Skip to main content
SpringerLink
Log in

Systemic interest rate and market risk at US banks

  • Original Paper
  • Published:
Journal of Business Economics Aims and scope Submit manuscript

Abstract

This paper is the first to quantify and analyze the dynamics of market risk (MR) and interest rate risk (IRR) of the system of US bank holding companies (BHCs) based on time-varying risk exposures estimated using the Kalman filter. These dynamics can be ex-plained to a considerable degree by the development of the macro economy as well as by the state and structure of the banking system itself. We further determine each single bank’s contribution to the banking system’s MR and IRR and show that single banks have non-trivial leverage over the banking system’s systematic risk exposure at specific times. Such risk contributions can be explained by banks’ financing or deposit base, maturity transformation intensity and interest income, earnings diversification and the liquidity of banks’ holdings. Our findings thus facilitate better oversight and management of the systematic risks inherent in the banking system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. We use the expressions “BHC” and “bank” interchangeably. When referring to banking subsidiaries of BHCs, we use the term “commercial bank”.

  2. We follow, e.g., Kashyap et al. (2002), acknowledging the same biases in these variables (like double counting of inter-subsidiary business or the omission of non-bank activities).

  3. We follow the standard approach to screening the Thomson/Reuters Datastream return data introduced by Ince and Porter (2006).

  4. See Micro Report Series Description, http://www.federalreserve.gov/reportforms/mdrm/pdf/BHCF.PDF “Beginning March 31, 2006, the FR Y-9C and the FR Y-9LP filing threshold was increased from $150 million to $500 million or more and the reporting exception that required each lower-tier bank holding company with total consolidated assets of $1 billion or more to file the FR Y-9C was eliminated.”.

  5. Under this definition of the interest rate factor negative IRR betas indicate a negative bank portfolio stock return for increases in interest rates.

  6. The first 355 states estimated on return data available before the sample period are used to allow for enough time for the diffuse initialization but are dropped from further analyses also due to the constrained availability of macro and banking variables.

  7. As each month’s last weekly beta is later matched to end-of-month macro variables, we already present results and base the following arguments on each month’s last weekly betas to conserve space. As expected from a measure without unit like a regression coefficient, distributions of betas at the weekly frequency are highly similar and this approach does not change conclusions drawn in this section. Descriptive statistics of IRR betas at the weekly frequency can be obtained from the authors on request.

  8. Variables 1–19 describe output with production in different sectors, variables 20–44 employment and working hours, variables 45–54 contain information on the stock of orders, 55–64 housing including prices and starts of construction, 65–87 describe the financial environment including stock market, interest rates and spreads and exchange rates, 88–94 describe the monetary policy with monetary bases and reserve requirements, and 95–119 describe prices for producers and consumers. For detailed definitions of the numbered macroeconomic variables (most of them on a seasonally-adjusted basis) and of the transformations applied to ensure stationarity, see Appendix 1.

  9. Visual inspection of the scree plot leads to the decision for the cutoff at nine factors, as additional factors add substantially less marginal explanatory power to the factor structure.

  10. We use lagged rather than contemporary independent variables to control for endogeneity and reverse causality of the relations.

  11. See, e.g., Marcus (1984) or Dewatripont and Tirole (1994) for analyses of the behavior of banks that have lost the basis for successful continuation of their business models.

  12. According to the procedure for monthly aggregation described in Footnote 7 in Sect. 3.2 thereby following Brunnermeier et al. (2012).

  13. Multicollinearity is not an issue here, as shown by variance inflation factors (VIF): mean VIF of the variables is 1.45 with NPL exhibiting the highest value of 2.03.

References

  • Bessler W, Kurmann P (2014) Bank risk factors and changing risk exposures: capital market evidence before and during the financial crisis. J Financ Stab 13:151–166

    Article  Google Scholar 

  • Brunnermeier MK, Oehmke M (2013) The maturity rat race. J Financ 68(2):483–521

    Article  Google Scholar 

  • Brunnermeier MK, Dong G, Palia D (2012) Banks’ non-interest income and systemic risk. Working Paper. Princeton University, Columbia University, Rutgers Business School. http://ssrn.com/abstract_id=1786738. Accessed 21 July 2016

  • Choudhry T, Wu H (2008) Forecasting ability of GARCH vs Kalman filter method: evidence from daily UK time-varying beta. J Forecast 27(8):670–689

    Article  Google Scholar 

  • Czaja M-C, Scholz H, Wilkens (2009) Interest rate risk of German financial institutions: the impact of level, slope, and curvature of the term structure. Rev Quant Financ Acc 33(1):1–26

    Article  Google Scholar 

  • Demsetz RS, Strahan PE (1997) Diversification, size, and risk at bank holding companies. J Money Credit Bank 29(3):300–313

    Article  Google Scholar 

  • Dewatripont M, Tirole J (1994) The prudential regulation of banks. MIT Press, Cambridge

    Google Scholar 

  • Diamond DW, Dybvig PH (1983) Bank runs, deposit insurance, and liquidity. J Polit Econ 91(3):401–419

    Article  Google Scholar 

  • Elliott G, Müller UK (2006) Effcient tests for general persistent time variation in regression coefficients. Rev Econ Stud 73(4):907–940

    Article  Google Scholar 

  • English WB, Van den Heuvel SJ, Zakrajsek E (2012) Interest rate risk and bank equity valuations. FEDS Working Paper 2012–26. http://www.federalreserve.gov/pubs/feds/2012/201226/201226pap.pdf. Accessed 21 July 2016

  • Entrop O, von la Hausse L, Wilkens M (2016) Looking beyond banks’ average interest rate risk: Determinants of high exposures. Q Rev Econ Financ. doi:10.1016/j.qref.2016.04.008

    Google Scholar 

  • Farhi E, Tirole J (2012) Collective moral hazard, maturity mismatch, and systemic nailouts. Am Econ Rev 102(1):60–93

    Article  Google Scholar 

  • Flannery MJ, James CM (1984) The effect of interest rate changes on the common stock returns of financial institutions. J Financ 39(4):1141–1153

    Article  Google Scholar 

  • Froot KA, Stein JC (1998) Risk management, capital budgeting, and capital structure policy for financial institutions: an integrated approach. J Financ Econ 47(1):55–82

    Article  Google Scholar 

  • Gorton G, Metrick A (2012) Securitized banking and the run on repo. J Financ Econ 104(3):425–451

    Article  Google Scholar 

  • Gropp R, Kok C, Lichtenberger JD (2007) The dynamics of bank spreads and financial structure. Q J Financ 4(4):1450014.1–1450014.53

    Google Scholar 

  • Gurkaynak RS, Sack B, Wright JH (2007) The US treasury yield curve, 1961 to the present. J Monet Econ 54(8):2291–2304

    Article  Google Scholar 

  • Hanson SG, Shleifer A, Stein JC, Vishny RW (2015) Banks as patient fixed income investors. J Financ Econ 117:449–469

    Article  Google Scholar 

  • Hellwig M (1994) Liquidity provision, banking, and the allocation of interest rate risk. Eur Econ Rev 38(7):1363–1389

    Article  Google Scholar 

  • Hellwig M (1998) Financial institutions in transition: banks, markets, and the allocation of risks in an economy. J Inst Theor Econ 154(1):328–345

    Google Scholar 

  • Hirtle B (1997) Derivatives, portfolio composition, and bank holding company interest rate risk exposure. J Financ Serv Res 12(2–3):243–266

    Article  Google Scholar 

  • Hoerdahl P, King, MR (2008) Developments in Repo Markets During the Financial Turmoil. BIS Quarterly Review 12/2008. http://www.bis.org/publ/qtrpdf/r_qt0812e.pdf. Accessed 21 July 2016

  • Hovakimian A, Kane EJ, Laeven L (2012) Variation in systemic risk at US banks during 1974–2010. NBER Working Paper 18043. http://www.nber.org/papers/w18043. Accessed 21 July 2016

  • Ince OS, Porter RB (2006) Individual equity return data from Thomson Datastream: handle with care. J Financ Res 29(4):463–479

    Article  Google Scholar 

  • Jagannathan R, Wang Z (1996) The conditional CAPM and the cross-section of ex-pected returns. J Financ 51(1):3–53

    Article  Google Scholar 

  • Kaiser HF (1958) The varimax criterion for analytic rotation in factor analysis. Psychometrika 23:187–200

    Article  Google Scholar 

  • Kane EJ, Unal H (1988) Change in market assessments of deposit-institution riskiness. J Financ Serv Res 1(3):207–229

    Article  Google Scholar 

  • Kane EJ, Unal H (1990) Modeling structural and temporal variation in the market’s valuation of banking firms. J Financ 45(1):113–136

    Article  Google Scholar 

  • Kashyap AK, Rajan R, Stein JC (2002) Banks as liquidity providers: an explanation for the coexistence of lending and deposit-taking. J Financ 57(1):33–73

    Article  Google Scholar 

  • Kaufman GG (1984) Measuring and managing interest rate risk: a primer. Econ Perspect 8(1):16–29

    Google Scholar 

  • Laeven L, Levine R (2007) Is there a diversification discount in financial conglomerates? J Financ Econ 85:331–367

    Article  Google Scholar 

  • Litterman R, Scheinkman J (1991) Common Factors Affecting Bond Returns. J Fixed Income 1(1):54–61

    Article  Google Scholar 

  • Ludvigson SC, Ng S (2009) Macro factors in bond risk premia. Rev Financ Stud 22(12):5027–5067

    Article  Google Scholar 

  • Mamaysky H, Spiegel M, Zhang H (2008) Estimating the dynamics of mutual fund alphas and betas. Rev Financ Stud 21(1):233–264

    Article  Google Scholar 

  • Marcus AJ (1984) Deregulation and bank financial policy. J Bank Financ 8(4):557–565

    Article  Google Scholar 

  • Mergner S, Bulla J (2008) Time-varying beta risk of Pan-European industry portfolios: a comparison of alternative modeling techniques. Eur J Financ 14(8):771–802

    Article  Google Scholar 

  • Merton RC (1977) An analytic derivation of the cost of deposit insurance and loan guarantees an application of modern option pricing theory. J Bank Financ 1(1):3–11

    Article  Google Scholar 

  • Nelson CR, Siegel AF (1987) Parsimonious modeling of yield curves. J Bus 60(4):473–489

    Article  Google Scholar 

  • Patton AJ, Verardo M (2012) Does beta move with news? Firm-specific information flows and learning about profitability. Rev Financ Stud 25(9):2789–2839

    Article  Google Scholar 

  • Schrand C, Unal H (1998) Hedging and coordinated risk management: evidence from thrift conversions. J Financ 53(3):979–1013

    Article  Google Scholar 

  • Staikouras SK (2006) Financial intermediaries and interest rate risk: II. Financ Mark Inst Instrum 15(5):225–272

    Article  Google Scholar 

  • Stock JH, Watson MW (2002) Macroeconomic forecasting using diffusion indexes. J Bus Econ Stat 20(2):147–162

    Article  Google Scholar 

  • Stone BK (1974) Systematic interest-rate risk in a two-index model of returns. J Financ Quant Anal 9(5):709–721

    Article  Google Scholar 

  • Toevs AL (1983) Gap Management: Managing interest rate risk in banks and thrifts. In: Federal Reserve Bank of San Francisco (ed.): Economic Review 9(1):20–35

  • Whited TM, Wu G (2006) Financial constraints risk. Rev Financ Stud 19(2):531–559

    Article  Google Scholar 

  • Zagonov M (2011) Securitization and bank intermediation function. Working Paper. Toulouse Business School. http://ssrn.com/abstract_id=1663061. Accessed 21 July 2016

Download references

Author information

Authors and Affiliations

  1. Chair of Finance and Banking, University of Augsburg, Universitätsstr. 16, 86159, Augsburg, Germany

    Ludwig von la Hausse, Martin Rohleder & Marco Wilkens

Authors
  1. Ludwig von la Hausse
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Martin Rohleder
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marco Wilkens
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ludwig von la Hausse.

Additional information

We thank Oliver Entrop and two anonymous reviewers for very helpful comments and suggestions to improving the paper. All remaining errors are our own.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 4647 kb)

Appendices

Appendix 1

See Table 7.

Table 7 List of macroeconomic variables
Full size table

Appendix 2

See Table 8.

Table 8 Variable definitions
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

von la Hausse, L., Rohleder, M. & Wilkens, M. Systemic interest rate and market risk at US banks. J Bus Econ 86, 933–961 (2016). https://doi.org/10.1007/s11573-016-0830-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11573-016-0830-8

Keywords

JEL Classification

Search

Navigation