Search results

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.

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.

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.

This study aims to investigate the determinants of credit spreads in hotel loans securitized into commercial mortgage-backed securities (CMBS) between 2010 and 2015.

The sample represents 1,579 US hotel fixed interest rate whole loans with an aggregate mortgage value of $26.6bn at loan origination. The relationship between credit spreads and property, loan and market characteristic is examined via multiple regression analysis. Additionally, the method of 2-stage least squares is used to control for endogeneity bias and identify the effect of the loan-to-value (LTV) ratio on credit spreads.

The multiple regression models explain 80 per cent of the variation in credit spreads and show a significant association of credit spreads with hotel and loan characteristics and market conditions. The findings indicate the debt coverage ratio to be the most important predictor of credit spreads followed by the loan maturity term, implied capitalization rate, LTV and yield curve. The results show the debt yield premium to be a stronger predictor of credit spreads than the debt yield ratio. The spread between the debt yield ratio and mortgage interest rate could be used in future research as an instrumental variable to identify the effect of the LTV on credit spreads.

This study is limited to the CMBS market and the period after the financial crisis. Additional limitations include sample selection bias, exclusion of multi-property loans and variable interest rate loans.

Interest rate increases in an expanding economy would likely increase the cost of borrowing for hotel owners leading to higher debt service payments and lower profitability. If an increase in interest rates is offset by a decline in credit spreads, hotel owners will still benefit from the ensuing stability in borrowing interest rates. The evidence also suggests that CMBS lenders favor select service and extended stay hotels. Owners and operators of these efficient and profitable hotels will likely obtain loans with lower credit spreads given their lower risk of default.

The current study provides evidence on the effects of loan and property characteristics in the pricing of loan risk and serves to inform CMBS market participants about the factors that drive credit spreads in hotel mortgage loans.

The purpose of this paper is to derive a new option pricing model for options on futures calendar spreads. Calendar spread option volume has been low and a more precise model to price them could lead to lower bid-ask spreads as well as more accurate marking to market of open positions.

The new option pricing model is a two-factor model with the futures price and the convenience yield as the two factors. The key assumption is that convenience follows arithmetic Brownian motion. The new model and alternative models are tested using corn futures prices. The testing considers both the accuracy of distributional assumptions and the accuracy of the models’ predictions of historical payoffs.

Panel unit root tests fail to reject the unit root null hypothesis for historical calendar spreads and thus they support the assumption of convenience yield following arithmetic Brownian motion. Option payoffs are estimated with five different models and the relative performance of the models is determined using bias and root mean squared error. The new model outperforms the four other models; most of the other models overestimate actual payoffs.

The model is parameterized using historical data due to data limitations although future research could consider implied parameters. The model assumes that storage costs are constant and so it cannot separate between negative convenience yield and mismeasured storage costs.

The over 30-year search for a calendar spread pricing model has not produced a satisfactory model. Current models that do not assume cointegration will overprice calendar spread options. The model used by the Chicago Mercantile Exchange for marking to market of open positions is shown to work poorly. The model proposed here could be used as a basis for automated trading on calendar spread options as well as marking to market of open positions.

The model is new. The empirical work supports both the model’s assumptions and its predictions as being more accurate than competing models.

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 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 investigate the political cost hypothesis and the effects of political sensitivity-induced governance in the US bond market by using yield spreads from bonds issued by a diverse sample of US government contractors.

Fixed effects regression analysis is used to test the relation between the political sensitivity of government contractor firms and their cost of debt.

Results illustrated that government contractors with greater political sensitivity are associated with larger yield spreads, indicating that bondholders require a premium when firms endure the costs of increased political oversight and the threat of outside intervention, reducing the certainty of future income. However, despite the overall positive impact of political sensitivity on bond yield spreads on average, the authors found that the additional government oversight is associated with lower spreads when the firm is facing greater repayment risk.

Despite the benefits of winning a government contract, this paper identifies a direct financial cost of increased political sensitivity because of additional firm oversight and potential intervention. Importantly, it also finds that this governance is valued by bondholders when faced with increased risk. Firms must balance their desire for government receipts with the costs and benefits of dependence on those expenditures.

This paper contributes to the literature in its exploration of political sensitivity as an important determinant of the cost of debt for corporate government contractors. Specifically, the authors document a significant risk premium in bond pricing because of the joint effects of the visibility and importance of government contracts to the firm.

This paper aims to provide an empirical analysis of the macroeconomic determinants of sovereign bond yield spreads in the Eurozone from 2000 until August 2012, when the Outright Monetary Transactions programme was launched.

The authors constructed an unbalanced panel with quarterly data from 2000 Q1 to 2012 Q2 for the 12 Eurozone countries: Austria, Belgium, Finland, France, Germany, Greece, Ireland, Luxembourg, Italy, The Netherlands, Portugal and Spain. The authors propose a model that explains spreads through the main categories of variables observed in the literature. The relationship between variables is analysed using ordinary least squares and quantile regressions. As discussed by the authors, quantile regressions provide a more precise estimation, given the huge heterogeneity across counties that can be observed in the Eurozone.

Results show that the relationship between sovereign risk and macroeconomic fundamentals is affected by a strong country sentiment effect. The impact of country sentiment on sovereign risk is larger for those countries that were already experiencing higher spreads. Regardless the impact that European Central Bank’s (ECB) intervention had on sovereign risk from 2012, quantile regression results suggest that policy recommendations and goals should be adapted to each country’s market perception.

The results obtained improve on previous findings on this topic (De Grauwe and Ji, 2012) in two ways. First, they show that even introducing every category of determinants found in the literature in the main specification, fundamentals can only partially explain the evolution of sovereign risk in the Eurozone. Second, they find there is a country-sentiment effect that affects the relationship between macroeconomic indicators and sovereign risk. Furthermore, the paper finds that the country-sentiment effect is larger for countries facing high spreads.

This paper aims to examine the role of term spreads to predict domestic output and inflation in Malaysia, a country with a relatively less-developed bond market.

The paper uses regression time-series regressions and probit models that control for past values of the dependent variable to determine the forecast performance of term spread on inflation and output in Malaysia.

The paper finds that term spread contains little information about future output and inflation at short horizons. Moreover, the usefulness of term spread to play a greater role in monetary analysis beyond conventional indicators in the case of Malaysia is limited. The degree of usefulness of term spread impediment could be attributed to the relatively fragmented, illiquid and captive bond market characteristics as compared to what is available in more matured and developed markets.

It is useful to incorporate technical and model-based approaches using yield curves beyond the usual indicator analysis from the policy point of view. Models could be used in tandem with other monetary and financial indicators to support discussions on the direction of monetary policy.

An efficient bond market could also play an important role in propagating monetary impulses via the relevant monetary transmission channels. Based on the findings, the paper suggests that there is a strong case to deepen domestic bond market. This would greatly enhance price discovery among market participants, improve risk management away from the traditional source for funds (i.e. banking system) and address supply-related issues.