Results 1  10
of
24
The Determinants of Credit Spread Changes
, 2001
"... 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 crossco ..."
Abstract

Cited by 308 (2 self)
 Add to MetaCart
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 crosscorrelated, 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 creditrisk factors and standard proxies for liquidity.
The intersection of market and credit risk
, 2000
"... 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 ma ..."
Abstract

Cited by 44 (2 self)
 Add to MetaCart
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, 6370 model. Here default probabilities are correlated due to their dependence on common economic factors.
An econometric model of credit spreads with rebalancing, arch and jump effects. In: Fitch Ratings
, 2003
"... 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 heteroscedasti ..."
Abstract

Cited by 4 (0 self)
 Add to MetaCart
(Show Context)
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 optionadjusted spreads with ratings from AAA to C for the period January, 1997 through August, 2002. We find no evidence
Market Efficiency, the Pareto Wealth Distribution, and the Lévy Distribution of Stock Returns
, 2001
"... The Pareto (powerlaw) 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 pr ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
The Pareto (powerlaw) 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.
Exploring the Common Factors in the Term Structure of Credit Spreads,” Arizona State University working paper
, 2008
"... This paper provides a factor analysis of the term structure of credit spreads. We show that credit spread innovations are subject to three common factors, two strong factors and one weak factor. A novelty is that our factors are extracted using canonical relations between credit spreads and a set of ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
This paper provides a factor analysis of the term structure of credit spreads. We show that credit spread innovations are subject to three common factors, two strong factors and one weak factor. A novelty is that our factors are extracted using canonical relations between credit spreads and a set of observable or estimated variables. This approach appears to estimate the factors in credit spreads better than the conventional principal component approach. The first strong factor is related to the contemporaneous state of the economy. The second strong factor represents investors ’ expectations about future economic conditions, and is shown to have predictive power for the state of the economy over a twoquarter horizon. The weak factor is mainly related to the errorcorrection processes in shortterm spreads.
AN ANALYSIS OF PRIVATE LOAN GUARANTEE PORTFOLIOS
"... et Finance Appliquée, especially Dr. JeanPierre Paré. We gratefully acknowledge financial support from ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
(Show Context)
et Finance Appliquée, especially Dr. JeanPierre Paré. We gratefully acknowledge financial support from
THE RISK OF PRIVATE LOAN GUARANTEES PORTFOLIOS
"... This paper uses contingent claims analysis (CCA) to evaluate portfolios of vulnerable private loan guarantees and investigate their risk diversification properties. Results from Monte Carlo simulations are consistent with those in the previous literature on loan guarantees with respect to the asset ..."
Abstract
 Add to MetaCart
(Show Context)
This paper uses contingent claims analysis (CCA) to evaluate portfolios of vulnerable private loan guarantees and investigate their risk diversification properties. Results from Monte Carlo simulations are consistent with those in the previous literature on loan guarantees with respect to the asset value and the risk posture of the guarantor and the insured firms, as well as the correlation between them. In particular it is shown that, for plausible base line value of the parameters, the nonsystematic diversifiable credit risk can be eliminated in a portfolio of ten insured firms. We also show how further diversification can be achieved by an appropriate choice of insured firms ’ risk postures and of correlations between them and the guarantor. THE RISK OF PRIVATE LOAN GUARANTEES PORTFOLIOS
Macroeconomic Determinants of the Term Structure of Corporate Spreads
, 2008
"... We investigate the macroeconomic determinants of corporate spreads using a noarbitrage technique. Structural shocks are identified by a NewKeynesian model. Treasury bonds are priced in an affine model with timevarying risk premia. Corporate bonds are priced in a reducedform credit risk model whe ..."
Abstract
 Add to MetaCart
We investigate the macroeconomic determinants of corporate spreads using a noarbitrage technique. Structural shocks are identified by a NewKeynesian model. Treasury bonds are priced in an affine model with timevarying risk premia. Corporate bonds are priced in a reducedform credit risk model where default risk depends on macroeconomic state variables. Using U.S. data, we find that the monetary policy shock contributes to more than 50 % the corporate spread variations at different forecasting horizons. Its contribution, in general, declines with credit classes. In contrast, the aggregate supply and demand shocks contribute more to the spread variations in low credit classes than in high credit classes. In addition, they in general contribute more for longer forecasting horizons.
The Dynamics of Australian Dollar Bonds with Different Credit Qualities
"... The working papers are a series of manuscripts in their draft form. Please do not quote without obtaining the author's consent as these works are in their draft form. ..."
Abstract
 Add to MetaCart
The working papers are a series of manuscripts in their draft form. Please do not quote without obtaining the author's consent as these works are in their draft form.
Corresponding addresses:
"... Dynamic equilibrium correction modelling of yen Eurobond credit spreads ..."