Abstract
We use a vector autoregressive approach to investigate the determinants of US Dollar LIBOR and Euribor swap spread variation during the 2007–2009 crisis in global credit and money markets. Using market-quoted yield and spread data from the highly liquid credit default swap (CDS) and overnight index swap (OIS) markets, we provide compelling empirical evidence that liquidity risk factor shocks have been the dominant drivers of the variation in swap spreads over this period. Our findings provide an explanation for the temporal differences that liquidity shocks have on swap spreads and provide a contemporary perspective on the dynamical interplay between credit-default and liquidity risk-factors in these markets. As all our risk-factor proxies are traded in liquid derivatives markets, our findings have implications for proprietary hedge fund traders hedging an exposure to swap-spread risk, for bank treasurers managing their liquidity requirements and for central bankers seeking to better understand the response of markets to their macroeconomic policy implementation and liquidity management actions. Indeed our markets-based analysis suggests that the European Central Bank (ECB) has underperformed relative to the Federal Reserve in terms of the differing levels of market confidence placed in its macroeconomic policy actions and remedial liquidity interventions during the period.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
Source: Securities Industry and Financial Markets Association (SIFMA).
Hereafter, D&S97.
For ease of reference, the same notation as that proposed by D&S97 is used here.
Hereafter, H&N03.
For ease of reference, the same notation as that proposed by H&N03 is used here.
In a spot-starting ‘vanilla’ fixed for floating interest rate swap, the floating rate reference is typically the prevailing 3 or 6-month London Inter-Bank Offer Rate (LIBOR)—i.e. the published “fixing rate” typically published by an agency such as the British Bankers Association.
This is a measure of the premium a bank would be willing to pay for a LIBOR-referenced term deposit over a rolling overnight funding strategy for the term of the loan. A widening of the OIS spread, reflecting a willingness to pay a higher premium, is seen as a “ceteris-paribus” indication of an anticipated deterioration in interbank liquidity conditions going forward.
Hedging a multi-variate exposure can be quite robust when the standard market model is used in conjunction with a markets-acquired mix of intuition and common sense. It has been shown (Bakshi et al. 1997) that a daily re-calibrated Black–Scholes model is quite a robust tool for delta-hedging equity options even when the underlying market dynamics are driven by a stochastic volatility, jump-diffusion process.
The H&N03 rationalization of a contracting LIBOR swap spread in response to a positive shock from their particular choice of a “term structure slope factor” proxy for liquidity risk is in fact sound. Under the latter scenario, the typically negative-signed principal component factor loadings associated with short-dated yields would indeed be consistent with a positive steepening of the slope of the (defaultable) yield curve, manifesting in falling short-term rates. Generating a positive “tilt” in the forward (LIBOR) curve, such a downward steepening will indeed drive “equilibrium” swap rates (weighted averages of forward LIBOR rates) down, at least for short-dated maturities.
Such a scenario would be ceteris-paribus consistent with a positive shock from the “slope factor” and (given the typically negative factor loadings) a downward movement— but upwards tilt—in the term structure at the short end. This might typically be seen as a signal for expected near-term cuts in short-term interest rates, and hence of lower spot funding costs in the overnight market in particular.
See www.markit.com.
A VAR analysis is predicated on variable stationarity. An adjusted Dickey–Fuller test was conducted on all the VAR4 variables and found all t-test statistics less than -10 at the 5% level. This demonstrates strong stationarity for all variables.
Intuitively since a simple AR(1) specification will explain most of the “self-driven” variation in a mean-reverting or conjectured AR(p) time-series, it is to be expected that only a very few lags anyway will explain well the variation in a conjectured AR(p) time-series. All these spread variables are known to be strongly mean-reverting stochastic processes, so p = 1 or 2 will result in R 2 AR(p) OLS regression outputs in the 90%+ range.
References
Bakshi G, Cao C, Chen Z (1997) Empirical performance of alternative option pricing models. J Finance 52(5):2003–2049
Berndt A, Douglas R, Duffie JD, Ferguson M, Schranz D (2004) Measuring default risk premia from default swap rates and EDFs. BIS working paper no. 173. EFA 2004 Maastricht meetings paper no. 5121
Black F, Cox JC (1976) Valuing corporate securities: some effects of bond indenture provisions. J Finance 31(2):351–367
Chen L, Lesmond DA, Wei J (2007) Corporate yield spreads and bond liquidity. J Finance 62:119–149. doi:10.1111/j.1540-6261.2007.01203.x
Collin-Dufresne P, Goldstein RS, Martin SJ (2001) The determinants of credit spread changes. J Finance 56:2177–2207. doi:10.1111/0022-1082.00402
Duffee GR (1999) Estimating the price of default risk. Rev Financ Stud 12:197–226. doi:10.1093/rfs/12.1.197
Duffie D, Singleton KJ (1997) An econometric model of the term structure of interest-rate swap yields. J Finance 52(4):1287–1321
Duffie D, Singleton KJ (1999) Modeling term structures of defaultable bonds. Rev Financ Stud 12:687–720
Elton EJ, Gruber MJ, Agrawal D, Mann C (2001) Explaining the rate spread on corporate bonds. J Finance 56:247–277. doi:10.1111/0022-1082.00324
Friedman BM, Kuttner KN (1993) Why does the paper-bill spread predict real economic activity? NBER working paper no. W3879, pp 213-253
Geske R (1977) The valuation of corporate liabilities as compound options. J Financ Quant Anal 12(4):541–552
Granger CWJ (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37(3):424–438
Grinblatt M (1995) An analytic solution for interest rate swap spreads. Int Rev Financ 2(3):113–149
Hamilton JD (1994) Time series analysis. Princeton University Press
Huang JZ, Huang M (2003) How much of corporate-treasury yield spread is due to credit risk?: A new calibration approach. In: 14th annual conference on financial economics and accounting (FEA). Texas Finance Festival, 15 May 2003
Huang Y, Neftci S (2003) What drives swap spreads, credit or liquidity? ISMA Center working papers in finance 2003-05
Hull J, White A (2000) Valuing credit default swaps I: no counterparty default risk. J Deriv 8(1):29–40
Jarrow RA, Turnbull SM (1995) Pricing derivatives on financial securities subject to credit risk. J Finance 50:53–85
Jarrow RA, Lando D, Turnbull SM (1997) A markov model for the term structure of credit risk spreads. Rev Financ Stud 10:481–523
Lang LHP, Litzenberger RH, Luchuan Liu A (1998) Determinants of interest rate swap spreads. J Bank Financ 22(12):1507–1532
Lesmond DA, Ogden JP, Trzcinka CA (1999) A new estimate of transaction costs. Rev Financ Stud 12:1113–1141
Longstaff FA, Schwartz ES (1995) A simple approach to valuing risky fixed and floating rate debt. J Finance 50(3):789-819
Longstaff FA, Mithal S, Neis E (2005) Corporate yield spreads: default risk or liquidity? New evidence from the credit default swap market. J Finance 60:2213–2253. doi:10.1111/j.1540-6261.2005.00797.x
Merton RC (1974) On the pricing of corporate debt: the risk structure of interest rates. J Finance 29:449–470
Pesaran HH, Shin Y (1998) Generalized impulse response analysis in linear multivariate models. J Econ Lett 58(1):17–29
Sims CA (1980) Macroeconomics and reality. Econometrica 48:1–48
Vasicek O (1977) An equilibrium characterization of the term structure. J Financ Econ 5(2):177–188
Zhu H (2006) An empirical comparison of credit spreads between the bond market and the credit default swap market. J Financ Serv Res 29:211–235. doi:10.1007/s10693-006-7626-x
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Murphy, F., Murphy, B. A vector-autoregression analysis of credit and liquidity factor dynamics in US LIBOR and Euribor swap markets. J Econ Finan 36, 351–370 (2012). https://doi.org/10.1007/s12197-010-9122-2
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12197-010-9122-2