Can broker-dealer client surveys provide signals for debt investing?

We use a novel data set to study return predictability in debt markets. The data are collected from J.P. Morgan’s periodic surveys on its clients’ outlook for changes in US Treasury yields and corporate credit spreads. We document that simple signals constructed from such surveys predict excess returns on debt portfolios formed on the basis of duration (2-years minus zero) or credit quality (BBB minus AAA). A linear trading strategy placing equal weight on Treasury and Credit signals has an annualized Information Ratio equal to 1.18, before transaction costs. We also show that predictability is likely to stem from private information possessed by survey respondents rather than from risk premia.     

Market conditions,default risk and credit spreads

This study empirically examines the impact of the interaction between market and default risk on corporate credit spreads. Using credit default swap (CDS) spreads, we find that average credit spreads decrease in GDP growth rate, but increase in GDP growth volatility and jump risk in the equity market. At the market level, investor sentiment is the most important determinant of credit spreads. At the firm level, credit spreads generally rise with cash flow volatility and beta, with the effect of cash flow beta varying with market conditions. We identify implied volatility as the most significant determinant of default risk among firm-level characteristics. Overall, a major portion of individual credit spreads is accounted for by firm-level determinants of default risk, while macroeconomic variables are directly responsible for a lesser portion.     

Theory and evidence on the dynamic interactions between sovereign credit default swaps and currency options

Using sovereign CDS spreads and currency option data for Mexico and Brazil, we document that CDS spreads covary with both the currency option implied volatility and the slope of the implied volatility curve in moneyness. We propose a joint valuation framework, in which currency return variance and sovereign default intensity follow a bivariate diffusion with contemporaneous correlation. Estimation shows that default intensity is much more persistent than currency return variance. The market price estimates on the two risk factors also explain the well-documented evidence that historical average default probabilities are lower than those implied from credit spreads.     

A Multifactor Model of Credit Spreads

We represent credit spreads across ratings as a function of common unobservable factors of the Vasicek form. Using a state-space approach we estimate the factors, their process parameters, and the exposure of each observed credit spread series to each factor. We find that most of the systematic variation across credit spreads is captured by three factors. The factors are closely related to the implied volatility index (VIX), the long bond rate, and S&P500 returns, supporting the predictions of structural models of default at an aggregate level. By making no prior assumption about the determinants of yield spread dynamics, our study provides an original and independent test of theory. The results also contribute to the current debate about the role of liquidity in corporate yield spreads. While recent empirical literature shows that the level and time-variation in corporate yield spreads is driven primarily by a systematic liquidity risk factor, we find that the three most important drivers of yield spread levels relate to macroeconomic variables. This suggests that if credit spread levels do contain a large liquidity premium, the time variation of this premium is likely driven by the same factors as default risk.     

Time‐Varying Asset Volatility and the Credit Spread Puzzle

Most extant structural credit risk models underestimate credit spreads—a shortcoming known as the credit spread puzzle. We consider a model with priced stochastic asset risk that is able to fit medium‐ to long‐term spreads. The model, augmented by jumps to help explain short‐term spreads, is estimated on firm‐level data and identifies significant asset variance risk premia. An important feature of the model is the significant time variation in risk premia induced by the uncertainty about asset risk. Various extensions are considered, among them optimal leverage and endogenous default.     

The cross-sectional relation between conditional heteroskedasticity,the implied volatility smile,and the variance risk premium

This paper estimates how the shape of the implied volatility smile and the size of the variance risk premium relate to parameters of GARCH-type time-series models measuring how conditional volatility responds to return shocks. Markets in which return shocks lead to large increases in conditional volatility tend to have larger variance risk premia than markets in which the impact on conditional volatility is slight. Markets in which negative (positive) return shocks lead to larger increases in future volatility than positive (negative) return shocks tend to have downward (upward) sloping implied volatility smiles. Also, differences in how volatility responds to return shocks as measured by GARCH-type models explain much, but not all, of the variations in excess kurtosis and multi-period skewness across different markets.     

The effect of banking regulation on cross-border lending

Banking regulations often differ between countries: Some regulators require banks to document their evaluation of firms’ creditworthiness, which determines the banks’ choice of lending technology. In a theoretical model, we study how differences in regulation influence competition between domestic and foreign banks and analyze the effect of regulatory harmonization on cross-border lending. We predict that lending rates are lower and access to credit is easier for firms in a border region if the national regulations differ. Using unique bank- and firm-level data from Germany, we show that firms in a border region have better access to credit if regulation differs.     

Downside risk and the size of credit spreads

We investigate why spreads on corporate bonds are so much larger than expected losses from default. Systematic factors make very little contribution to spreads, even if higher moments or downside effects are taken into account. Instead we find that sizes of spreads are strongly related to idiosyncratic-risk factors: not only to idiosyncratic equity volatility, but even more to idiosyncratic bond volatility and idiosyncratic bond value-at-risk. Idiosyncratic bond volatility helps to explain spreads because it reflects not just the distribution of firm value but is also a proxy for liquidity risk. Idiosyncratic bond value-at-risk adds to this by capturing the left-skewness of the firm-value distribution. We confirm our results both for the initial 1997-2004 sample period and also out of sample for 2005-2009, which includes the sub-prime crisis. Overall, credit spreads are large because they incorporate a large risk premium related to investors’ fears of extreme losses.     

The Greek financial crisis: Growing imbalances and sovereign spreads

We discuss the origins of the Greek financial crisis as manifested in the growing fiscal and current-account deficits since euro-area entry in 2001. We then extend a model typically used to explain risk premia to assess the extent to which credit ratings captured these premia. Next, we estimate a cointegrating relationship between spreads and their long-term fundamental determinants and compare the spreads predicted by this estimated relationship with actual spreads. We find that spreads were significantly below what would be predicted by fundamentals from end-2004 up to the middle of 2005; by contrast, since May 2010, actual spreads have exceeded predicted spreads by some 400 basis points.     

Daily pricing of emerging market sovereign CDS before and during the global financial crisis

In this paper, we study the determinants of daily spreads for emerging market sovereign credit default swaps (CDSs) over the period April 2002–December 2011. Using GARCH models, we find, first, that daily CDS spreads for emerging market sovereigns are more related to global and regional risk premia than to country-specific risk factors. This result is particularly evident during the second subsample (August 2007–December 2011), where neither macroeconomic variables nor country ratings significantly explain CDS spread changes. Second, measures of US bond, equity, and CDX High Yield returns, as well as emerging market credit returns, are the most dominant drivers of CDS spread changes. Finally, our analysis suggests that CDS spreads are more strongly influenced by international spillover effects during periods of market stress than during normal times.