Abstract
We test whether organizational risk management matters to bondholders of U.S. bank holding companies (BHCs), and find that debt financing costs increase when the BHC has lower-quality risk management. Consistent with bailouts giving rise to moral hazard among bank creditors, we find that bondholders put less emphasis on risk management in large institutions for which bailouts are expected ex-ante. BHCs that maintained strong risk management before the financial crisis had lower debt costs during and after the crisis, compared to other banks. Overall, quality risk management can curtail risk exposures at BHCs and result in lower debt costs.
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Notes
We use the terms “non-deposit debt financing,” “debt financing,” and “bond financing” interchangeably throughout the paper.
In a theoretical model, Gennaioli, Shleifer, and Vishny (2012) show that investors may neglect certain highly unlikely risks, and as a result, financial intermediaries cater to their beliefs and engineer securities that investors perceive as safe but actually are exposed to such neglected risks. An example of this narrative is the securitization of mortgages during the 2000s, where investors, financial institutions, and rating agencies believed that these securities were safe. They justified their beliefs by relying on historically low default rates on mortgages in the U.S. and continuously rising home prices. Jarrow, Li, Mesler, and van Deventer (2007) and Coval, Jurek, and Stafford (2009) also support this view, showing that before the financial crisis, rating agencies and investors did not consider the sensitivities of structured products such as CDOs to home prices.
The risk management index (RMI) we use is a hand-collected measure based on 10-Ks and proxy statements from BHCs in the United States. We thank Professors Ellul and Yerramilli for sharing their risk management index data with us. We also extend this dataset based on their methodology. See data section for details.
We thank the editor for suggesting these tests.
We thank the editor for suggesting these tests.
The experience of the global financial crisis of 2007–2009, during which bondholders of many distressed institutions were able to avoid losses thanks to government bailouts, lends credence to the bondholder moral hazard argument. Acharya et al. (2016) also find that secondary bond yield spreads of large financial institutions are lower compared with other similar financial institutions even after controlling for their risk exposures. They attribute this phenomenon to bondholder moral hazard due to expectations of implicit state guarantees for large institutions.
CRO Present is an indicator variable that identifies whether a CRO (or an equivalent officer) is present within the BHC; CRO Executive is an indicator variable that identifies whether the CRO is an executive officer of the BHC; CRO Top5 is an indicator variable that identifies whether the CRO is among the five highest-paid executives at the BHC; and CRO Centrality is the ratio of the CRO’s total compensation, excluding stock and option awards, to the CEO’s total compensation.
Risk Committee Experience is an indicator variable that identifies whether at least one of the independent directors on the board’s risk committee has banking and finance experience; Active Risk Committee is an indicator variable that identifies whether the BHC’s board risk committee meets more frequently during the year compared to the average board risk committee across all BHCs.
Our hand-collected data consist of BHCs with total assets ranging from $1.0 billion at the 1st percentile to $1.9 trillion at the 99th percentile, including a higher percentage of smaller BHCs than the data in Ellul and Yerramilli (2013).
Note that we also calculate the weighted average of bond control variables when there is more than a single issue per BHC-year.
Data availability on TRACE drives our selection of 2005 as the starting point of the sample period.
The procedure removes retail-size noninstitutional trades (i.e., those below $100,000); dirty prices that include dealer commissions; trades with missing execution time or date; trades with missing trade size; genuine duplicates; trade reversals along with the original trade that is being reversed; trades with missing or negative yields; and same-day trade corrections and cancellations.
In unreported tests, we create interaction terms between the two governance variables and RMI (PCT_INST*RMI and DUAL*RMI, respectively) and add them to the main regression. Although PCT_INST*RMI is not statistically significant, DUAL*RMI is negative and statistically significant at the 5% level. This is consistent with the notion that bond investors are concerned with powerful CEOs who could make risk-shifting choices. Better risk management can therefore help alleviate such agency problems and is rewarded by bond investors.
In further tests, we control for the potential effect of banks being regulated by different agencies, such as the FED, FDIC, and OCC. The untabulated results are qualitatively similar to those reported in Table 3 and available upon request.
As a result, our instrument only measures the average change in RMI from 1998 to 2000 for all other BHCs in a given BHC’s size decile in 1998, and it is not specific to any particular BHC.
With one exogenous instrument, the first-stage F-statistic must exceed 8.96 for the 2SLS inference to be reliable (see Table I in Stock et al. 2002). Our F-statistic values are all higher than 8.96, despite the fact that we have a small sample and we cluster standard errors at the BHC level.
We thank the referee for making this suggestion.
Note that CRISISt is equal to 1 for an observation that occurs in one of the eight quarters during Q1:2007-Q4:2008, and 0 otherwise. Consequentially, for CRISISt = 1, RMIt-1, represents the value of RMI in one of the eight quarters during Q4:2006-Q3:2008, and SPREADt + 1 is measured in one of the quarters during Q2:2007-Q1:2009. For example, if the current time period t is the first quarter of 2007, CRISISt = 1, RMIt-1 is measured one quarter before the onset of the crisis (fourth quarter of 2006), and SPREADt + 1 is measured during the second quarter of 2007. If the current time period t is Q4:2008, CRISISt = 1, RMIt-1 is measured within the crisis time period (Q3:2008), and SPREADt + 1 is measured one quarter after the end of the crisis (Q1:2009). If the current time period t is Q1:2011, CRISISt = 0, RMIt-1 is measured during Q4:2010, and SPREADt + 1 is measured during Q2:2011.
Our results remain qualitatively similar when TARP is coded as 1 for the first quarter of 2009 for the aforementioned bank which received TARP in January 2009.
We thank the editor for suggesting a test that examines the impact of risk management on the bond yield spreads of bailed out banks, conditional on bondholder expectations of a government bailout.
Note that RMI is measured annually whereas TARP is observed in the fourth quarter of 2008. From a coding standpoint, all quarters in a given year receive the same end of year RMI value. Therefore, in columns (5)-(7), when TARP = 1, RMI will receive its 2008 value, the same year TARP was given. In columns (8)-(10), since TARP is observed during t-1 and RMI is observed during t, RMI values will be observed in 2009 when TARP = 1 (recall that TARP is coded as 1 for Q4 of 2008), which is the following year after the year TARP was given.
References
Acharya VV, Anginer D, Warburton AJ (2016) The end of market discipline? Investor expectations of implicit government guarantees. NYU Working Paper
Acharya VV, Pederson LH, MP (2009) Restoring financial stability: How to repair a failed system. Chapter Regulating systemic risk. Wiley, Hoboken, NJ, pp 283–303
Amihud Y (2002) Illiquidity and stock returns: Cross-section and time series effects. J Fin Markets 5:31–56
Anginer D, Demirguc-Kunt A, Huizinga H, Ma K (2013) How does corporate governance affect bank capitalization strategies? Policy Research WPS 6636, World Bank
Asquith P, Wizman TA (1990) Event risk, covenants, and bondholder returns in leveraged buyouts. J Financ Econ 27:195–214
Beltratti A, Stulz R (2009) Why did some banks perform better during the credit crisis: a cross-country study of the impact of governance and regulation. ECGI Working Paper Series in Finance, Working Paper 254/2009, pp 1–38. https://doi.org/10.3386/w15180
Berg T (2015) Playing the devil’s advocate: The causal effect of risk management on loan quality. Rev Financ Stud 28(12):3367–3406
Bhattacharya S, Boot AWA, Thakor AV (1998) The economics of bank regulation. J Money, Credit, Bank 30:745–770
Black LK, Hazelwood LN (2013) The effect of TARP on bank risk-taking. J Financ Stab 9:790–803
Blume ME, Lim F, Mackinlay AC (1998) The declining credit quality of U.S. corporate debt: Myth or reality? J Finance 53(4):1389–1413
Bradley M, Roberts MR (2015) The structure and pricing of corporate debt covenants. Q J Finance 5:1–37
Campbell JY, Taksler GB (2003) Equity volatility and corporate bond yields. J Finance 58:2321–2350
Cargill TF (1989) CAMEL ratings and the CD market. J Financ Serv Res 3:347–358
Chava S, Ganduri R, Yerramilli V (2021) Do bond investors price tail risk exposures of financial institutions? Q J Financ 11(1):1–43
Coval JD, Jurek JW, Stafford E (2009) The economics of structured finance. J Econ Perspect 23(1):3–26
Cremers M, Nair V, Wei C (2007) Governance mechanisms and bond prices. Rev Financ Stud 20:1359–1388
Demirguc-Kunt A, Detragiache E (2002) Does deposit insurance increase banking system stability? An empirical investigation. J Monet Econ 49:1373–1406
Demsetz RS, Saidenberg MR, Strahan PE (1997) Agency problems and risk-taking at banks, Working paper, Banking Studies Department, Federal Reserve Bank of New York
Demsetz RS, Strahan PE (1997) Diversification, size, and risk at U.S. bank holding companies. J Money, Credit, Bank 29:300–313
Dick-Nielsen J (2009) Liquidity biases in TRACE. The Journal of Fixed Income 19(2):43
Dick-Nielsen J, Feldhutter P, Lando D (2012) Corporate bond liquidity before and after the onset of the subprime crisis. J Financ Econ 103:471–492
Ellis DM, Flannery MJ (1992) Does the debt market assess large banks’ risk? J Monet Econ 30:481–502
Ellul A (2015) The role of risk management in corporate governance. Annu Rev Financ Econ 7:279–299
Ellul A, Yerramilli V (2013) Stronger risk controls, lower risk: Evidence from U.S. bank holding companies. J Finance 68(5):1757–1803
Erkens DH, Hung M, Matos P (2012) Corporate governance in the 2007–2008 financial crisis: evidence from financial institutions worldwide. J Corp Finane 18:389–411
Fahlenbrach R, Prilmeier R, Stulz RM (2012) This time is the same: Using bank performance in 1998 to explain bank performance during the recent financial crisis. J Finance 67:2139–2185
Gennaioli N, Shleifer A, Vishny R (2012) Neglected risks, financial innovation, and financial fragility. J Financ Econ 104:452–468
Han S, Zhou X (2016) Informed bond trading, corporate yield spreads, and corporate default prediction. Manage Sci 60:675–694
Hannan T, Hanweck G (1988) Bank insolvency risk and the market for large certificates of deposit. J Money, Credit, Bank 20:203–211
Hellmann TF, Murdock KC, Stiglitz JE (2000) Liberalization, moral hazard in banking, and prudential regulation: Are capital requirements enough? Am Econ Rev 90:147–165
Hoenig TM (2008) Maintaining stability in a changing financial system: Some lessons relearned again? Econ Rev, Federal Reserve Bank of Kansas City, issue Q I: 5-16
Holderness CG, Kroszner RS, Sheehan DP (1999) Were the good old days that good? Changes in managerial stock ownership since the Great Depression. J Finance 54:435–469
Jagtiani J, Kaufman G, Lemieux C (2002) The effect of credit risk on bank and bank holding company bond yields: Evidence from the post- FDICIA period. J Financ Res 25(4):559–575
Jarrow R, Li L, Mesler M, van Deventer D (2007) CDO valuation: Fact and fiction. The definitive guide to CDOs, Risk Publications
Jensen MC, Meckling WH (1976) Theory of the firm: managerial behavior, agency costs and ownership structure. J Financ Econ 3:305–360
Kashyap AK, Rajan R, Stein J (2002) Banks as liquidity providers: An explanation for the coexistence of lending and deposit-taking. J Finance 57:33–74
Kaufman GG (1997) The new depositor preference act: Time inconsistency in action. Manag Financ 23:56–63
Keeley MC (1990) Deposit insurance, risk, and market power in banking. Am Econ Rev 80(5):1183–1200
Laeven L, Levine R (2009) Bank governance, regulation and risk-taking. J Financ Econ 93:259–275
Minton BA, Taillard J, Williamson RG (2011) Do independence and financial expertise of the board matter for risk taking and performance? Fisher College of Business Working Paper No. 2010–03–014
Nelson C, Siegel AF (1987) Parsimonious modeling of yield curves. J Bus 60:473–489
Penas M, Unal H (2004) Gains in bank mergers: Evidence from the bond markets. J Financ Econ 74:149–179
Staiger D, Stock JH (1997) Instrumental variables regression with weak instruments. Econometrica 65:557–586
Stock JH, Wright JH, Yogo M (2002) A survey of weak instruments and weak identification in generalized method of moments. J Bus Econ Stat 20:518–529
Strahan PE (2013) Too big to fail: Causes, consequences, and policy responses. Annu Rev Financ Econ 5(1):43–61
Stulz R (2008) Risk management failures: What are they and when do they happen? J Appl Corp Financ 29:39–48
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Appendix: Variable definitions
Appendix: Variable definitions
RMI and primary market issues
SPREAD | Weighted average yield spread of bonds issued in a given year (in percentage points) |
RMI | Risk management index as in Ellul and Yerramilli (2013) |
SIZE | Natural logarithm of the book value of total assets |
SIZE2 | SIZE squared |
ROA | Net income before discontinued operations divided by total assets |
MAT | Weighted average maturity of bonds issued in a given year |
PROCEEDS | Natural log of weighted average proceeds of bonds issued in a given year |
COV | 1 if bonds are issued with at least one debt covenant, and 0 otherwise |
DEFAULT | Default risk as measured by default rates (in percentage points) based on weighted average S&P ratings of bonds issued in a given year |
SENIOR | 1 for senior bond issuance, and 0 otherwise |
CALL | 1 for callable bond, and 0 otherwise |
PCT_INST | Percentage of outstanding shares held by 13-F institutional investors |
DUAL | 1 if the CEO is also the chairman of the board, and 0 otherwise |
TIER1 | Tier-1 capital ratio |
NONINT | Total noninterest income divided by net operating income |
LOAN | Total loans divided by total assets |
DEPOSIT | Total deposits divided by total assets |
VOL | Total risk, calculated as the standard deviation of daily stock returns |
ES | Total tail risk, calculated as the negative of the average return on the BHC’s stock during the 5% worst return days |
MES | Systematic tail risk, calculated as the negative of the average return on the BHC’s stock during the 5% worst return days for the market (S&P 500) |
ESIDIO | Idiosyncratic tail risk, calculated as the sum of the residual and constant estimated by BHC specific regressions of ES on MES |
NPLOAN | Total loans that are 90 days or more past due divided by total assets |
Q | Tobin’s q, measured as the sum of the market value of equity and the book value of liabilities divided by the book value of total assets |
Additional variables from secondary market transactions
SPREAD | Quarterly yield spread in a given year (in percentage points) |
INT_COV_D1 | The IRC ratio if it is less than 5, and 5 if IRC is above 5, where the IRC ratio is operating income after depreciation divided by interest expenses |
INT_COV_D2 | 0 if the IRC ratio is below 5, IRC minus 5 if IRC is between 5 and 10, and 5 if IRC is above 10, where the IRC ratio is operating income after depreciation divided by interest expenses |
INT_COV_D3 | 0 if the IRC ratio is below 10, IRC minus 10 if IRC is between 10 and 20, and 10 if IRC is above 20, where the IRC ratio is operating income after depreciation divided by interest expenses |
INT_COV_D4 | 0 if the IRC ratio is below 20, IRC minus 20 if IRC is between 20 and 80, and 80 if IRC is above 100, where the IRC ratio is operating income after depreciation divided by interest expenses |
TTM | Average time to maturity for bonds traded in the quarter of a given year (in quarters) |
AGE | Average age of bonds traded in the quarter of a given year (in quarters) |
COUPON_RATE | Average coupon rate of the bonds traded in the quarter of a given year |
ILLIQUID | Average illiquidity of bonds traded in the quarter as in Amihud (2002) in a given year |
CRISIS | 1 if the current quarter is during one of the eight quarters of 2007–2008, and 0 otherwise |
TARP | 1 for the fourth quarter of 2008 if a BHC received TARP funds, 0 otherwise |
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Hasan, I., Peng, E., Waisman, M. et al. The effect of bank organizational risk-management on the pricing of non-deposit debt. J Financ Serv Res (2024). https://doi.org/10.1007/s10693-024-00425-x
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DOI: https://doi.org/10.1007/s10693-024-00425-x