Estimating liquidity premium of corporate bonds using the spread information in on- and off-the-run Treasury securities

2017 ◽  
Vol 7 (2) ◽  
pp. 134-162 ◽  
Author(s):  
Haitao Li ◽  
Chunchi Wu ◽  
Jian Shi

Purpose The purpose of this paper is to estimate the effects of liquidity on corporate bond spreads. Design/methodology/approach Using a systematic liquidity factor extracted from the yield spreads between on- and off-the-run Treasury issues as a state variable, the authors jointly estimate the default and liquidity spreads from corporate bond prices. Findings The authors find that the liquidity factor is strongly related to conventional liquidity measures such as bid-ask spread, volume, order imbalance, and depth. Empirical evidence shows that the liquidity component of corporate bond yield spreads is sizable and increases with maturity and credit risk. On average the liquidity spread accounts for about 25 percent of the spread for investment-grade bonds and one-third of the spread for speculative-grade bonds. Research limitations/implications The results show that a significant part of corporate bond spreads are due to liquidity, which implies that it is not necessary for credit risk to explain the entire corporate bond spread. Practical implications The results show that returns from investments in corporate bonds represent compensations for bearing both credit and liquidity risks. Originality/value It is a novel approach to extract a liquidity factor from on- and off-the-run Treasury issues and use it to disentangle liquidity and credit spreads for corporate bonds.

Subject Emerging market corporate bonds enter bubble territory. Significance Strong appetite for higher-yielding emerging market (EM) assets this year has compressed corporate bond spreads the most since the global financial crisis, fuelling concerns of a bubble. The sharpest compression has occurred in Asia where spreads on the Asian component of JPMorgan’s benchmark EM corporate bond index have fallen below their mid-2014 post-crisis low. Low volatility and the enduring ‘search for yield’ are underpinning demand but the scope for a correction is increasing as valuations are increasingly stretched -- particularly in Asian high-yield, and in non-investment grade bonds -- while concerns are high about China’s crackdown on financial leverage. Impacts The dollar has erased its post-election gain; it may fall more in coming weeks. The oil price has risen 10% since May 9 on rising confidence that OPEC will extend output cuts but further increases will be limited. The ‘Vix’ equities volatility index, Wall Street’s ‘fear gauge’, is close to a historic low despite the political turmoil in Washington.


2020 ◽  
Vol 21 (4) ◽  
pp. 399-422
Author(s):  
Amira Abid ◽  
Fathi Abid ◽  
Bilel Kaffel

Purpose This study aims to shed more light on the relationship between probability of default, investment horizons and rating classes to make decision-making processes more efficient. Design/methodology/approach Based on credit default swaps (CDS) spreads, a methodology is implemented to determine the implied default probability and the implied rating, and then to estimate the term structure of the market-implied default probability and the transition matrix of implied rating. The term structure estimation in discrete time is conducted with the Nelson and Siegel model and in continuous time with the Vasicek model. The assessment of the transition matrix is performed using the homogeneous Markov model. Findings The results show that the CDS-based implied ratings are lower than those based on Thomson Reuters approach, which can partially be explained by the fact that the real-world probabilities are smaller than those founded on a risk-neutral framework. Moreover, investment and sub-investment grade companies exhibit different risk profiles with respect of the investment horizons. Originality/value The originality of this study consists in determining the implied rating based on CDS spreads and to detect the difference between implied market rating and the Thomson Reuters StarMine rating. The results can be used to analyze credit risk assessments and examine issues related to the Thomson Reuters StarMine credit risk model.


2017 ◽  
Vol 07 (02) ◽  
pp. 1750003 ◽  
Author(s):  
Edith Hotchkiss ◽  
Gergana Jostova

This paper studies the determinants of trading volume and liquidity of corporate bonds. Using transactions data from a comprehensive dataset of insurance company trades, our analysis covers more than 17,000 US corporate bonds of 4,151 companies over a five-year period prior to the introduction of TRACE. Our transactions data show that a variety of issue- and issuer-specific characteristics impact corporate bond liquidity. Among these, the most economically important determinants of bond trading volume are the bond’s issue size and age — trading volume declines substantially as bonds become seasoned and are absorbed into less active portfolios. Stock-level activity also impacts bond trading volume. Bonds of companies with publicly traded equity are more likely to trade than those with private equity. Further, public companies with more active stocks have more actively traded bonds. Finally, we show that while the liquidity of high-yield bonds is more affected by credit risk, interest-rate risk is more important in determining the liquidity of investment-grade bonds.


2012 ◽  
Vol 02 (02) ◽  
pp. 1250006 ◽  
Author(s):  
Frank de Jong ◽  
Joost Driessen

This paper explores the role of liquidity risk in the pricing of corporate bonds. We show that corporate bond returns have significant exposures to fluctuations in treasury bond liquidity and equity market liquidity. Further, this liquidity risk is a priced factor for the expected returns on corporate bonds, and the associated liquidity risk premia help to explain the credit spread puzzle. In terms of expected returns, the total estimated liquidity risk premium is around 0.6% per annum for US long-maturity investment grade bonds. For speculative grade bonds, which have higher exposures to the liquidity factors, the liquidity risk premium is around 1.5% per annum. We find very similar evidence for the liquidity risk exposure of corporate bonds for a sample of European corporate bond prices.


2014 ◽  
Vol 04 (01) ◽  
pp. 1450004 ◽  
Author(s):  
Marco Rossi

I propose a friction measure of bond round-trip liquidity costs that is robust to outliers and accounts for the idiosyncratic information behind trading decisions. Particularly effective with investment-grade bonds, the proposed measure displays properties consistent with the credit risk puzzle. Using transactions from January 2004 to December 2011, I find that liquidity costs display a strong correlation with credit conditions and peaked during the sub-prime crisis. After controlling for equity volatility with high-frequency measures, liquidity costs explain a substantial fraction of the variation in the yield spreads of highly rated bonds, but become less important for speculative-grade bonds.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huan Yang ◽  
Jun Cai

PurposeThe question is whether debt market investors see through managers' attempts to hide their pension obligations. The authors establish a robust relation between understated pension liabilities and corporate bond yield spreads after controlling for factors that have been previously identified as having a significant impact on firms' cost of borrowing. The results support the idea that bond market investors are not being misled by the use of high pension liability discount rates by some companies to lower their reported pension obligations. For a small fraction of debt issuers, the reported pension liabilities are larger than the pension liabilities valued at the stipulated interest rate benchmarks. For these issuers with overstated pension liabilities, bond investors adjust their borrowing costs downward.Design/methodology/approachThe authors investigate the relation between corporate bond yield spreads and understated pension liabilities relative to long-term Treasury and high-grade corporate bond yields. They aim to answer two questions. First, what are the sizes of over or understated pension liabilities relative to guideline benchmarks? Second, do debt market investors see through the potential management manipulation of pension discount rates? The authors find that firms with large understated pension liabilities face higher marginal borrowing costs after taking into account issue-specific features, firm characteristics, macroeconomic conditions and other pension information such as funded status and mandatory contributions.FindingsThe average understated projected benefit obligations (PBOs) are understated by $394.3 and $335.6, equivalent to 3.5 and 3.0% of the beginning of the fiscal year market value, respectively. The average understated accumulated benefit obligations (ABOs) are understated by $359.3 and $305.3 million, equivalent to 3.1 and 2.6%, of the beginning of the fiscal year market value, respectively. Relative to AA-grade corporate bond yields, the average difference between firm pension discount rates and benchmark yields becomes much smaller; the percentage of firm pension discount rates higher than benchmark yields is also much smaller. As a result, understated pension liabilities become negligible. The authors establish a robust relation between corporate bond yield spreads and measures of understated pension liabilities after controlling for issue-specific features, firm characteristics, other pension information (funded status and mandatory contributions), macroeconomic conditions, calendar effects and industry effects.Originality/valueS&P Rating Services recognizes the issue that there is considerably more variability in discount rate assumptions among companies than in workforce demographics or the interest rate environment in which firms operate (Standard and Poor's, 2006). S&P also indicates that it would be desirable to normalize different discount rate assumptions but acknowledges that it is difficult to do so. In practice, S&P Rating Services conducts periodic surveys to see whether firms' assumed discount rates conform to the normal standard. The paper makes an initial attempt to quantify the size of understated pension liabilities and their impact on corporate bond yield spreads. This approach can be extended to study firms' costs of equity capital, the pricing of seasoned equity offerings and the pricing of merger and acquisition transaction deals, among other questions.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nisful Laila ◽  
Sylva Alif Rusmita ◽  
Eko Fajar Cahyono ◽  
W.N.W. Azman-Saini

Purpose This study aims to analyze the determinants of ratings of corporate bonds and sukuk issued by firms listed on the Indonesia Stock Exchange (IDX) for the 2013–2019 period. Design/methodology/approach This study uses a quantitative approach by testing hypotheses and using logistic regression. Ordinal logistic endogenous (or dependent) variables (Y) in ordinal logistics use data in the form of levels (ordinal scale). Independent (or exogenous) variables (X), include financial and non-financial factors for dependent (or endogenous) variables (Y), namely, of corporate bonds and sukuk ratings. There are two approaches to the study they are Logit and Gompit (Negative Log-Log. The population of the study is Indonesian companies listed on the IDX that issued bonds and sukuk for the 2013–2019 periods. The sampling technique is purposive. In total, 16 corporate companies adhering to the above criteria and issuing bonds and sukuk were chosen. In total, 270 types of bonds and 280 types of sukuk were selected as samples. Findings The results of the Logit and Gompit regression show that leverage ratio, firm size, security structure and maturity date are important determinants of corporate bond ratings while profitability and liquidity ratios appear to have no influence on the rating. In the case of sukuk, profitability, liquidity and maturity date play important roles in influencing the corporate sukuk rating. However, there is no evidence to suggest that leverage ratio, company size and security structure may affect sukuk ratings. Research limitations/implications For both sukuk and bond issuers, it is necessary to pay attention to the factors that may affect the ratings. Specifically, Sukuk issuers need to pay attention to the return of asset, current ratio, growth and structure. On the other hand, bond issuers need to consider depth to equity, structure and maturity. As for investors, the findings of this study reveal that both bond and sukuk ratings reflect their performance. Practical implications This study provides useful information for investors that allows them to assess the risk of sukuk or bonds chosen based on rating and financial performance. Originality/value The novelty of this study lies in its econometric methodology used to identify factors which influence sukuk and bond ratings. Specifically, this study used two different techniques that allow a robust conclusion to be drawn. Furthermore, this study provides a systematic analysis which allows comparison between factors which affect bond and sukuk ratings in Indonesia.


2016 ◽  
Vol 42 (8) ◽  
pp. 830-848
Author(s):  
Mehdi Mili ◽  
Sami Abid

Purpose – The purpose of this paper is to examine the relationship between corporate governance (CG) and firms’ bond recovery rates (RRs). The authors hypothesize that governance features impact RRs by controlling agency costs that result from conflicts between bondholders and shareholders. The authors also test the relationship between CG and RRs during the last crisis. Design/methodology/approach – The authors use a generalized method of moments regression model to test the relationship between CG and firms’ bond RRs. The authors employ a direct measure of recoveries rates from Moody’s ultimate recovery database covering the period from 2003 to 2012. Both firm-level CG and country-level variables are used to examine the determinants of corporate bonds RRs. Findings – The results support a significant impact of CG mechanisms on bond RRs mainly during crisis period. The authors find that firms operating with CEO-Duality decrease their bond RRs during financial crisis. This implies wealth transfers from bondholders to shareholders and provides one explanation why some firms operate with weak governance. Originality/value – This paper provides the first direct evidence that corporate bond RRs are directly related to CG mechanisms. The authors combine firm-level CG and country-level variables to examine the determinants of corporate bonds RRs. Earlier studies focussed on financial firm-level data and macro-economic variables. The authors also test the impact of board composition and ownership structure on bond recoveries.


2018 ◽  
Vol 10 (4) ◽  
pp. 370-386 ◽  
Author(s):  
Zhongdong Chen ◽  
Karen Ann Craig

Purpose The purpose of this paper is to investigate the impact of January sentiment on investors’ asset allocation decisions in the US corporate bond market during the rest of the year. Specifically, the study evaluates if the shift in January sentiment is a predictor of corporate bond spreads from February to December. Design/methodology/approach Using corporate bond trades reported in TRACE between 2005 and 2014, the authors examine the ability of the Index of Consumer Sentiment and the Index of Investor Sentiment to predict bond spreads over the 11 months following January. The study evaluates both the sign of the change in sentiment and the magnitude of the change in sentiment using two generalized linear models, controlling for industry, bond and firm fixed effects. Portfolios are analyzed based on yield, firm size and firm leverage. Additional analysis is performed to ensure results are robust to the impacts of the subprime financial crisis. Findings This paper finds that the changes in the sentiment measures in January predict bond spreads associated with bond trades in the subsequent 11 months, and this phenomenon, which the authors label as the “January sentiment effect,” has opposing impacts on risky and less risky bond portfolios. Originality/value This paper adds to the literature on the relationship between sentiment and investor’s allocation decisions. The evidence documented in this study is the first known to find that investors’ allocation decisions in a year are driven by their sentiment in January.


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