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This paper selects the data of corporate bond from 2005 to 2019, then divides them into long term bond and short term bond according to maturity of bond. Climate risk is found have significant impact on long term bond yield. Climate risk has no significant impact on short term bond yield. Callability has significant effect on both long term and short term bond yield, while callability has large effect on short term bond and relatively small effect on long term bond. The resale has significant effect on both long term and short term bond yield. The significant effect of the resale on short term bond yield explains large part of the short term bond yield. Issuance has significant impact on both long term and short term bond, with larger impact on short term bond yield. Maturity has significant effect on the yield of both long term and short term bond, and the effect is larger for short term bond. Bearish sentiment is negatively and significantly related to long term bond yield, but has no significant effect on short term bond yield. Credit ratings have large impact on long term bond yield and explain large part of this. However, credit ratings have no significant effect on short term bond yield. [ABSTRACT FROM AUTHOR]

In this paper we collect data of corporate bonds and government bonds issued from 2005 to 2019 from CSMAR database. Firstly, we make a stepwise regression analysis and research on the impact of climate risk, selling back and cross-market transaction on corporate bond yield. The impact of climate risk on corporate bond yield is positive because if carbon dioxide emission is more, the earth will be warmer and sea levels will be higher, then companies will face more climate risks and corporate bond yields will increase. The impact from the selling back on corporate bond yield is negative because if the bond can be resold, the risk will be lower and the bond yield will decrease. The impact of cross-market transaction on corporate bond yields is positive because if corporate bonds cannot be traded, the liquidity of corporate bonds will be low, and the risk will increase, then corporate bond yield will increase. Secondly, logarithmic regression analysis of climate risk factors shows that the climate risk is still significant and the model fits well. Selling back, cross-market trading and other factors are significant, and the pattern is more significant. Compared with the original model, it can better explain corporate bond yield. [ABSTRACT FROM AUTHOR]

This paper studies the impact of climate risk on the yields of corporate bonds with different credit ratings. We find the impact of climate risk on AAA rated corporate bonds. When climate risk increases, the yield of AAA rated corporate bonds increases. But it explains only a tiny fraction of corporate bond yields. The model is more significant after taking the logarithm of climate risk. After maturity is added to the model, both the impact from climate risk and from maturity on the yield of AAA rated corporate bonds is significant. But the impact of climate risk on AA+ corporate bond yields is not significant and the impact of selling back on the yield of AA+ corporate bonds is significant and negative. When the selling back increases, the yield of AA+ corporate bonds decrease. The impact from the issuance on the yield of AA+ corporate bonds is significant and positive. When the issuance increases, the yield of AA+ corporate bonds increase. For AA rated corporate bonds, the impact from the independent variables on the yield of AA rated corporate bonds is not significant. Model does not hold. [ABSTRACT FROM AUTHOR]

Large corporations usually cover their capital and operating expenses by issuing bonds with fixed rates and different maturities. This paper proposes a multistage stochastic programming (MSP) model with multiple objectives to optimize bond issuance by satisfying the three common objectives of corporate managers, as follows: (i) Minimizing expected discounted cost under cash liquidity and financial leverage risk constraints. (ii) Minimizing financial leverage risk under expected discounted cost and cash liquidity risk constraints. (iii) Minimizing cash liquidity risk under expected discounted cost and financial leverage risk constraints. We measure liquidity risk as conditional payment-at-risk (C P a R), according to the corporation's financial characteristics. Financial leverage risk is captured by conditional financial leverage-at-risk C F L a R , which we design based on conditional value-at-risk (C V a R). Through empirical analysis of a company in China, we explore the efficient frontier curves for the three above objectives and provide the corresponding issuance compositions of an optimal bond portfolio. Our MSP model offers guidance for corporations on achieving a trade-off between cost and risk when issuing corporate bonds. [ABSTRACT FROM AUTHOR]

This paper selects weekly transaction data from the Shenzhen Exchange and Shanghai Exchange for 2012 to 2018 to investigate factors including corporate size, the ration of book-to-market, default risk, term and credit rating that influence the corporate bond spread. It can be concluded that small firms prefer to issue high yield spread bonds while large firms issue bonds with low yield spreads. High (low) book-to-market firms issue high (low) yield spread bonds. The most important factors influencing corporate bond spread yield are default risk, terms, and credit ratings. We suggest that China Securities Regulatory Commission should encourage small firms to issue corporate bonds and there should be more kinds of credit ratings bonds in China bond market. [ABSTRACT FROM AUTHOR]

This paper proposes a defaultable bonds pricing model extending the traditional spread process definition. The posited model is able to incorporate any potential cyclical, non-linear, or long-term process not fully captured by the stochastic behavior of the spot rate and the instantaneous default rate process. Under this framework, we analyze the empirical ability of our model to capture the spread dynamics of three different Investment-grade US Corporate bonds indexes. Our findings show that when compared to the Benchmark, our model improves the empirical performance reducing the yield spread mispricing by 35%, 37%, and 29% for the High grade, Upper medium grade, and Lower medium grade index, respectively. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of multidimension liquidity, credit risk, and the interaction between liquidity and credit risk on corporate bond spreads based on a large transaction data set from July, 2006 to June, 2016, including the monthly data of 3716 bonds in China. Our main findings reveal that liquidity premiums are the main parts of corporate bond spreads. The interaction between liquidity and credit risk plays a significant role in determining corporate bond spreads. In addition, the differences between the interbank market and the exchange market have a significant impact on corporate bond spreads in normal period, and the interaction between liquidity and credit risk has an enhanced impact on corporate bond spreads during financial crisis. We also find that the interaction between liquidity and credit risk will increase with the increase of liquidity risk and credit risk and it is a time-varying dynamic process. [ABSTRACT FROM AUTHOR]

The role of green financing in propelling corporate green transformation and sustainable growth has attracted a lot of interest. Regarding their function in promoting corporate green transformation, green bonds—a crucial part of green finance—pose an important research question. This study, targeting Chinese A-share listed corporates, employing double machine learning models, aims to delve into the impact and mechanisms of green bond issuance on corporate green transformation. The findings indicate that issuing green bonds significantly drives corporate green transformation, especially in state-owned, smaller-scale, and non-manufacturing firms, where the impact is more evident. Further analysis discloses that green bond issuance primarily facilitates corporate green transformation through its functions in green investment and financing, green regulatory compliance, and green governance. This study serves as a theoretical reference, guiding businesses in seizing emerging opportunities in the green bond market and actively undertaking green transformation projects, thereby catalyzing a comprehensive economic transition. [ABSTRACT FROM AUTHOR]

From the angle of research and development (R&D) input, this paper analyzes how bond financing affects corporate total factor productivity (TFP). Based on the 2007–2019 data on listed enterprises, the influence and action mechanism of bond financing on corporate TFP were empirically examined. The results show that bond financing significantly boosts corporate TFP. The mechanism analysis reveals that bond financing promotes TFP by stimulating corporate R&D input. The research sheds new light on the relationship between finance and TFP from the perspective of bond financing and provides a reference for policymakers to boost corporate TFP by promoting bond financing. [ABSTRACT FROM AUTHOR]

This study investigates the factors impacting the price difference between the interbank market and the exchange market for the same bond using a large transaction dataset from July 2006 to June 2016 in China. We find that market liquidity and macrofactors mainly affect the price difference between the two markets for the same bond. And individual bond liquidity explains only a small part of the price difference. We also find that the interaction between liquidity and credit risk is an important factor affecting the price difference, and the effect is greater during financial crisis. [ABSTRACT FROM AUTHOR]

This paper explores the pricing implications of green bonds in the Chinese corporate bond market. We document a large greenium in the Chinese green bond market, whereby green bonds are issued at lower offering yield spreads in the primary market and traded at lower yields in the secondary market. The magnitude of the Chinese greenium is substantially greater than other international green bond markets. Exploring the underlying mechanisms, we document convincing evidence that mitigation of information asymmetry and exposure to salient environmental stimuli such as air pollution are plausible explanations of the greenium. • Green certification has pricing implications in the Chinese corporate bond market. • This study documents a greenium in the Chinese bond market. • Green bonds are issued at lower offering yield spreads in the primary market. • Green bonds are traded at lower yields in the secondary market. • The Chinese greenium is greater than other international green bond markets. [ABSTRACT FROM AUTHOR]

Sustainability-Linked Bonds (SLBs) are a new type of general corporate purpose bond in which payments are tied to an issuer's sustainability key performance indicators (KPIs) with respect to the environmental, social, and governance (ESG) criteria. The structure is complementary to green bonds. The Tesco SLBs are linked to the firm's ability to cut its greenhouse gas emissions by 60%. The priority is to reduce its reliance on nonrenewable grid electricity, which contributed 65% of Tesco's global carbon emissions footprint. Tesco accounts for 1% of electricity demand in the UK. Failure to meet the goals will result in a coupon step-up by 25 basis points on the last three coupons. The aim of our study is to investigate the presence of, how we call it 'ESG spread', marked by negative yield difference between SLB and regular bonds. It is something similar to 'greenium', that is, a premium paid by bondholders for green bonds when compared to nongreen bonds. We compare the bid and ask yields of SLBs with the interpolated yields, calculated for the yields of Tesco and Carrefour notes. Then, we look into the SLB yields in coupon step-up scenario to answer the question if the issuer's failure to keep up with KPIs results in changing of ESG spread from negative to positive. [ABSTRACT FROM AUTHOR]

Abstract: In this article we introduce a scoring system (EMS Model) for Emerging Corporate Bonds. The scoring system provides an empirically based tool for the investor to use in making relative value determinations. The EMS Model is an enhanced version of the statistically proven Z-Score model. Unlike the original Z-Score model, our approach can be applied to nonmanufacturing companies, and manufacturers, and is relevant for privately held and publicly owned firms.The adjusted EMS Model incorporates the particular credit characteristics of emerging markets companies, and is best suited for assessing relative value among emerging markets credits. The model combines fundamental credit analysis and rigorous benchmarks together with analyst-enhanced assessments to reach a modified rating, which can then be compared to agency ratings (if any) and market levels. We have included a summary of Mexican companies for which we have applied the EMS Model. We have included in this a description of Mexican company credits, first from prior to the Mexican crisis (1994) then followed, in some cases, to a more recent date. [Copyright &y& Elsevier]

This paper analyzes the impact of corporate junk bond offering announcements on stock prices for a sample of 680 issues of below investment grade bonds, during the 1976-1989 period. The sample shows a -1.0% cumulative abnormal return (CAR) for a two day event window period, and the zero CAR hypothesis is rejected with 99% confidence. The cumulative abnormal returns are negative and significant for combined announcements of bond and equity issues (CAR of -2.10%), and for announcements of convertible bond issues (CAR of -1.24%). Announcements of issues of straight bonds (CAR of -0.24%) are not significantly different from zero. Differences in CARs are observed across subsamples formed on the basis of size of the issuer, relative size of the issue, rating of the issue, name of the underwriter, market value of the issuer, and year of issue, but these variables are not significant when used in cross sectional regressions. The only variables with some explanatory power in those regressions are the ones indicating type of the issue, recession periods, and the dummy used to identify announcements made in 1976 (the first year junk bond issues were allowed). [ABSTRACT FROM AUTHOR]

Credit risk modeling by debt pricing has been a popular theme in both academia and practice since the subprime crisis. In this paper, we devote our study to the indifferent price of a corporate bond with credit risk involving both default risk and credit rating migration risk in an incomplete market. The firm's stock and a financial index on the market as tradable assets are introduced to hedge the credit risk, and the bond price is determined by the indifference of investors' utilities with and without holding the bond. The models are established under the structural framework and result in Hamilton–Jacobi–Bellman (HJB) systems regarding utilities subject to default boundary and multiple migration boundaries. According to dynamic programming theory, closed-form solutions for pricing formulas are derived by implementing an inverted iteration program to overcome the joint effect of default and multiple credit rating migration. Therefore, with the derived explicit pricing formulas for the corporate bond, the models can be easily applied in practice, and investors can generate their strategies of hedging the credit risk by easily analyzing the impacts of the parameters on the bond price. [ABSTRACT FROM AUTHOR]

• Presents a new multicriteria approach. • Enables a preference disaggregation approach on the TOPSIS-Sort method. • Presents a numerical validation for the proposed method. • Improves decision process by reducing cognitive efforts to establish parameters. • Evaluate Brazilian corporate bonds based on financial statements. This paper presents a new version of the TOPSIS method for sorting problems. The proposed method, called Preference Disaggregation on Technique for Order of Preference by Similarity to Ideal Solution - Sort (PDTOPSIS-Sort), is based on nonlinear programming for inferring parameters and uses expert's holistic evaluations. The existing TOPSIS-Sort method demands a significant number of parameters from the expert, including the definition of boundary profiles and weights. The proposed method contributes to the literature by relieving the demand for cognitive effort observed in prior methods. Instead of providing boundary profiles for the limit between every two consecutive classes, the expert provides decision examples. In addition, the specification of weights is not required. A numerical validation of PDTOPSIS-Sort was undertaken based on results previously obtained from the literature for TOPSIS-Sort, which has been presented in detail as supplementary material. In addition, the first analysis of Brazilian corporate bonds supported by an MCDM/A model is presented. To do so, data were collected from the financial statements published by the issuers of these bonds. In total, the method proposed classified 50 debentures and the results were consistent with the preferences of the decision-maker, an investment-banking expert. [ABSTRACT FROM AUTHOR]