TY - JOUR
T1 - From default probabilities to credit spreads
T2 - Credit risk models do explain market prices
AU - Denzler, Stefan M.
AU - Dacorogna, Michel M.
AU - Müller, Ulrich A.
AU - McNeil, Alexander J.
PY - 2006/6
Y1 - 2006/6
N2 - Credit risk models like Moody's KMV are now well established in the market and give bond managers reliable estimates of default probabilities for individual firms. Until now it has been hard to relate those probabilities to the actual credit spreads observed on the market for corporate bonds. Inspired by the existence of scaling laws in financial markets by Dacorogna et al. [2001. An Introduction to High Frequency Finance. Academic Press, San Diego, CA] and Di Matteo et al. [2005. Journal of Banking and Finance 29, 827-851] deviating from the Gaussian behavior, we develop a model that quantitatively links those default probabilities to credit spreads (market prices). The main input quantities to this study are merely industry yield data of different times to maturity and expected default frequencies (EDFs) of Moody's KMV. The empirical results of this paper clearly indicate that the model can be used to calculate approximate credit spreads (market prices) from EDFs, independent of the time to maturity and the industry sector under consideration. Moreover, the model is effective in an out-of-sample setting, it produces consistent results on the European bond market where data are scarce and can be adequately used to approximate credit spreads on the corporate level.
AB - Credit risk models like Moody's KMV are now well established in the market and give bond managers reliable estimates of default probabilities for individual firms. Until now it has been hard to relate those probabilities to the actual credit spreads observed on the market for corporate bonds. Inspired by the existence of scaling laws in financial markets by Dacorogna et al. [2001. An Introduction to High Frequency Finance. Academic Press, San Diego, CA] and Di Matteo et al. [2005. Journal of Banking and Finance 29, 827-851] deviating from the Gaussian behavior, we develop a model that quantitatively links those default probabilities to credit spreads (market prices). The main input quantities to this study are merely industry yield data of different times to maturity and expected default frequencies (EDFs) of Moody's KMV. The empirical results of this paper clearly indicate that the model can be used to calculate approximate credit spreads (market prices) from EDFs, independent of the time to maturity and the industry sector under consideration. Moreover, the model is effective in an out-of-sample setting, it produces consistent results on the European bond market where data are scarce and can be adequately used to approximate credit spreads on the corporate level.
KW - Actual default probability and risk-neutral default probability
KW - Bond pricing
KW - Credit risk modeling
KW - Credit spread
KW - Default risk
KW - Expected default frequency
UR - http://www.scopus.com/inward/record.url?scp=33646522194&partnerID=8YFLogxK
U2 - 10.1016/j.frl.2006.01.004
DO - 10.1016/j.frl.2006.01.004
M3 - Article
AN - SCOPUS:33646522194
SN - 1544-6123
VL - 3
SP - 79
EP - 95
JO - Finance Research Letters
JF - Finance Research Letters
IS - 2
ER -