Corporate Bond Portfolios Research Articles

Sovereign Risk Spillover into Euro Corporate Spreads

We document and quantify the spillover of sovereign risk onto corporate credits throughout the Eurozone. We characterize the dynamics of spread movement in Euro corporates and show how this has changed over time due to the effects of the sovereign crisis. We show that when analyzing risk exposures in a portfolio of European corporate bonds, it has become important to partition by country, in addition to, or even instead of, partitioning by industry. We document a clear relationship between the peer spreads of corporate bonds in a given country over industry-matched German corporates and the sovereign spread of the country of domicile: Once sovereign spreads exceed 100 bp, every additional 100 bp of sovereign spread is associated with about 50 bp of corporate peer spread. We introduce changes to the POINT Global Risk Model that account for the sovereign risk exposures in European corporate bonds. We document the advantages of the specific model selected for implementation over several possible alternatives, and provide some examples of the effect of the new model on projected portfolio risk. How much sovereign exposure is embedded in a given corporate bond position? We propose a model that can be applied at the level of individual issuers, both for purposes of hedging the sovereign risk in a corporate portfolio, and for the decomposition of corporate spreads into sovereign and corporate components. <b>TOPICS:</b>Fixed income and structured finance, developed

The Riskiness of Corporate Bonds

We use an index of riskiness recently proposed by Aumann and Serrano () to analyze how the riskiness of diversified portfolios of corporate bonds changes across rating classes and through time and how it compares to the riskiness of other financial instruments. We find that differences in riskiness among portfolios of bonds belonging to different rating classes are seldom statistically significant. We instead find significant time variation in riskiness, driven mainly by return volatility, inflation, and average bond yields. In particular, we find that increases in average bond yields have historically tended to reduce the riskiness of portfolios of corporate bonds by increasing their expected return and by lowering the probability of portfolio losses.

Duration Targeting: No Magic for High-Yield Investors

Over time, the annualized return of a duration-targeting, investment-grade corporate bond portfolio will nearly match its initial yield. A high-yield bond portfolio’s performance is not similarly predictable. Furthermore, the difference between the high-yield universe’s initial yield and annualized return has a sharply negative bias. The absence of benefits from duration targeting has a bearing on valuation of the high-yield asset class and helps explain the instability in its investor base.

EFFICIENCY IN LARGE DYNAMIC PANEL MODELS WITH COMMON FACTORS

This paper deals with asymptotically efficient estimation in exchangeable nonlinear dynamic panel models with common unobservable factors. These models are relevant for applications to large portfolios of credits, corporate bonds, or life insurance contracts. For instance, the Asymptotic Risk Factor (ARF) model is recommended in the current regulation in Finance (Basel II and Basel III) and Insurance (Solvency II) for risk prediction and computation of the required capital. The specification accounts for both micro- and macrodynamics, induced by the lagged individual observations and the common stochastic factors, respectively. For large cross-sectional and time dimensionsnandT, we derive the efficiency bound and introduce computationally simple efficient estimators for both the micro- and macroparameters. The results are based on an asymptotic expansion of the log-likelihood function in powers of 1/n, and are linked to granularity theory. The results are illustrated with the stochastic migration model for credit risk analysis.

The Return/Volatility Trade-Off of Distressed Corporate Debt Portfolios

This article analyzes the returns of distressed high-yield corporate bond portfolios based on the volatility characteristics of their corresponding option-adjusted spreads (“OAS”). Applying Capital Asset Pricing Model (“CAPM”) theory to a portfolio of distressed bonds generates different results depending on whether overall high-yield market OAS volatility is considered. CAPM expectations (higher risk investments demand higher expected returns) are not generally fulfilled in both time-independent and time-dependent space after normalizing the data for overall high-yield market OAS volatility, i.e. the lowest OAS volatility portfolios outperform the highest volatility portfolios. We provide evidence that this phenomenon is a result of the idiosyncratic characteristics of the securities that comprise the lowest OAS volatility portfolios, which generate higher returns because they experience lower default rates and higher terminal values relative to the securities in the highest OAS volatility portfolios. Alternatively, we find that CAPM generally holds under two conditions: 1) in time-independent space where no consideration is given to the OAS volatility of the overall high-yield corporate debt market; and, 2) in time-dependent space where an investor possesses market timing skills. Because persistent market timing skill is rare, investing based on a buy-and-hold strategy, comprised of portfolios of the lowest OAS volatility distressed bonds, may be a practical solution for the long-term distressed debt investor.

Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk

We propose a dynamic factor model for mixed-measurement and mixed-frequency panel data. In this framework time series observations may come from a range of families of parametric distributions, may be observed at different time frequencies, may have missing observations, and may exhibit common dynamics and cross-sectional dependence due to shared exposure to dynamic latent factors. The distinguishing feature of our model is that the likelihood function is known in closed form and need not be obtained by means of simulation, thus enabling straightforward parameter estimation by standard maximum likelihood. We use the new mixed-measurement framework for the signal extraction and forecasting of macro, credit, and loss given default risk conditions for U.S. Moody’s-rated firms from January 1982 until March 2010. Our joint modelling framework allows us to construct predictive (conditional) loss densities for portfolios of corporate bonds in the presence of different sources of credit risk such as frailty effects and systematic recovery risk.

Fixed-Income Portfolio Selection

This paper formulates and solves the selection problem for a portfolio of credit swaps. The problem is cast as a goal program that entails a constrained optimization of preference-weighted moments of the portfolio value at the investment horizon. The portfolio value takes account of the exact timing of protection premium and default loss payments, as well as any mark-to-market profits and losses realized at the horizon. The constraints address collateral and solvency requirements, initial capital, position limits, and other trading constraints that credit swap investors often face in practice. The multi-moment formulation accommodates the complex distribution of the portfolio value, which is a nested expectation under risk-neutral and actual probabilities. It also generates computational tractability. Numerical results illustrate the features of optimal portfolios. In particular, we find that credit swap investment constraints can have a significant impact on optimal portfolios, even for simple investment objectives. Our problem formulation and solution approach extend to corporate bond portfolios and mixed portfolios of corporate bonds and credit derivatives.

Credit Portfolio Management in a Turning Rates Environment

We give a detailed account of correlations between credit sector/quality and treasury curve factors, using the robust framework of the Barclays POINT® Global Risk Model. Consistent with earlier studies, we find a strong negative correlation between sector spreads and rate shifts. However, we also observe that the correlations between spreads and Treasury twists reversed recently, which is likely attributable to the Fed’s ongoing quantitative easing. We also find that short-term effective durations in the banking industry are now significantly lower than historical patterns would indicate. Our findings are relevant for credit portfolio managers contemplating the impact of rising interest rates and steepening Treasury curve on corporate bond portfolios.

A methodology for computing and comparing implied equity and corporate-debt Sharpe Ratios

This paper presents a macro-economic methodology for evaluating the forward-looking Sharpe Ratios of the equity and debt components of the United States public company capital structure. Using this framework, it is shown that the equity and debt Sharpe Ratios are both time variant and disparate. The methodology is used to review the risk aversion behavior of equity and debt market participants surrounding the past three major market events, the 1987 crash, the 2000–2001 Internet bubble and the 2008–2009 credit crisis. The forward-looking Sharpe Ratios are used to construct a dynamic portfolio of stocks and corporate bonds that outperforms a static portfolio on a risk-adjusted basis. This paper then offers market segmentation and the differing behavior of equity and corporate bond investors as an explanation for the observed Sharpe Ratios.

Credit portfolio management in a turning rates environment

We give a detailed account of correlations between credit sector/quality and treasury curve factors, using the robust framework of the Barclays POINT Global Risk Model. Consistent with earlier studies, we find a strong negative correlation between sector spreads and rate shifts. However, we also observe that the correlations between spreads and Treasury twists reversed recently, which is likely attributable to the Fed's ongoing quantitative easing. We also find that short-term effective durations in the banking industry are now significantly lower than historical patterns would indicate. Our findings are relevant for credit portfolio managers contemplating the impact of rising interest rates and steepening Treasury curve on corporate bond portfolios.

The Impact of Hedge Funds on Asset Markets

This paper provides evidence of the impact of hedge funds on asset markets. We construct a simple measure of the aggregate illiquidity of hedge fund portfolios, based on the cross-sectional average first order autocorrelation coefficient of hedge fund returns, and show that it has strong and robust in- and out-of-sample forecasting power for 72 portfolios of international equities, corporate bonds, and currencies over the 1994 to 2013 period. The forecasting ability of hedge fund illiquidity for asset returns is in most cases greater than, and provides independent information relative to, well-known predictive variables for each of these asset classes. We rationalize these findings using a simple equilibrium model in which hedge funds provide liquidity in asset markets.

Credit Portfolios, Credibility Theory, and Dynamic Empirical Bayes

We begin with a review of (a) the pricing theory of multiname credit derivatives to hedge the credit risk of a portfolio of corporate bonds and (b) current approaches to modeling correlated default intensities. We then consider pricing of insurance contracts using credibility theory in actuarial science. After a brief discussion of the similarities and differences of both pricing theories, we propose a new unified approach, which uses recent advances in dynamic empirical Bayes modeling, to evolutionary credibility in insurance rate-making and default modeling of credit portfolios.

A Model-Based Approach to Constructing Corporate Bond Portfolios

The authors develop a model-based approach for constructing investment-grade and high-yield corporate bond portfolios that outperforms their respective prevalent benchmark indices and popular exchange-traded funds (ETFs), with better risk–return profiles—that is, higher returns with lower or similar risk. More importantly, they obtain outperformance after controlling for credit risk, duration risk, and downside risk. The outperformance is robust across a number of different specifications of the strategy and over time. The authors also achieve outperformance by using relatively smaller, more realistic portfolios. These model portfolios can be potentially converted into new fixed-income indices or ETFs. Their model-based approach uses Moody’s Analytics’ EDF™ (expected default frequency) credit measures and the fair-value spread (FVS) valuation framework as powerful tools to control for credit risk and to exploit relative value in the bond market. To make our approach realistic and operational, we compile our investment universe from the Merrill Lynch Corporate Master Indices by applying a number of filtering criteria to our bond selection rules. We assess our model portfolios’ performance relative to Merrill Lynch (ML) and iBoxx indices, the two most widely-used fixed income portfolio benchmarks. To obtain a closer measure of the actual returns investors can achieve, we also compare results to the popular fixed-income Exchange Traded Funds (iShares ETFs) that focus on corporate credit. Additionally, we compare performance relative to the actively managed mutual fund universe, the respective U.S. fixed core fund universe. Our analyses factor in transaction costs.

Generalized Affine Model for Credit Risk Analysis

The main goal of this paper is to provide a generalised version of the Affine Model for Credit Risk Analysis, introduced by Gourieroux, Monfort and Polimenis (2003), for pricing securities exposed to such a risk, as the defaultable corporate bonds, and measuring portfolio risk. The assessment of credit risk is an important tool in risk management. Managing a corporate bond portfolio is much more difficult and complicated than managing a treasury bond (T-bond) portfolio. We focus on the case of default of one firm in the same framework as the Affine Model for Credit Risk Analysis where, for sake of simplicity, the assumption of zero-recovery rate is made. The idea behind the model is the following: there are two types of factors, which generate individual default. Firstly, all firms are influenced by a common pool of economic factors called general factors, such as the macroeconomic situation, the business cycle, the GDP (Gross National Product) gap, etc. Secondly, we consider the corporate specific factors which allow for considering the default occurrences of a given corporate at different points in time. Given the past, present and future values of these common factors, individual defaults become independent.

Sources of Momentum in Bonds

This paper documents that momentum profits in corporate bonds prevail during weakening aggregate credit conditions, and are driven by losers. Consistent with this, we find that a conditional default factor explains the cross-section returns of corporate bond portfolios sorted by past performance. Based on the evidence, we develop a model connecting bond momentum returns to the ability of bondholders to recover value when firms default. Specifically, we propose that firms with more (less) intangible capital and growth options are more (less) costly to liquidate and, therefore, they have lower (higher) recovery value. In this case, the bond momentum can exist, because the “recovery premium” becomes more important when firm default becomes highly probable. We provide strong empirical support to these predictions. Related, the U.S. government bonds display no momentum, yet it emerges in sovereign bond returns. Time-varying aggregate default shocks and firm characteristics determining the growth and liquidation of issuers are the main sources of momentum in bonds.

Factor decomposition and diversification in European corporate bond markets

In this paper we present an analysis of diversification strategies on portfolios of European corporate bonds. From the perspective of a US-based investor we study whether mean–variance diversification strategies change as a result of the introduction of the European Economic and Monetary Union (EMU). Using a comprehensive and unique data set of European corporate bonds we show that country factors are more important than industry factors to describe the cross-section of European corporate bonds. In particular we find that in the Post-EMU period country factors remain important.

The Credit Spread Puzzle

Spreads on corporate bonds tend to be many times wider than what would be implied by expected default losses alone. These spreads are the difference between yields on corporate debt subject to default risk and government bonds free of such risk.2 While credit spreads are often generally understood as the compensation for credit risk, it has been difficult to explain the precise relationship between spreads and such risk. In 1997–2003, for example, the average spread on BBB-rated corporate bonds with three to five years to maturity was about 170 basis points at annual rates. Yet, during the same period, the average yearly loss from default amounted to only 20 basis points.In this case, the spread was more than eight times the expected loss from default. The wide gap between spreads and expected default losses is what we call the credit spread puzzle. In this article we argue that the answer to the credit spread puzzle might lie in the difficulty of diversifying default risk. Most studies to date have implicitly assumed that investors can diversify away the unexpected losses in a corporate bond portfolio. However, the nature of default risk is such that the distribution of returns on corporate bonds is highly negatively skewed. Such skewness would require an extraordinarily large portfolio to achieve full diversification. Evidence from the market for collateralised debt obligations (CDOs) indicates that in practice such large portfolios are unattainable, and thus unexpected losses are unavoidable. Hence, we argue that spreads are so wide because they are pricing undiversified credit risk. We first review the existing evidence on the determinants of credit spreads, including the role of taxes, risk premia and liquidity premia. We then discuss the role of unexpected losses and the difficulties involved in diversifying credit portfolios, drawing on evidence from the CDO market.

Managing the Risks of Corporate Bond Portfolios: New Evidence in the Light of the Sub‐Prime Crisis

We consider modeling errors in the hedging of a portfolio composed from BBB‐rated bonds. By doing this, we open a new perspective to the debate on the relationship between corporate bonds and CDS spreads. We find that in ordinary times the added value of indexlinked credit derivatives is very limited: hedging portfolios including only T‐bond futures can reduce the variance by 80‐85%. This compares well to the maximum variance reduction of 50% reported by previous studies. On the contrary, in times of extraordinary volatility – such as the years 2008 and 2009 ‐ T‐bond futures would have been insufficient to successfully hedge the bond portfolio. However, including the 5‐year CDX contract would have only slightly improved the quality of hedging. This is consistent with the literature identifying an important non‐default component within corporate bond spreads. Our results encourage the offering of collateralized credit spread forwards as more effective hedging instruments than non‐collateralized CDS contracts.

VIX Futures and the Hedging of Bond Portfolios

Equity volatility, as replicated by widely traded ETFs and ETNs linked to the S&P 500® VIX® Futures Index Series, is frequently used to hedge equity portfolios. But is it appropriate for bond portfolios?The bond market is broad and diverse, ranging from low-risk government bonds to relatively high-risk high-yield corporate bonds and emerging market bonds. As a result, equity volatility relates to each segment of the bond market in the following different ways:- Treasury and municipal bonds are positively correlated with equity volatility because they often serve as safe-haven choices when equity risk is at heightened levels. Therefore, adding S&P 500 VIX Futures Index Series exposure to a portfolio of treasury and municipal bonds does not provide diversification benefits.- Investment-grade corporate bonds have a weakly positive correlation with equity volatility futures, while high-yield corporate bonds have a weakly negative correlation. During extreme downturns, equity volatility futures can offer corporate bond portfolios some tail risk hedging benefits, but there are occasions when these benefits may not be realized. Risk-return benefits can also be obtained by adding a dynamic allocation of the S&P 500 VIX Futures Index Series to a corporate bond portfolio.- The most beneficial application of the S&P 500 VIX Futures Index Series is in emerging market bond portfolios. Adding the S&P 500 VIX Futures Index Series generally provides a clear tail risk hedging benefit. Over the period of study, equity volatility futures provided downside protection on all but four of the worst 25 days for emerging market bonds. An ongoing dynamic allocation to the S&P 500 VIX Futures Index Series has also produced better risk-adjusted returns, with statistically significant outperformance.

A Methodology for Computing and Comparing Implied Equity and Corporate Debt Sharpe Ratios

This paper presents a macro-economic methodology for evaluating the forward-looking Sharpe Ratios of the equity and debt components of the United States public company capital structure. Using this framework, it is shown that the equity and debt Sharpe Ratios are both time variant and disparate. The methodology is used to review the risk aversion behavior of equity and debt market participants surrounding the past three major market events, the 1987 crash, the 2000-2001 Internet bubble and the 2008-2009 credit crisis. The forward-looking Sharpe Ratios are used to construct a dynamic portfolio of stocks and corporate bonds that outperforms a static portfolio on a risk-adjusted basis. This paper then offers market segmentation and the differing behavior of equity and corporate bond investors as an explanation for the observed Sharpe Ratios.