does fair value accounting contribute to systemic risk in ... · urooj khan, columbia business...

Does Fair Value Accounting Contribute to Systemic Riskin the Banking Industry?*

UROOJ KHAN, Columbia Business School†

ABSTRACTI investigate whether fair value accounting can contribute to the banking industry’s systemic risk. Ifocus on the adoption of Statement of Financial Accounting Standard No. 115 (SFAS No. 115), whichrequired available-for-sale (AFS) securities to be recognized at fair value with unrealized gains andlosses included in equity through accumulated other comprehensive income. SFAS No. 115 increasedbanks’ regulatory risk because, at the time, calculation of regulatory capital closely conformed withGAAP equity. I find that systemic risk increased following the adoption of SFAS No. 115. Further-more, following a subsequent regulatory amendment—which excluded unrealized gains and losses onAFS securities from regulatory capital but did not change their GAAP treatment—systemic riskdecreased. Taken together, the evidence suggests that fair value accounting has the potential to increasesystemic risk through the explicit inclusion of volatile fair value estimates in regulatory bank capitaladequacy assessments. I do not, however, find evidence of fair value accounting impacting systemicrisk in its information role; that is, by providing information to a bank’s external stakeholders about itsfinancial position and performance. I also show that higher fair value volatility of investment securities,lower bank capital, and larger AFS security holdings increase banks’ marginal contribution to systemicrisk. My findings should interest regulators and policymakers, as recent regulatory changes in light ofBasel III recommendations require unrealized gains and losses on AFS securities to be included in reg-ulatory capital for advanced approaches banks.

La comptabilité à la juste valeur contribue-t-elle au risquesystémique dans le secteur bancaire?

RÉSUMÉL’auteur se demande si la comptabilité à la juste valeur peut contribuer au risque systémique dansle secteur bancaire. Il s’intéresse plus particulièrement à l’adoption de la norme SFAS n�

115 exigeant que les titres disponibles à la vente soient comptabilisés à leur juste valeur, les profitset pertes latents étant inclus dans les capitaux propres par l’intermédiaire du cumul des autres élé-ments du résultat global (AERG). La norme n� 115 a augmenté le risque lié à la réglementationauquel sont exposées les banques du fait qu’à l’époque, le calcul du capital réglementaire

*Accepted by J. Douglas Hanna. I thank two anonymous reviewers, B.W. Baer, Jannis Bischof, Robert Bowen, MatthiasBreuer, Dave Burgstahler, Charles Calomiris, Ki-Soon Choi, Elizabeth Chuk, Douglas Hanna, Jarrad Harford, TrevorHarris, Richard Hartman, Leslie Hodder, Frank Hodge, Jon Karpoff, Sharon Katz, Todd Kravet, Christian Leuz, DawnMatsumoto, Suresh Nallareddy, Doron Nissim, Jeffrey Ng, Stephen Penman, Shiva Rajgopal, Ed Rice, Edward Riedl,Stephen Ryan, Richard Sansing, Cathy Shakespeare, Terry Shevlin, Mark Soliman, Abhishek Varma, Dushyant Vyas,Chris Williams, Jerry Zimmerman, Jenny Zhang, and seminar participants at the AAA Annual Meeting, AAA FARSMidyear Meeting, Boston University, Columbia University, joint workshop of Deutsche Bundesbank and RTF of BaselCommittee on Banking Supervision, Emory University, Georgia State University, Georgetown University, Harvard Busi-ness School, London Business School, Pennsylvania State University, Rutgers University, SUNY Binghamton, TuckSchool of Business, University of California at Berkeley, University of Colorado at Boulder, University of Houston,University of Michigan at Ann Arbor, University of Rochester, University of Washington, Yale Accounting ResearchConference, and the Yale Financial Crisis Conference for their helpful comments and suggestions. An earlier version ofthis manuscript was awarded the 2012 American Accounting Association’s Competitive Manuscript Award.

†Corresponding author.

Contemporary Accounting Research Vol. 00 No. 00 (Month 2019) pp. 1–22 © CAAA

doi:10.1111/1911-3846.12501

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s’apparentait de près à celui des capitaux propres selon les PCGR. L’auteur constate que le risquesystémique a augmenté à la suite de l’adoption de la norme SFAS n� 115. Il a par ailleurs diminuéaprès une modification réglementaire subséquente — selon laquelle les gains et pertes latents affér-ents aux titres disponibles à la vente ont été exclus du capital réglementaire tout en demeurantassujettis au même traitement en vertu des PCGR. Dans leur ensemble, ces constatations semblentindiquer que la comptabilité à la juste valeur a le potentiel d’accroître le risque systémique parsuite de l’intégration explicite d’estimations à la juste valeur volatiles dans les évaluationsréglementaires du caractère adéquat du capital bancaire. L’auteur ne relève cependant rien qui per-mette d’affirmer que la comptabilité à la juste valeur ait une incidence sur le risque systémiquedans son rôle informatif, soit celui de fournir aux parties prenantes externes d’une banque del’information au sujet de la situation et de la performance financières de cette dernière. Il montreen outre qu’une plus grande volatilité de la juste valeur des titres de placement, un capital bancairemoins élevé et la détention d’un plus grand volume de titres disponibles à la vente accroissent lacontribution marginale des banques au risque systémique. Les observations de l’auteur devraientintéresser les autorités de réglementation et les responsables de l’élaboration des politiques,puisque les modifications récemment apportées à la réglementation dans la foulée des rec-ommandations de Bâle III exigent que les gains et pertes latents afférents aux titres disponibles àla vente soient inclus dans le capital réglementaire des banques utilisant les approches avancées.

1. Introduction

To investigate the relation between fair value accounting and the systemic risk of the bankingsector,1 I examine changes in systemic risk around (i) the adoption of Statement of FinancialAccounting Standard No. 115 (SFAS No. 115), “Accounting for Certain Investments in Debtand Equity Securities,”2 which required unrealized gains and losses on available-for-sale (AFS)securities to be included in equity and, consequently, in bank regulatory capital, and (ii) a sub-sequent regulatory amendment that excluded unrealized gains and losses on AFS securitiesfrom regulatory capital. I find that systemic risk increased following the adoption of SFASNo. 115 and then decreased after the regulatory amendment. The evidence suggests that includ-ing volatile fair value estimates in bank capital adequacy assessments can exacerbate systemicrisk. My findings should interest regulators and policymakers because Basel III recommenda-tions as adopted by U.S. bank regulators require advanced approaches banks3—the largest andmost important banks in the economy—to include unrealized gains and losses on AFS securi-ties in regulatory capital.

With respect to financial instruments, accounting standard setters typically choosebetween amortized cost and fair value accounting as accounting measurement bases. TheFASB and the IASB have issued standards that increasingly require firms to use fair valueaccounting in financial reporting, especially with respect to financial instruments. Standardsetters believe that, as a measurement basis, fair value meets the conceptual frameworkcriteria better than other measurement bases (Barth 2006, 2014). However, the use of fairvalues in financial reporting is not without controversy. Proponents argue that an accountingsystem based on fair values provides the most timely and up-to-date information because fairvalues incorporate current economic information, while the critics assert that fair value esti-mates are excessively volatile.

In the banking industry, accounting serves at least two important roles. In its informationrole, which applies to all public companies, accounting informs a firm’s external stakeholders

1. Systemic risk is the risk or probability of breakdowns in an entire system, as opposed to breakdowns in individualparts or components (Kaufman and Scott 2003).

2. Accounting Standards Codification ASC 320. In the rest of the paper, I refer to ASC 320 by its pre-codification ref-erence, SFAS No. 115.

3. A bank qualifies as an advanced approaches bank if it has at least $250 billion in total consolidated assets or at least$10 billion in total on-balance-sheet foreign exposure.

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about its financial performance and position. In its regulatory role, accounting provides estimatesand disclosures that are used as inputs in the regulatory oversight of the banking sector. The FederalDeposit Insurance Corporation Improvement Act of 1991 (FDICIA) closely aligned the RegulatoryAccounting Principles (RAP) with GAAP, requiring that regulatory accounting standards be no lessstringent or conservative than GAAP.

Alternative accounting measurement bases can differentially introduce volatility in financialstatements. Fair value–based earnings and equity are more volatile than those based on amortizedcost, and banks could violate regulatory capital requirements more frequently if fair value account-ing rather than amortized cost accounting is used to compute regulatory capital (e.g., Barth et al.1995; Hodder et al. 2006). Focusing on the use of fair value accounting for investment securities,Barth et al. (1995) report that enhanced regulatory capital volatility related to fair value accountingincreases potential regulatory capital violations of banks. Hence, fair value accounting can contrib-ute to the instability of the banking system by increasing the risk of capital shortfalls and of costlyregulatory intervention.

Both the information and the regulatory roles of accounting could potentially increase the sys-temic risk of the banking sector. In its regulatory role, fair value accounting could increase systemicrisk by increasing the risk of regulatory intervention due to the greater likelihood of regulatory capi-tal violations when fair value estimates are used to compute regulatory capital. In its informationrole, fair value accounting could increase systemic risk if, independently of increased regulatoryrisk, a bank’s external stakeholders decrease the availability or increase the cost of credit inresponse to the increased risk of capital shortfalls and more volatile fair value–based earnings(Flannery 1996). My empirical setting, described below, helps to disentangle the effects of the tworoles of accounting on the relation between fair value accounting and systemic risk.

My empirical analyses focus on the adoption of SFAS No. 115. Prior to SFAS No. 115, mostinvestment securities were recognized at amortized cost. SFAS No. 115, which was effective for fis-cal years beginning after December 15, 1993, required AFS securities to be recognized at fair valueand the related unrealized gains and losses to be included in equity via the accumulated other com-prehensive income (AOCI). When SFAS No. 115 was adopted, the regulatory capital calculationclosely conformed with GAAP equity. As a result, the inclusion of fair value changes in the valueof AFS securities in regulatory capital increased the likelihood of potential capital shortfalls and therisk of regulatory intervention (Barth et al. 1995; Hodder et al. 2002).

In November 1994, bank regulators amended the rules for calculating regulatory capital andrequired that unrealized AFS security gains and losses be excluded from regulatory capital.4

Hence, between the adoption of SFAS No. 115 and the November 1994 amendment, unrealizedgains and losses on AFS securities are included in GAAP equity and regulatory capital. However,following the November 1994 amendment, unrealized AFS security gains and losses are includedin GAAP equity but excluded from regulatory capital. I exploit these quasi-exogenous shocks tothe extent to which fair value accounting is used in financial reporting and regulatory supervisionto examine changes in systemic risk.

Following Adrian and Brunnermeier (2016), I measure systemic risk using a reduced-formestimate that uses equity returns to capture the tail risk codependence between the financial sys-tem as a whole and individual banks (see section Measuring Systemic Risk for additional detailsabout this measure). My sample comprises all U.S. bank holding companies (BHCs) that file FRY-9C reports and have the requisite data available for the period 1993:Q2–1995:Q1. Controllingfor changes in bank-specific characteristics and the macroeconomic environment, I find that theadoption of SFAS No. 115 is associated with a significant increase in the systemic risk of the

4. https://www.gpo.gov/fdsys/pkg/FR-1994-11-25/html/94-29110.htm. Following the amendment, net unrealizedlosses on equity securities classified as AFS were still included in the calculation of regulatory capital. Typically,banks hold minimal quantities of equity securities classified as AFS. Banks’ AFS security portfolios consist largelyof debt securities.

Fair Value Accounting and Systemic Risk 3


https://www.gpo.gov/fdsys/pkg/FR-1994-11-25/html/94-29110.htm

banking sector. Furthermore, following the November 1994 amendment, the systemic risk decreasessignificantly. The difference in the systemic risk in the post-November 1994 and the pre-SFASNo. 115 periods is statistically insignificant. Taken together, this suggests that fair value accountingcontributes to systemic risk only through its regulatory role (when bank regulators include fair valueestimates explicitly in capital adequacy assessments). I do not find evidence of fair value accountingcontributing to systemic risk when accounting is only serving its information role.

Next, I conduct several cross-sectional tests to identify characteristics associated with an individ-ual bank’s contribution to the systemic risk of the banking sector. First, I predict and find that higherfair value volatility of investment securities is associated with greater marginal contribution of banksto systemic risk during the period when unrealized gains and losses on AFS securities are included inregulatory capital. Following the November 1994 amendment, which excluded unrealized gains andlosses on AFS securities from regulatory capital, this relation is statistically insignificant.

Second, I predict and find that the marginal systemic risk contribution of banks with relativelyhigher capital is smaller when unrealized gains and losses on AFS securities are included in regula-tory capital. Finally, I predict and find that larger holdings of AFS securities are associated withgreater marginal contribution to systemic risk. Following the November 1994 regulatory amend-ment, that positive association is significantly reduced. While the underlying composition of theAFS and held-to-maturity (HTM) security portfolios is largely similar (e.g., Xie 2016), unrealizedgains and losses on HTM securities are not included in GAAP equity or regulatory capital.5 Hence,holdings of securities classified as HTM result in lower uncertainty about potential capital inade-quacy than holdings of AFS securities. I find that HTM security holdings are positively related to abank’s marginal contribution to systemic risk; however, this association is significantly smaller thanthe association between AFS securities and systemic risk. The November 1994 amendment did notsignificantly change the relation between HTM securities and a bank’s marginal contribution tosystemic risk.

To rule out alternative explanations and to demonstrate the robustness of my findings, I con-duct several additional analyses, including (i) examining the association between trading securi-ties and systemic risk, (ii) adjusting for early adoption of SFAS No. 115, and (iii) ruling outgeographical diversification or consolidation as an alternative explanation. Overall, I find that fairvalue accounting contributed to systemic risk following the adoption of SFAS No. 115 throughits regulatory role. Furthermore, a bank’s marginal contribution to systemic risk was positivelyassociated with the fair value volatility of its investment securities and the size of its AFS securityholdings and negatively associated with its level of capital.

This study makes several contributions. First, as accounting standard setters and bank regulatorscontinue to grapple with the extent to which fair values should be used in financial reporting and bankregulation, this study provides evidence of an unintended externality in the form of increased systemicrisk. Following new regulatory capital guidelines under Basel III, U.S. federal bank regulatorsremoved the AOCI prudential filter and require advanced approaches banks to include unrealizedgains and losses on AFS securities in regulatory capital (Federal Deposit Insurance Corporation[FDIC] 2013).6 My findings directly speak to the implications of this change for the systemic risk ofthe financial system. Other recent studies show that removing the AOCI filter imposed regulatorycosts on banks, to which banks responded by adjusting their assets and liabilities to mitigate the addi-tional capital volatility (e.g., Chircop and Novotny-Farkas 2016; Kim et al. 2017).

Second, this study extends the literature on economic consequences of accounting standards(e.g., Khan et al. 2018), in general, and of SFAS No. 115, in particular. Prior studies limit theirinvestigation of SFAS No. 115 to bank level consequences, finding that banks altered the size,

5. Other-than-temporary impairments of HTM securities reduce GAAP equity and regulatory capital. Hence, HTMsecurities can contribute to the regulatory risk of banks if they are other-than-temporarily impaired.

6. Non-advanced-approaches banks were provided a one-time permanent election to opt out of including unrealizedgains and losses on AFS securities in regulatory capital.



maturity, and volatility of their investment security portfolios in response to SFAS No. 115(e.g., Beatty 1995; Hodder et al. 2002; Iselin et al. 2017). I demonstrate that SFAS No. 115 alsohad macroeconomic consequences, increasing the systemic risk of the entire banking sector. I alsohighlight bank characteristics associated with a bank’s marginal contribution to that risk.

Finally, my study contributes to the growing literature on the accounting-related and financialreporting–related drivers of the systemic risk of the financial system (e.g., Bowen and Khan2014; Bushman and Williams 2015; Bushman et al. 2016). In the wake of the Global FinancialCrisis, it has been debated whether fair value accounting exacerbated bank contagion by fuelingfire sales of assets (e.g., Ryan 2008; Laux and Leuz 2009, 2010). I highlight an alternativechannel—an increase in regulatory risk—by which fair value accounting can contribute to sys-temic risk. I find that fair value accounting only contributes to systemic risk when fair value esti-mates are explicitly included in regulatory assessments of capital adequacy. I find no evidence offair value accounting contributing to systemic risk through its information role.

The rest of the paper is organized as follows. Section 2 develops my predictions and dis-cusses related literature. Section 3 describes my research design and variable measurement.Section 4 discusses data. Section 5 reports the results. Section 6 concludes.

2. Theoretical development and related literature

Fair value accounting and systemic risk

Alternative accounting measurement bases can have differential impact on the properties ofaccounting estimates and financial statements (e.g., Khan et al. 2019). The two most commonmeasurement bases are amortized cost and fair value. Driven by standard setters’ belief that fairvalues provide the most relevant information to financial statement users, the use of fair value asan accounting measurement basis has become more pervasive (Barth 2006, 2014).

One implication of using fair value rather than amortized cost is an increase in the volatilityof accounting estimates. Fair values summarize the present value of expected future cash flows.Any change in expected cash flows or in their riskiness leads to a change in fair value. Often,changes in fair values are attributable to short-term market movements that later reverse, makingfair value–based accounting estimates more volatile. Barth et al. (1995) report that the volatilityof bank earnings that include unrealized fair value gains and losses of investment securities is26 percent greater than that of historical cost earnings for the median bank. Hodder et al. (2006)provide complementary evidence and report that the volatility of full fair value income is morethan three times that of comprehensive income and more than five times that of net income.7

In the banking industry, accounting serves a dual role. In its information role, it providesperiodic financial statements and related disclosures informing external stakeholders about thebank’s financial position and performance. In its regulatory role, accounting provides estimatesthat are important inputs in the regulatory supervision of banks. The FDICIA requires that RAPbe no less stringent than GAAP and that, unless stated otherwise, banks should follow GAAPaccounting to prepare regulatory filings. The FDICIA also introduced “prompt corrective action”to resolve capital deficiencies at insured banks and required early and costly regulatory interven-tion if regulatory capital fell towards or below statutory minimum thresholds (FDIC 2013).

Because, in its regulatory role, accounting provides estimates used as inputs to assess bankcapital adequacy, fair value accounting could increase systemic risk. Higher volatility of fairvalue–based estimates increases the volatility of bank capital and the likelihood of costly regula-tory intervention (Beatty 1995; Hodder et al. 2002). Barth et al. (1995) report that if fair valuegains and losses on investment securities were included in regulatory capital, bank violation ofminimum regulatory capital thresholds would increase by 43.6 percent. In its information role,

7. Hodder et al. (2006) develop a measure of full fair value income that includes unrealized fair value gains and losseson all financial instruments held by banks.



independent of its impact on regulatory risk, fair value accounting can increase systemic risk byincreasing uncertainty among bank counterparties and investors about the riskiness of banks andtheir ability to meet their obligations. Excessive and temporary write-downs of assets potentiallyrequired under fair value accounting can increase concerns about counterparty risk, leading todrying up of liquidity and market unraveling (e.g., Flannery 1996).

SFAS No. 115 and systemic risk

Prior to SFAS No. 115, most securities held by banks were reported at amortized cost. Regulatorsand other critics argued that the resulting book values of securities did not reflect changes in mar-ket interest rates (e.g., Schuetze 1992). In response, the FASB issued SFAS No. 115 in May1993, requiring that investments in equity securities with readily determinable fair values and alldebt securities be classified as HTM,8 trading, or AFS. Securities classified as HTM were to berecognized at amortized cost. Trading securities were required to be recognized at fair value withunrealized gains and losses included in earnings. The accounting treatment of trading securitiesdid not change significantly with SFAS No. 115, as these securities were already carried at mar-ket value. Finally, securities classified as AFS were to be recognized at fair value with theunrealized gains and losses included in equity via AOCI. Thus, if a bank classified securities asAFS, its GAAP equity would be more volatile under SFAS No. 115.9

When SFAS No. 115 was enacted, calculation of regulatory capital closely conformed withGAAP equity. As a result, unrealized gains and losses on AFS securities also impacted regulatorycapital. This increased the volatility of regulatory capital and uncertainty about future compliancewith regulatory capital thresholds, thereby increasing the risk of costly regulatory intervention(e.g., Beatty 1995; Hodder et al. 2002), and potentially enhanced the systemic risk of the bankingindustry. I formally state this expectation in alternative form as

HYPOTHESIS 1. The adoption of SFAS No. 115 increased the systemic risk of the bankingindustry.

In November 1994, the calculation of regulatory capital was amended. Bank regulatorsreversed their decision to include unrealized gains and losses on AFS securities in regulatory cap-ital (Office of the Comptroller of the Currency 1994), effective December 27, 1994. Unrealizedgains and losses on AFS securities thus continued to contribute to the volatility of GAAP equity,while regulatory capital was unaffected by the changes in the fair value of AFS securities.10 Thus,there was less uncertainty about future regulatory compliance and the risk of costly regulatoryintervention after the amendment. To the extent that greater regulatory risk related to the inclusionof unrealized gains and losses of AFS securities in regulatory capital contributed to systemic risk,I expect a reduction in systemic risk following the amendment. I formally state this expectation inalternative form as

HYPOTHESIS 2. The November 1994 regulatory capital amendment decreased the systemic riskof the banking industry.

8. Only debt securities could be classified as HTM securities.9. It can be argued that in its information role, fair value accounting should not increase systemic risk around the

adoption of SFAS No. 115 because banks were already required to disclose the fair value of all financial instru-ments under SFAS No. 107. However, research suggests that recognition versus disclosure of accounting informa-tion impacts the decision-usefulness of information (e.g., Barth et al. 2003; Hirshleifer and Teoh 2003; Ahmedet al. 2006). Ahmed et al. (2006) show that valuation coefficients on recognized fair values of derivatives are signif-icant, while those on disclosed fair values of derivatives are not.

10. Net unrealized losses on equity securities with readily available fair values classified as AFS continued to beincluded in regulatory capital.



Research has examined bank-level economic consequences of SFAS No. 115, finding thatbanks and insurance companies experienced negative stock returns around standard-setting eventsrelated to SFAS No. 115 (Beatty et al. 1996; Cornett et al. 1996; Khan et al. 2018). Other studiesfind that banks were concerned about the potential volatility in equity induced by SFAS No. 115.Beatty (1995) reports that banks decreased the proportion and maturity of investment securities inthe quarter in which SFAS No. 115 was adopted. Hodder et al. (2002) show that banks classifiedtoo few securities as AFS and altered the size of their investment securities portfolios along withtheir interest rate risk and credit risk. Iselin et al. (2017) document that low-capital banks traded offinvestments in high-volatility assets for those in low-volatility assets. Godwin et al. (1998) showthat property-liability insurers made liquidity and volatility risk trade-offs when classifying invest-ment securities under SFAS No. 115. However, unrealized gains and losses on AFS securities,unlike those in the banking sector, were never included in regulatory capital for insurance firms(Hodder et al. 2002).

My study complements these studies by examining economy-wide consequences of SFASNo. 115 and expands the scope of investigation beyond bank level outcomes. Moreover, it is nota foregone conclusion that SFAS No. 115 contributed to systemic risk due to increased equityand regulatory capital volatility. Barth et al. (1995) conclude that the additional equity volatilityinduced by SFAS No. 115 is unlikely to be important to investors and regulators. Similarly,Carey (1995) concludes that the net effects of SFAS No. 115 are likely to be small. It is thereforean empirical question whether SFAS No. 115 impacted the systemic risk of the banking industry.Finally, considering the removal of the prudential AOCI filter for the advanced approaches banksfollowing the adoption of Basel III recommendations, this study makes an important and timelycontribution by examining the systemic risk consequences of including unrealized gains andlosses on AFS securities in regulatory capital.11

3. Research design and measurement of variables

Testing the relation between fair value accounting and systemic risk

An ideal setting to examine fair value accounting’s relation with systemic risk would be one in whichI could compare the systemic risk of the banking sector in an economy in which the banks are notsubject to fair value accounting to that in an otherwise identical economy in which banks are subjectto fair value accounting. Because such an experimental setting does not exist, I take advantage of aquasi-exogenous accounting and regulatory change presented by SFAS No. 115, which required theinclusion of unrealized gains and losses on securities classified as AFS in banks’ GAAP equity andin regulatory capital. I also exploit the subsequent November 1994 regulatory amendment excludingunrealized gains and losses on AFS securities from regulatory capital to examine the differentialimpact of fair value accounting on systemic risk through its information role versus its regulatoryrole.12 I estimate the following OLS regression for the period 1993:Q2 to 1995:Q1:

11. Basel III recommendations included the removal of the prudential AOCI filter for all banks. However, the FinalRules adopted by the U.S. regulators only require advanced approaches banks to include unrealized gains and losseson AFS securities in regulatory capital. The Final Rules permit a one-time permanent election by non-advanced-approaches banks to opt out of the provisions removing the AOCI filter.

12. The removal of the prudential AOCI filter following the adoption of the Basel III recommendations presents analternate setting in which to examine the relation between systemic risk and the inclusion of unrealized gains andlosses on AFS securities in regulatory capital. In this setting, however—unlike the SFAS No. 115 setting—multipleimportant regulatory policy changes occurred simultaneously with the removal of the prudential AOCI filter, mak-ing it hard to credibly identify the impact of using fair value estimates in regulatory capital on systemic risk. More-over, the SFAS No. 115 setting, unlike the Basel III setting, allows me to investigate the systemic risk effects ofexcluding unrealized gains and losses on AFS securities from regulatory capital following the November 1994amendment.



ΔCoVaRsystemjiq, t = β0 + β1FV_Regt + β2FV_NoRegt +Controls+Bank fixed effects + εt, ð1Þ

where ΔCoVaRsystemjiq, t is a quarterly estimate of the systemic risk of the banking sector (Adrian

and Brunnermeier 2016). The estimation of ΔCoVaR is described in detail in section MeasuringSystemic Risk. SFAS No. 115 was effective for fiscal years beginning after December 15, 1993.Banks whose fiscal years ended in December could adopt the new standard as of December 1993or for the fiscal year beginning January 1994. FV_Reg is an indicator variable that equals oneduring the period in which unrealized gains and losses on AFS securities are included in the cal-culation of regulatory capital (i.e., from 1993:Q4 to 1994:Q3), and zero otherwise.13 FV_NoRegis an indicator variable that equals one during the period 1994:Q4 to 1995:Q1 (i.e., the post-SFASNo. 115 period), and zero otherwise. Thus, the coefficient on FV_Reg, β1, captures the incremen-tal change in systemic risk during the period when unrealized AFS security gains and lossesexplicitly impact GAAP equity and regulatory capital, relative to the pre-SFAS No. 115 period.The coefficient on FV_NoReg, β2, represents the incremental change in systemic risk during thepost-SFAS No. 115 period—when unrealized AFS security gains and losses are included in GAAPequity but not in the computation of regulatory capital—relative to the pre-SFAS No. 115 period.Furthermore, a comparison of β1 and β2 demonstrates the impact of including versus excludingunrealized gains and losses on AFS securities in regulatory capital on systemic risk in the post-SFAS No. 115 period.

I include several variables to control for variation in banks’ asset holdings and businessmodels as well as for macroeconomic conditions. C&I Loans, RE Loans, and Other Loans are theratios of commercial and industrial loans, real estate loans, and all other loans, respectively, tototal assets. These variables control for the differences in the composition of banks’ loan portfo-lios. Loan Growth is the growth in total loans during the quarter. Mismatch is the differencebetween total liabilities and cash scaled by total liabilities; it controls for differences in banks’funding risk associated with debt. Core Deposits, defined as the total of core deposits scaled bytotal assets, also controls for the funding structure of banks. Revenue Mix is the noninterestincome scaled by the sum of interest and noninterest income and controls for the extent of banks’nonlending activities. Size is the natural log of total assets.

In response to SFAS No. 115, banks altered the asset allocation as well as the maturity oftheir investment securities along with their credit and interest rate risks. Furthermore, their reac-tions depended on their level of capital (e.g., Beatty 1995; Hodder et al. 2002; Iselin et al. 2017).So, I control for the maturity and composition of investment securities as well as for banks’ creditrisk, interest rate risk, and capital. USSecs is the proportion of investment securities comprisingTreasuries and other debt securities issued or guaranteed by the U.S. government or its agencies.SecsMat is the bank’s maturity-weighted investment portfolio scaled by total investment securi-ties. CRSecs is the weighted average of regulatory credit risk categories for investment securitiesscaled by total investment securities. CRLoans is the weighted average of regulatory credit riskcategories for loans scaled by total loans. IntSecs is the interest and dividend income on securitiesscaled by total investment securities. Capital is the ratio of equity to total assets.

I also include market-based measures of bank risk, liquidity, and performance as controls.MTB is the market-to-book ratio. As equity risk measures, I include (i) the bank’s market betafrom a single-factor traditional capital asset pricing model, estimated using daily returns over thequarter (Beta), and (ii) the quarterly SD of daily equity returns (ST Dev). Illiquid is the naturallog of the average, over the quarter, of the daily absolute value of the bank’s stock returns scaled

13. Beatty (1995) and Hodder et al. (2002) note that a significant number of banks adopted SFAS No. 115 early in 1993:Q4. Hence, I include 1993:Q4 in the FV_Reg period. As a robustness check, in section SFAS No. 115 and SystemicRisk, I (i) exclude 1993:Q4 from my sample period and (ii) include 1993:Q4 in the pre-SFAS No. 115 period.



by the trading volume for the day in dollars. Return is the market-adjusted cumulative equityreturn over the quarter.

Interest rates had decreased to historic lows during 1993. In 1994, the Federal Reserve Bankincreased the rate seven times, gradually increasing the prime rate from 3.2 to 6.7 percent(Hodder et al. 2002). This decreased the value of the U.S. bonds by more than $600 billion; sev-eral financial institutions suffered heavy losses (Ehrbar 1994).14 I explicitly control for the risinginterest rates and the evolving macroeconomic conditions using T-Bill Rate, the quarterly averageof the daily three-month Treasury bill rate, and CSpread, the difference between Moody’s sea-soned Baa and Aaa corporate bond yields (which accounts for changes in the price of risk).Time-varying bank-specific control variables account for the impact of changing interest rates andmacroeconomic conditions on an individual bank’s contribution to systemic risk. I include bankfixed effects to control for time-invariant bank characteristics. All control variables are measuredwith a lag of one quarter. The Appendix defines all variables.

Measuring systemic risk

Systemic risk is the risk that the capacity of the entire financial system will be impaired; it can bemeasured as the increase in tail risk codependences that arise due to the spreading of financial dis-tress across institutions (Adrian and Brunnermeier 2016). Currently, the literature lacks consensuson the best way to measure systemic risk (e.g., Hansen 2014). A growing stream of literature usesequity prices of banks to estimate systemic risk (e.g., Gray et al. 2008; Acharya et al. 2010; Grayand Jobst 2010; Adrian and Brunnermeier 2016), the advantage being that equity prices are avail-able with a high frequency and reflect the market’s expectation about bank risk from a wide rangeof underlying channels, including direct contractual and counterparty exposures and indirect spill-overs related to price effects and liquidity spirals. Following Adrian and Brunnermeier (2016), Iuse a reduced-form measure of systemic risk, ΔCoVaR, that uses bank equity losses to capturethe cross-sectional tail dependency between the whole financial system and an individual bank.15

CoVaR for an individual bank is defined as the value-at-risk (VaR) of the whole financial sys-tem conditional on the state of the individual bank. VaR is the maximum potential loss of an insti-tution over a defined period for a given confidence interval. If the VaR of a bank measured interms of equity return loss is 10 percent at a one-week, 99 percent confidence level, then the like-lihood that the bank’s equity return loss will be greater than 10 percent in any given week is 1 per-cent. ΔCoVaR is the difference between an individual bank’s CoVaR conditional on the bankbeing in distress and its CoVaR conditional on being in the median state. Intuitively, ΔCoVaRestimates a bank’s marginal contribution to the tail risk of the financial system as a whole as thatbank moves from its normal state to a state of distress. Formally, ΔCoVaR is defined as

ΔCoVaRsystemjiq, t =CoVaR

systemjXi =VaRiq

q, t −CoVaRsystemjXi =VaRi

50q, t , ð2Þ

where ΔCoVaRsystemjiq is the change in CoVaR for the whole financial sector, system, at time

t conditional on an individual bank, i, experiencing an event C(Xi). C(Xi) is institution i’s equityreturn loss, Xi, being at or above its VaR at the q-percent-confidence level (i.e., VaRi

qÞ, which, bydefinition, occurs with a likelihood of (1− q) percent.

Empirically, the following quantile regressions are estimated using weekly data toestimate ΔCoVaRsystemji

q :

14. The losses suffered by banks in 1994 due to investments in bonds suggest that there should be an increase in sys-temic risk over the year. In contrast, I predict that systemic risk decreased following the November 1994 regulatorycapital amendment (Hypothesis 2).

15. See section I of Adrian and Brunnermeier (2016) for a detailed discussion of related papers and other measures ofsystemic risk.



Xit = α

iq + γ

iqMt−1 + ε

iq, t, ð3aÞ

Xsystemjit = αsystemjiq + γsystemjiq Mt−1 + β

systemjiq Xi

t + εsystemjiq, t , ð3bÞ

where Xit is bank i’s equity return losses in week t. Mt−1 is a vector of lagged macroeconomic

state variables that capture the variation in the conditional moments of returns. These macroeco-nomic variables include:

i. change in the yield of the three-month Treasury bill,ii. change in the slope of the yield curve measured by the spread between the composite

long-term bond yield and the three-month Treasury bill rate,iii. the TED spread calculated as the difference between the three-month LIBOR rate and

the three-month secondary market Treasury bill rate,16

iv. change in the credit spread between Baa-rated bonds and the 10-year Treasury rate,v. the weekly return of the S&P500,vi. the weekly real estate sector return in excess of the market financial sector return, andvii. the 22-day rolling SD of the daily CRSP equity market return.

Next, predicted values are obtained from those regressions to estimate

VaRiq, t = α̂

iq + γ̂

iqMt−1, ð4aÞ

CoVaRsystemjiq, t = α̂systemjiq + γ̂systemjiq Mt−1 + β̂

systemjiq VaRi

q, t: ð4bÞ

In the final step, a bank’s contribution to the systemic risk of the financial sector when mov-ing from a normal (i.e., median) state to a distressed state is calculated as

ΔCoVaRsystemjiq, t =CoVaRsystemji

q, t −CoVaRsystemji50, t : ð5Þ

These regressions provide weekly estimates of ΔCoVaRsystemjiq : The quarterly estimates of

ΔCoVaRsystemjiq are the average of the weekly ΔCoVaRsystemji

q in a quarter and are expressed as per-

cent equity return losses. More positive values of ΔCoVaRsystemjiq indicate that as an individual

bank moves from its median state to a distressed state, its marginal contribution to the financialsystem’s systemic risk has increased. In the reported analysis, I consider the 99 percent quantileof equity return losses, which occur with the likelihood of 1 percent, as the distressed state forindividual banks. Note that Adrian and Brunnermeier (2016), by conditioning on a quantile ratherthan on a certain level of returns, ensure that the likelihood of the conditioning event C(Xi) isindependent of the individual bank’s asset holdings or business model.

4. Data and descriptive statistics

My sample comprises the U.S. BHCs that file regulatory consolidated financial statements (FR Y-9C reports) and have the requisite accounting information available for the period 1993:Q2 to1995:Q1. Quarterly observations are required to have positive total assets and total loans andnon-missing values for shareholder’s equity and income before extraordinary items. Finally, sam-ple banks must have stock price data in CRSP. The final sample consists of 2,216 bank-quarterobservations from 305 unique BHCs.

16. The TED spread is a proxy for short-term liquidity risk.



Table 1 reports the sample’s descriptive statistics. The mean (median) ΔCoVaRsystemjiq, t is

1 (0.90) percent. With respect to the composition of the loan portfolio, real estate loans make up,on average, the highest proportion at 35 percent of total assets. The mean loan growth is about3 percent each quarter. The average bank is relatively well capitalized, the mean ratio of totalequity to total assets being approximately 8.5 percent. In the post-SFAS No. 115 period, the mean(median) holdings of AFS securities are 11 (10) percent of total assets. Banks classify similaramounts of investment securities as HTM: the mean (median) holdings of HTM securities are12 (10) percent of total assets. In contrast, banks hold minimal quantities of trading securities: themean holdings of trading securities are less than 1 percent of total assets, with the median bankholding no trading securities. The mean of the three-month Treasury bill rate during my sampleperiod is 3.97 percent. Both the mean and the median spreads between Moody’s seasoned Baaand Aaa corporate bond yields are 68 basis points.

Figure 1 plots the quarterly mean ΔCoVaRsystemjiq, t over my sample period. Around the adoption

of SFAS No. 115, ΔCoVaRsystemjiq, t increases from 0.98 percent at the end of 1993:Q4 to 1.11 per-

cent by the end of 1994:Q1. It then decreases around the November 1994 regulatory capitalamendment, from 1.05 percent at the end of 1994:Q3 to 0.95 percent by the end of 1994:Q4.Figure 1 provides preliminary evidence that SFAS No. 115 is associated with an increase in thesystemic risk of the banking sector. Further, there was a decrease in the systemic risk followingthe November 1994 amendment.

TABLE 1Descriptive statistics

Variable N Mean Median 5th percentile 95th percentile SD

ΔCoVaRsystemjiq, t 2,216 1.0002 0.8975 0.0908 2.3383 0.6860

C&I Loans 2,216 0.1198 0.1069 0.0208 0.2641 0.0736RE Loans 2,216 0.3469 0.3404 0.1166 0.5895 0.1364Other Loans 2,216 0.1321 0.1318 0.0154 0.2675 0.0775Mismatch 2,216 0.9420 0.9475 0.8926 0.9759 0.0294Core Deposits 2,216 0.7238 0.7534 0.4507 0.8677 0.1300Revenue Mix 2,216 0.1614 0.1426 0.0550 0.3506 0.0931Capital 2,216 8.4575 8.2427 6.0661 11.6789 1.7280Size 2,216 14.5679 14.2822 12.3993 17.7721 1.7015USSecs 2,216 0.8890 0.9341 0.5921 0.9953 0.1313SecsMat 2,216 4.2306 4.2519 1.7156 6.7818 1.5545CRSecs 2,216 0.1831 0.1750 0.0384 0.3591 0.0952CRLoans 2,216 0.8449 0.8571 0.6770 0.9637 0.0868IntSecs 2,216 0.0144 0.0144 0.0108 0.0178 0.0022MTB 2,216 1.4051 1.3783 0.7599 2.2253 0.4372Illiquid 2,216 −1.7780 −0.8956 −7.0930 2.0197 3.0296Loan Growth 2,216 0.0327 0.0247 −0.0348 0.1375 0.0567Return 2,216 0.0042 −0.0042 −0.1590 0.1915 0.1084ST Dev 2,216 0.0226 0.0191 0.0101 0.0454 0.0125Beta 2,216 0.5051 0.4862 −0.7153 1.7660 0.7567Trading 2,216 0.0083 0 0 0.0456 0.0316AFS 1,692 0.1100 0.0972 0 0.3107 0.0937HTM 1,692 0.1157 0.1036 0 0.3046 0.1055T-Bill Rate 8 3.9727 3.6277 2.9676 5.7353 1.0942CSpread 8 0.0068 0.0068 0.0060 0.0073 0.0005

Notes: This table reports the descriptive statistics of the sample. All variables are defined in the Appendix.



5. Results

SFAS No. 115 and systemic risk

I begin by investigating the impact that the inclusion of unrealized gains and losses on AFS securities inGAAP equity and in regulatory capital under SFASNo. 115 had on systemic risk. The results of estimatingequation (1) are reported in panel A of Table 2. Consistent with Hypothesis 1, the coefficient on FV_Reg,β1, is positive and significant (coefficient = 0.0735, p ≤ 0.01).17 This suggests that following SFASNo. 115, the systemic risk of the banking sector increases. The coefficient onFV_NoReg, β2, is positive butinsignificant (coefficient = 0.0007, p = 0.97), suggesting that the systemic risk in the period during whichunrealized gains and losses on AFS securities are included in GAAP equity but not in regulatory capital isindistinguishable from the pre-SFAS No. 115 period, during which unrealized gains and losses on AFSsecurities were not included in GAAP equity or regulatory capital. Consistent with Hypothesis 2, the coeffi-cient β1 is significantly greater than β2 (p ≤ 0.01), suggesting that systemic risk decreased following the reg-ulatory amendment that excludes unrealized AFS security gains and losses from regulatory capital. Takentogether, I find evidence that the regulatory role of fair value accounting contributes to systemic risk, but Ido not find any evidence that fair value accounting increases systemic risk in its information role.

With respect to control variables, real estate loans, size, and capital are positively associatedwith a bank’s marginal contribution to systemic risk,18 while commercial and industrial loans,core deposits, holdings of investment securities guaranteed by the U.S. government or its agen-cies, loan growth, and the market beta are negatively associated. Systemic risk is heightenedwhen the spread between Moody’s seasoned Baa and Aaa corporate bond yields is wider.19

Figure 1 Systemic risk during the sample period

0.85

0.9

0.95

1

1.05

1.1

1.15

6/30/93 9/30/93 12/31/93 3/31/94 6/30/94 9/30/94 12/31/94 3/31/95

Δ

Notes: This figure plots the mean ΔCoVaRsystemjiq, t of my sample for each quarter over the period 1993:Q2 to

1995:Q1.

17. In the reported analyses, the standard errors are not clustered by bank. However, the inferences are not sensitive tosuch clustering.

18. Because riskier banks are required by regulators to maintain larger equity cushions, it is not surprising that capitalis positively associated with a bank’s marginal systemic risk contribution.

19. In September 1994, the Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994 (IBBEA) was enacted,removing several obstacles to banks opening branches across state lines. The IBBEA had a significant impact on bankcompetition, individual bank risk, and the overall risk of the banking industry (Bushman et al. 2016) and could be a con-founding event in my analyses. However, although the IBBEA was passed in 1994, its provisions first came into effectin September 1995, after my sample period. To further rule out the effect of geographical diversification or consolida-tion, in general, as a confounding influence in my tests, I reestimate equation (1) after removing from the sample banksthat began operations in a new state or shut operations in a given state during my sample period. I use the Summary ofDeposits data to identify changes in banks’ branch network (e.g., Khan and Ozel 2016). My inferences are unchanged.



TABLE 2SFAS No. 115 and systemic risk

Panel A: SFAS No. 115 and systemic risk

Variables Coefficient Prediction Estimate p-value

FV_Regt β1 (+) 0.0735 < 0.01***FV_NoRegt β2 (+/−) 0.0007 0.97C&I Loanst−1 −0.5154 0.05**RE Loanst−1 0.2832 0.07*Other Loanst−1 −0.0654 0.76Mismatcht−1 −0.2957 0.21Core Depositst−1 −0.2565 0.05**Revenue Mixt−1 0.0200 0.86Capitalt−1 0.0109 0.04**Sizet−1 0.0852 0.01***USSecst−1 −0.0842 0.04**SecsMatt−1 −0.0023 0.66CRSecst−1 −0.0639 0.43CRLoanst−1 0.1649 0.17IntSecst−1 −0.6903 0.66MTBt−1 −0.0103 0.54Illiquidt−1 0.0051 0.36Loan Growtht−1 −0.1987 < 0.01***Returnt−1 0.0315 0.25ST Devt−1 −0.7052 0.20Betat−1 −0.0124 < 0.01***T-Bill Ratet−1 0.0169 0.14CSpreadt−1 55.0174 0.02**Bank fixed effects YesN 2,216Adjusted R2 0.97F-tests

FV_Regt − FV_NoRegt 0.0728 < 0.01***

Panel B: SFAS No. 115 and systemic risk with alternative specifications of FV_Reg

Column 1 Column 2

Variables Coefficient Prediction Estimate p-value Estimate p-value

FV_Regt β1 (+) 0.1463 < 0.01*** 0.1873 < 0.01***FV_NoRegt β2 (+/−) −0.0080 0.56 0.0009 0.97C&I Loanst−1 −0.4335 0.09* −0.3442 0.19RE Loanst−1 0.2926 0.06* 0.3361 0.04**Other Loanst−1 −0.1284 0.55 −0.1829 0.42Mismatcht−1 −0.0591 0.79 0.0750 0.76Core Depositst−1 −0.2229 0.08* −0.2451 0.07*Revenue Mixt−1 0.0558 0.60 0.0888 0.46Capitalt−1 0.0171 < 0.01*** 0.0161 0.01***Sizet−1 0.1066 < 0.01*** 0.1124 < 0.01***USSecst−1 −0.0628 0.11 −0.0661 0.11SecsMatt−1 −0.0044 0.39 −0.0032 0.55CRSecst−1 −0.0404 0.61 −0.0486 0.58

(The table is continued on the next page.)



Beatty (1995) and Hodder et al. (2002) report that 44 and 37 percent of the banks in theirsamples, respectively, adopted SFAS No. 115 early in 1993:Q4. Therefore, in my main analysis,FV_Reg equals one for 1993:Q4. However, I conduct two additional tests to assess whether theevidence presented in panel A of Table 2 is sensitive to classifying 1993:Q4 as a part of theperiod during which the new rules under SFAS No. 115 are effective. First, I redefine FV_Reg toequal 1 during the period 1994:Q1 to 1994:Q3 and 0 otherwise; that is, I include 1993:Q4 in thepre-SFAS No. 115 period. Second, I exclude 1993:Q4 from my sample; that is, 1993:Q4 isincluded in neither the pre-SFAS No. 115 nor the post-SFAS No. 115 period.

The results of estimating equation (1) using these alternative definitions of FV_Reg are pres-ented in panel B of Table 2. In column (1), FV_Reg is redefined as one during 1994:Q1 to 1994:Q3and zero otherwise. Its coefficient, β1, remains positive and significant (coefficient = 0.1463,p-value ≤ 0.01), while that on FV_NoReg, β2, is insignificant (coefficient = −0.0080, p = 0.56). Incolumn (2), I estimate equation (1) using a sample that excludes 1993:Q4. The coefficient onFV_Reg, β1, is positive and significant (coefficient = 0.1873, p ≤ 0.01), while that on FV_NoReg,β2, is, again, insignificant (coefficient = 0.0009, p = 0.95). In both columns (1) and (2), β1 is sig-nificantly greater than β2 (p ≤ 0.01 and < 0.01, respectively). Thus, the inferences are unchanged.

Overall, the evidence in Table 2 suggests that systemic risk increased when unrealized gainsand losses on AFS securities are included in GAAP equity and in regulatory capital. Followingthe exclusion of unrealized gains and losses from regulatory capital, which reduced banks’ regula-tory risk, systemic risk decreased. Moreover, the systemic risk in the pre-SFAS No. 115 period,when unrealized gains and losses on AFS securities are not included in GAAP equity or in

TABLE 2 (continued)

Panel B: SFAS No. 115 and systemic risk with alternative specifications of FV_Reg

Column 1 Column 2

Variables Coefficient Prediction Estimate p-value Estimate p-value

CRLoanst−1 0.0904 0.46 0.0738 0.58IntSecst−1 −0.3310 0.83 0.5892 0.74MTBt−1 0.0045 0.79 0.0144 0.42Illiquidt−1 0.0063 0.25 0.0087 0.13Loan Growtht−1 −0.1255 0.02** −0.1657 0.01***Returnt−1 −0.0374 0.15 −0.0015 0.96ST Devt−1 −0.7622 0.15 −0.5160 0.31Betat−1 −0.0085 0.03** −0.0081 0.05**T-Bill Ratet−1 −0.0208 0.06* −0.0021 0.86CSpreadt−1 106.8195 < 0.01*** 181.2551 < 0.01***Bank fixed effects Yes YesN 2,216 1,943Adjusted R2 0.97 0.97F-tests

FV_Regt − FV_NoRegt 0.1543 < 0.01*** 0.1864 < 0.01***

Notes: This table reports the results of estimating equation (1), which investigates the relation between fairvalue accounting and systemic risk by examining the change in systemic risk around the adoption of SFAS

No. 115. The sample period is 1993:Q2–1995:Q1. The dependent variable is ΔCoVaRsystemjiq, t . All variables

are defined in the Appendix. In panel A, FV_Reg equals one for the period 1993:Q4–1994:Q3 and zerootherwise. Panel B uses alternative specifications of FV_Reg. In column (1) of panel B, FV_Reg equals onefor the period 1994:Q1 to 1994:Q3 and zero otherwise. In column (2) of panel B, 1993:Q4 is excluded fromthe sample period. *, **, and *** represent significance at the 10, 5, and 1 percent levels, respectively, usinga one-tailed t-test if a directional prediction is made, two-tailed otherwise.



regulatory capital, is statistically indistinguishable from that in the period following the November1994 regulatory amendment, when unrealized gains and losses on AFS securities are included inGAAP equity but not in regulatory capital. Thus, it appears that fair value accounting can contrib-ute to systemic risk in its regulatory role, but I do not find any evidence of fair value accountingincreasing systemic risk in its information role.20

Cross-sectional tests

Having established that fair value accounting can contribute to systemic risk through its regula-tory role, I conduct cross-sectional tests to examine the influence of certain bank characteristicson a bank’s marginal contribution to systemic risk.

Fair value volatility of investment securities

SFAS No. 115 increased banks’ regulatory risk because including unrealized gains and losses onAFS securities increased the volatility of regulatory capital, which, in turn, increased the uncertaintyabout future regulatory compliance. I expect banks with greater fair value volatility of investmentsecurities to experience a larger increase in regulatory risk and hence to make a larger contributionto systemic risk. Furthermore, following the November 1994 regulatory amendment, banks’ regula-tory risk decreased. I therefore expect the relation between fair value volatility of investment securi-ties and a bank’s contribution to systemic risk to be attenuated after November 1994.

I estimate the fair value volatility of a bank’s investment securities portfolio as the SD of theratio of the quarterly fair value of investment securities to the securities’ amortized cost, measuredover the prior eight quarters (e.g., Iselin et al. 2017).21 To investigate the impact of investmentsecurities’ fair value volatility, I modify equation (1) thus:

ΔCoVaRsystemjiq, t = β0 + β1FVVolt−1 + β2FV_Regt + β3FV_Regt ×FVVolt−1

+ β4FV_NoRegt + β5FV_NoRegt ×FVVolt−1

+Controls +Bank fixed effects + εt, ð6Þ

where FVVol equals one if the fair value volatility of a bank’s investment securities portfolio is abovethe 75th percentile in a given quarter, and zero otherwise. All other variables are as defined before.

The results of estimating equation (6) are presented in Table 3. While all control variables inequation (1) are included in equation (6), for the sake of brevity, I only report the estimated coeffi-cients of the main variables of interest. The coefficient on FVVol, β1, is insignificant (coefficient =−0.0189, p = 0.15), suggesting that before SFAS No. 115, the fair value volatility of investmentsecurities is not significantly associated with a bank’s marginal contribution to systemic risk. The posi-tive and significant coefficient on FV_Reg, β2, (coefficient = 0.0714, p ≤ 0.01) implies that following

20. On September 1, 1998, bank regulators amended regulatory capital standards to include up to 45 percent of netunrealized gains on equity securities classified as AFS in supplementary capital (i.e., Tier 2 capital). In untabulatedanalyses, I find that this amendment is not associated with a significant change in the banking sector’s systemic risk.One reason is that banks hold relatively small quantities of equity securities classified as AFS. As of September30, 1998, the median (mean) holdings of AFS equity securities as a percentage of total assets is 0.86 (1.19) percentfor my sample. Another reason is that limited unrealized gains on AFS equity securities are included only in supple-mentary capital. The calculation of primary capital continues to exclude net unrealized gains on AFS securities.

21. I resort to estimating the fair value volatility of a bank’s entire investment securities portfolio rather than only ofinvestment securities classified as AFS because the data on banks’ classification of investment securities as HTMand AFS do not become available until March 31, 1994. Because the fair value volatility is computed using datafrom the prior eight quarters, I am unable to estimate the fair value volatility using the data on AFS securities exclu-sively. However, in an untabulated robustness check, I construct an alternate measure of the fair value volatility ofthe investment securities portfolio using fair value and amortized cost of the entire investment securities portfoliofor the period prior to 1994:Q1 and the fair value and amortized cost of investment securities classified as AFS forthe period 1994:Q1 onwards. My inferences are unchanged.



the adoption of SFAS No. 115, the marginal contribution to systemic risk increases for banks whoseinvestment securities have relatively low fair value volatility. Importantly, the marginal contribution tosystemic risk of high fair value volatility banks is significantly greater than that of the other banks fol-lowing the adoption of SFAS No. 115, as suggested by the positive and significant coefficient on theinteraction term FV_Reg × FVVol, β3 (coefficient = 0.0252, p = 0.04). After the November 1994 regu-latory capital amendment, the marginal contribution to systemic risk of high- and low-volatility banksdecreases; β4 is significantly smaller than β2 (p ≤ 0.01), and the sum of β4 and β5 is significantly smallerthan that of β2 and β3 (p ≤ 0.01). Also, the high-volatility banks’ marginal contribution to systemic riskis not significantly different from that of the other banks after November 1994. The coefficient on theinteraction term FV_NoReg × FVVol, β5, is insignificant (coefficient = 0.0217, p = 0.25).

Level of capital

Following the enactment of FDICIA, prompt corrective action mandated bank regulators to intervene ifcapital levels approach or fall below statutory minimum thresholds. SFAS No. 115 increased future uncer-tainty about banks’ compliance with regulatory capital requirements by including volatile unrealized gainsand losses on AFS securities in capital. However, banks with more capital should experience a smallerincrease in regulatory risk upon the adoption of SFAS No. 115, as they have bigger equity cushions toabsorb the additional volatility and, thus, are less likely to violate regulatory capital thresholds. The increasein the marginal systemic risk contribution of relatively well-capitalized banks following the adoption ofSFAS No. 115 should therefore be smaller than that of the other banks. To test this conjecture, I modifyequation (1) thus:

ΔCoVaRsystemjiq, t = β0 + β1HiCapt−1 + β2FV_Regt + β3FV_Regt ×HiCapt−1 + β4FV_NoRegt

+ β5FV_NoRegt ×HiCapt−1 +Controls +Bank fixed effects + εt, ð7Þ

where HiCap equals one if a bank’s Capital is above the 75th percentile relative to other banks ineach total assets tercile in a given quarter, and zero otherwise. Thus, HiCap reflects a bank’s capital

TABLE 3Fair value volatility of investment securities and systemic risk


FVVolt−1 β1 (+/−) −0.0189 0.15FV_Regt β2 (+) 0.0714 < 0.01***FV_Regt × FVVolt−1 β3 (+) 0.0252 0.04**FV_NoRegt β4 (+/−) −0.0006 0.97FV_NoRegt × FVVolt−1 β5 (+/−) 0.0217 0.25Controls YesBank fixed effects YesN 2,180Adjusted R2 0.97F-tests

FV_Regt − FV_NoRegt 0.0720 < 0.01***(FV_Regt + FV_Regt × FVVolt−1)

− (FV_NoRegt + FV_NoRegt × FVVolt−1) 0.0755 < 0.01***

Notes: This table reports the results of estimating equation (6), which investigates the influence of the fairvalue volatility of investment securities on the relation between fair value accounting and a bank’s marginalcontribution to systemic risk. The sample period is 1993:Q2–1995:Q1. The dependent variable is

ΔCoVaRsystemjiq, t . All variables are defined in the Appendix. ** and *** represent significance at the 5 and

1 percent levels, respectively, using a one-tailed t-test if a directional prediction is made, two-tailed otherwise.



strength relative to banks of similar size rather than the absolute level of capital (e.g., Hodder et al.2002). Hodder et al. (2002) note another advantage of using a relative rather than absolute measureof capital: Around the adoption of SFAS No. 115, few banks are below the regulatory minimumthreshold. Nonetheless, regulatory scrutiny and the risk of costly regulatory intervention increasesas banks approach minimum thresholds. All other variables are as defined before.

Table 4 reports the results of estimating equation (7). In the pre-SFAS No. 115 period, thereis no significant difference between the marginal contribution to systemic risk of high-capitalbanks and that of the other banks. The coefficient on HiCap, β1, is insignificant (coefficient =−0.0019, p = 0.90). Following the adoption of SFAS No. 115, banks with relatively low capitalexperience a significant increase in their marginal contribution to systemic risk, as suggested bythe positive and significant coefficient on FV_Reg, β2 (coefficient = 0.0799, p ≤ 0.01). Consistentwith relatively higher capital levels attenuating a bank’s marginal systemic risk contribution, thecoefficient on the interaction term FV_Reg × HiCap, β2, is negative and significant (coefficient =−0.0230, p = 0.03). Following the exclusion of unrealized gains and losses on AFS securitiesfrom regulatory capital, the marginal systemic risk contribution of both high-capital banks andother banks decreases; β2 is significantly greater than β4 (p-value ≤ 0.01), and the sum of β2 andβ3 is greater than that of β4 and β5 (p = < 0.01).

Investment securities classification

SFAS No. 115 required banks to classify their investment securities as HTM, AFS, or tradingsecurities. The composition of trading securities differs significantly from that of HTM and AFSand, typically, only the largest banks hold economically relevant quantities of trading securities.22

TABLE 4Level of bank capital and systemic risk


HiCapt−1 β1 (+/−) −0.0019 0.90FV_Regt β2 (+) 0.0799 < 0.01***FV_Regt × HiCapt−1 β3 (−) −0.0230 0.03**FV_NoRegt β4 (+/−) 0.0082 0.64FV_NoRegt × HiCapt−1 β5 (+/−) −0.0355 0.02**Controls YesBank fixed effects YesN 2,216Adjusted R2 0.97F-tests

FV_Regt − FV_NoRegt 0.0716 < 0.01***(FV_Regt + FV_Regt × HiCapt−1)

− (FV_NoRegt + FV_NoRegt × HiCapt−1) 0.0842 < 0.01***

Notes: This table reports the results of estimating equation (7), which investigates the influence of the levelof bank capital on the relation between fair value accounting and a bank’s marginal contribution to systemic

risk. The sample period is 1993:Q2–1995:Q1. The dependent variable is ΔCoVaRsystemjiq, t . All variables are

defined in the Appendix. ** and *** represent significance at the 5 and 1 percent levels, respectively, usinga one-tailed t-test if a directional prediction is made, two-tailed otherwise.

22. For my sample, the mean (median) of trading securities scaled by total assets is 0.83 (0.00) percent. Also, SFASNo. 115 did not alter the accounting treatment of trading securities significantly (Beatty 1995). In untabulated ana-lyses, I find that trading securities are, on average, not associated with a bank’s marginal systemic risk contribution,arguably due to the relatively small amounts of trading securities held by banks.



On the other hand, AFS and HTM security portfolios consist of largely similar proportions ofmortgage-backed securities, asset-backed securities, municipal bonds, and Treasuries. Furthermore,the unrealized gains and losses on AFS and HTM securities are impacted similarly over time (Xie2016). However, the treatment of unrealized gains and losses on AFS and HTM securities differs sig-nificantly under SFAS No. 115. Unrealized gains and losses on AFS securities are included in GAAPequity and in regulatory capital (only until the November 1994 regulatory amendment), whereas thoseon HTM securities are not. Although unrealized gains and losses on HTM securities are not includedin regulatory capital, HTM securities contribute to the regulatory risk of banks because other-than-temporary impairments of HTM securities reduce regulatory capital. Thus, following the adoption ofSFAS No. 115, investment securities classified as AFS will increase regulatory risk to a larger extentthan those classified as HTM. I therefore conjecture that the association between banks’ AFS securityholdings and their marginal contribution to systemic risk should be greater than the associationbetween their HTM security holdings and their marginal contribution to systemic risk.

In addition, the November 1994 regulatory capital amendment should attenuate the relationbetween AFS security holdings and a bank’s contribution to systemic risk, but have no effect on therelation between HTM securities and a bank’s marginal contribution to systemic risk, becauseunrealized gains and losses on HTM securities were already excluded from regulatory capital. Finally,given the comparable composition of HTM and AFS securities, I expect no difference in the relationbetween the holdings of these securities and a bank’s marginal contribution to systemic risk after theNovember 1994 amendment, as unrealized gains and losses on both HTM and AFS securities areexcluded from regulatory capital. I test these conjectures by estimating the following equation:

ΔCoVaRsystemjiq, t = β0 + β1AFSt−1 + β2HTMt−1 + β3FV_NoRegt

+ β4FV_NoRegt ×AFSt−1 + β5FV_NoRegt ×HTMt−1

+Controls +Bank fixed effects + εt, ð8Þ

where AFS and HTM are the book value of investment securities classified as AFS and HTM,respectively, scaled by total assets. Unlike the sample period for the prior tests, the sample periodfor this test begins in 1994:Q1, when details of banks’ investment security classifications becomeavailable. β1 and β2 capture the relationship between a bank’s investment securities classified asAFS and HTM, respectively, and its marginal contribution to systemic risk during the period inwhich unrealized gains and losses on AFS securities are included in GAAP equity and in regulatorycapital but those on HTM securities are excluded. β4 and β5 reflect the incremental change in theserelationships following the November 1994 amendment. All other variables are defined as before.

Table 5 reports the results of estimating equation (8). The coefficient on AFS, β1,(coefficient = 0.4871, p ≤ 0.01) and the coefficient on HTM, β2, (coefficient = 0.2598, p ≤ 0.01) are posi-tive and significant, suggesting that investment securities classified as AFS and as HTM are positivelyrelated to a bank’s marginal contribution to systemic risk. Importantly, β1 is significantly greater thanβ2 (p ≤ 0.01), consistent with the conjecture that classifying investment securities as AFS increases abank’s marginal contribution to systemic risk to a larger extent than classifying securities as HTM does.

The association between investment securities classified as AFS and a bank’s marginal contribu-tion to systemic risk decreases significantly when regulatory capital calculations are changed to excludeunrealized gains and losses on AFS securities. The coefficient on the interaction term FV_NoReg × AFS,β4, is negative and significant (coefficient = −0.2382, p = 0.01). In contrast, the relation betweeninvestment securities classified as HTM and a bank’s marginal contribution to systemic risk isunchanged; the coefficient on FV_NoReg × HTM, β5, is insignificant (coefficient = 0.0477,p = 0.54). Finally, after November 1994, the relation between investment securities classified as AFSand a bank’s marginal contribution to systemic risk is not significantly different from that betweeninvestment securities classified as HTM and a bank’s marginal contribution to systemic risk. The dif-ference between the sum of β1 and β4 and the sum of β2 and β5 is insignificant (p = 0.70).



6. Conclusion

I investigate the relation between fair value accounting and the systemic risk of the U.S. banking indus-try. I focus on SFAS No. 115, which increased the use of fair value accounting in financial reportingand in the regulatory assessment of bank capital adequacy by requiring AFS securities to be recognizedat fair value. I find that, relative to the pre-SFAS No. 115 period, the adoption of SFAS No. 115 is asso-ciated with increased systemic risk in the banking sector. Furthermore, a subsequent amendment inNovember 1994 to the calculation of regulatory capital that excludes the use of unrealized gains andlosses on AFS securities in the assessment of banks’ capital adequacy is associated with decreased sys-temic risk. This amendment did not impact the accounting treatment of AFS securities under GAAP.The systemic risk in the post-November 1994 regulatory amendment period does not differ significantlyfrom that in the pre-SFAS No. 115 period, suggesting that fair value accounting contributes to systemicrisk only through its regulatory role. I do not find any evidence that fair value accounting can exacerbatesystemic risk through its information role. I also show that a bank’s marginal contribution to systemicrisk is positively associated with the fair value volatility of investment securities and the amount ofinvestment securities classified as AFS, and is negatively associated with bank capital.

My findings should interest policymakers, regulators, and academics. Following Basel III rec-ommendations, the U.S. bank regulators have removed the prudential AOCI filter for advancedapproaches banks (FDIC 2013). My study suggests that the inclusion of unrealized gains and losseson AFS securities could exacerbate systemic risk in the banking industry. I also contribute to the lit-eratures on the relation between financial reporting and systemic risk (e.g., Bushman and Williams2015; Bushman et al. 2016) and on the economic consequences of SFAS No. 115 (e.g., Beatty1995; Hodder et al. 2002; Iselin et al. 2017).

In conclusion, I would like to add a caveat that accounting and regulatory changes are rarelytruly exogenous. They are often an outcome of deliberations and lobbying. I have designed myempirical tests carefully to account for potential confounding influences and factors. However,assessing economic consequences of accounting and regulatory changes is inherently difficult.Hence, I advise some caution in interpreting the evidence presented.

TABLE 5Investment securities classification and systemic risk


AFSt−1 β1 (+) 0.4871 < 0.01***HTMt−1 β2 (+) 0.2598 < 0.01***FV_NoRegt β3 (−) −0.0470 0.02**FV_NoRegt × AFSt−1 β4 (−) −0.2382 0.01***FV_NoRegt × HTMt−1 β5 (+/−) 0.0477 0.54Controls YesBank fixed effects YesN 1,492Adjusted R2 0.97F-tests

AFSt−1 − HTMt−1 0.2274 < 0.01***(AFSt−1 + FV_NoRegt × AFSt−1) − (HTMt−1 + FV_NoRegt × HTMt−1) −0.0585 0.70

Notes: This table reports the results of estimating equation (8), which investigates the influence of theclassification of investment securities as HTM or AFS under SFAS No. 115 on the association between fairvalue accounting and a bank’s marginal contribution to systemic risk. The sample period is 1994:Q1–1995:

Q1. The dependent variable is ΔCoVaRsystemjiq, t . All variables are defined in the Appendix. ** and ***

represent significance at the 5 and 1 percent levels, respectively, using a one-tailed t-test if a directionalprediction is made, two-tailed otherwise.



Appendix

Definitions of variables

ΔCoVaRsystemjiq, t Estimate of systemic risk of the financial system (Adrian and Brunnermeier 2016). It

represents a bank’s marginal contribution to the tail risk of the financial system as thebank moves from its normal state to a state of distress. See section Measuring SystemicRisk for details

AFS Ratio of fair value of available-for-sale securities to total assetsBeta Market beta from a single-factor traditional CAPM model estimated using daily returns

over the quarterC&I Loans Ratio of commercial and industrial loans to total assetsCapital Ratio of total equity to total assetsCore Deposits Ratio of core deposits to total assetsCRLoans Weighted average of regulatory credit risk categories for loans scaled by total loansCRSecs Weighted average of regulatory credit risk categories for investment securities scaled by

total investment securitiesCSpread Difference between Moody’s seasoned Baa and Aaa corporate bond yieldsFV_Reg An indicator variable that equals one during the period in which unrealized fair value gains

and losses on AFS securities are included in regulatory capital and GAAP equity(i.e., from 1993:Q4 to 1994:Q3), and zero otherwise

FV_NoReg An indicator variable that equals one during the period in which unrealized fair value gainsand losses on AFS securities are excluded from regulatory capital but included in GAAPequity (i.e., from 1994:Q4 to 1995:Q1), and zero otherwise

FVVol An indicator variable that equals one if the fair value volatility of a bank’s investmentsecurities portfolio is above the 75th percentile in a given quarter, and zero otherwise.The fair value volatility is the SD of the ratio of quarterly fair value of investmentsecurities to their amortized cost measured over the prior eight quarters

HiCap An indicator variable that equals one if Capital is above the 75th percentile relative toother banks in each total assets tercile in a given quarter, and zero otherwise

HTM Ratio of amortized cost of held-to-maturity securities scaled by total assetsIlliquid Natural log of the average, over the quarter, of the daily absolute value of the bank’s stock

return scaled by the trading volume for the dayIntSecs Ratio of interest and dividend income on securities to total investment securitiesLoan Growth Growth in total loans during the quarterMismatch Ratio of the difference between total liabilities and cash to total assetsMTB Market-to-book ratioOther Loans Ratio of all loans other than real estate loans and commercial and industrial loans to total assetsRE Loans Ratio of real estate loans to total assetsReturn Market-adjusted cumulative equity return over the quarterRevenue Mix Ratio of noninterest income to the sum of interest and noninterest incomeSecsMat Maturity-weighted investment portfolio scaled by total investment securitiesSize Natural log of total assetsST Dev Standard deviation of daily equity returns over the quarterT-Bill Rate Quarterly average of the daily three-month Treasury bill rateTrading Ratio of fair value of trading securities to total assetsUSSecs Ratio of investment securities comprising Treasuries and other debt securities issued or

guaranteed by the U.S. government or its agencies to total investment securities

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