Measuring Default Risk Premia from Default Swap Rates and EDFs

Abstract

the BIS held a workshop on "The pricing of credit risk". This event brought together central bankers, academics and market practitioners to exchange views on this issue (see the conference programme in this document). This paper was presented at the workshop. The views expressed are those of the author(s) and not those of the BIS. v BIS workshop on "The pricing of credit risk"

Unveiling Sovereign Effects in European Banks CDS Spreads Variations

“…While remaining model-specific, their conclusions could provide useful guidance for our research. Hence, through the estimation of default risk premia from US corporate bonds, Berndt et al (2005) find that the expected default frequencies from the Moody's KMV model explain a large proportion of the cross-sectional variation in CDS spreads. However, substantial variation is noted for a given default probability.…”

“…Gilchrist et al (2011) for instance demonstrated the importance of considering the business cycle perspective in explaining the determinants of credit spreads. Similarly, Berndt et al (2005) suggest that CDS spreads are likely not attributed to credit risk alone and Annaert et al (2013) notably conclude that liquidity and global economic variables are important to explain CDS variations. More recently, Keiler and Eder (2013) investigate the degree of systemic risk and the importance of potential spill-over effects in the banking system by analyzing the determinants of CDS spreads using spatial econometric approach.…”

“… For the general level and structure of interest rates: is the weekly change of the risk-free rate at time t proxied by the 10-year EMU bond index obtained from Datastream and represents the term structure slope at time t proxied by the spread between the 10-year EMU bond index and the 2-year EMU bond index;  For the general business climate: following Collin-Dufresne et al (2001), Zhu (2006) and Annaert et al (2013), we include being the market wide stock index return at time t based on the weekly Eurostoxx 50 data obtained from Datastream and following Berndt et al (2005) and Annaert et al (2013), we use being the weekly change in the stock index volatility at time t based on the weekly VSTOXX data obtained from Datastream to measure market wide implied volatility;  Finally, considering that our study aims specifically at the banking industry, we opt for the spread between Libor and OIS as a proxy for the general state of the banking system 17 but also as a reflection of possible market wide liquidity strains. This approach is similar to Keiler (2013).…”

Concentrated Capital Losses and the Pricing of Corporate Credit Risk

“…74 Driessen (2002) and Berndt, Douglas, Duffie, Ferguson, and Schranz (2008) provide evidence that, on average, ⇧ rt ⇡ 1.9. In other words, for every unit of actual default risk taken, the seller of protection must be compensated as if she is taking roughly double that amount of default risk.…”

“…To make Equation (19) empirically operational I need to have estimates of P rt and LGD Q rt . Like in Berndt, Douglas, Duffie, Ferguson, and Schranz (2008), I proxy for P rt using Moody's 5-year annualized EDF. 75 Analogously, I obtain separate estimates of LGD Q rt from Markit and Moody's.…”