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This study aims to investigate how high-speed railway (HSR) development affects urban construction investment (UCI) bond yield spreads based on China’s background.

This study constructs a quasi-natural experiment and adopts regression analyses to empirically examine the relation between HSR development and UCI bond yield spreads. The empirical analysis is based on a Chinese sample of 15,109 bond offering observations from 2008 to 2019.

The results show that HSR development reduces UCI bond yield spreads. Mechanistic analysis shows that HSR development increases land prices and the level of urbanization, which in turn lowers the UCI bond yield spreads. In addition, the impact of HSR development on UCI bond yield spreads is more significant at higher marketization levels and lower degrees of dependence on land finance cities where UCI corporations are located.

The results imply that transportation infrastructure improvement, such as HSR development, helps to enhance the credit of local governments and the solvency of UCI corporations and ultimately reduces the financing cost of UCI bonds.

This paper provides theoretical support and empirical evidence for the impact of transportation infrastructure construction on the implicit debt risks of local governments in China, which enriches the research on the “HSR economy” from a micro perspective and expands the research on the influencing factors of local governments’ debt risk.

The purpose of this paper is to investigate two research questions: do accounting reports provide information that helps bondholders assess credit risk of financial institutions? What are the relevant accounting variables related to financial institutions’ credit spreads?

The authors estimate all models of credit spread by specifying fixed effects with year dummies.

The authors’ document that financial institutions’ cash flows and loan loss provisions (LLP) are significantly correlated with bond spreads. The authors observe that an increase in nondiscretionary LLP predicts an increase in credit spreads, as the former reflects a higher default risk. Bondholders also react negatively to an increase in discretionary LLP, viewed as evidence that a financial institution is engaged in opportunistic earnings or tax management. Finally, the authors demonstrate that the relationship between accounting data and credit spreads is stronger for high-yield bonds than for low-yield bond.

This study has certain limitations due to the sample size and data frequency.

First, this paper provides strong evidence to all market participants that financial accounting reports are useful in forecasting credit risk in emerging markets. Second, the paper highlights the importance of disclosure policies and accounting transparency of financial institutions in emerging markets. Third, the results are also of practical interest to standard setters and financial regulators. The latter should consider monitoring accruals, especially the discretionary component of LLP, to mitigate the effects of accounting manipulations and managers’ opportunism.

First, the previous literature does not focus on financial institutions despite their key role in the economy. Second, the paper is the first to study the credit relevance of accounting information in emerging markets (Tunisia).

The 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.

The 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.

The 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.

S&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.

The purpose of this paper is to investigate whether the bond market disciplines all banks equally, in the sense of demanding the same relative risk premium across banks of different risk over the business cycle.

To test this hypothesis, the paper compares the difference between the credit spreads in the primary market of bank and firm bonds with the same credit rating issued during expansions with that same difference of spreads for bonds issued during recessions.

The paper finds that during recessions investors demand higher risk premiums. Importantly, the paper finds that the impact of recessions is not uniform across banks – it affects riskier banks more than safer ones. In other words, in recessions investors are relatively more demanding on riskier banks than on safer ones.

These findings are novel. They also have important policy implications because they show that a bond‐issuance policy aimed at promoting market discipline could affect the relative funding costs of banks over the business cycle. They also indicate that the information which can be extracted from the credit spreads on bank bonds varies across banks for reasons unrelated to their risk.

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.

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.

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.

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.

This paper aims to analyze how banks transmit shocks that hit the debt market to their borrowers. Recent financial crisis demonstrated that the banking system can be a pathway for shock transmission.

Bank-level panel regressions.

This paper shows that when banks experience a shock to the cost of their bond financing, they pass a portion of their extra costs or savings to their corporate borrowers. While banks do not offer special protection from bond market shocks to their relationship borrowers, they also do not treat all of them equally. Relationship borrowers that are not bank-dependent are the least exposed to bond market shocks via their bank loans. In contrast, banks pass the highest portion of the increase in their cost of bond financing to their relationship borrowers that rely exclusively on banks for external funding.

These findings show that banks put more weight on the informational advantage they have over their relationship borrowers than on the prospects of future business with these borrowers. They also show a potential side effect of the recent proposals to require banks to use CoCos or other long-term funding.

The findings are timely, given the ongoing debates on the proposals to introduce bail-in programs and proposals to require banks to use CoCos or other long-term funding.

Credit spread change is a key issue for investors to earn the excess return from corporate bonds. Generally, there are two kinds of different effects that support the changing of credit spread: asset allocation effect and credit risk change effect. The existing literature based on US data supports credit spread change is driven by credit risk change; however, this issue based on Chinese market data has not been investigated clearly. This paper seeks to address this issue.

The authors adopt Markov regime switching model to investigate the changing mode of the credit spread in the Chinese bond market. They select three kinds of variables: the credit risk variables, the asset allocation variables and the liquidity condition variables. With ML estimators, the authors can find the changing mode and further they study the relationship between the regime switching and some observed variables, such as macro economy variables and turnover of stock market.

The authors find it is driven by asset allocation effect in most time and by credit risk change only in shorter period. Empirical results show that the switching of dominance from one effect to another isn't closely related with macro‐economy variables, but related with the turnover of stock market.

These results indicate that in China the credit risk of corporate bonds is relatively low and the corporate bonds are still auxiliary asset for investors.

In this paper, the authors have the following two contributions: first, they discuss the asset allocation effect in the Chinese bond market and introduce the stock market variables and bank credit variable to describe the asset allocation effect; second, based on Chinese bond market data, they find different findings from the existing literature about US and European bond markets, showing that the changing of credit spread is mostly related with asset allocation effect but not credit risk change.

The purpose of this paper is to estimate the effects of liquidity on corporate bond spreads.

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.

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.

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.

The results show that returns from investments in corporate bonds represent compensations for bearing both credit and liquidity risks.

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.

The purpose of this paper is to model the components of credit risk in primary debt markets and evaluate changes in these factors in times of crisis.

The authors use a unique dataset consisting of nearly 163,000 new loans and bond issues in the USA and internationally during the period January 1992 through December 2005.

The authors find that credit spreads are related to market liquidity, best represented by total proceeds, ratings and the interaction between maturity and rating. The authors control for various crisis periods, including regional financial crises and find that spreads generally increased in response to the Asian Crisis with the international markets exhibiting the larger increases. There is mixed evidence of asymmetric effects of shocks. In the US loan markets, the adjustment factor reduces forecast variance (Θ1<0). In contrast, the adjustment factor is not significant for US bonds, possibly indicating a more rapid adjustment and greater efficiency in this market. The opposite effect is seen in the international loan and bond markets with Θ1>0, indicating a persistent increase in spread volatility.

The paper extends our understanding of the components of primary credit spreads and the interactions between primary debt markets during crisis periods.

Although the pervasive influence of investor sentiment in equity markets is well documented, little is known about behavioral manifestations in bond markets. In this paper, we explore the impact of investor sentiment on corporate bond yield spreads. Our results reveal that bond yield spreads co‐vary with sentiment, and sentiment‐drivenmispricings and systematic reversal trends are very similar to those for stocks. Bonds appear underpriced (with high yields) during pessimistic periods and overpriced (with low yields) when optimism reigns. Consequent reversals result in predictable trends in post‐sentiment yield spreads.When beginning‐of‐period sentiment is low, subsequent yield spreads are low; high sentiment periods are followed by high spreads. High‐yield bonds (low ratings, Industrials and Utilities, extreme maturities or low durations, specially if low rated) demonstrate greater susceptibility to mispricings due to sentiment compared to low‐yield bonds. The incremental yield spread gap between highand low‐yield bonds converges subsequent to periods of low sentiment, and diverges after high sentiment. Equity attributes marginally influence the impact of sentiment on bond spreads, but mostly for distressed bonds only.