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Market Reaction to Securitization Retained Interest Impairments during the

Financial Crisis of 2007-2008: Are Implicit Guarantees Worth the Paper They’re

Not Written On?

Dan Amiram, 1 Wayne R. Landsman,1 Kenneth Peasnell,2 Catherine Shakespeare3

December 2010

1. Kenan-Flagler Business School, University of North Carolina at Chapel Hill, Chapel Hill,

NC 27599 2. The Management School, Lancaster University, Lancaster, LA1 4YX, UK 3. Steven M. Ross School of Business, University of Michigan, Ann Arbor, MI 48109

Earlier drafts of this study were circulated under the title “Market Reaction to Financial Assets Impairments during the Financial Crisis of 2007-2008.” We thank Bill Beaver, Phil Brown, Hans Christensen, Justin Hopkins, Mark Maffett, Steve Monahan, Panos Patoukas, Theodore Sougiannis, Dan Taylor, and workshop participants at the 2010 AAA Annual Conference, the 2010 EAA Annual Congress, the 2010 London Business School Accounting Research Conference, the 2010 Mid-South Research Consortium, the 2010 Norwegian Research School Conference, University of Bristol, Carnegie-Mellon University, Cornell University, University of Edinburgh, Lancaster University, Michigan State University, University of North Carolina, Ohio State University, and University of Utah for helpful comments. We also thank Beth Blankespoor, Elicia Cowins, Brad Hendricks, and Tianshu Qu for research assistance. We gratefully acknowledge funding from the KPMG research fund at the University of North Carolina and the Paton Accounting Center at the University of Michigan. Corresponding author: Wayne Landsman, Kenan-Flagler Business School, University of North Carolina, Chapel Hill, NC 27599-3490, 919-962-3221, [email protected].

Market Reaction to Securitization Retained Interest Impairments during the

Financial Crisis of 2007-2008: Are Implicit Guarantees Worth the Paper They’re

Not Written On?

Abstract

We use equity market reactions to the announcement of impairments of retained interests arising from asset securitizations made by financial institutions during the Financial Crisis of 2007-2008 as a means of obtaining insights into the nature of the implicit guarantees associated with this form of financing. We use the market reaction to announcements of loan losses and writedowns of asset-backed securities purchased as investments as a benchmark to compare the market reaction to the retained interest writedowns. Although retained interest impairments are relatively small in magnitude, they potentially indicate exposure to a much larger loss associated with off-balance sheet assets and liabilities. We find there is an increase in spreads, which is consistent with an increase in information asymmetry. The increase is greatest for announcements of retained interest writedowns, which is consistent with greater information asymmetry among investors regarding implicit guarantees associated with assets retained from securitizations. Further analysis reveals that the increases in bid-ask spreads are concentrated among banks with low managed assets, banks which are unregulated, and banks that are relatively well capitalized. We also find trading volume and implied volatility increase for retained interest writedowns to a greater extent than they do for impairments of other assets. Taken together, our findings suggest that a binary approach to accounting for securitizations may not capture fully the economic nature of the transaction. Keywords: securitizations; asset writedowns; retained interest; information asymmetry; financial crisis; financial institutions Data Availability: All analyses are based upon publicly available data

1. Introduction

A critical question in financial reporting is when to recognize a liability and the amount

to recognize. The approach of accounting standard setters generally has been to treat

recognition of liabilities as a binary decision—all or nothing. For example, leases are treated as

being either capital in nature, requiring full recognition of the liability and the associated asset,

or operating, requiring no recognition of the liability. Problems with this binary definition have

led standard setters to consider putting operating lease commitments on the balance sheet.

Derecognition and consolidation rules relating to asset securitizations have been similarly

binary in character. Until recently, US securitization accounting rules resulted in asset transfers

being treated either as off-balance financing or as a collateralized on-balance sheet borrowing,

although in practice banks generally avoided the latter treatment.

In this study, we use equity market reactions to the announcement of impairments of

retained interests arising from asset securitizations made by financial institutions during the

Financial Crisis of 2007-2008 as a means of obtaining insights into the nature of the implicit

guarantees associated with this form of financing. Findings from our analyses suggest that a

binary approach to securitizations may not capture fully the economic nature of the transaction.

In particular, whereas the commitments entered into by banks originating loans and sponsoring

subsequent securitizations would be likely to be fully honored in normal economic conditions,

the implicit nature of such guarantees leaves open the possibility that they might not be honored

under conditions of extreme stress associated with the Financial Crisis.

In the past two decades, asset securitizations were used extensively by financial

institutions as an indirect means of borrowing from capital providers beyond the traditional

sources (demand deposits and unsecured debt). Typical securitizations involved the transfer by

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a sponsor-originator bank (S-O) of financial assets, including mortgages and receivables, to a

special purpose entity (SPE) that issued debt securities to finance the acquisition of the

transferred assets.1 Securitizations provided benefits to financial institutions by enabling them

to diversify their asset holdings, by extending their capital base to wholesale money market

funds, and by enabling them to arbitrage regulatory capital rules, as banks keep debt off-balance

sheet that otherwise would be on-balance sheet, thereby reducing regulatory capital.

A common feature of securitizations is that the S-O retains an interest in the transferred

assets by holding the most junior asset-backed securities issued by the SPE, i.e., “retained

interests.” Retained interests help keep the cost of borrowing low for the SPE (and implicitly,

the S-O), by having the S-O absorb first loss. However, all else equal, the direct benefit of

lowering borrowing costs is likely to be small because financial institutions cannot retain a large

stake in SPE assets as this would reduce or eliminate the benefits of securitization. In addition,

accounting rules that applied during the Financial Crisis prohibited S-Os from offering explicit

contractual guarantees regarding the performance of transferred assets to SPE creditors if the

transactions were to be accounted for as a sale, resulting in derecognition of the transferred

assets. Thus, S-Os had to find a means to provide non-contractual guarantees to SPE investors to

obtain beneficially lower borrowing costs.

To be credible, the implicit guarantee must be costly to the S-O. For repeated players in

the securitization markets this primarily took the form of a reputational stake that depended on

honoring the implicit understanding to cover SPE losses. The extent of the implicit guarantee

has to be greater the more risky are the SPE assets, all else equal. Because retained interest

empirically exists typically only for SPEs with risky assets and because retained interest is

1 Our sample includes banks as well as other financial institutions. We use the terms interchangeably throughout, although we conduct some analyses that distinguish between regulated and non-regulated financial entities.

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observable to parties outside the S-O and SPE creditors, we hypothesize that the existence of

retained interest is a useful proxy for the existence of implicit guarantee provided by the S-O.

Note that if retained interest fully covered most potential losses of SPE investors, then it would

be unnecessary for the S-O to offer any implicit guarantees. However, because retained interest

is costly to the S-O, it cannot be large enough to cover all expected losses and thus must be

accompanied by an implicit guarantee. The question arises as to the conditions under which the

S-O will honor such implicit guarantees.

During periods of rising asset prices, losses in SPE assets are likely to be infrequent and

uncorrelated across securitizations. Under these conditions, any losses associated with SPE

assets from a particular securitization are likely to be sufficiently small either to be covered by

the S-O’s retained interest or, if not, to be fully covered by the implicit guarantee. In contrast,

when asset prices fall systematically across the economy, as was the case during the Financial

Crisis, it is unlikely that retained interests will be sufficient to cover the losses in value in assets

securitized by the S-O, and the question therefore arises whether the S-O has the means to honor

all of its implicit guarantees. In such a situation, the S-O’s decision to honor its implicit

guarantees depends on whether the cost associated with the loss of its reputation with its

creditors from failing to make good on its promises is less than the cash flow cost of assuming

the SPE losses. Prior research provides evidence that the stock market values bank equities as if

managed SPE debt is economically S-O debt, i.e., as if there are implicit guarantees it would

honor. However, given the relatively benign economic conditions that characterize the sample

periods in prior research, any loss of reputation of not honoring its implicit guarantees likely

would have exceeded the cash cost of paying off the SPE creditors.

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If it were possible to observe implicit guarantees, it is highly likely that one would also

observe retained interest. However, the converse need not necessarily follow because there may

well be instances for which retained interest is sufficient ex ante to immunize SPE debtholders

from loss. Nevertheless, we use retained interest as a useful proxy for the existence of an

implicit guarantee provided by the S-O. Observing a retained interest writedown indicates that at

a minimum the S-O has absorbed first loss and creates uncertainty as to whether it will honor any

implicit guarantees it has provided.

By their very nature implicit guarantees are difficult to observe. We use writedowns of

retained interests by S-O banks during the Financial Crisis as a means to infer whether market

participants took actions reflecting their belief that the S-O banks would honor some implicit

guarantees. We investigate this by examining the market reaction to the retained interest

writedown announcements in 8-K disclosures made by the largest 100 financial institutions in

the U.S. during the period October 1, 2007 to December 31, 2008. We use the market reaction to

the 8-K announcements of loan losses, and writedowns of asset-backed securities (ABS)

purchased as investments as a benchmark to compare the market reaction to the retained interest

writedowns.

A critical feature of our analysis is that although retained interest impairments are

relatively small in magnitude, compared to these other writedowns, such writedowns are

consistent with the possibility of exposure to a much larger loss associated with off-balance sheet

assets and liabilities. Consequently, we expect the market makers in S-O stocks will widen the

bid-ask spread when news of the impairments is released to price protect themselves against

insiders with private information who otherwise may take advantage of the situation to hide their

transactions (Copeland and Galai, 1983; Krinsky and Lee, 1996). Furthermore, we predict that

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the effect on the bid-ask spread will be largest for the retained interest writedowns as market

makers will be concerned that the insiders (including bank managers) are trading to take

advantage of the private information they have about actions the S-O will take regarding whether

and the extent to which the institution will absorb the losses of its SPEs beyond those associated

with its proportional stake in the SPE. In contrast, the market maker has less cause to worry that

insiders have private information about the cash flow consequences of the other two impairment

types. Consistent with predictions, we find that all three types of impairments lead to an increase

in the bid-ask spread, with the increase being greatest for retained interest impairments.

If disclosure of the impairments of any of the three types of assets is newsworthy to

investors, i.e., information is released via the 8-K, we expect there to be an increase in trading

volume. Based on prior literature, we predict that all three types of impairments have

information content, and hence abnormal trading volume will increase. We expect the increase

in trading volume to be particularly pronounced for retained interest because we expect investor

disagreement regarding the potential losses to which the S-O shareholders are exposed to be

greater for retained writedowns than for the other impairments. Consistent with these

predictions, we find a positive and significant relation between each of the impairment types and

abnormal trading volume with retained interest having the largest coefficient across the

impairment types.

Next, we consider stock price volatility implied in call option prices. Prior research

indicates that if a firm announcement can be anticipated, e.g., as is the case in most earnings

announcements, implied equity volatility decreases following the announcement, as investor

uncertainty is resolved. Because the 8-K disclosures in our sample typically involve earnings

announcements, implied volatility should increase before each impairment announcement then

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fall on the day of the announcement, if uncertainty is resolved. However, because retained

interest impairments can create rather than resolve investor uncertainty about what actions

management will take regarding honoring implicit guarantees granted to SPE creditors, we

predict implied volatility to increase when retained interest writedowns are announced. Findings

support this prediction. In contrast, loan impairment announcements lead to a drop in implied

volatility and therefore suggest such announcements result in a resolution of investor uncertainty.

Finally, for completeness, we examine whether each asset impairment announcement

affected bank stock returns. Predicting effects of the announcements on stock return is difficult

because it involves measuring changes in investors’ expectations regarding future cash flow and

cost of capital. Predicting the sign of stock return for retained interest writedowns is problematic

because of the difficulty in determining the extent to which there is heterogeneity in investor

expectations regarding whether S-Os will honor their implicit guarantees, and whether failing to

honor implicit guarantees is good or bad news. In contrast, in the case of loan and CDO

writedowns, investors are likely to have more homogenous expectations regarding the

information content of the announcements because the S-O’s potential losses are limited to the

carrying amount of loans and CDOs. Results indicate no significant effect on stock return from

any of the impairment announcements, including retained interests. These findings are

consistent either with no changes in investor expectations regarding future cash flows or risk, or

heterogeneity in the sample being obscured by treating all banks similarly in our tests.

Taken together, the above findings based on the full sample suggest there is

heterogeneity in investor beliefs regarding whether banks will honor their implicit guarantees.

An implication of this is that economically there is no clear answer whether the proper

accounting treatment is to treat SPE debt as S-O debt or as being distinct from the S-O.

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However, there may be heterogeneity in the sample regarding the ability and intent to honor

implicit guarantees. To explore this possibility, we partition the sample based on the extent to

which SPE managed assets—i.e., securitized assets from which the S-O derives servicing

rights—comprise a relatively large share of the S-O’s recognized assets, whether the S-O is a

regulated or unregulated institution, and the extent to which the S-O is well capitalized. S-Os

that have substantial managed assets have the most to lose from failing to honor their implicit

guarantees, and therefore investors are likely to be in agreement that they will honor their

guarantees. To the extent that an S-O is subject to regulatory constraints or is not sufficiently

capitalized, investors are likely to agree that honoring the guarantees is prohibitively costly for

the S-O. Consistent with these predictions, we find that increases in bid-ask spreads are

concentrated among banks with low managed assets, banks which are unregulated, and banks

that are relatively well capitalized.

Our study makes two contributions to the literature. First, our research raises questions

whether a binary approach to securitizations captures fully the economic nature of the

transaction. Second, our findings complement those from prior research that the market views

SPE assets and liabilities as assets and liabilities of the S-O. By focusing on the Financial Crisis,

our analysis is done in a setting that reveals new information regarding the underlying economics

of the securitization transaction.

The remainder of the paper proceeds as follows. Section 2 provides background of the

role of securitizations in the Financial Crisis and motivation for our predictions. Section 3

discusses our predictions and section 4 presents our empirical tests. Section 5 describes our data

and sample. Section 6 presents the findings, and section 7 presents a summary and concluding

remarks.

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2. Background and Motivation

At the heart of the credit crisis of 2007-2008 is asset securitization, a Wall Street

innovation that has become a large source of corporate financing over the last two decades. By

the end of 2007, the outstanding securitization market was valued at $9.3 trillion, making it over

twice the size of U.S. treasuries, which were valued at $4.5 trillion (Securities Industry and

Financial Markets Association 2008). Asset securitizations enable a firm to obtain cash for

assets transferred to another entity.2 In a typical securitization, the S-O sets up an SPE, which

borrows funds from third parties to purchase the securitized assets from the S-O, using the assets

as collateral. A common feature of securitizations is that the S-O retains an interest in the most

junior asset-backed securities issued by the SPE. Such securities are commonly referred to as

“retained interests.” Another common feature is for the S-O to continue to service the portfolio

of loans transferred to the SPE—charging the SPE for this service—because the SPE is typically

no more than a passive trust.

Securitizations became a major source of bank financing for three reasons. First,

securitization is a significant mechanism for banks to access the wholesale money markets,

thereby expanding their capital sources beyond the traditional depositor base and unsecured

long-term borrowing. Second, securitization enabled banks to diversify their asset-holdings

beyond commercial and real estate loans in their local markets by selling to other investors and

institutions loans they originated, replacing them with securities backed by loans originated by

other institutions in other regions. Third, securitization provides a means to arbitrage regulatory

2 A wide range of assets has been securitized, from mortgages and consumer loans to royalty payments and receipts of sporting events.

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capital rules, as banks keep debt off-balance sheet that otherwise would be on-balance sheet,

thereby reducing regulatory capital.3

These benefits for S-O banks are more likely to be obtained if the investors to whom the

asset-backed securities are sold can be convinced that the underlying assets are shielded from the

general financial risk (i.e., other creditors) of the S-O. A key method to achieve this goal is to

place the underlying assets in an SPE structured in such a way as to signal to SPE investors that

the value of their claims are independent of the bankruptcy risk of the sponsor (Landsman,

Peasnell, and Shakespeare, 2008). Thus, securitization is a vehicle that helps to guarantee SPE

investors priority of claims over the securitized assets.4

However, what the SPE investors lose by this investment vehicle is claim to the assets of

the S-O. As a result, other things equal, the cost associated with the failure of the SPE assets to

perform is borne entirely by the SPE investors. This risk of loss is ex ante higher the lower is the

quality of the assets that have been transferred to the SPE.5 The risk is ex ante lower the higher

is the proportion of capital provided to the SPE in the form of equity. That is, non-performance

will affect equity holders before debt holders. Banks can, therefore, reduce implicit borrowing

costs by retaining an equity-like stake in the SPE. Such a stake is typically referred to as

3 Bleck and Gao (2010) provide several reasons for why retaining loans on the balance sheet is costly to regulated and unregulated financial institutions. Among the costs are capital requirements, deposit insurance premia, lack of portfolio diversification, the advantage financial institutions have to originate loans relative to their ability to manage them, and financial constraints. 4 Another player that can affect the effectiveness of protecting the SPE creditors’ claims to the assets of the SPE is the Federal Deposit Insurance Corporation (FDIC). In December 2009, the FDIC proposed new safe harbor rules that would affect whether S-O’s creditors can gain access to the SPE assets in the event of the S-O’s bankruptcy. See “FDIC Seeks to Toughen Rules on Banks’ Securitizations,” Jody Shenn and Theo Francis, Bloomberg, December 15, 2009. 5 Pricing the SPE debt securities can be particularly problematic if it is difficult to assess the riskiness of the underlying assets. Although, in principle, SPE investors could assess the risk of assets securing their claims through the voluminous prospectus data typically provided by S-Os, in practice they relied upon the ratings provided by the credit rating agencies. Investors’ reliance on credit rating agencies was predicated on the assumption that the agencies could sift through the data and make an accurate determination. Evidence suggests that this was not the case. See, e.g., “Flawed Credit Ratings Reap Profits as Regulators Fail Investors,” D. Evans and C. Salas, Bloomberg, April 29, 2009.

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‘retained interest,’ which as described above is the tranche of debt securities issued by the SPE

with lowest priority.6

Although retained interest helps keep borrowing costs lower by having the S-O absorb

first loss, this is the primary direct contractual benefit to the SPE investors. Other things equal,

the greater is the amount of retained interest, the lower is the interest rate required by SPE

creditors (Leland and Pyle, 1977). Indeed, if S-Os were willing to retain a substantial interest in

the SPE, then a point would likely be reached whereby the SPE creditors would be effectively

protected from all prospect of loss. However, retaining substantial interests in SPEs would

negate many of the benefits associated with the securitization transaction, in particular the

accessing of external capital, as well as the reduction in regulatory capital requirements because

each additional dollar of retained interest must be backed by additional capital.7’8

Thus, the typical amount of retained interest observed in practice is of limited

effectiveness in protecting the SPE creditors against loss. Ideally, they would like to have some

other explicit contractual guarantee from the S-O or a third party (e.g., one of the monoline

insurers). However, Statement of Financial Accounting Standards No. 140 (SFAS 140), which

was in effect before and during the Financial Crisis, requires that there be no explicit guarantees

by the S-O or recourse from the SPE to the S-O if the S-O is to be able to account for the

securitization as a sale. Otherwise, the S-O would have to include the SPE’s assets and liabilities

6 Retained interest also helps to mitigate some information problems that are inherent in securitization transactions. Without some “skin in the game” banks will potentially have incentives to generate and sell low quality loans. In addition, retaining the low quality tranche of the sold assets may signal to the SPE investors that the sold tranches are of high quality. 7 The regulatory cost is even higher after taking into account that the risk-weighting attached to a dollar of retained interest is greater than that for a dollar of the assets typically transferred. In November 29, 2001 several federal agencies including the Office of the Comptroller of the Currency and the Federal Deposit Insurance Corporation, issued a rule that requires banks, in most cases, to maintain capital that is equal to the face amount of the retained interest. 8 See Bleck and Gao (2010) and footnote 3 for several additional costs associated with retaining loans on the balance sheet.

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on its balance sheet, which would negate many of the benefits from securitization. In particular,

including the SPE’s assets and liabilities on the S-O’s balance sheet likely would result in the

loss of priority protection in bankruptcy for the SPE creditors (Landsman, Peasnell, and

Shakespeare, 2008), and the elimination of regulatory capital arbitrage. The cost of third party

guarantees sufficient to cover all of the potential losses of the SPE creditors was likely too high

to offset the benefits provided by securitization.

Thus, S-Os have to find an indirect but convincing method of providing a non-contractual

guarantee that effectively gives the SPE creditors access to the S-O’s assets in the event of non-

performance of SPE assets. One mechanism is for the S-O not to retain an interest but to offer an

implicit guarantee. To be credible, such an implicit guarantee must be costly to the S-O. For

repeated players in the securitization markets this will primarily take the form of a reputational

stake that would be destroyed if they failed to honor the understanding they would cover SPE

creditor losses. An example of this form of an implicit guarantee is revolving loan

securitizations that typically involve little or no retained interest (Gorton and Souleles, 2006;

Chen, Liu, and Ryan, 2008). A more typical arrangement is for the S-O to retain interest in the

SPE assets at a level that is not sufficient to provide a buffer for all expected SPE losses and

therefore has to be accompanied by the unobservable implicit, reputation-based guarantees. The

extent of the implicit guarantee has to be greater the more risky are the SPE assets. In benign

states of the world when asset prices are generally stable or rising, losses in SPE assets are likely

to be infrequent and uncorrelated across securitizations. Under these conditions, any losses

associated with SPE assets from a particular securitization are likely to be sufficiently small

either to be covered by the S-O’s retained interest or, if not, to be fully covered by the implicit

guarantee. In contrast, when asset prices fall systematically across the economy, as was the case

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during the Financial Crisis, the question arises whether the S-O has the means or willingness to

honor all of its implicit guarantees. The S-O’s decision to honor its implicit guarantees then

depends on whether the cost associated with the loss of its reputation with its creditors from

failing to make good on its promises is less than the cash flow cost of assuming the SPE losses.

Prior research provides evidence that the stock market values bank equities as if managed SPE

debt is economically S-O debt (Nui and Richardson, 2006; Landsman, Peasnell, and

Shakespeare, 2008), i.e., as if there are implicit guarantees it would honor. Because the sample

periods in prior research precede the Financial Crisis, it is likely any loss of reputation of not

honoring the S-Os’ implicit guarantees would have exceeded the cash cost of paying off the SPE

creditors. Therefore, one cannot safely extrapolate from findings in prior research that investors

in the S-O’s would view SPE debt as if it were economically debt of the S-O during the Financial

Crisis.

If this conjecture is correct, the way in which equity prices of banks reflect implicit

guarantees should differ substantially before and during the Financial Crisis. The appendix

provides evidence of this by estimating versions of the valuation models in Landsman, Peasnell,

and Shakespeare (2008) at a date for a sample of banks before and during the crisis period.

Findings for 2006 in each specification are consistent with those reported in tables 3 and 4 of

Landsman, Peasnell, and Shakespeare (2008) in that they indicate the market values SPE assets

and liabilities similarly to recognized assets and liabilities. In other words, in the period

preceding the Financial Crisis bank equities were priced as if banks would honor their implicit

guarantees to SPE creditors. Findings for 2008 contrast starkly with those for 2006. Most

importantly regarding our conjecture, the evidence indicates that in neither of the specifications

that include SPE assets and liabilities does the market value bank equities as if banks would

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honor their implicit guarantees to SPE creditors. Moreover, the 2008 findings suggest that the

valuation approach of Landsman, Peasnell, and Shakespeare (2008) may not be adequate in

explaining cross-sectional variation in bank equity prices during the turbulent times of the

Financial Crisis.

When risky assets are transferred—particularly those whose risk characteristics are

difficult to assess—it is almost inevitable that the transfer will be accompanied by retained

interest. Indeed, Chen, Liu, and Ryan (2008) confirms this by providing evidence that retained

interest empirically exists typically only for SPEs with such risky assets. As we describe above,

retained interest may be insufficient to compensate SPE debtholders for the risk they face from

the transferred assets; in which case the S-O will have to provide an implicit guarantee to cover

potential losses. If it were possible to observe implicit guarantees, it is highly likely that one

would also observe retained interest. However, the converse need not necessarily follow because

there may well be instances for which retained interest is sufficient ex ante to immunize SPE

debtholders from loss. Nevertheless, the existence of a retained interest can be viewed as a

useful proxy for the existence of an implicit guarantee provided by the S-O. Observing a

retained interest writedown indicates that at a minimum the S-O has absorbed first loss and the

question then arises whether it will honor its implicit guarantees. Under normal conditions, it is

in the interest of the S-O to honor its guarantees, but during the Financial Crisis, the S-O’s

decision is more difficult to predict. Because retained interest is observable to parties outside the

S-O and SPE creditors, the writedown event is therefore an opportunity to assess whether there is

uncertainty in the minds of investors regarding actions management will take.

A striking example of honoring an implicit guarantee is the action taken by Citigroup,

which, in December 2007, brought back on balance sheet $49 billion of SPE assets that it had

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previously securitized. The related liabilities would have been much higher, as the same assets

were valued at $87 billion in August of the same year. The net loss incurred by Citigroup must

have been far in excess of the value of the associated retained interests, as their total retained

interests in all securitizations was only $25.8 billion as of December 31, 2006. As we now know

that December 2007 was the beginning of the Financial Crisis, the question arises as to whether

Citigroup would have followed this course of action even a few months later. That is, what

appeared to Citigroup’s management to be an optimal tradeoff between the cost of honoring its

implicit guarantees and the benefit to maintaining Citigroup’s reputation in the securitization

market may have been viewed differently when it became apparent that the market for new

securitizations ceased to exist.

Announcements of losses in value of bank assets other than retained interest, i.e., on-

balance sheet loans and asset-backed securities held for trading purposes, are unlikely to pose

major interpretive problems for investors or the market maker because losses are limited to the

value of these assets. In contrast, announcements of retained interest writedowns are likely to be

more difficult for investors or the market maker to interpret to the extent that they are associated

with off-balance sheet exposure to losses in value of SPE assets. Whereas investors and market

makers generally cannot determine whether and to what extent the implicit guarantees associated

with SPE assets would be fully honored by the S-O banks, bank managers and informed traders

are in a position to know what actions the bank will take. In other words, there is an information

asymmetry between informed traders and investors or the market maker regarding the exact

weight to attach to a retained interest writedown. 9 Information asymmetry is unlikely to be as

9 Adding to the information asymmetry is that investors could not easily assess the value of SPE assets because there were no required disclosures beyond those provided in the initial offer documentation. The problem was exacerbated in that SPE assets often comprised re-securitizations, whereby an SPE’s asset backed securities (ABS) were often bundled with other ABSs (including those issued by other S-Os) and sold to yet another special purpose

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pronounced for writedowns of on-balance sheet loans and asset-backed securities held for trading

purposes as it is for retained interest writedowns. In the case of a writedown of a loan or an

asset-backed security, there could well be information asymmetry regarding whether future

writedowns will occur, the amount is restricted—unlike retained interest writedowns—to what is

recognized as an asset on the S-O’s balance sheet.

3. Predictions

To investigate whether retained interest writedowns during the Financial Crisis affected

investors’ perceptions of the probability that banks would honor implicit guarantees to SPE

creditors, we examine various metrics of bank equity reaction. We do this by gathering a sample

of retained interest writedowns and comparing market reactions associated with such writedowns

to those associated with bank loan loss provisions and writedowns of asset backed securities

banks held for trading purposes. These comparisons permit us to exploit differences in expected

market reactions reflecting differences in the information impairment of each type of asset

conveys. For our sample of large financial institutions, we examine their 8-K filings during the

Financial Crisis for disclosures related to writedowns of retained interests, writedowns of CDOs,

i.e., purchased securities issued by SPEs, and disclosures of “large” loan losses, defined as an

increase in the loan loss provision that is higher than the amount announced in the previous

quarter.

We begin our analysis by examining whether each asset impairment announcement

affected bank stock bid-ask spreads. We expect the market makers in S-O stocks will widen the

bid-ask spread when news of the impairments is released to price protect themselves against

insiders with private information who otherwise may take advantage of the situation to hide their

entity that finances the purchase of the bundle of securities by issuing new ABSs usually referred to as collateralized debt obligations or CDOs. Indeed, the process was often repeated again, by selling different CDOs in a further round of securitizations to create so-called “CDO2” securities. See Markowitz (2009) for further discussion.

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transactions (Copeland and Galai, 1983; Krinsky and Lee, 1996). Furthermore, we predict that

the effect on the bid-ask spread will be largest for the retained interest writedowns as market

makers will be concerned that the insiders (including bank managers) are trading to take

advantage of the information they have about actions the S-O will take regarding whether and

the extent to which the institution will absorb the losses of its SPEs beyond those associated with

its proportional stake in the SPE. In contrast, the market maker has less cause to worry that

insiders have private information about the cash flow consequences of the other two impairment

types. Thus, although we predict bid-ask spreads increases for all three impairments, we predict

the effect on spreads will be larger for retained interest impairments than for CDO and loan

impairments.

We next examine changes in trading volume around the announcement of each type of

asset impairment. If disclosure of any of the impairments, i.e., the retained interest writedowns,

CDO writedowns, or loan loss provisions, is newsworthy to investors, i.e., information is

released via the 8-K, we expect there to be an increase in trading volume. Prior literature on

earnings announcements indicates generally a significant increase in abnormal trading volume

during the announcement period (Beaver, 1968; Bamber, Barron and Stober, 1997; Landsman

and Maydew, 2002). Some theoretical models predict an increase in trading volume is likely to

occur if an announcement increases investor disagreement (Kim and Verrecchia, 1991). More

generally, Beaver (1968) predicts an increase in trading volume if an announcement has

information content. We therefore predict that all three types of impairments have information

content, and hence abnormal trading volume will increase. Although retained interest

impairments are relatively small in magnitude compared to other writedowns, our hypothesis

suggests that they reveal information of exposure to a much larger loss associated with off-

17

balance sheet assets and liabilities. We therefore predict trading volume increases are largest for

retained interest writedowns. However, to the extent that investors use other sources of

information (e.g., the information in other banks’ announcements or ABX indices) to anticipate

retained interest writedowns and other impairments or the information in such announcements is

ambiguous, it is possible to observe little or no change in trading volume.

The third announcement measure we consider is stock price volatility implied in call

option prices. Prior research indicates that if a firm announcement can be anticipated, e.g., as is

the case in most earnings announcements, implied equity volatility decreases following the

announcement, as investor uncertainty is resolved (Patell and Wolfson, 1979 and 1981). If the

announcement is not anticipated, e.g., there is an exogenous shock, investor uncertainty is likely

to increase with such an announcement. 8-K disclosures are typically anticipated as most

involve earnings announcements and firms typically schedule press conferences a few days in

advance of 8-K filings. Therefore, for a typical 8-K filing in which earnings are announced, we

predict implied volatility will fall on the day of the announcement, as uncertainty is resolved.

However, we expect retained interest impairments to create rather than resolve uncertainty as

investors become uncertain about what actions management will take regarding honoring

implicit guarantees granted to SPE creditors. Therefore, we predict implied volatility to increase

when retained interest writedowns are announced. In contrast, it is difficult to predict whether

implied volatility is expected to change with announcements of loan losses or writedowns of

CDOs. For example, in the case of CDO writedowns, investors may not have been surprised by

the news because news about the drop in CDO prices generally was available to investors. Loan

loss writedowns might even be expected to reduce investor uncertainty.

18

For completeness, we also examine whether each asset impairment announcement

affected bank stock returns. Predicting the sign of stock return for retained interest writedowns

is problematic because of the difficulty in determining the extent to which there is heterogeneity

in investor expectations regarding whether S-Os will honor their implicit guarantees, and

whether failing to honor implicit guarantees is good or bad news. There are at least three

scenarios to consider. The first two lead to corner solutions (loss limited to retain interest and

loss extending to a substantial proportion of SPE debt, respectively):

1. Investors have homogeneous beliefs about implicit guarantees and, furthermore, do not

expect them to be honored.

2. Investors have homogeneous beliefs about implicit guarantees and expect them to be

honored.

3. Investors have heterogeneous beliefs about implicit guarantees.

The stock return effect for scenario one is likely to be small or near zero. This is because

investors view the SPE debt as not being economically an obligation of the S-O. However, if

previously investors had believed S-Os would honor the debt (Landsman, Peasnell, and

Shakespeare, 2008), it is conceivable that return could be positive because they now believe the

S-O’s because the S-O’s future cash flow will be higher than anticipated. For this outcome to be

possible it would be necessary that the “good news” associated with the S-O not honoring its

implicit guarantees would outweigh the “bad news” of loss in value of the SPE’s assets. The

stock return effect for scenario two is expected to be negative and possibly large, to the extent

that the decline in value of the SPE’s assets has not been fully anticipated, and expectations

regarding the S-O its implicit guarantees are unchanged. In this case, the stock return effect will

reflect both the loss in value of the retained interest and the possibly substantial off-balance sheet

19

obligations of the S-O. Lastly, scenario three lies somewhere between scenarios one and two

because of heterogeneity in investor beliefs regarding whether the S-O will honor its implicit

guarantees and the value of the SPE assets. In this case the stock return effect will reflect the

expected loss in value of the retained interest, the uncertain substantial off-balance obligations of

the S-O, and any increase in cost of capital arising from an increase in bid-ask spreads associated

with investor heterogeneity of beliefs. It is therefore difficult to form a clear prediction for the

sign or magnitude of return for scenario three.10

In contrast to retained interest writedowns, investors are likely to have more homogenous

expectations regarding the information content of the announcements of loan and CDO

writedowns because the S-O’s potential losses are limited to the carrying amount of loans and

CDOs. Nonetheless, predicting effects of all impairment announcements on stock return is

difficult because it involves measuring changes in investors’ expectations regarding future cash

flow and cost of capital. In the case of loan and CDO writedowns, we predict that their

announcements are more likely to change investor expectations regarding the magnitude of

future cash flow rather than the riskiness of such cash flows. For example, in the case of loans,

the announcement of an increase in the loan loss provision from the prior quarter indicates that

future cash flows will be lower than expected.11 Thus, we predict stock returns to be negative for

loan and CDO writedowns.

10 Return predictions for retained interest as well as the other two asset impairments are also complicated by the possible confounding effects of strategic impairment disclosure. That is, it is entirely possible that banks may time writedown events and magnitudes to influence investor expectations. However, because of the difficulty in modeling strategic disclosure, we do not consider strategic disclosure when making our predictions. 11 It is possible for the loan loss announcement to convey “good news” to the market in that it signals that management is finally taking steps to minimize future loan losses. In this case, the stock price reaction is difficult to predict because the negative cash flow news is offset by the positive news of management’s ability to address future losses.

20

4. Empirical Design

Our basic estimating equation is similar for studying the announcement effects on bank

stock returns, bank stock price bid-ask spreads, stock price volatility implied in option prices of

bank equities, and bank equity trading volume. In particular, we begin by estimating the

following cross-sectional regression:

.12 (1)

DEP_VAR is either daily stock return,13 RETURN, daily bid-ask spread, SPREAD, daily implied

volatility, IMPVOL, or daily abnormal trading volume, AVOLUME. LOAN_LOSS,

RET_INTEREST, and ABS_CDO are indicator variables that take on a value of one if a bank, i,

announces a “large” loan loss provision, retained interest writedown, or asset backed

security/CDO writedown on day t, and zero otherwise. We estimate equation (1) using daily

data for all sample banks during the sample period comprising the Fiscal Crisis (see data section

below for details).

We do not consider the magnitude of the loan loss provision, retained interest and CDO

writedowns because of the inherent difficulty associated with determining investor expectations

for each variable. For example, investors might fully anticipate a large loan loss provision for

one bank, but completely fail to anticipate a small writedown by another bank. Whereas in the

case of the former bank, the market reaction would be expected to be small, in the case of the

latter bank the reaction could be large. Moreover, in the case of the retained interest writedowns,

as noted above, we do not expect there to be any clear relation between the magnitude of retained

interests and the value of implicit guarantees. Indeed, because retained interests are costly they

comprise only a small fraction of bank assets. In principle, using indicator variables results in a 12 For the sake of parsimony, we use the same notation for coefficients and regression errors for each of the four equations implied by equation (1). In all likelihood they differ. 13 Untabulated findings based on excess stock returns yield inferences identical to those reported in section 6 below.

21

loss of information. However, this is unlikely to be the case for retained interests, as the shape of

the function relating retained interests to the value of implicit guarantees is unobservable.

Taking into account these considerations, we therefore make the weaker prediction that the

market reaction is related to the incidence but not the size of each writedown or provisioning

event.14

Based on predictions in section 3, we predict the following for the regression coefficients:

• SPREAD:

• AVOLUME:

• RETURN:

• IMPVOL:

Prior literature (Krinsky and Lee, 1996; Leuz and Verrecchia, 2000) indicates that bid-

ask spreads depend on the firm’s information environment, bank size, trading volume, and the

volatility of the bank’s returns. Failure to control for these factors could result in correlated

omitted variable bias. As a result, when SPREAD is the dependent variable, we estimate a

second model, given as equation (2), which includes proxy variables designed to serve as

controls for the firm’s information environment and other factors known to affect bid-ask

spreads:

. (2)

For each sample observation, LATQ is total assets measured as of the beginning of the calendar

quarter, LMVOLUMEQ is the natural log of mean daily trading volume during the calendar 14 Another concern with including the magnitude of each impairment in the estimating equations arises from the fact that observations are measured daily, wherein no such writedowns occur for a great majority of days. As a result, each impairment variable would be ill-behaved for purposes of drawing statistical inferences on the regression coefficients. In addition, because not all 8-Ks include information regarding impairment magnitudes, the sample size of event days would be reduced.

22

quarter, and STDRET is the standard deviation of daily stock return during the calendar quarter.

Based on prior literature, larger banks with higher volume are predicted to have lower bid-ask

spreads , while banks with higher return volatility are expected to have higher bid-ask

spreads . Theoretical guidance for the potential impact of the firm’s information

environment on the other three dependent variables, RETURN, IMPVOL, and AVOLUME, is

sparse. However, because the information environment as reflected in LATQ, LMVOLUMEQ,

and STDRET might also create correlated omitted variable bias in the RETURN, IMPVOL, and

AVOLUME equations, we also estimate equation (2) for these three dependent variables.

Finally, because announcements of impairments and loan losses often coincide with

earnings announcements, we extend equation (2) by including an indicator variable, EADUM,

that takes on a value of one if firm earnings are announced on day t, and zero otherwise:

. (3)

Based on prior research, we predict for each dependent variable.15

We use a five percent significance level under a two-sided alternative to evaluate whether

particular coefficients differ from zero. We use a one-sided alternative when evaluating whether

a coefficient for a particular impairment type is greater than another. Standard errors are

computed with firm-level clustering, except when comparing coefficient magnitudes because

Lahiri and Li (2009) suggest that F-statistics based on samples with small number of clusters can

be problematic.16

15 Untabulated findings from estimations that include variables measuring the magnitude of the earnings surprise are included in place of EADUM result in unchanged inferences. 16 Inferences based on clustered standard errors are unchanged for the retained interest and CDO writedown coefficient comparisons, although the difference between the retained interest and loan loss coefficients is insignificant.

23

5. Sample and Data

For the purpose of our analysis, we identify the largest 100 financial institutions in the

U.S. that are available on Compustat. We retrieve from Compustat the largest 100 firms based

on total assets as of December 31, 2006 with SIC codes between 6000-6300 (financial

institutions). The identified sample accounts for more than 90% of the total U.S. financial

institutions’ market and book values as of December 31, 2006. We use 8-K forms filed with the

SEC from October 1, 2007 to December 31, 2008 to identify the firms in our sample that

announced material impairment to their financial assets. For each sample firm, we hand collect

impairment information disclosed in the 8-K form. This procedure yields information for 71

financial institutions and 228 event days.

LOAN_LOSS equals 1 if the provision expense or net charge-off (a) is mentioned in the

8-K and (b) the firm’s loan loss allowance scaled by gross loans has increased compared to the

previous quarter. RET_INTEREST is an indicator variable that equals one if a write-down of

retained interest was mentioned in the 8-K. ABS_CDO is an indicator variable that equals one if

a CDO write-off was mentioned in the 8-K.17 Each indicator variable equals zero on all days but

the announcement day.

We obtain daily data from CRSP for the period from October 1, 2007 to December 31,

2008 for returns (RETURN), price (PRICE) volume (VOLUME) and the parameters needed to

calculate the bid-ask spread (SPREAD). The bid-ask spread is calculated by subtracting the low

bid price from the high ask price and dividing the result by the daily price. The abnormal volume

(AVOLUME) for each firm is calculated similarly to Landsman and Maydew (2002);

specifically, we subtract firm’s daily volume from its mean volume and divide the result by the

17 We include within the CDO_ABS impairment announcements writedowns of non-asset-backed security investments, e.g., corporate debt held as an investment by a bank.

24

standard deviation of the firm’s volume during our sample period. To mitigate the effects of

outliers, we winsorize each of the dependent variables at the 1% level. Return volatility

(STDRET) is the standard deviation of stock returns over our sample period. Quarterly volume

(MVOLUMEQ) is the mean of daily volume in the calendar quarter in which the impairment

event was announced. Deleting all firm-day observations with missing values creates a daily

dataset with 21,082 firm-day observations.

We retrieve quarterly accounting information for sample firms from the Compustat

Fundamentals quarterly database. For each sample firm, we obtain the dates on which they

announced their quarterly earnings and their total assets at the end of every quarter (ATQ). We

also create an indicator variable (EADUM) for the day earnings were announced. The quarterly

accounting information is merged with every daily observation in the three months that preceded

the end of the quarter date.

We obtain the implied volatility data (IMPVOL) for our analysis from the OptionMetrics

standardized options database. The implied volatility metric is based on the at-the-money call

option with an expiration of 91 days. We match the implied volatility information with the daily

dataset based on the security tickers. The data in OptionMetrics are available through September

30, 2008. Not all the financial institutions in our analysis have implied volatility data on the

OptionMetrics database during our sample period; thus the sample we use to analyze implied

volatility contains only 14,201 firm-day observations.

Table 1 presents descriptive statistics for the variables. All the institutions in the sample

experienced an impairment of at least one of the three classes of assets we consider during the

period in question. Because there are many more non-event days than event days, the medians

for all the event variables, , , , and are zero.

25

is a composite indicator variable constructed from the three event variables such that it

takes the value of one if one or more of , , is equal to

one, and zero otherwise. We include to provide a descriptive measure of the incidence

of writedowns. Panel B shows that on the event days, i.e., when equals one, whereas a

loan loss occurred 79% of the time, a writedown of retained interests occurred on only 7% of

occasions. Untabulated statistics also reveal that retained interest writedowns tend to be

substantially smaller in magnitude than either CDO writedowns or loan loss provisions. For

example, on days for which both retained interest writedowns and loan loss provisions were

announced, the mean amounts for each are $1.57 billion and $0.29 billion. As a fraction of total

assets, these amounts are 0.86% and 0.21%.

[Insert table 1 here]

Table 2 provides details of the bivariate correlations between the variables. The

correlations between the explanatory variables used in the regressions are generally well below

the level likely to cause multicollinearity problems, with the notable exception of

and , an association to be expected, given that loan writedowns are commonplace in the

sample.


To gain a better understanding of the extent to which our sample firms are active players

in the securitization market, we reviewed the 2007 annual reports of the firms in our sample and

identified 37 financial institutions that disclose either retained interests or managed assets. Eight

of these financial institutions account for approximately 50 percent of the managed assets of the

whole sample, with Citigroup alone making up 40 percent of the sample managed assets.18

18 The importance of Citigroup to the securitization market is revealed by our untabulated finding that its retained interest impairment event results in increases in trading volume, spread, and implied volatility for other sample S-O

26

Although our sample contains only 16 retained interest writedown events, these events are for

the financial institutions with the lion share of managed assets. Furthermore, we have identified

all retained interest writedowns disclosed in the 8-Ks for the top 100 financial institutions. It is

possible that other banks had retained interest writedowns but these impairments do not have a

material impact on earnings and hence were not separately disclosed.

6. Empirical Results

6.1 SPREAD Estimations

Table 3 presents regression summary statistics associated with estimation of equations

(1), (2), and (3) using SPREAD as the dependent variable. The equation (1) findings indicate

that the coefficient on each of the announcement indicator variables, is significantly positive.

The “large” loan loss, retained interest, and CDO writedown announcement coefficients, ,

and — 0.027, 0.052, and 0.017—indicate that on average, spreads increase markedly with

each announcement, relative to the non-announcement spread coefficient, —0.069. In

addition, the findings also are consistent with the prediction that the largest increase in spread is

for retained interest writedown announcements, which is approximately double and triple the

increase for “large” loan loss and CDO writedowns. Untabulated t-statistics indicate that in 5 of

6 possible cases, and at less than the 7% level. The exception is for the

comparison of the retained interest writedown and loan loss coefficients in equation (2).

However, the difference becomes significant once EADUM is included in equation (3).19 Thus,

banks. This finding is consistent with information transfer taking place. However, other untabulated findings from estimating equations (1) through (3) excluding Citigroup result in no change in inferences from those based on the full sample that includes Citigroup. Thus, the market reaction to impairments is not simply a Citigroup phenomenon. 19 These tests are conducted based on unclustered standard errors because simulation findings in Lahiri and Li (2009) suggest that F-statistics based on samples with small number of clusters can be problematic. .Using standard

27

despite the fact the retained interest writedowns represent a small fraction of total assets or small

fraction of total writedowns, the effect on spreads is, as predicted, more pronounced than for

other asset writedowns because such writedowns make the market maker concerned about the

private information held by informed investors.

The findings from equation (2), in which control variables are included, and equation (3),

which also includes EADUM, also indicate that, on average, spreads generally increase

significantly with each announcement. For equations (2) and (3) the “large” loan loss, retained

interest, and CDO writedown announcement coefficients, , and , are significantly

positive, with the exception of in equation (3). In addition, the equations (2) and (3) findings

also are consistent with our prediction that the largest increase in spread is for retained interest

writedown announcements, although inclusion of the control variables, not surprisingly, decrease

coefficient magnitudes.20


6.2. AVOLUME Estimations


(1), (2), and (3) using AVOLUME as the dependent variable. The findings across all

specifications generally support the prediction that abnormal volume increases for each of the

three announcements. The coefficients are largest for retained interest writedowns (0.934, 0.882,

and 0.635), followed by “large” loan losses (0.718, 0.735, and 0.309), and CDO writedowns

errors based on clustering by firm leaves inferences unchanged for the retained interest and CDO writedown coefficient comparisons, but the difference between the retained interest and loan loss coefficients becomes insignificant. This is to be expected, given that we have a small number of clusters. 20 Untabulated findings from estimations in which we consider whether market reactions vary by quarter suggest that the increase in SPREAD associated with retained interest writedowns is concentrated in the first three quarters. However, because there are few writedowns in later quarters, it is difficult to determine whether this result is indicative of investors “learning” over time or lack of power.

28

(0.267, 0.247, and 0.113). Under our postulated one-sided alternative, the “large” loan loss

provision coefficient, , and the retained interest writedown coefficient, , are always

significantly positive. The CDO writedown coefficient is marginally significantly positive in

equations (1) and (2), but drops to insignificant when EADUM is included as a regressor.

Overall, these results are consistent with each of the announcements having information content.


6.3. IMPVOL Estimations


(1), (2), and (3) using IMPVOL as the dependent variable. Findings from equation (1), in which

no control variables are included, indicate that the only significant coefficient is that on retained

interest writedowns, with = 0.106. Using the benchmark non-announcement day implied

volatility given by the intercept, = 0.529, implied volatility increases approximately 20%

when retained interest writedowns are announced (0.106/0.529). These findings indicate that,

consistent with predictions, retained interest writedowns increase investor uncertainty on the

days they are announced.

Inclusion of control variables in equations (2) and (3) continue to show a significant

percentage increase in implied volatility over the non-announcement days when retained interest

writedowns are announced of more than 20% (0.094/0.428 and 0.096/0.428). However,

inclusion of controls also results in the “large” loan loss provision announcement coefficient

becoming significantly negative, −0.043 and −0.041 in equations (2) and (3). Thus, in contrast to

retained interest writedowns, “large” loan loss provisions appear to reduce investor uncertainty

rather than increase it. The findings across all three specifications indicate that CDO writedowns

fail to have a significant effect on implied volatility.

29


6.4 RETURN Estimations


(1), (2), and (3) using RETURN as the dependent variable. Results in all specifications indicate

no significant effect on stock return from retained interest impairment announcements, i.e., ,

is insignificantly different from zero. The findings indicate that only the coefficient on the

“large” loan loss provision , is significantly different from zero in any of the specifications. It

is significantly positive, 0.015, in equation (1), in which no control variables are included, and in

equation (2), when controls are included. This finding indicates that announcement of “large”

loan loss provisions has an incremental effect of increasing stock return, on average, by 1.5%.

However, when earnings announcements are considered, as is the case in equation (3), which

also includes EADUM, becomes insignificantly different from zero. The coefficient on

EADUM, , is significantly positive, 0.011, indicating that on average earnings announcement

news is apparently positive on days that earnings is announced. The results in all specifications

also indicate no significant effect on stock return from CDO impairment announcements, i.e.,

is insignificantly different from zero. Taken together, the findings in table 6 indicate that the

mean effect of impairments on stock prices is zero, which is consistent with our prediction that

the impact of impairment announcements on stock return is difficult to predict because of the

challenge in measuring changes in investors’ expectations regarding future cash flow and cost of

capital. 21


21 In addition, Cready and Hurtt (2002) provides evidence that power negatively affects the ability to assess market reaction based on stock returns to a greater extent than for other measures of investors’ reaction to news events.

30

6.5 Differing Incentives to Honor Implicit Guarantees

Taken together, the findings discussed above indicate that although announcements of

impairments of each asset class have information content in terms of an increase in trading

volume, retained interest impairments exhibit the largest and most consistent increases in spread.

Moreover, despite the fact the retained interest writedowns represent a small fraction of total

assets or small fraction of total writedowns, their effect on spreads is consistent with our

prediction that they increase information asymmetry regarding whether banks would honor their

implicit guarantees to SPE creditors during the crisis.

The preceding analysis treats retained interest writedowns by all banks similarly.

However, it is important to recognize that there is likely to be heterogeneity in the sample. First,

securitization differs in its importance across banks. Banks with a proportionately larger stake in

managed assets (i.e., securitized assets from which the S-O derives servicing rights) are more

likely to honor their implicit commitments than those with a proportionately lower stake because

the former have greater reputational capital to lose from not doing so. Second, banks subject to

regulatory oversight are less capable of absorbing losses incurred by SPEs. Thus, because banks

with a lower proportionate stake in managed or subject to regulatory oversight are less likely to

honor implicit guarantees, we predict that announcements of retained interest writedowns by

these banks create less information asymmetry.

To determine whether this is the case, we re-estimate equation (3) for SPREAD,

partitioning the sample based on the extent to which a bank has high or low amounts of managed

assets, and the extent to which a bank faces regulatory constraints. We define high/low managed

asset banks as those whose managed assets are above/below the sample median for the subset of

firms with managed assets. We use two proxies for whether banks regulatory constraints. The

31

first is whether a bank is “regulated” or “unregulated.” For our purposes, we define “regulated”

entities to be those that have a Tier 1 capital ratio available in either Compustat or the regulatory

call reports dataset provide by the federal reserve bank of Chicago. Matching the call report

dataset to our data is based on a link table provided by the Federal Reserve Bank of New York.

The second is whether Tier 1 capital is above and below the sample median. We predict that the

retained interest announcement effect on the spread is larger banks with low managed assets and

facing low regulatory constraints.

Findings support our predictions in that there is a significant increase in SPREAD when

retained interest writedowns are announced only for those banks with low managed assets and

facing low regulatory constraints. However, because there are only three or four retained interest

writedowns among the set of banks facing high regulatory constraints, it is difficult to determine

whether the lack of a spread effect for such banks is attributable to low power, or, as we predict,

there being little information asymmetry associated with retained interest impairments for these

banks. We therefore tabulate the findings relating to equation (3) only for the high and low

managed assets partition. Table 7 reveals that whereas for high managed asset banks the retained

interest writedown coefficient, , 0.005, is in insignificant (t-statistic = 0.413), for low

managed asset banks, = 0.068, which is significantly positive (t-statistic = 2.510).22


22 We also estimate equation (3) for volume, return, and implied volatility using the same three sample partitionings. The most notable untabulated finding is that the retained interest coefficient is significantly negative in the return specification for high managed asset banks, but insignificantly different from zero for low managed asset banks. Together with the spread result showing no increase for high managed asset banks, this finding is consistent with retained interest impairment by high managed asset banks confirming the market’s expectation that such banks will honor their implicit guarantees, and thereby suffer an economic loss.

32

7. Summary and Concluding Remarks

In this study, we use equity market reactions to the announcement of impairments of

retained interests arising from asset securitizations made by financial institutions during the

Financial Crisis of 2007-2008 as a means of obtaining insights into the nature of the implicit

guarantees associated with this form of financing. Whereas the commitments entered into by

banks originating loans and sponsoring subsequent securitizations would be likely to be fully

honored in normal economic conditions, the implicit nature of such guarantees leaves open the

possibility that they might not be honored under conditions of extreme stress associated with the

Financial Crisis. By their very nature implicit guarantees are difficult to observe. We use

writedowns of retained interests by S-O banks during the Financial Crisis as a means to infer

whether market participants took actions reflecting their belief that the S-O banks would honor

some implicit guarantees. We use the market reaction to announcements of loan losses and

writedowns of asset-backed securities purchased as investments as a benchmark to compare the

market reaction to the retained interest writedowns. Although retained interest impairments are

relatively small in magnitude, compared to these other writedowns, we hypothesize that they

reveal information of exposure to a much larger loss associated with off-balance sheet assets and

liabilities.

We find evidence that each of the announcements has information content as indicated by

an increase in trading volume, although, consistent with predictions, the increase is greatest for

retained interest writedowns. This increase in trading volume is also accompanied by a predicted

increase in bid-ask spreads. The increase in spreads is greatest for announcements of retained

interest writedowns, which is consistent with the market being concerned that implicit guarantees

associated with assets retained from securitizations could expose banks to the risk of substantial

33

future losses. Findings from additional analyses reveal that increases in bid-ask spreads are

concentrated among banks with low managed assets, banks which are unregulated, and banks

that are relatively well capitalized. We also predict and find that implied equity volatility

increases with retained interest writedown announcements, which is consistent with such

announcements increasing investor uncertainty. Finally, none of the announcements has a

significant effect on stock returns.

Taken together, our findings suggest that a binary approach to accounting for

securitizations may not capture fully the economic nature of the transaction. Treating

securitizations as sales, which results in derecognition of transferred assets and non-recognition

of SPE debt, or as secured borrowings by the S-O, which puts the SPE assets and liabilities on

the S-O’s balance sheet, masks the economic effects of the transactions. Our findings suggest

that an alternative approach considered in the IASB Exposure Draft, Derecognition, Proposed

Amendments to IAS 39 and IFRS 7 (IASB, 2009) to derecognize transferred assets and recognize

as assets and liabilities rights and obligations retained or obtained in the transfer, including all

derivatives at their fair values, better captures the economic characteristics of securitizations.

We acknowledge the formidable challenges involved in identifying implicit guarantees and

measuring their fair values. Sometimes implicit guarantees are worth the paper they are not

written on, and sometimes they are not.

34

Appendix

The appendix presents regression summary statistics from estimating versions of the

valuation models in Landsman, Peasnell, and Shakespeare (2008) for our sample banks,

estimated separately before (2006) and during (2008) the crisis period. The first two columns

present results for 2006 and 2008 for the base model that excludes SPE assets and liabilities.

Columns three and four present results for the extended model that includes SPE assets and

liabilities. The last two columns present results for the extended model but with net income

excluded from the specification.

Findings for 2006 in each specification are consistent with those reported in tables 3 and

4 of Landsman, Peasnell, and Shakespeare (2008) in that they indicate the market values SPE

assets and liabilities similarly to recognized assets and liabilities. For example, in column three,

the coefficient on ADJ_ASSET, i.e., recognized S-O assets adjusted for our consolidation of SPE

assets, is 0.88 (t-statistic = 9.37), and the coefficient on SPE_ASSET, i.e., our measure of SPE

assets, is 0.79 (t-statistic = 2.02). Likewise, the coefficient on LIAB, i.e., recognized S-O

liabilities, is −0.87 (t-statistic = −4.75), and the coefficient on SPE_LIAB, i.e., our measure of

SPE liabilities, is −0.81 (t-statistic = −2.04). Untabulated F-statistics indicate that the differences

in the ADJ_ASSET and SPE_ASSET coefficients, and the differences in the LIAB and SPE_LIAB

coefficients are insignificantly different from zero. In other words, in the period preceding the

Financial Crisis bank equities were priced as if banks would honor their implicit guarantees to

SPE creditors.

Findings for 2008 contrast starkly with those for 2006. Most importantly regarding our

conjecture, the evidence indicates that in neither of the specifications that include SPE assets and

liabilities does the market value bank equities as if banks would honor their implicit guarantees

35

to SPE creditors. For example, in column four, the coefficient on ADJ_ASSET is 0.31 (t-statistic

= 1.62), and the coefficient on SPE_ASSET is 0.79 (t-statistic = 1.45). Likewise, the coefficient

on LIAB is −0.25 (t-statistic = −1.21), and the coefficient on SPE_LIAB is −0.81 (t-statistic =

−1.47). These findings indicate that the market no longer prices SPE assets and liabilities as

belonging to the S-O in 2008. However, the findings are surprising in that they indicate the

market no longer prices recognized assets and liabilities as belonging to the S-O! Even the base

model findings for 2008 in column two are difficult to interpret in that recognized S-O liability

coefficient is insignificantly different from zero. Furthermore, the sizeable drop in the net

income coefficient from 5.64 in 2006 to 1.12 in 2008 is consistent with the market viewing

current earnings as being a poor predictor of future profitability during the Financial Crisis.

To explore the possibility of whether inclusion of earnings results in a misspecification of

the valuation model in 2008, we re-estimate the Landsman, Peasnell, and Shakespeare (2008)

valuation model for 2006 and 2008 without net income. The 2006 findings in column 5 are

broadly consistent with those in column 3 in which net income is included. That is, the

coefficients for ADJ_ASSET and LIAB are significantly different from zero, as are the SPE asset

and liability coefficients. In addition, untabulated F-statistics indicate that the differences in the

ADJ_ASSET and SPE_ASSET coefficients, and the differences in the LIAB and SPE_LIAB

coefficients are insignificantly different from zero.23 The 2008 findings in column 6 are more

sensible than those in column 4, in that the coefficients on recognized assets and liabilities are

significantly different from zero, albeit smaller in absolute magnitude relative to the

corresponding coefficients in 2006. However, the coefficients on SPE_ASSET and SPE_LIAB

remain insignificantly different from zero.

23 The increase in absolute magnitude of all coefficients in column 5 relative to column 3 is consistent with the omission of a correlated omitted variable, i.e., net income, in column 5.

36

Taken together, the findings in table A.1 suggest that the market’s expectations regarding

the likelihood of banks honoring their implicit guarantees of SPE asset performance changed

during the turbulent conditions in the Financial Crisis. However, the instability of the

coefficients on recognized assets and liabilities as well as that on net income during the Financial

Crisis suggest that the valuation approach of Landsman, Peasnell, and Shakespeare (2008) can

only offer limited insight into the expectations of investors.

[Insert table A.1 here]

37

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41

Table 1 -Descriptive Statistics The descriptive statistics presented below are taken from a pooled sample of 71 financial institutions for which an impairment event occurred at least once between October 1, 2007 to December 31, 2008. Panel A describes the data for the full sample. Panel B describes the data only for days in which an impairment event occurred. LOAN_LOSS equals 1 if the provision expense or net charge-off (a) is mentioned in the 8-K and (b) the firm’s loans loss allowance scaled by gross loans has increased compared to the previous quarter. RET_INTEREST is an indicator variable that equals one if a write-down of retained interest was mentioned in the 8-K. ABS_CDO is an indicator variable that equals one if a CDO write-off was mentioned in the 8-K. Each indicator variable equals zero on all days but the announcement day. EVENT is a composite indicator variable constructed from the three event variables such that it takes the value of one if one or more of LOAN_LOSS, RET_INTEREST , and ABS_CDO is equal to one, and zero otherwise. RETURN is the daily return, LPRICE is the log of daily price. SPREAD is the daily bid ask spread and is calculated by subtracting the low bid price from the high ask price and dividing the result by the daily price. To calculate AVOLUME we subtract firm’s daily volume from its mean volume and divide the result by the standard deviation of the firm’s volume during our sample period. STDRET is the standard deviation of stock returns over our sample period. LMVOLUMEQ is the log of the mean of daily volume in the calendar quarter in which the impairment event was announced. EADUM is an indicator variable that takes the value of 1 at the day of the earnings announcement. LATQ is the log of the firm’s total assets at the end of the quarter prior calendar quarter in which the event occurred .IMPVOL is the daily implied volatility is based on at the money call option with expiration of 91 days.

Panel A- Full sample

Variable N Mean Median Std Dev Minimum Maximum

10th Pctl

90th Pctl

SPREAD 21,082 0.07 0.05 0.06 0.01 0.42 0.02 0.13 RETURN 21,082 0.00 0.00 0.05 -0.20 0.24 -0.06 0.05 AVOLUME 21,082 -0.01 -0.25 0.91 -1.37 4.77 -0.83 1.06 IMPVOL 14,201 0.53 0.46 0.23 0.22 1.67 0.32 0.83 EVENT 21,082 0.01 0.00 0.10 0.00 1.00 0.00 0.00 LOAN_LOSS 21,082 0.01 0.00 0.09 0.00 1.00 0.00 0.00 RET_INTEREST 21,082 0.00 0.00 0.03 0.00 1.00 0.00 0.00 ABS_CDO 21,082 0.00 0.00 0.06 0.00 1.00 0.00 0.00 EADUM 21,082 0.02 0.00 0.12 0.00 1.00 0.00 0.00 LATQ 21,082 10.94 10.61 1.48 9.14 14.63 9.45 13.60 LPRICE 21,082 3.02 3.05 0.91 -1.83 5.19 1.95 4.01 LMVOLUMEQ 21,082 15.02 15.09 1.69 8.90 19.14 13.11 17.24 STDRET 21,082 0.06 0.05 0.02 0.02 0.13 0.03 0.08

42

Table 1 -Descriptive Statistics – continued

Panel B - Just EVENT days

Variable N Mean Median Std Dev Minimum Maximum

10th Pctl

90th Pctl

SPREAD 228 0.10 0.08 0.06 0.02 0.42 0.04 0.17 RETURN 228 0.01 0.00 0.08 -0.20 0.24 -0.09 0.12 AVOLUME 228 0.76 0.46 1.28 -0.98 4.77 -0.55 2.51 IMPVOL 159 0.52 0.46 0.22 0.22 1.63 0.32 0.86 LOAN_LOSS 228 0.79 1.00 0.41 0.00 1.00 0.00 1.00 RET_INTEREST 228 0.07 0.00 0.26 0.00 1.00 0.00 0.00 ABS_CDO 228 0.34 0.00 0.48 0.00 1.00 0.00 1.00 EADUM 228 0.77 1.00 0.42 0.00 1.00 0.00 1.00 LATQ 228 11.03 10.86 1.49 9.24 14.53 9.46 13.60 LPRICE 228 3.05 3.07 0.85 -0.40 5.13 1.96 3.98 IMVOLUMEQ 228 15.20 15.17 1.63 8.90 19.14 13.48 17.36 STDRET 228 0.06 0.05 0.02 0.02 0.13 0.03 0.08

43

Table 2 - Correlation table This table presents correlations between variables used in the analysis. Pearson correlations are above the diagonal and Spearman correlations are below the diagonal. All variables are described in table 1.

Correlation table for the full sample:

Variable SPREAD RETURN AVOLUME IMPVOL EVENT LOAN_LOSS RET_INTEREST ABS_CDO EADUM LATQ LPRICE LMVOLUMEQ STDRET

SPREAD -0.02 0.48 0.62 0.06 0.05 0.03 0.04 0.06 0.04 -0.46 0.15 0.34

RETURN -0.05 0.08 -0.09 0.02 0.02 0.01 0.00 0.03 -0.01 0.05 -0.01 -0.04

AVOLUME 0.50 0.03 0.35 0.09 0.08 0.03 0.04 0.10 0.00 -0.11 0.10 0.00

IMPVOL 0.66 -0.12 0.36 0.00 -0.01 0.01 0.01 -0.01 0.07 -0.63 0.30 0.58

EVENT 0.07 0.01 0.07 0.00 0.89 0.26 0.58 0.64 0.01 0.00 0.01 0.01

LOAN_LOSS 0.06 0.02 0.07 -0.01 0.89 0.05 0.34 0.61 -0.01 0.00 -0.01 0.00

RET_INTEREST 0.03 0.00 0.02 0.02 0.26 0.05 0.08 0.14 0.01 -0.01 0.02 0.01

ABS_CDO 0.05 0.00 0.04 0.01 0.58 0.34 0.08 0.32 0.03 0.00 0.02 0.01

EADUM 0.07 0.02 0.09 -0.01 0.64 0.61 0.14 0.32 0.00 0.01 0.00 0.00

LATQ 0.03 -0.02 0.01 0.11 0.01 -0.01 0.01 0.02 0.00 0.19 0.79 0.31

LPRICE -0.44 0.06 -0.14 -0.60 0.00 0.00 -0.01 0.00 0.01 0.25 -0.17 -0.51

LMVOLUMEQ 0.17 -0.03 0.11 0.30 0.01 -0.01 0.02 0.02 0.00 0.82 -0.09 0.40

STDRET 0.38 -0.06 -0.02 0.63 0.01 0.00 0.01 0.01 0.00 0.25 -0.53 0.41

44

Table 3 - The relation between bid ask spread and impairment events This table presents the results of the estimation of equations (1), (2), and (3) in which daily bid ask spread (SPREAD) on the impairments indicators and control variables. All variables are described in table 1. t-statistics are in parenthesis and based on clustered by firm standard errors *** Significance at the 10% level, ** significance at the 5% level, * significance at the 1% level

SPREAD Model 1 Model 2 Model 3 LOAN_LOSS 0.027* 0.029* 0.012** (5.10) (6.54) (2.11) RET_INTEREST 0.052** 0.042** 0.032** (2.38) (2.49) (1.98) ABS_CDO 0.017* 0.015* 0.009 (2.66) (2.98) (1.65) LATQ 0.008* 0.008* (3.55) (3.54) LPRICE -0.030* -0.030* (11.24) (11.22) LMVOLUMEQ -0.004** -0.004** (2.01) (2.00) STDRET 0.242** 0.242** (2.35) (2.34) EADUM 0.024* (6.40) Constant 0.069* 0.125* 0.125* (26.89) (6.73) (6.71) Observations 21,082 21,082 21,082 R-squared 0.004 0.239 0.241

45

Table 4 - The relation between abnormal volume and impairment events This table presents the results of the estimation of equations (1), (2), and (3) in which daily abnormal volume (AVOLUME) on the impairments indicators and control variables. All variables are described in table 1. t-statistics are in parenthesis and based on clustered by firm standard errors *** Significance at the 10% level, ** significance at the 5% level, * significance at the 1% level

AVOLUME

Model 1 Model 2 Model 3

LOAN_LOSS 0.718* 0.735* 0.309**

(6.74) (6.86) (2.00)

RET_INTEREST 0.934** 0.882** 0.635***

(2.57) (2.42) (1.79)

ABS_CDO 0.267*** 0.247*** 0.113

(1.96) (1.83) (0.85)

LATQ 0.047* 0.047*

(4.10) (4.08)

LPRICE -0.189* -0.189*

(5.27) (5.27)

STDRET -5.156* -5.160*

(4.74) (4.73)

EADUM 0.570*

(5.71)

Constant -0.018* 0.329* 0.327*

(10.36) (2.89) (2.88)

Observations 21,082 21,082 21,082

R-squared 0.008 0.029 0.032

46

Table 5 - The relation between implied volatility and impairment events This table presents the results of the estimation of equations (1), (2), and (3) in which daily implied volatility (IMPVOL) on the impairments indicators and control variables. All variables are described in table 1. t-statistics are in parenthesis and based on clustered by firm standard errors *** Significance at the 10% level, ** significance at the 5% level, * significance at the 1% level

IMPVOL

Model 1 Model 2 Model 3

LOAN_LOSS -0.031 -0.043* -0.041**

(1.43) (2.90) (2.11)

RET_INTEREST 0.106*** 0.094** 0.096**

(2.00) (2.04) (2.03)

ABS_CDO 0.05 0.041 0.042

(1.29) (1.49) (1.46)

LATQ -0.028* -0.028*

(3.53) (3.53)

STDRET 7.110* 7.110*

(11.10) (11.10)

EADUM -0.002

(0.21)

Constant 0.529* 0.428* 0.428*

(25.69) (5.17) (5.18)

Observations 14,201 14,201 14,201

R-squared 0 0.359 0.359

47

Table 6 - The relation between return and impairment events This table presents the results of the estimation of equations (1), (2), and (3) in which daily return (RETURN) is regressed on the impairments indicators and control variables. All variables are described in table 1. t-statistics are in parenthesis and based on clustered by firm standard errors. *** Significance at the 10% level, ** significance at the 5% level, * significance at the 1% level

RETURN Model 1 Model 2 Model 3 LOAN_LOSS 0.015** 0.015** 0.006 (2.50) (2.50) (0.84) RET_INTEREST 0.01 0.01 0.006 (0.37) (0.38) (0.20) ABS_CDO -0.007 -0.007 -0.01 (0.68) (0.65) (0.89) LATQ -0.000*** -0.000*** (1.78) (1.83) LMVOLUMEQ 0 0.000*** (1.63) (1.67) STDRET -0.095* -0.095* (7.00) (7.09) EADUM 0.011** (2.06) Constant -0.002* 0.002 0.002 (5.64) (1.05) (1.00) Observations 21,082 21,082 21,082 R-squared 0.001 0.002 0.002

48

Table 7 – Partitions based on high and low managed assets financial institutions This table presents the results of the estimation of equations (3) in which the bid ask spread (SPREAD), is regressed on the impairments indicators and control variables. SPREAD is estimated based on sub-samples portioned on high and low managed securitized assets. All variables are described in table 1. t-statistics are in parenthesis and based on clustered-by-firm standard errors.

*** Significance at the 10% level, ** significance at the 5% level, * significance at the 1% level

High Managed

Assets Low Managed

Assets SPREAD SPREAD LOAN_LOSS -0.004 0.016** (-0.366) (2.450) RET_INTEREST 0.005 0.068** (0.413) (2.510) ABS_CDO 0.003 0.013** (0.309) (2.141) LATQ 0.001 0.011* (0.179) (3.881) LPRICE -0.037* -0.029* (-5.415) (-8.620) LMVOLUMEQ 0.003 -0.006** (0.474) (-2.567) STDRET 0.250 0.234 (1.455) (1.565) EADUM 0.027* 0.022* (5.109) (4.905) Constant 0.115*** 0.113* (1.964) (5.582) Observations 5,450 15,632 R-squared 0.246 0.247

49

Table A.1 – Landsman, Peasnell and Shakespeare (2008) valuation regressions for 2006 and 2008. This table presents the results of the estimation of the equations presented in Landsman, Peasnell and Shakespeare (2008) for a sample of financial institutions that had securitization activity at the end of 2006 and at the end of 2008. The estimation is done separately for the end of 2006 and the end of 2008. The dependent variable in all columns, MVE, is the market value of equity at the end of the fiscal year, calculated as the price at the end of the year times the number of outstanding shares at the end of the fiscal year. ASSET is total assets at the end of the year, LIAB is total liabilities at the end of the year and NI is the net income for the year. ADJ_ASSET is ASSET less Retained interest and servicing rights from securitization transactions obtained from the 10-K. ADJ_LIAB equals to LIAB. SPE_ASSET equals managed loans off-balance sheet disclosed in the 10-K. SPE_LIAB equals to SPE_ASSET less Retained interest and servicing rights from securitization transactions obtained from the 10-K. t-statistics are in parenthesis *** Significance at the 10% level, ** significance at the 5% level, * significance at the 1% level

(1) (2) (3) (4) (5) (6)

2006 2008 2006 2008 2006 2008

MVE

ASSET 0.892* 0.316***

(5.148) (1.706)

LIAB -0.889* -0.254

(-4.989) (-1.269)

ADJ_ASSET 0.881* 0.308 1.264* 0.611*

(4.937) (1.622) (6.704) (3.732)

LIAB -0.876* -0.248 -1.238* -0.572*

(-4.754) (-1.208) (-6.158) (-3.207)

SPE_ASSET 0.790** 0.792 1.003*** 0.332

(2.016) (1.449) (2.055) (0.582)

SPE_LIAB -0.807** -0.806 -1.018** -0.337

(-2.039) (-1.469) (-2.062) (-0.590)

NI 5.682* 0.810** 5.641* 1.120**

(4.088) (2.365) (3.948) (2.555)

Constant 5.025 -6.427** 6.130*** -4.717 9.711** -8.604**

(1.576) (-2.129) (1.786) (-1.383) (2.331) (-2.550)

Observations 30 30 30 30 30 30

Adjusted R-squared 0.922 0.885 0.919 0.884 0.871 0.858

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