Using dealer’s quotes and transactions prices on straight industrial bonds, we investigate the determinants of credit spread changes. Variables that should in theory determine credit spread changes have rather limited explanatory power. Further, the residuals from this regression are highly cross-correlated, and principal components analysis implies they are mostly driven by a single common factor. Although we consider several macroeconomic and financial variables as candidate proxies, we cannot explain this common systematic component. Our results suggest that monthly credit spread changes are principally driven by local supply0 demand shocks that are independent of both credit-risk factors and standard proxies for liquidity.

Economic theory tells us that market and credit risks are intrinsically related to each other and not separable. We describe the two main approaches to pricing credit risky instruments: the structural approach and the reduced form approach. It is argued that the standard approaches to credit risk management -- CreditMetrics, CreditRisk+ and KMV -- are of limited value when applied to portfolios of interest rate sensitive instruments and in measuring market and credit risk. Empirically returns on high yield bonds have a higher correlation with equity index returns and a lower correlation with Treasury bond index returns than do low yield bonds. Also, macro economic variables appear to influence the aggregate rate of business failures. The CreditMetrics, CreditRisk+ and KMV methodologies cannot reproduce these empirical observations given their constant interest rate assumption. However, we can incorporate these empirical observations into the reduced form of Jarrow and Turnbull (1995b). Drawing the analogy. Risk 5, 63-70 model. Here default probabilities are correlated due to their dependence on common economic factors.

In this paper, we examine the dynamic behavior of credit spreads on corporate bond portfolios. We propose an econometric model of credit spreads that incorporates portfolio rebalancing, the near unit root property of spreads, the autocorrelation in spread changes, the ARCH conditional heteroscedasticity, jumps, and lagged market factors. In particular, our model is the first that takes into account explicitly the impact of rebalancing and yields estimates of the absorbing bounds on credit spreads induced by such rebalancing. We apply our model to nine Merrill Lynch daily series of option-adjusted spreads with ratings from AAA to C for the period January, 1997 through August, 2002. We find no evidence

et Finance Appliquée, especially Dr. Jean-Pierre Paré. We gratefully acknowledge financial support from

The Pareto (power-law) wealth distribution, which is empirically observed in many countries, implies rather extreme wealth inequality. For instance, in the U.S. the top 1% of the population holds about 40% of the total wealth. What is the source of this inequality? The answer to this question has profound political, social, and philosophical implications. We show that the Pareto wealth distribution is a robust consequence of a fundamental property of the capital investment process: it is a stochastic multiplicative process. Moreover, the Pareto distribution implies that inequality is driven primarily by chance, rather than by differential investment ability. This result is closely related to the concept of market efficiency, and may have direct implications regarding the economic role and social desirability of wealth inequality. We also show that the Pareto wealth distribution may explain the Lvy distribution of stock returns, which has puzzled researchers for many years. Thus, the Pareto wealth distribution, market efficiency, and the Lvy distribution of stock returns are all closely linked.

This paper explores empirically the usefulness of credit default swap (CDS) prices as market indicators. The sample of reference entities consists of large, internationally active German banks and the observation period covers three years. By analysing the explanatory power of three risk sources, idiosyncratic credit risk, systematic credit risk, and liquidity risk, we gain important insights for modelling the dynamics of CDS spreads. The impact of systematic risk, for example, has two components, one related to the overall state of the economy and the other to a banking– sector specific component. Contrary to previous research for corporate bonds we find that CDS premia of German banks rise with an increasing risk–free interest rate, which may be explained by its impact on term transformation risk. We compare default probabilities, inferred from a tractable reduced form model for CDS spreads, with expected default frequencies from the Moody’s KMV model. The results provide empirical support to the hypothesis that structural models based on equity market prices may be less informative than reduced–form models of CDS spreads, especially for banks with major investment banking activities, because the leverage looses explanatory power. Although the CDS market appears to have matured in the observation period, in certain periods premiums for liquidity risk can substantially increase which limits their value as market indicators. We conclude that equity prices and CDS premia should be considered together to fully exploit the information content of both market indicators and to mitigate their respective drawbacks.

Discussion Papers represent the authors ’ personal opinions and do not necessarily reflect the views of the

This paper investigates the long-term relationship between daily yields, from June 1993 to October 1998, of Japanese Government bonds and high-grade (AAA and AA) Yen denominated Eurobonds with maturities of 2, 3, 5, 7, 10 and 20 years. We find the cointegration vector differs slightly from the expected order predicted by the expectations hypothesis. There is evidence of two-way causality between bonds of different credit classes which we attribute to differences in liquidity in the Yen Eurobond and Japanese Government bond markets. The findings have implications for the debt issuance policy of the Japanese authorities and also for risk management since the estimated models can be used to improve estimates of the credit spread needed, for example, in pricing credit spread derivatives. We conclude that the concentration of new Japanese Government issues into maturities of 5 to 10 years, combined with the practice by the authorities of holding a significant amount of outstanding bonds, has distorted the transmission process between different risk classes of bonds along the term structure.

Corporate bonds expose the investor to credit risk, which will be reflected in the credit spread. Based on the EMU Broad Market indices, we study the inter-temporal stability of the covariance and correlation matrices of credit spread changes. Within a multivariate framework, the Box and Jennrich tests are most commonly used test statistics in the literature. However, we show that for small samples these tests are not well specified when the normality assumption is relaxed. A bootstrap-based statistical inference provides evidence that correlations between various (investment grade) credit spread changes remain stable over the 1998-2000 period. Covariances on the other hand, turn out to be time-varying over that period.

Abstract—The behaviour of the efficient frontier for CDOs of bespoke portfolios is investigated under one-factor copula marginal distributional assumptions. This approach has been thoroughly used in statistical literature. The main feature of these models is that default events, conditional on some latent state variable, are independent. This eases the computation of the aggregate loss distribution, a crucial element in credit portfolio optimisation. Both Gaussian and Clayton copula models are applied to the default dependence structure. The Clayton copula model demonstrates superiority in capturing the default dependence inherent in credit portfolios. The portfolio optimisation problem set-up under the newly defined Copula Marginal Expected Tail Loss (abbreviated as CMETL) risk measure is convex and can be easily solved in terms of linear programming algorithms. Numerical analysis is conducted by creating a Bespoke CDO collateral portfolio using the iTraxx Europe IG Series 5 index constituents as an illustrative example.