2004
DOI: 10.3905/jfi.2004.461450
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Credit Spread Modeling with Regime-Switching Techniques

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Cited by 38 publications
(40 citation statements)
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References 18 publications
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“…In using such an expansive data history I am able to uncover significantly different causal relationships in the key credit spread determinants using recently developed regime switching time series techniques. In doing so the analysis builds upon previous empirical work such as Morris, Neale, and Rolph (1998), Bevan and Garzarelli (2000) and Davies (2004) by conditioning upon alternative inflationary and volatility environments during a significantly extended 85 year data sample.…”
Section: Introductionmentioning
confidence: 98%
“…In using such an expansive data history I am able to uncover significantly different causal relationships in the key credit spread determinants using recently developed regime switching time series techniques. In doing so the analysis builds upon previous empirical work such as Morris, Neale, and Rolph (1998), Bevan and Garzarelli (2000) and Davies (2004) by conditioning upon alternative inflationary and volatility environments during a significantly extended 85 year data sample.…”
Section: Introductionmentioning
confidence: 98%
“…When the interest level is high, the put option level decreases; then the risky debt value increases and leads to a smaller credit spread. and Davies (2004) provide empirical support for the inverse relationship. However, Morris et al (1998) obtain the opposite result, supporting a positive relationship between the interest rate level and credit spread.…”
Section: Credit Spreadsmentioning
confidence: 77%
“…Furthermore, when statistically significant, this effect is positive for market-stress regimes and is persistent. 49 Each evaluation of the log-likelihood requires to apply the recursive formulas given in Propositions 3 and 5 for each obligor. For a weekly frequency and a maximum maturity of 10 year, this implies to run [66] formula, for other countries, the Newey-West (1987) [118] method is employed to correct for possible autocorrelation and heteroskedasticity of the residuals.…”
Section: Estimation Results and Interpretationmentioning
confidence: 99%
“…Nonetheless, the estimation would be highly time consuming for a standard computer. 49 Alternatively, we resort to a sequential approach. First, we estimate a smaller-scale statespace model by MLE, using yields of a subset of debtors: Germany, KfW and Italy, which provides us with some estimates of the latent factors y c,t and y ,t (see Figure 8).…”
Section: 33mentioning
confidence: 99%