Regime dependent determinants of credit default swap spreads

Regime Switching Determinants of the Japanese Sovereign Credit Default Swaps Spreads

“…Our results are consistent with existing literature that have found strong evidence that the coefficients in the volatile regime tend to be higher than those in the normal regime (as in [16] and [17]). The statistical importance of our model is on average around 90% in the volatile regime as compared to a 52% explanatory power in the normal period.…”

“…The Implied Volatility on the CBOE Index (VIX) exerts strong positive significance on Japanese Sovereign CDS spreads in both regimes. earlier findings (as in Chan and Marsden [19]; Alexander and Kaeck [17]) who find a positive relationship between VIX and CDS Indexes. Though the VIX show a positive impact on CDS spreads in the less volatile regime, the significance reduces to a 1% level and magnitude of the coefficient reduces as compared to the volatile regime.…”

“…Also, applying a linear regression and a Markov Switching model to iTraxx Europe Indices, Alexander and Kaeck [17], find that the impact of the determinants is regime specific. Specifically, the impact of implied volatility is more sensitive to spread changes during volatile periods and Stock returns are more sensitive to spread changes during normal periods.…”

Credit spreads: An empirical analysis on the informational content of stocks, bonds, and CDS

“…19 Of course, an additional difference is the use the log of credit spread series in our case. 20 Interestingly, Alexander and Kaeck (2008) report that CDS are extremely sensitive to stock market volatility during periods of CDS market turbulence, but in ordinary market circumstances CDS spreads are more sensitive to stock returns than they are to stock volatility. 21 The detailed investigation of factors underlying the price discovery process -as much in the time series as in the cross-section -seems a promising line of research, but beyond the scope of the present study.…”

Are CDS spreads predictable? An analysis of linear and non-linear forecasting models

“…Recent studies which have tried to explain CDS spread levels and changes are from Blanco et al (2005), Longstaff et al (2005), Benkert (2004), Alexander and Kaeck (2008), Zhang et al (2009), Ericsson et al (2009) and Cao et al (2010. Their findings are generally more encouraging (than previous studies on credit spreads) as credit variables seem to explain a great deal of the variation in CDS spreads.…”