bankruptcy is due to fraud or illegalactivities, this might be considered a company specific event and have less of a conta-gious effect. Deposit insurance provided by the Federal Deposit Insurance Corporation(FDIC), as well as the FDICs practice of helping problem banks to be acquired by sol-

vent banks, reduces the risk of losses to depositors, thereby reducing the probability ofbank runs. Very large banks may be more immune to bankruptcy because of the percep-tion that regulators would not allow them to fail. Consequently, contagion effects mayless negatively impact larger solvent banks.

Aharony and Swary (1996) test these assertions by examining the impact of threebank failures on a sampling of other banks. Two of these bank failures stemmed fromcompany-specific fraud or illegal activities. As anticipated, they find that these failureshave no contagion effect on the other banks. The third bank failure was caused by heavylosses resulting from risky foreign exchange transactions and led to significant negativeperformance in the sample bank groups. Within the sample group, losses were twice aslarge for the largest banks as for the smallest banks. Aharony and Swary attribute this tothe market perception that the larger banks were more likely to have similar foreign ex-

change losses, supporting the theory that the contagion effect will be most pronouncedwhere the negative developments involve industry-specific factors.

Several researchers, e.g., Swary (1986), Sinkey and Carter (1999) and Karafiathand Glascock (1989) focus on the contagion effects related to specific events. The find-ings generally indicate some contagion effect, but in some cases the market treated theevent as firm specific. Swary (1986) examines the stock price reaction of several banks tothe failure of Continental Illinois Bank and finds a general negative reaction. Not only didhe find the expected negative market reaction for other banks with questionable liabilitymanagement, but he also finds negative contagion effects for banks whose solvency did

Volume 30 Number 9 2004 21


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not appear to put them at risk of failure. Akhigbe and Madura (2001) confirm contagion

effects, and document how the effects are conditioned on specific bank characteristics.

While there is clear evidence that rival banks can be affected by news of a bankfailure, there is limited research on how the other types of information about a singlebank may affect rival banks. Sinkey and Carter (1999) study the reaction of bank stockprices to several well-publicized reports during 1994 of corporations incurring substantiallosses in interest rate swaps and other derivative transactions. Sinkey and Carter analyzethe stock price reaction of Bankers Trust (the lead dealer on most of the transactions) andthree portfolios of banks: (a) large banks that are major dealers of derivatives; (b) otherbanks that use, but do not deal in derivatives and (c) banks that neither use nor deal in de-rivatives. As expected, they find that Bankers Trust and the large dealer banks have thelargest and most significant negative returns. They also find that non-dealer user bankshave smaller and less significant negative reactions while the banks that neither deal in

nor use derivatives have insignificant reaction. This result appears to indicate that al-though there is some evidence of contagion, the market is able to separate those banksthat are not affected by the derivative meltdown. We find that the contagion effects forbanks, although statistically significant, are smaller than that for non-banking firms.

Bank Signaling Hypotheses

Several studies show that enacting specific policies by a firm results in intra-industry ef-fects as other firms react to perceived signals. For example, Akhigbe and Madura (1999)assess the intra-industry effects of acquisition announcements. They conclude that thevaluation effects of rival bank portfolios are positively related to the valuation effects ofthe target banks, and inversely related to the size and prior performance of rival bankportfolios. The intra-industry effects result as investors discriminate based on event-

specific and rival bank-specific characteristics when interpreting the signal transmitted asa result of bank acquisitions. Further, Slovin, Sushka and Bendeck (1991) assess intra-industry effects of going private transactions, whereby a firms management or a special-ized firm acquires the shares of a firm to convert a publicly-traded business into aprivately-held business. They find that these transactions generate positive and signifi-cant valuation effects for industry rivals.

Signals About Banks That Issue Profit Warnings

Commercial bank stocks have been shown to react differently to market stimuli by sev-eral researchers such as Slovin, Sushka and Polonchek (1992). Specifically, banks aresubject to regulation, and may be less likely to engage in hidden business activities thatcould cause major losses. Yet, banks have information about their loans and other busi-

ness relationships that is not disclosed to investors. Given this asymmetric information,the announcement of a profit warning can emit a signal about the bank that was not previ-ously disclosed to the public. Investors attempt to distinguish bank-specific signals frombank industry signals. Profit warnings may serve as an industry signal because they pro-vide an update on the overall performance of a bank, which is likely influenced by exter-nal forces (economic conditions) that may also affect the performance of other banks.Jackson and Madura (2003) document that profit warnings elicit a significant negativemarket response on average. However, their sample excluded banks. We hypothesize thatbanks issuing profit warnings will experience negative valuation effects at the time of theannouncement.



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Signals From Bank Versus Nonbank Profit Warnings

Given the unique characteristics of banks, the valuation effects of a profit warning are notnecessarily equal to that of other firms. The commercial banking industry is highly regu-lated by government-appointed regulators to ensure financial stability. Public trust andconfidence in the banking system is critical for an efficient and orderly transfer of capitalfrom depositors to borrowers. However, regulators also restrict managers from expandinginto other industries or growing the bank through mergers and acquisitions. By settinglimits on financial ratios such as the proportion of highly leveraged loan transactions,regulators attempt to stabilize commercial bank performance. Thus, regulation may im-pose governance over banks that limit their potential losses.

Regulation ensures viability and maintains consumer confidence in the smoothfunctioning of the financial sector and in the payments system. Investors may therefore

expect that regulators will intervene to correct a banks problems if it issues a profit warn-ing. Specifically, the regulators can force the bank to maintain sufficient capital, whichmay require a financially troubled bank to seek an acquirer who can provide it with nec-essary capital. Regulations may therefore limit the downside risk following a profit warn-ing by a bank. Consequently, the market reaction to profit warnings will therefore be lesspronounced than that for other firms.

Bank Profit Warnings as Signals About Rival Banks

To the extent that a banks profit warning emits a signal about industry conditions, it maysignal negative information about rival banks. Therefore, we hypothesize that upon theannouncement of a banks profit warning, corresponding rival banks will experiencenegative valuation effects. While a profit warning is a milder form of news than a bank

failure, it may still offer valuable information about other banks.

Methodology

Our methodology is structured to test the three hypotheses that were introduced earlier.

Measuring Bank Valuation Effects

The cumulative abnormal returns (CARs) are calculated over a two-day event window forall banks in the sample. We use a market-model residual that first estimates an expectedreturn based on a historical 200-trading day time-series analysis. The difference betweenthe actual and expected return is given as the abnormal return. Since the market reactioncould occur the day after the announcement, (e.g., if the announcement occurs after trad-ing hours), we use a two-day announcement window of (0, +1) where day 0 is the date ofthe profit warning.

Comparing Bank Versus Nonbank Effects

To determine whether the bank valuation effects differ from a control sample of non-bankfirms, the following methodology is applied. A cross-sectional regression is estimatedwith a dummy variable that identifies commercial bank stocks. If the share price responseof commercial banks is less negative than other firms that issue profit warnings, thisdummy variable will be positive. The regression equation also includes variables to con-trol for the size of forecast change and firm size. Profit warnings are expected to cause



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more pronounced valuation effects when the size of the warning surprise (as measured by

the dollar difference between the most recent consensus forecast and the profit warning)is larger. We also include a variable for firm size as the valuation effects are also expectedto be more negative for smaller firms, because there is a limited amount of informationavailable on these firms. Therefore, the warning is expected to relay more informationabout smaller firms. A fourth variable included in the model is a timing variable that sig-nifies whether RFD had already been implemented. This regulation, imposed in October2000, (See How Regulation FD Has Changed Corporate Disclosure in Venture CapitalJournal, June 1, 2001) forces firms to disclose material information to all investors simul-taneously, and therefore may provide the market with more information prior to the warn-ing. Consequently, the warning may not be as much of a surprise. Jackson and Madura(2003) found that profit warnings for non-bank firms have a less pronounced effect afterimplementation of RFD. However, they did not assess commercial banks. Since RFDcould influence the valuation effects of commercial banks that issue profit warnings, this

variable is included in our model. The following cross-sectional equation is estimated:

CAR CB WSIZE FSIZE RFD= + + + + + b b b b b (1)

Where;

CAR j is the cumulative abnormal return for firm j,

CB is a dummy variable assigned a value of 1 for commercial banks and 0 otherwise,

WSIZEj is a continuous variable of the size of the profit warning

(measured as a dollar deviation from the consensus estimate),

FSIZEj is a continuous variable of the natural log of firm size, and

RFD is a dummy variable equal to 1 if the event occurred after implementation ofRegulation Fair Disclosure and 0 otherwise.

Measuring Effects on Rival Banks

To test the extent of the signaling effects among commercial banks consequent to profitwarnings, we use a similar methodology applied by Akhigbe and Madura (2001). Com-mercial banks are matched by market size and geography, and abnormal returns are cal-culated for each bank in the matched-firm portfolio. Statistically significant results forrivals at the time of the profit warning would indicate that although the event is firm spe-cific, the market adjusts the value of rivals due to a perceived contagion effect.

We next estimate a regression equation to test the intra-industry effect of a profitwarning by a bank. We include continuous variables to control for warning size, banksize, and the 2-day CAR for the warning bank, as well as a dummy variable to indicatewhether the warning occurred prior to or after RFD.

INTRAIND CAR WSIZE FSIZE RFD= + + + +b b b b b (2)

Where;



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INTRAIND is the intra-industry two-day return for non-warning bank j.

CAR is the two-day announcement cumulative abnormal return for commercial

bank j.

WSIZE , FSIZE and RFD are defined as in equation (1) above

Statistical significance of the RFD coefficient would indicate that the contagion ef-fect is also dependent on the time period in which the warning is made.

Data

To identify profit warnings, we use data provided by First Call / Thomson Financial Serv -ices in their database of Company Issued Guidelines (CIG). Warnings are defined as an-nouncements that indicate that the firms profit will fall short of the consensus analystsestimate, or announcements indicating the firms performance will be at the low end of a

range of analysts forecasts. In the absence of analyst forecasts, if the firm issues a CIGupdate that indicates erosion in earlier profit projections then these are also classified aswarnings. The matching firms in the intra-industry analysis are determined usingCompustat and the CRSP database is used as the source of stock-price information.

Table 1Profit Warnings by Commercial Banks

Panel A:Distribution of Pre-Regulation FD Warnings,

October 1, 1998 to October 22, 2000

Month # of Events

October - December 1998 9

January March 1999 7April - June 5

July - September 3

October - December 4

January March 2000 6

April - June 4

July October 22 14

TOTAL 52

Panel B:Distribution of Post-Regulation FD Warnings,

October 23, 2000 to September 30, 2001

Month # of Events

October 23 December 2000 6

January March 2001 11

April June 16

July September 7

TOTAL 40



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The operations of the matching sample of non-bank firms are clearly different from

the bank sample. To the extent that the bank operations are more transparent to investors,the industry signal from profit warnings by banks would be smaller. The initial dataset in-cludes all profit-warning announcements made by firms on a daily basis between October1, 1998 and September 30, 2001. The event date, day 0, is the actual date the announce-ment is made. However, since some events occur near to or after the end of the tradingday, we calculate a two-day CAR (0, +1) to capture the full market response to the profitwarning. All events are screened for contemporaneous events (defined as another firmevent within ten days of the profit warning that could influence stock price movementse.g., stock repurchase announcements, management dismissal etc). The Wall Street Jour-nal Index is used as the primary screen of the data for contemporaneous events. Commer-cial banks are identified by SIC classification and a total of 92 announcements areexamined in the pre and post-RFD periods (See Table 1). Of the 92 total warnings, 52 oc-curred before RFD and 40 after implementation of RFD.

Results

Results of the analyses are disclosed in the order of the hypotheses tested.

Valuation Effects of Bank Profit Warnings

Valuation effects of commercial banks that issued profit warnings are reported for thepre- and post-RFD periods in Tables 2 and 3 respectively. Pre-RFD warnings had two-day announcement CARs of 9.63% (with z-value of 18.664, statistically significant at1%). In the post-RFD period, the two-day announcement CARs was 3.51% (with a z-value of 5.027, statistically significant at 1%). Table 4 compares the abnormal returns ofbank profit warnings during the pre- and post-RFD periods. The table shows a significantdifference, which confirms that the profit warning effects have been reduced since RFD.

Signals of Banks versus Nonbank Firms

Table 5 presents the results of the regression to test the hypothesis regarding the differ-ence in the profit-warning signal between commercial banks and non-bank firms. Thedummy variable CB has a positive coefficient of 0.033, which is statistically differentfrom zero at the 5% level (t-value 2.037) thereby indicating that the CARs for commer-cial bank stocks are generally less negative than that of other U.S. stocks. The coefficientof WSIZE (size of the bank profit warning) is not significant, which suggests that whileinvestors penalized banks for the warnings; they did not discriminate according to size.They may process the size of the warning in accordance with their own expectations ofbank profitability. The FSIZE coefficient is 0.039 (with a t-value of 2.393) and is statisti-cally significant at 5% thus indicating that smaller firms have a more pronounced nega-

tive market reaction to profit warnings. The RFD coefficient is statistically significant(coefficient value of 0.217 with a t-value of 13.192 which is significant at 1%). This re-sult indicates that there is a statistically significant difference in market reaction to profitwarnings the pre- and post-RFD periods. However, the size of the warning is not statisti-cally significant, implying that the market reaction is not conditioned on the size of thewarning.

We also use an alternative dependent variable, which captures a profit-warning sig-nal over the eleven-day window ending on (and including) Day -1. This measurement in-cludes the leakage of information shortly before the profit-warning announcement.



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Results are disclosed in Table 6. The CB dummy variable remains positive but is no

longer significant, indicating no difference in the extent of leakage for commercial banksand non-banking firms. However, the RFD variable is positive and significant, thus indi-cating that the extent of information leakage, as measured by the negative CARs in thedays preceding the warning, is attenuated in the post-RFD period.

Table 2Daily Pre-FD Abnormal Returns and CARs for Selected Windows for Commercial Banks with

Profit Warnings.

Abnormal Returns calculated as the Market Model residual using an Equally Weighted Index. CARscalculated by summing daily returns in the respective event window. The third column shows the numberof CARs that are positive versus negative on a particular event day. The fourth column shows the Z-valuethat tests whether the CAR is significantly different from zero.

DayMean Abnormal

ReturnPositive:

Negative z-value

-11 -0.36% 21:31 -0.769-10 -0.38% 18:34 -1.371

-9 -0.11% 24:28 -0.209

-8 -0.82% 20:32 -2.359**

-7 -1.51% 21:31 -4.808***

-6 -0.95% 19:33 -3.001***

-5 0.05% 22:30 0.233

-4 0.76% 27:25 2.275**

-3 -0.66% 20:32 -1.765*

-2 -0.34% 25:27 -1.016

-1 0.59% 31:21 0.842

0 -5.62% 15:37 -15.499***

+1 -4.01% 18:34 -10.897***

+2 0.64% 29:23 1.897*

+3 -0.57% 23:29 -1.238

+4 -0.62% 23:29 -1.960**

+5 0.50% 21:31 1.574

+6 -1.02% 19:33 -2.784***

+7 0.29% 25:27 0.941

+8 -0.47% 20:32 -1.285

+9 0.28% 24:28 0.261

+10 -0.21% 23:29 -0.686

+11 -0.08% 24:28 -0.722

Day

Mean CumulativeAbnormal

ReturnPositive:

Negative z-value

(0,0) -5.62% 15:37 -15.499***

(0,+1) -9.63% 11:41 -18.664***

(-11,-1) -3.74% 15:37 -3.602***

The symbols *, **, and *** denote statistical significance at the 10%, 5%, and 1% levels, respectively,using a 2-tail test.



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Table 3

Daily Post-FD Abnormal Returns and CARs for Selected Windows for Commercial Banks withProfit Warnings.

Abnormal Returns calculated as the Market Model residual using an Equally Weighted Index. CARscalculated by summing daily returns in the respective event window. The third column shows the numberof CARs that are positive versus negative on a particular event day. The fourth column shows the Z-valuethat tests whether the CAR is significantly different from zero.

DayMean Abnormal

ReturnPositive:

Negative z-value

-11 -0.70% 14:26 -1.103

-10 0.15% 17:23 -0.301

-9 -0.19% 18:22 -0.627

-8 -0.18% 20:20 -0.238

-7 -0.76% 15:25 -0.685

-6 -0.65% 16:24 -0.698

-5 0.70% 22:18 0.006

-4 -0.95% 15:25 -0.880

-3 0.06% 17:23 -1.069

-2 -0.52% 19:21 -0.144

-1 0.91% 22:18 1.110

0 -1.46% 11:29 -3.527***

+1 -2.05% 14:26 -3.583***

+2 -0.33% 19:21 0.085

+3 0.92% 20:20 1.096

+4 0.63% 22:18 0.742

+5 0.46% 22:18 1.178

+6 -0.76% 16:24 -0.633

+7 1.00% 16:24 0.041

+8 0.36% 20:20 1.354

+9 -0.98% 21:19 -1.312

+10 0.50% 23:17 1.165

+11 -0.48% 19:20 0.009

Day

Mean CumulativeAbnormal

ReturnPositive:

Negative z-value

(0,0) -1.46% 11:29 -3.527***

(0,+1) -3.51% 14:26 -5.027***

(-11,-1) -2.13% 14:26 -1.396




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Table 4Comparison of Pre- and Post-RFD CARs for Commercial Bank Stocks with Profit Warnings.

Abnormal Returns calculated as Market Model residual using an Equally Weighted Index. The eventwindow cumulative abnormal returns (CARs) are reported along with theirz-values in parentheses. Thefourth column discloses the difference between the CARs in the pre- versus post-RFD periods, along witha test for whether the difference is equal to zero.

EventWindow Pre-RFD Post-RFD Difference

(0, 0)

(0, +1)

(-11, -1)

-5.62%(-15.499)***

-9.63%(-18.664)***

-3.74%(-3.602)***

-1.46%(-3.527)***

-3.51%(-5.027)***

-2.13%(-1.396)

-4.16%(-2.694)***

-6.12%(-2.892)***

-1.61%(-0.956)


Table 5Estimates of Firm Type, Warning Size, Firm Size, and Event Time on the Announcement (0, +1)

Abnormal Returns.CARj = b + b CBj + b WSIZEj + b FSIZEj+b RFD + e (1)

Where CAR is the two-day (0, +1) cumulative abnormal return for firm j. CB is a dummy variableassigned a value of 1 for commercial banks and 0 otherwise. WSIZEj is a continuous variable of the sizeof the earnings warning. FSIZEj is a continuous variable of the natural log of firm size (marketcapitalization used for size) and RFD is adummy variable assigned a value of 1 for events in Post-RFDand 0 otherwise. The regression coefficients are reported along with their t-values in parentheses.

DescriptiveStatistics CB WSIZE FSIZE RFD

Coefficients 0.033

(2.037)**

-0.018

(-1.134)

0.039

(2.393)**

0.217

(13.192)***

R Square = 0.053Adjusted R Square = 0.052F = 50.513***The symbols *, **, and *** denote statistical significance at the 10%, 5% and 1% levels respectively.

Table 6Estimates of Firm Type, Warning Size, Firm Size, and Event Time on the Pre-Announcement

(-11, -1) Abnormal Returns.CARj = b + b CBj + b WSIZEj + b FSIZEj+ b RFD + e (1)

Where CAR is the eleven-day (-11, -1) cumulative abnormal return for firm j. CB is a dummy variableassigned a value of 1 for commercial banks and 0 otherwise. WSIZEj is a continuous variable of the sizeof the earnings warning. FSIZEj is a continuous variable of the natural log of firm size (marketcapitalization used for size) and RFD is a dummy variable assigned a value of 1 for events in Post-FD and0 otherwise. The regression coefficients are reported along with their t-values in parentheses.

CB WSIZE FSIZE RFD

Coefficients 0.009

(0.526)

0.003

(0.186)

-0.027

(-1.581)

0.065

(3.840)***

R Square = 0.004Adjusted R Square = 0.003F = 3.971**The symbols *, **, and *** denote statistical significance at the 10%, 5% and 1% levels respectively.



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Effects on Bank Rivals

Rival effects in response to commercial bank warnings are summarized in Table 7. Forthe total sample of commercial banks, rivals had two-day announcement ACARs of-1.05% with a t-value of 2.655 (statistically significant at 5%). In the pre-RFD period,the impact was larger with a value of 1.46% (t-value 2.399, significant at 5%). The re-sults for the post-RFD period are also negative but was statistically insignificant. Thus,while the contagion effects are present in the pre-RFD period, there is no evidence of con-tagion effects since the implementation of RFD.

Table 7Contagion Effects of Profit Warnings (Pre- and Post-Regulation FD).

Abnormal returns calculated as the Market Model Residual using an Equally Weighted Index. The eventwindow cumulative abnormal returns are reported along with their z-values in parentheses.

Events WarningBanks

Non-WarningBanks Difference

All Events

Pre-FD

Post-FD

-6.97%(-6.384)***

-9.43%(-18.664)***

-3.51%(-5.027)***

-1.05%(-2.655)**

-1.46%(-2.399)**

-0.48%(-1.175)

-5.92%(-2.856)***

-7.97%(-3.869)***

-3.03%(-2.137)**

The symbols *, **, and *** denote statistical significance at the 10%, 5% and 1% levels respectively.

Summary

Bank profit warnings reflect an attempt by banks to correct the markets expectations of

its earnings. Since the bank is the insider, its issuance of a profit warning may reduce theasymmetric information between itself and the market. Our objective is to measure thesignals contained within profit warnings about the issuing bank and its rivals. We findthat banks issuing profit warnings experience negative and significant valuation effects.Second, the valuation effects experienced by banks are less pronounced than those of acontrol sample of nonbank firms that also issued profit warnings.

Third, the banks profit warnings result in significant negative valuation effects forits corresponding rival banks in the period before RFD. Thus, bank profit warnings carrysignals not only about the banks who transmit the information, but also about correspond-ing rivals in that period. The warnings relay a signal about industry conditions, which themarket uses to alter the valuations of rival banks. However, since the passage of RFD, thecontagion effects are attenuated. This may be caused by more information in the market,

such that investors rely less on information about one bank when valuing others. That is,the degree of asymmetric information held by banks has been reduced. As accountingregulations are phased in to ensure more transparency, investors should have more directmethods of valuing banks.

Acknowledgements

We wish to thank an anonymous reviewer, Elyas Elyasiani (Co-Editor of this Issue), JoelHarper, Judy Swisher, and Joan Wiggenhorn for their valuable suggestions and FirstCall/Thomson Financial for providing data.



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References

Aharony, Joseph and Itzhak Swary. 1996. Additional Evidence on the Information-basedContagion Effects of Bank Failures. Journal of Banking & Finance, 57-69.

Akhigbe, Aigbe and Jeff Madura. 1999. Intra-industry Signals Embedded in Bank Acqui-sition Announcements. Journal of Banking and Finance, 1637-1654.

Akhigbe, Aigbe and Jeff Madura. 2001. Why do Contagion Effects vary Among BankFailures? Journal of Banking and Finance, 657-680.

Beller, Kathryn. 2001. How Regulation FD Has Changed Corporate Disclosure. VentureCapital Journal, June 1, 2001.

Jackson, Dave and Jeff Madura. 2003. Profit Warnings and Timing. The Financial Re-view, 38: 497-513.

Jackson, Dave and Jeff Madura, 2002, Impact of Regulation Fair Disclosure on the Infor-mation Flow Associated With Profit Warnings. Working Paper.

Karafiath, Imre and John Glascock. 1989. Intra-Industry Effects of a Regulatory Shift:

Capital Market Evidence from Penn Square. The Financial Review, 123-134.

Lang, Harry and Rene Stulz. 1992. Contagion and Competitive Intra-Industry Effects ofBankruptcy Announcements: An Empirical Analysis. Journal of Financial Economics,45-60.

Sinkey, Joseph F. Jr. and David A. Carter. 1999. The Reaction of Bank Stock Prices toNews of Derivatives Losses by Corporate Clients. Journal of Banking and Finance,1725-1743.

Slovin, M.B., M.E. Sushka, and Y.E. Bendeck. 1991. The Intra-industry Effects of GoingPrivate Transactions. The Journal of Finance, 46:1537-1549.

Slovin, M.B., M.E. Sushka, and J.A. Polonchek. 1992. Informational Externalities ofSeasoned Equity Issues: Differences Between Banks and Industrial Firms. Journal of Fi-nancial Economics, 87-101.

Swary, Itzhak. 1986. Stock Market Reaction to Regulatory Action in the Continental Illi-nois Crisis. The Journal of Business, 451-473.


Bank Profit

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