Corporate Bond Prices Research Articles

The Option to Re-organize Firms with Valuable Growth Options and Risky Bond Prices

We develop a structural model of corporate bond prices which accounts for the option held by bondholders to liquidate or re-organize a firm that ends up in bankruptcy. Although there is a wide body of literature in corporate finance that examines the trade-offs between liquidation and re-organization for creditors in financially distressed firms, our paper is the first to incorporate these options into the ex-ante value of risky debt. The option to liquidate or to re-or ganize has value in our model due to the presence of valuable growth options. Liquidation value being the depreciated value of assets in place, ignores the value of these options. But were bondholders to take over control of the firm, the value of the firm is, with some ef ficiency loss, the sum of the value of assets in place and the value of future growth options.

A Stochastic Model for Credit Spreads Under a Risk-Neutral Framework Through the Use of an Extended Version of the Jarrow, Lando and Turnbull Model

The model derives risky corporate bond prices (or equivalently credit spreads) subject to credit default and migration risk, based on an extended version of the Jarrow, Lando and Turnbull model, under a risk-neutral framework, as a result of the simulation of a continuous time, time-homogeneous Markov chain. The inclusion of credit default and migration risk is made possible due to an allowance for a credit risk premium that varies stochastically. While the standard Jarrow-Lando-Turnbull model assumes that the credit risk premium is a deterministic function of time which, along with the assumption of a constant “real-world” transition matrix and constant recovery rate, leads to deterministic credit spreads, the extension proposed through this article captures a stochastic risk premium in order to better fit with historical observation. The model is of particular importance in the European Embedded Value (i.e. EEV) context where risk-neutral scenarios are required for calculating the Time Value of Options and Guarantees (i.e. TVOG) covering all material options and guarantees embedded following the requirements of EEV principles. Moreover, the model can also be used in a real-world framework for pricing government and risky corporate debts with the exclusion of the Markov chain. This allows to capture the marginal impact of credit default and migration risk at the TVOG level due to the corresponding changes that arise on the economic scenarios. The methodology is applied to corporate debts, but the extension proposed is flexible enough to be applicable to other securities as well.

The Same Bond at Different Prices: Identifying Search Frictions and Selling Pressures

I model how corporate bond prices are affected by search frictions and occasional selling pressures, and test my predictions empirically. A key prediction in my model is that in a distressed market with more sellers than buyers, the midprice (i.e. the average of bid and ask price) paid by institutional investors is lower than that of retail investors. Using a structural estimation, the model is able to identify liquidity crises based on the relative prices of institutional and retail investors. I identify two liquidity crises (i.e. high estimated numbers of forced sellers), namely the downgrade of GM and Ford in 2005 and the current crisis. I also estimate that search costs for institutional investors increase strongly during the subprime crisis, while search costs for retail investors appear stable. Finally, search costs have the highest impact on yields for bonds with short maturities according to the estimation.

Investment-Based Corporate Bond Pricing

A standard assumption of structural models of default is that firms' assets evolve exogenously. In this paper, we examine the importance of accounting for investment options in models of credit risk. In the presence of financing and investment frictions, fi rm-level variables that proxy for asset composition are significant determinants of credit spreads beyond leverage and asset volatility, because they capture the systematic risk of firms' assets. Cross-sectional studies of credit spreads that fail to control for the interdependence of leverage and investment decisions are unlikely to be very informative. Such frictions also give rise to a realistic term structure of credit spreads in a production economy.

What risks do corporate bond put features insure against?

Corporate bond prices are known to be influenced by default and term structure risk in addition to non‐default risks such as illiquidity. Putable corporate bonds allow investors to sell their holdings back to the issuer and may thus provide insurance against all of these risks. We first document empirically that embedded put option values are related to proxies for all three. In a second step, we develop a valuation model that simultaneously captures default and interest rate risk. We use this model to disentangle the reduction in yield spread enjoyed by putable bonds that can be attributed to each risk. Perhaps surprisingly, the most important reduction is due to mitigated default or spread risk, followed by term structure risk. The reduction in the non‐default component is present but rather small.

The Cross-market Effects of Stock Market System Risk Factors on the Corporate Bond Pricing: Empirical Study Based on the Panel Data Model

The research in capital asset pricing focuses on the pricing within the market, and the research on cross-market pricing are relatively small. Using corporate bonds in Shanghai and Shenzhen Stock Exchange from January 1st, 2001 to March 31st, 2010 as the sample, this paper investigates the cross-market effects of stock market system risk factors on the corporate bond pricing in China. The results shows that in the longer term and the lower the credit rating of corporate bonds, the stock market system risk factors receive higher risk compensation; system risk factors of stock market have strong cross-market effects on corporate bond yields; bond pricing structure model variables and target firm characteristics variables significantly affects the bond yield spreads. Key words: Systematic risk factor; Cross-market; Pricing; Corporate bonds Resume: La recherche en matiere de tarification des immobilisations se concentre sur les prix dans le marche, et la recherche sur la croisee du marche de prix sont relativement faibles. Utiliser des obligations d'entreprises a Shanghai et a Shenzhen Stock Exchange du 1er Janvier 2001 au 31 Mars 2010, comme l'echantillon, cette etude examine les effets croises de marche des facteurs de risque de marche d'actions sur le systeme de fixation des prix des obligations d'entreprises en Chine. Les resultats montrent que dans le long terme et la baisse la cote de credit des obligations de societes, les facteurs de risque du marche actions du systeme recevoir une indemnisation plus elevee de risque, les facteurs de risque du systeme des marches boursiers ont fortement effets croises sur les rendements des obligations d'entreprises; modele de la structure des prix obligataires variables et les variables caracteristiques de l'entreprise cible affecte de maniere significative les ecarts de rendement obligataire. Mots cles: Facteur de risque systematique; Croix¬ marche; Tarification; Obligations de societes

The CDS-Bond Basis Arbitrage and the Cross Section of Corporate Bond Returns

We provide a comprehensive empirical analysis on the implication of CDS-Bond basis arbitrage for the pricing of corporate bonds. Basis arbitrageurs introduce new risks such as funding liquidity and counterparty risk into the corporate bond market, which was dominated by passive investors before the existence of CDS. We show that a basis factor, constructed as the return differential between LOW and HIGH quintile basis portfolios, is a superior empirical proxy that captures the new risks. In the cross section of investment grade bond returns, the basis factor carries an annual risk premium of about 3% in normal periods. However, speculative grade bonds are not affected by the basis factor as they are not widely used in the basis arbitrage.

Pricing corporate bonds in an arbitrary jump-diffusion model based on an improved Brownian-bridge algorithm

We provide an efficient and unbiased Monte Carlo simulation for the computation of bond prices in a structural default model with jumps. The algorithm requires the evaluation of integrals with the density of the first-passage time of a Brownian bridge as the integrand. Metwally and Atiya suggest an approximation of these integrals. We improve this approximation in terms of precision. We show, from a modeling point of view, that a structural model with jumps is able to endogenously generate stochastic recovery rates. It is well known that allowing a sudden default by a jump results in a positive limit of credit spreads at the short end of the term structure. We provide an explicit formula for this limit, depending only on the Lévy measure of the logarithm of the firm-value process, the recovery rate and the distance to default.

Stochastic Optimization for Portfolios Consisting of Corporate Bonds in an Integrated Market and Credit Risk Framework

High credit spreads in 2009 have attracted a lot of interest from investors seeking higher yields outside of government bonds. Investment grade corporate bonds have indeed been a popular investment in 2009. The corporate bond market today is one of the largest and most liquid of the financial markets. Corporate bonds markets can be appealing as they are generally considered safer than stocks and they often provide higher yields and more liquidity than government bonds markets. After the World Financial Crisis central banks set interest rates at their historically low level affecting positively bonds’ prices. The question for a corporate bond portfolio manager is which decisions to take in order to hedge portfolio against volatility of interest rates. Additionally managers have to analyse the factors that affect bonds’ prices volatility and is due to credit risk. For this reasons managers have to implement a risk management framework in order to identify the factor that affect whole portfolio value and finally optimize its value. In an integrated market and risk perspective the future value of a corporate bond portfolio is decomposed into the risk that a bond issued by a firm downgraded by rating agencies and possible drives to default, the correlation between credit events, the risk that changes occur on the average spread of exposures with the same final rating as the firm and the effect of interest rate uncertainty.In chapter 1 we introducing the main types of bonds, analyzing how to valuate non-callable bonds and calculating their yielding and we present factors that affect bond process and price volatility when interest rates changes a bit in a parallel way.In chapter 2 we make an introduction to risk management by referring the risks that affect corporate bond prices. Then we explain the term structure of interest rates and how we can immunize a portfolio of bonds when interest rates changes in a parallel way. Then we introduce a multi-factor model for corporate bonds and present a portfolio immunization model based on factors to protect portfolio value against non-parallel changes of interest rates, introducing the appearance of shape risk.In chapter 3 we added an introduction of credit risk referring the main sources of credit risk in a portfolio of corporate bonds. Then we model credit risk based on a reduced-form approach which defines the default as the instantaneous likelihood of default, called the hazard rate. In chapter 4 we present an integrated market and credit risk framework using scenario generation in order later to optimize a corporate bond portfolio using stochastic programming models. Scenario generation is a tool to model the uncertainty. We develop a model for stochastic interest rates and credit spreads based on the Hull-White algorithm. Interest rates and credit spreads stochasticity based on extended Vasicek model and we produce scenarios of interest rates and credit spreads using trinomial lattice structures which capture the correlation between interest rates and default intensities. Finally we model the correlation between default and migration.In chapter 5 we present the necessity for Conditional Value-at-Risk as a coherent risk measure for corporate bond portfolios. The right risk measure is of paramount importance when we optimize corporate bond portfolios because of tail effects (heavy tails) in the distribution of returns that could result in significant losses and destroy portfolio efficiency. Then we present a linear program for minimizing portfolio risk using CVaR.In chapter 6 we implement portfolio optimization models using stochastic programming in a dynamic aspect. Initially we present an anticipative model where we only take into account stochasticity in future prices without taking recourse actions. Then we present a multistage recourse model where we can take recourse decisions at the preceding time periods based on information we take at discrete time in the future. We assume that there are transaction costs when we buy or sell bonds in order to make models more sophisticated. Finally we analyze one by one the equations of multistage recourse model.

Dissecting Corporate Bond and CDS Spreads

In this article, the authors propose a new method to estimate the components of corporate bond and CDS spreads. They develop a CDS pricing model with default and nondefault factors and a corporate bond pricing model with default, tax, and liquidity factors using the reduced-form approach, and they jointly estimate parameters of both models from the pooled data. By formulating default intensity as a common factor in the prices of the CDS and reference bonds, the authors are able to identify the default and nondefault components of yield spreads more precisely. They find that, on average, the liquidity premium accounts for about 20–25% of corporate yield spreads across ratings and the size of the liquidity premium increases as the rating decreases. Furthermore, they find that the CDS spread contains a nontrivial nondefault component. Ignoring this component in the CDS spread thus results in a serious bias in the estimate of spread components when using the CDS information to aid in decomposition of corporate yield spreads.

Dissecting Corporate Bond and CDS Spreads

In this paper, we propose an alternative approach to estimate the components of corporate bond and CDS spreads. We develop a CDS pricing model with default and nondefault factors, and a corporate bond pricing model with default, tax and liquidity factors using the reduced-form approach, and jointly estimate parameters of both models from pooled data. By formulating default intensity as a common factor in the prices of the CDS and reference bonds, we are able to identify the liquidity and other components of yield spreads more precisely. We find that on average the liquidity premium accounts for about 23% of the corporate yield spread and the size of the liquidity premium increases as the rating decreases. Furthermore, the CDS spread contains a significant nondefault component. Results show that ignoring the nondefault component in the CDS premium results in biased estimates of corporate yield spread components when using the CDS information to aid in decomposition of yield spreads.

Option Implied Volatilities and Corporate Bond Yields: A Dynamic Factor Approach

This paper estimates dynamic factors from the term structure of credit spreads and the term structure of equity option implied volatilities, and it provides a comprehensive characterization of the dynamic relationships among those credit spread factors and equity volatility factors. The paper finds strong evidence that the volatility factors, especially the volatility level factor, Granger cause credit spread levels, confirming the theoretical predictions of Merton (1974) in a significantly richer and more nuanced environment than previously achieved. Simultaneously, the paper also finds evidence of reverse Granger causality from credit spreads to equity volatility, operating through the slope factors, consistent with the market microstructure literature, which finds that price discovery often happens first in bond markets. Hence the results extend both the corporate bond pricing literatures, deepening our understanding of stock and bond market interaction and suggesting profitable trading strategies.

Momentum and Reversal Effects in Corporate Bond Prices and Credit Cycles

This article studies momentum and reversal patterns in corporate bond prices. The authors analyze returns on two momentum trading strategies—buying bonds with the best past performances (past winners) and buying bonds with the worst past performances (past losers). They consider formation and holding periods of 1 to 24 months. In the case of high-yield bonds, a strategy that buys past winners provides higher cumulative returns than a strategy of buying past losers over the 1998–2009 period. The authors show that this momentum pattern can be attributed to the behavior of credit spreads during a credit cycle. Specifically, the momentum effect is strongest during periods of widening credit spreads and dominates the reversal effect that can be observed during periods of decreasing credit spreads. Alternately, the prices of investment-grade bonds exhibit a reversal pattern, which is due to differences in the durations of the bonds. In this study, the authors also adjust the returns of these portfolios for realistic transaction costs, estimate their risk, and address possible issues of liquidity.

Corporate Bond Pricing and the Effects of Endogenous Default and Call Options

Recent structural models for valuing callable corporate bonds show that both callability and default options have important implications for the interest-rate sensitivity of yield spreads and the bond duration. Special attention is given to the interaction between the two risks. In this article, the authors test the main implications of these models. Specifically, they examine the interest-rate elasticity of the call spread and that of the default spread, allowing for interaction between both spreads. Furthermore, they examine the impact of both risks and their interaction on the effective duration of corporate bonds. They also test theoretical predictions regarding corporate bond sensitivity to firm value. Their findings support the predictions of the theory for bonds carrying a standard fixed-price call option and those carrying the newer make-whole option.

The Risk Microstructure of Corporate Bonds: A Case Study from the German Corporate Bond Market

Abstract This article presents joint econometric analysis of interest rate risk, issuer‐specific risk (credit risk) and bond‐specific risk (liquidity risk) in a reduced‐form framework. We estimate issuer‐specific and bond‐specific risk from corporate bond data in the German market. We find that bond‐specific risk plays a crucial role in the pricing of corporate bonds. We observe substantial differences between different bonds with respect to the relative influence of issuer‐specific vs. bond‐specific spread on the level and the volatility of the total spread. Issuer‐specific risk exhibits strong autocorrelation and a strong impact of weekday effects, the level of the risk‐free term structure and the debt to value ratio. Moreover, we can observe some impact of the stock market volatility, the respective stock's return and the distance to default. For the bond‐specific risk we find strong autocorrelation, some impact of the stock market index, the stock market volatility, weekday effects and monthly effects as well as a very weak impact of the risk‐free term structure and the specific stock's return. Altogether, the determinants of the spread components vary strongly between different bonds/issuers.

Default Prone Bond Prices, Valuable Growth Options and the Option to Re-Organize

There is a wide body of literature in corporate finance that examines the tradeoffs between liquidation and re-organization for creditors in financially distressed firms (Kahl (2002), Hotchkiss (1995), Gertner and Scharfstein (1991)). We incorporate salient elements from this literature into a structural model of corporate bond prices. We derive the value of perpetual coupon-paying risky debt as a function of the option held by bondholders to either liquidate or to take control when a firm becomes financially distressed. Liquidation value is the depreciated value of assets in place. Firm value under bondholders is with some efficiency loss, the sum of assets in place and future growth options. We derive ex-ante values of corporate bond prices as a function of the current values of these two competing choices.

The impact of bond rating changes on corporate bond prices: New evidence from the over-the-counter market

I study the information content of bond ratings changes using daily corporate bond data from TRACE. Abnormal bond returns over a two-day event window that includes the downgrade (upgrade) are negative (positive) and statistically significant, although the reaction to upgrades is economically small. Monthly abnormal bond returns around downgrades and upgrades are statistically significant but overstate the magnitude of the reaction relative to two-day abnormal returns. Unlike the bond market, the stock market reaction to upgrades is statistically insignificant. Evidence suggests that the differing inferences on the effect of upgrades in the two markets can be attributed to wealth transfer effects rather than relative market inefficiencies. In the cross-section, the bond market response is stronger for rating changes that appear more surprising, rating changes of lower rated firms, and upgrades that move the firm from speculative grade to investment grade.

Structural models of corporate bond pricing with personal taxes

The structural approach offers an integrated framework to deal with yield spreads and default probability simultaneously. However, structural models perform poorly in predicting corporate bond spreads. It is unclear whether this poor performance is caused by characteristics of individual models, missing factors, or different calibration procedures. This study evaluates the performance of four structural models by incorporating two important factors, personal taxes and the liquidity factor, and calibrating these models to data. To ensure our results are not contingent on the calibration method, we further apply the maximum likelihood estimation method to a large sample of individual bonds. Results consistently show that the ability of structural models to predict spreads improves considerably when personal taxes and liquidity are taken into account. Our findings suggest that the poor performance of standard structural models is more likely due to missing factors than the characteristics of individual models or the calibration procedure.

Corporate Social Responsibility: Is it Rewarded by the Corporate Bond Market? A Critical Note

The question of whether corporate social responsibility (CSR) has a positive impact on firm value has been almost exclusively analysed from the perspective of the stock market. We have therefore investigated the relationship between the valuation of Euro corporate bonds and the standards of CSR of mainly European companies for the first time in this article. Generally, the debt market exhibits a considerable weight for corporate finance, for which reason creditors should basically play a significant role in the transmission of CSR into the valuation of financial instruments. Given that socially responsible firms are often regarded as economically more successful and less risky, they should have lower risk premia. The results of the empirical analysis, however, reveal that based on an extensive data panel the risk premium for socially responsible firms – according to the classification by SAM Group – was ceterius paribus higher than for non-socially responsible companies. However, only one case of the models investigated was weakly significant. Thus, largely the relationship has to be classified as marginal; so CSR has apparently not yet been incorporated into the pricing of corporate bonds.

Flight to Quality in a Hierarchical Factor Model

We use a hierarchical factor model to study the behavior of yield curves derived from the market prices of corporate bonds issued by industrial companies and traded in the U.S. market. The sample is comprised by curves of different risk levels, which allows identifying four global forces and interpreting some of them as manifestations of flight to quality. The main contributions of this paper are detecting movements that can be assigned to flight to quality through a hierarchical factor model, an econometric tool not yet used in empirical studies about the phenomenon, and adding new insights to the literature about the driving factors of corporate curves.