Banking Stress Test Effects on Returns and Risks

We investigate the effects of the announcement and the disclosure of the clarification, methodology, and outcomes of the US banking stress tests on banks' equity prices, credit risk, systematic risk, and systemic risk during the 2009-13 period. We find only weak evidence that stress tests after 2009 affected equity returns of large US banks. In contrast, CDS spreads declined in response to the disclosure of stress test results. We also find that bank systematic risk, as measured by betas, declined in some years after the publication of stress test results. Our evidence suggests that stress tests affect systemic risk.


Introduction
Bank supervisors expect banks to hold su cient capital to cover losses under adverse economic conditions. Stress testing has become an important tool for bank supervisors to achieve that goal. In stress tests the implications for individual banks' nancial positions under several macroeconomic scenarios are examined, taking the banks' exposures and business models into account. Stress tests have several characteristics (Goldstein and Sapra, ). First, they are forward looking. Second, they generally put high weight on highly adverse scenarios, thereby providing supervisors with information about tail risks. ird, common scenarios are applied to banks so that stress tests have the ability to provide more consistent supervisory standards across banks. Finally, unlike traditional supervisory examinations that generally are kept condential, the results of bank stress tests are frequently publicly disclosed in order to restore con dence and reduce market uncertainty (Federal Reserve, b). is paper examines the impact of banking stress tests in the US on banks' stock prices, CDS spreads, systematic risk (proxied by banks' betas), and systemic risk over the -period. e rst test considered is the Supervisory Capital Assessment Program (SCAP) of the largest Bank Holding Companies (BHCs).
e outcomes of this test were disclosed on May , . Since then the Federal Reserve implemented two supervisory programs. e rst program, the Comprehensive Capital Analysis and Review (CCAR), assesses the capital planning processes and capital adequacy of banks and has been conducted annually since . e CCAR links quantitative stress test results with qualitative assessments of capital planning processes of banks. e second program stems from the Dodd-Frank Act and requires assessing how bank capital levels would fare in stressful scenarios (Federal Reserve, b). e rst Dodd-Frank Act Stress Test (DFAST) results were publicly released on March , . It is widely believed that stress tests conducted in the US have provided valuable information to the market. Referring to post-crisis stress tests then Federal Reserve chairman Bernanke stated: "Even outside of a period of crisis, the disclosure of stress test results and assessments provides valuable information to market participants and the public, enhances transparency, and promotes market discipline. " (Bernanke, ) Indeed, according to Morgan et al. ( ), the disclosure of the SCAP test results caused credit default swap spreads to decline and equity returns to rise. We reassess this nding and examine whether it also holds for other stress tests.
Our paper adds to the literature in three ways. First, we examine the e ects of all post-crisis stress tests in the US. Second, in contrast to most previous research, our analysis is not con ned to the e ects of stress tests on equity returns and CDS spreads but also considers the impact of stress tests on bank betas. Betas capture systematic risk based on the co-movement of returns with the overall market and are therefore particularly relevant for understanding the e ects of stress tests. In addition, we study whether the change in betas is due to changes in individual bank risk, or due to changes in systemic risk following the approach suggested by Nijskens and Wagner ( ). Finally, we do not only consider the impact of the publication of the stress test outcomes, but also examine other disclosure events, such as the announcement of the stress test and the disclosure of the methodology to be used, as these may also provide information (Petrella and Resti, ; Gick and Pausch, ). As will be pointed out in more detail in Section , our paper is related to three strands of literature. e rst strand examines whether information provided by the disclosure of the outcomes of stress tests reduces the opacity of banks (Morgan et al., ; Cardinali and Nordmark, ; Beltratti, ; Ellahie, ; Petrella and Resti, ). Most (but not all) studies conclude that stress tests produce valuable information for market participants and can play a role in mitigating bank opacity. e second strand of related literature examines to what extent supervisory information should be disclosed (e.g. Goldstein and Sapra, ; Schuermann, ). Several of these studies conclude that it may not always be optimal to fully disclose stress test results. e nal related strand of literature examines how stress tests can be used to set capital ratios, limit capital distributions, and set-up resolution regimes in case of nancial distress (BCBS, ).
Our ndings suggest that the release of the stress test outcomes had no e ect on equity returns in contrast with the results of Morgan et al. ( ). Our ndings for post-crisis stress tests show some reaction of equity returns in some years but the e ects are small and statistically weak. In addition, we nd evidence that the publication of stress test results reduced CDS spreads in , and . We nd mixed results for other dates on which stress test information was released. Our analysis of systematic risk indicates that betas were a ected by the publication of the outcomes of nearly all stress tests. Moreover, we nd some evidence that the decline in betas is in part driven by the correlation of the banks' stocks with the market. We interpret these ndings as a decrease in systemic risk. e paper is structured as follows. Section provides a summary of related literature and outlines how our research is related to this literature. Section gives an overview of the stress tests conducted in the US. Section outlines our methodology and Section presents our ndings. Finally, Section concludes.

Related studies and contribution
Our paper is related to three strands of literature. First, several studies examine whether bank opacity differs from that of non-nancial rms in 'normal' times (cf. Morgan, ; Flannery et al., ; Iannotta, ; Jones et al., ; Haggard and Howe, ). A good example is the recent paper by Flannery et al. ( ) who study bank equity's trading characteristics and nd only limited evidence that banks are unusually opaque during normal times. From this perspective, some recent studies examine the information value of stress tests. Morgan et al. ( ) conclude that market participants correctly identi ed which institutions had su cient capital under the SCAP stress test, but were surprised by how much capital was required for under-capitalized banks.
Stress tests have also been conducted by European supervisors and several recent papers examine whether the disclosure of the outcomes a ected nancial markets. Petrella and Resti ( ) nd significant but modest market responses to the European Banking Authority (EBA) stress test in . Ellahie ( ) studies equity and credit market data of Eurozone banks that took part in the stress tests in and . His ndings indicate that equity and bid-ask spreads were not signi cantly a ected by stress test announcements but declined a er the disclosure of stress test results. Cardinali and Nordmark ( ) report that the announcements of the stress test and the clari cation of the methodology in were relatively uninformative to markets. In contrast, they nd that the disclosure in by EBA of the stress test methodology was highly informative for all stress-tested banks. Likewise, Beltratti ( ) argues that the EBA stress test produced new information, as investors could not a priori distinguish between capitalized and under-capitalized banks.
Table provides a summary of recent empirical papers on the market response to stress tests. In line with some previous papers on European stress tests, in our analysis of US stress tests we distinguish between several tests-related events, such as the announcement of the stress test and the disclosure of the methodology and the stress test outcomes. We also distinguish between banks with and banks without capital shortfalls. So our paper complements the work of Morgan et al. ( ) by documenting the e ects of stress tests on equity returns and CDS spreads for stress tests conducted in the US a er the SCAP. e literature on supervisory transparency and disclosure is also closely related to our work. e central question addressed in these studies is to what extent supervisory information should be disclosed. As shown by Liedorp et al. ( ), the transparency of banking supervisors di ers considerably. According to Goldstein and Sapra ( ), in certain environments more disclosure is not necessarily better if one considers economic e ciency. Accordingly, the costs associated with disclosure of stress test results can be minimized in particular by disclosing aggregate, rather than bank-speci c results. Also Schuermann ( ) argues that the degree of optimal disclosure may depend on the environment. During times of crisis, the need for bank-speci c disclosure is greater while during normal times the cost-bene t of stress testing disclosure may lean towards more aggregated information. Gick and Pausch ( ) argue that a supervisory authority can create value by disclosing the stress-testing methodology together with the stress test result. Bischof and Daske ( ) investigate the interaction between mandatory supervisory disclosure and voluntary disclosure strategies of banks that were subject to the EBA stress test in . eir ndings indicate that lower market liquidity is attributable to banks that did not voluntarily disclose their sovereign risk exposures. Banks disclosing their exposures witnessed increases in liquidity and decreases in the equity bid-ask spread.
Our paper is related to this line of literature, as we do not only examine the e ects of the publication of the stress test results, but also the e ects of the announcement of the stress test (Petrella and Resti, ) and the disclosure of the methodology (Gick and Pausch, ). Finally, our paper is related to the literature on the impact of regulation of Systemically Important Financial Institutions (SIFIs). Stress tests are used to set capital ratios, limit capital distributions, and setup resolution regimes in case of nancial distress (BCBS, ). Bongini and Nieri ( ) investigate the response of nancial markets to the Financial Stability Board's publication of the list of institutions that are too-big-to-fail. ey quantify the value of an implicit too-big-to-fail subsidy and nd that nancial markets did not strongly react to the proposed new regulation regarding SIFIs. Schaefer et al. ( ) investigate the reaction of the stock returns and CDS spreads of US and European banks to several regulatory reforms including the too-big-to-fail regulation in Switzerland. ese authors report signi cant market reactions in response to this regulation, which strongly increased CDS spreads of systemic banks, but a ected equity prices only mildly.
Our study is related to this literature as we examine the systematic risk of banks. We expect the beta of a bank to decline following the publication of the results of a stress test. e information provided by the stress tests could reduce the uncertainty on bank stability and therefore would lower the overall level of risk in the industry. is would lead to a decline in bank betas. To study the underlying shi s in systematic risk we decompose the changes in betas into changes in the correlation of stocks with the market (systemic risk) and changes in the relative variance (idiosyncratic risk) following a similar approach as Nijskens and Wagner ( ). ese authors study credit risk transfers of banks through issuance of CDS and CLO contracts. ey disentangle the changes in betas and nd that the increase in betas was primarily due to an increase in the correlation of stocks with the market. Although banks became individually less risky using credit risk transfers, systemic risk increased. As we examine the changes in betas in a similar way we can examine how stress tests have a ected systemic risk.

Stress tests in the US
e Federal Reserve's CCAR exercises conducted in -can be classi ed as micro-prudential supervisory stress tests. ey are 'top down' in the sense that the Fed independently produced loss estimates using its own supervisory models. Although the Fed publishes the results of stress tests, the speci cation of the models used to arrive at them remains a 'black box' (Bernanke, ). An important reason for this is to prevent the homogenization of stress test models, as banks would over time have fewer incentives to maintain independent risk management systems and adopt the speci cations used by the Fed. ese tests were conducted in the a ermath of the crisis and unlike the SCAP in were not crisis management stress tests. e latter di er in their emphasis on solvency, current risks, and their speci c 'constrained bottom-up' approach (Oura and Schumacher, ). For the SCAP exercise the Fed relied more on the banks' own estimates.
Although stress tests have been criticized because of insu cient coverage or their implementation strategy, they have become an important instrument in supervisory authorities' toolkit. is is true for micro-prudential (BCBS, ) as well as macro-prudential stress tests (Borio et al., ). Table provides a descriptive overview of the stress tests conducted in the US on which we focus. Stress test design evolved. In subsequent stress tests the Fed re ned the hypothetical scenarios taking into account the procyclicality of the nancial system and severe adverse developments on housing, equity, and asset markets (Federal Reserve, , a,b). To see how much attention stress tests received we collected news articles from a variety of news sources from the Dow Jones Factiva database for the -period. We searched for all news containing the words "stress test" related to the banking stress tests procedure. e number of news articles related to stress test events provides a crude indication of how much attention stress tests received. Our nal list of articles contains news on individual banks, the banking industry, and the US economy.
e news was ltered with all the relevant bank names and with the names of related government agencies, such as the Federal Reserve, FDIC and the US Department of the Treasury. We veri ed all news manually for relevance.
Our news analysis suggests that the SCAP received considerable more attention than the subsequent CCARs and DFAST. e news index also reveals that stress tests were a substantial part of market sentiment in -. About percent of all news about the US banking industry in this period relates to stress tests. Not surprisingly, the highest frequency of news reports on this topic appeared when the stress test outcomes were disclosed. Other peaks occurred when the details of the stress tests were announced and when the results for participating banks were released. In the remainder of our paper, we use an event study approach to quantify the e ects of the disclosure of stress test information on nancial markets.

Data and methodology . Data
We use equity returns of banks that have participated in the US stress tests over the -period. We employ the S&P returns index as proxy for the market portfolio. Data were obtained from Bloomberg. Table lists the participating banks considered in our research and shows the results of the stress tests. We also use daily data on -year senior CDS spreads for a subset of the banks. We employ the CDX Investment Grade Index provided by Bloomberg as proxy for a market portfolio in the CDS market. is index represents the rolling equally-weighted average of of the most liquid North American CDS series Macro-prudential stress testing has evolved over time. is type of stress tests is discussed e.g. by Cihak (  We have also considered the e ects of stress tests using price to book ratios as a measure of investors' beliefs in the banks' ability to generate pro ts. e ndings from this analysis are very similar to our main results. We include GMAC (Ally Financial) in our CDS analysis but exclude it from our stock analysis as it was not publicly traded. We also exclude MUFG Americas Holdings Corporation and Citizens Financial Group. e banks included in the stress tests cover at least of total US banking sector assets. e sample for our CDS analysis is smaller as credit default swaps of some banks were not available or not traded. e following banks are included in our CDS analysis: American Express, Bank of America, Capital One Financial, Citigroup, GMAC (Ally Financial), Goldman Sachs, JPMorgan Chase, Metlife, Morgan Stanley, and Wells Fargo. Ten banks with a capital gap. Tier common capital increased to bln. and Tier common equity ratio increased to . .

CCAR
Quantitative assessment of capital levels and qualitative assessment of internal capital planning processes of banks. Banks submit capital plans to the Fed, largest banks submit trading P&L statements.
Banks mostly had to lower their capital distributions, payout decreased to in from in .

CCAR
Banks that did not participate earlier are now subject to a Capital Plan Rule. Banks submit a description of internal processes for assessing capital adequacy; policies governing capital actions; planned capital actions; and results of company-run stress tests. Banks are solvent with a Tier common ratio.
Four banks had a capital gap. Doubling of weighted Tier common equity ratio.
DFAST Quantitatively assess how bank capital levels would fare in adverse economic conditions. Financial companies with total consolidated assets between bln and bln are required to conduct their own stress tests.
One bank failed to adhere to the minimum of Tier common equity ratio.

CCAR
Quantitative and qualitative evaluation of whether a bank's capital accretion and distribution decisions are prudent. Banks have to disclose their own estimates of stressed losses and revenues. e Fed also discloses whether or not it objected to each bank's capital plan.
Two banks conditionally approved, two banks not approved.
DFAST Assessment of additional banks with bln or more total consolidated assets. e Fed independently projects balance sheets and RWAs of each bank. e Basel III revised regulatory capital framework is incorporated into the assessment. A total of banks is assessed.
Over the nine quarters of the planning horizon, losses at the banks under the severely adverse scenario are projected to be bln. One bank did not pass the assessment.

CCAR
Banks with signi cant trading activities are required to apply a hypothetical Global Market Shock to trading and counter-party exposures. Banks are subject to a new counter-party default scenario requirement and must include losses from the default of their largest stressed counter-party. A bank's projected capital ratios are interpreted relative to the minimum capital requirements in e ect for each quarter of the planning horizon.
Five banks did not pass the test.

DFAST
A total of banks is assessed. All banks passed the test.

CCAR
Banks were required to re ect the transition arrangements and minimum capital requirements of the revised regulatory capital framework in their estimates of pro forma capital levels and capital ratios.
Two banks did not pass.

. Methodology
To examine whether stress tests have a ected equity or CDS markets we follow an event study methodology described e.g. in Brown and Warner ( ), ompson ( ), or MacKinlay ( ). Figure provides an overview of all the relevant stress test events. Following Morgan et al. ( ), we present ndings for a -days event window (-,+ ). Our estimation window for equity returns and CDS spreads consists of trading days, i.e. the (-,-) time interval, where t = is the event date of the corresponding stress test.
is window is su ciently long to conduct an event study using daily data (MacKinlay, ). When event windows are overlapping, or a single event a ects multiple banks, we can no longer assume that the abnormal returns of securities are cross-sectionally uncorrelated. Figure shows that the date of the methodology release and the date of the disclosure of the results of the CCAR in are particularly close. In this case the covariance may deviate from zero and we can no longer use the distributional results for the aggregated abnormal returns (MacKinlay, ). Consequently, we treat the disclosure of the methodology and the results of CCAR as a "large" event. To measure the impact of an event we set the abnormal return of a security as the di erence between the actual (ex post) return and the normal return over the relevant event window. Normal returns are estimated using the following market model, . ey disentangle the e ects of the events by considering how equity and bond-holders are a ected. ey reason that the former event mattered for both market participants but the release of the Capital Assistance Plan details mattered only for equity holders. is table presents the list of the banks which passed/failed the -stress tests. '+' means that a bank passed the stress test without any frictions ('No-Gap' banks), and '-' indicates that a bank did not meet the minimum post-stress capital ratio requirements or had de ciencies in its capital planning process that undermine its overall reliability of capital planning process ('Gap' banks). An empty cell denotes that the bank did not participate in the corresponding testing procedure. e banks are divided into global SIFIs, domestic SIFIs, and non-SIFIs according to the classi cation of the Financial Stability Board (FSB, where R i ,t is the daily return of equity of bank i at time t, and R m,t is the return of a market portfolio (the S&P returns index). Similarly the CDS spread of bank i at time t is regressed on the overall index, the CDX Investment Grade Index (cf. Norden and Weber, ; Morgan et al., ). e residuals or abnormal returns (AR) implied by the market model are given by, where the circum ex indicates that the parameter concerned is estimated. e abnormal returns are summed over the relevant window around the event date to compute the cumulative abnormal return (CAR). e t-statistics obtained from the estimation in ( ) are adjusted for event clustering and event induced volatility following Kolari and Pynnonen ( ). e adjusted t-statistics are employed to test whether the CAR signi cantly di ers from zero.
In order to assess the possible changes in systematic risk caused by stress test events we decompose the beta into a market correlation component and a volatility component following Nijskens and Wagner ( ). We estimate the relation between returns and a banks' beta using the following model, where α i is the bank xed e ect, D j is a dummy variable with value one up to ten trading days of the next event and j ∈ {A, C, M, R} denotes the announcement, clari cation, methodology, and result events, respectively. D A * R m,t , D M * R m,t , and D R * R m,t are the interaction terms of interest. eir coe cients will capture the change in bank betas a er the announcement events, methodology event, and a er the result events, respectively. Next, we decompose the changes in betas into changes in the correlation of stocks with the market and changes in the relative variance. at is, the beta can be represented by, where ρ i ,m is the correlation coe cient between the equity and the market and σ m the variance of the market. e beta in ( ) is the product of the correlation of a bank's equity price with the market and its standard deviation relative to that of the market. We then normalize our model in ( ) by dividing the equity and market returns by their respective standard deviations. As a consequence the coe cient of the With a slight abuse of notation, we denote the cumulative abnormal spreads obtained from the CDS counterpart of ( ) also as CARs.
In the presence of event clustering cross-correlation among securities may lead to over rejection of the null hypothesis of zero average abnormal returns. We have employed a GARCH analysis to verify that stress test events contributed to shi in volatility (not presented). Not all recent event studies adjust for clustering (e.g. Candelon and Sy, ), but in our view it is the proper procedure. See also Amici et al. ( ); Fratianni and Marchionne ( ); Elyasiani et al. ( ). Note that we exclude the clari cation and methodology events of in our beta analysis as they are very close to the announcement and result release of SCAP, respectively. Similarly, we only consider the announcement of DFAST and the results release of CCAR as these are the rst and last events of interest in , respectively. Our post-stress-test periods for evaluating beta vary over the years.
To arrive at ( ), note that individual stock beta β i = cov i ,m σ m can be represented as β i = ρ i ,m σ i σm using the correlation notation ρ i ,m = cov i ,m σ i σm . To identify shi s in the relative variance, σ i σm, we do the following decomposition: β = β + ∆β where the superscripts denote the beta before and a er the event. Using β = ρ i ,m the relative variance can be rearranged as and, therefore, a change in relative variance is ∆ normalized returns equals the correlation of the previous series, and ( ) changes to β i = ρ i . e regression equation is then changed to, and t i stands for the event date.

. How do stress tests a ect equity returns and credit risk?
We present our ndings in Tables and . Table shows reactions in the stock market and Table shows reactions in the credit market. We discuss each market in turn, considering the announcement, clari cation, methodology, and result events. Table , the announcements of stress tests generally had a mixed e ect on equity returns. e stock market reacted positively to the announcement of DFAST and CCAR in but negatively in . e mixed e ect on stock prices may re ect that generally stress test announcements provide limited (quantitative) information on the way the stress tests will be conducted or how their results will be used. e market's reaction to then chairman Bernanke's clari cation in that banks would not be nationalized caused an upward movement in equity returns. e clari cation event notably increased the CARs of gap banks by . percent as these banks were at the time considered to be at risk to be nationalized (Morgan et al., ). Similar to Morgan et al. ( ) we nd no evidence that the methodology disclosure of the SCAP has led to changes in stock prices. ere is some evidence that the publication of the methodology of CCAR in has a ected stock prices negatively. In the other years the methodology and results were released jointly.  (Kolari and Pynnonen, ). Table A in the Appendix provides ndings over extended event windows for the SCAP stress test.

Stock market As shown in
ere is very little evidence of stock market reactions for the SCAP stress test except for the clari cation event.
Overall the ndings suggest that the release of stress test results a er have had little e ects on equity markets. As shown in Table in some years stock markets reacted. In , for example, for the In the methodology and results were released on two consecutive days. As discussed in our methodology section we treat these events as a single 'large' event.
Another di erence is the estimation period. Morgan et al. ( ) estimate their analysis over a relatively less volatile period (July , to June , ). Our ndings are robust to a change in the estimation period. Using the same estimation period as Morgan et al. ( ) and correcting for clustering, we still nd that the results of the SCAP stress test did not a ect stock prices within a (-,+ ) window. Results are available upon request. sample of no-gap banks we nd that the equity market reacted positively to the disclosure of the results of stress tests. However, the ndings are statistically weak. Moreover, the magnitude of the impact in all years is lower than that in following chairman Bernanke's clari cation. Arguably, during a crisis the need for credible information is greater than in calmer periods so the market may have valued the information disclosed in the clari cation in more (Schuermann, ). Finally, the reactions in post-crisis stress tests are not always uniform.
is is particularly so for the announcement e ects (negative in and positive in ) but also for results (negative in and positive in ). Table shows, the announcement events had a mixed e ect on CDS spreads. Spreads were negatively a ected in for no-gap banks and positively in for gap banks. Moreover, we see that Bernanke's clari cation of the stress test in did not a ect the CDS market. is response is expected due to the structure of the CDS agreements where any change in ownership due to nationalization would not bring additional losses to contract parties.

Credit market As
For the methodology events we nd mixed results. For we nd no impact on CDS spreads. However, in CDS spreads declined signi cantly following the release of the stress test methodology. is suggests that the release of the methodology in was less informative for the market compared to . In there was no disclosure of stress test results, which could have led the market valuing the information provided by the methodology disclosure relatively strongly.
Table shows a decline in the average CDS spreads in for no-gap banks following the publication of the stress test results. Average spreads dropped . basis points for no-gap banks. e disclosure of the results of CCAR in and also have led to lower CDS spreads. In contrast, the results of DFAST seem to have been uninformative to the credit market. e fact that CCAR in a ected CDS spreads stronger than DFAST could be due to two reasons. Firstly, as Table shows, in DFAST all the banks in our stock sample received approval while in CCAR three of these banks were not approved. e market may therefore have attached more importance to the results of CCAR. Alternatively, it could be due to the underlying assumptions of the stress tests. While DFAST was conducted conditional on no change in the capital distributions, CCAR incorporated the capital plans proposed by the banks and, therefore, may have better re ected creditworthiness (Federal Reserve, a). Table A provides, again, ndings over extended event windows for the SCAP stress test. e results over longer event windows are in line with our main ndings for the credit market: spreads decline following the publication of stress test results. Overall, the ndings indicate that stress tests in some years a er the crisis have provided new information to CDS markets.

. How do stress tests a ect systematic and systemic risk?
Systematic risk Table presents event dummies associated with the stress tests and the interaction terms with betas. We focus our discussion on these interaction terms. Table shows that the impact of the announcement e ects are mixed. In the announcement of SCAP has led to an increase in systematic risk. For the remaining years there is no consistent evidence of movement in betas. Considering results Morgan et al. ( ) nd a decline in CDS spreads following the clari cation event (though only for gap banks). However, they consider CDS contracts with an MR document clause. is entails that these contracts do not suppose full coverage in case of a credit event. As we do not consider these types of contracts a possible nationalization would not a ect the spreads. e ndings over extended windows are, however, suggestive at best as the probability that other factors may a ect spreads increases as the event window is extended.

Stock market reaction to stress tests (in )
Notes: *** -, ** -, * -signi cance level. is table presents CARs for the main stress test events over the -period calculated using Equation ( ) with a (-,+ ) event window. Reported signi cance are based on corrected t-statistics. Column ' All' shows the e ects of events on the average CARs of all banks. Columns 'No-Gap' and 'Gap' separate the e ects into banks with and without capital shortfalls and/or disapproval of capital distribution plans. Column ' > ' indicates what fraction of the CARs of all banks were positive.

Credit market reaction to stress tests (in bp)
Notes: *** -, ** -, * -signi cance level. is table presents CARs for the main stress test events over the -period calculated using CDS spreads for an (-,+ ) event window. Reported signi cance are based on corrected t-statistics. Column ' All' shows the e ects of events on the average CARs of all banks. Columns 'No-Gap' and 'Gap' separate the e ects into banks with and without capital shortfalls and/or disapproval of capital distribution plans. Column ' > ' indicates what fraction of the CARs of all banks were positive.

events, in
the betas were reduced following the publication of the results of the SCAP. Speci cally, we nd a strong decline in systematic risk (-. ) a er the publication of results. Similarly, the beta of banks declined a er the release of stress test results in (-. ). ese ndings suggest that market participants expected stress test results to be worse than they ex-post turned out to be and as a consequence betas declined in and . Table presents the estimation results for our standardized model (Equation ( )). We are interested in the coe cients of the interaction terms, denoted by ρ. Following Nijskens and Wagner ( ), we interpret a decline in the correlation component as a decline in systemic risk. Except from a weak e ect in , we see no evidence that the announcement events a ected systemic risk of banks. However, the methodology release in increased ρ and contributed to the increase in beta reported in Table . For results events there is a decrease in the correlation of the stock series with the market in and , suggesting that systemic risk declined.

Gap vs no-gap banks
To examine whether systematic and systemic risk of gap and no-gap banks were a ected di erently, we re-estimate Equations ( ) and ( ) for no-gap banks and gap banks. e resulting regressions are shown in, respectively, Table and Table . In what follows we focus our discussion on the beta e ects associated with the results events.
Considering the rst two columns, we see that the decrease in the beta in as reported in Table  was due to the e ects on no-gap banks. e results of SCAP seem to have caused a signi cant decrease in betas of no-gap banks while the betas of gap banks were not a ected. is nding complements the ndings of Morgan et al. ( ) who show that market participants' ex ante expectations of capital shortfalls were worse than they ex post turned out to be. Earlier we reported that the results of CCAR in did not a ect the betas. It turns out that the publication of the CCAR result did a ect the betas of gap banks (. ). In , there is a large change in the overall beta following the results of CCAR for both gap (-. ) and no-gap (-. ) banks. Overall there is strong evidence of a decline in systematic risk following stress test results in most years. Table also shows that the changes in betas of gap banks signi cantly di er from changes in betas of no-gap banks in . As revealed by the stress test results, most banks had su cient capital to maintain their operations under the adverse economic scenario employed, but some banks appeared to be undercapitalized. e signs of betas in associated with stress test results for gap and no-gap banks suggest that the betas move in opposite directions.
Considering systemic risk for gap banks, ).
We attribute the insigni cance of the corresponding beta for CCAR in Table to the relative variance component, which may have added su cient noise to make the overall change in beta insigni cant.

Conclusion
As stress tests are an important tool for banking supervisors, it is important to consider their e ects on stock and credit markets. We have quanti ed the market reactions of US stress tests performed a er the start of the nancial crisis by considering their e ects on stock returns, CDS spreads, systematic risk, and systemic risk. Considering stock markets, our ndings indicate that the publication of stress test results had little e ect on stock returns. e clari cation event in by then Fed chairman Bernanke and the results of CCAR in did a ect stock markets positively. Considering credit markets, our ndings show evidence of decline in CDS spreads following the release of the stress test results in , , and . We conclude that the release of information about stress tests did occasionally move markets. In other words, stress tests may have provided information to markets.
Our analysis of banks' betas suggests that the publication of stress test results has a ected banks' systematic risk in and . Studying the changes in betas we nd that stress tests reduced systemic risk in and . Overall, we conclude that stress tests have produced valuable information for market participants and can play a role in mitigating bank opacity. So, our ndings suggest that stress tests are a useful tool in mitigating systematic and systemic risk in stock and credit markets.
de Larosiere, J., . e high-level group on nancial supervision in the EU. European Commission report on supervision.