Bond Credit Research Articles

How does informed trading affect credit bond spreads: Evidence from China's interbank bond market

China's interbank bond market is an institutional investor market, and transactions are more information-based. Whether and how informed trading can affect credit bond pricing is an urgent problem to be solved in the study of China's bond asset pricing. This paper uses credit bond issuance and trading data and stock high-frequency trading data from May 2014 to December 2020 to construct informed trading probability and bond liquidity indicators. Using regression analysis and adjustment and mediation effect test methods, this paper studies the impact of informed trading on China's interbank credit bond pricing and the channel role of liquidity. The results show that the probability of informed trading has a significant positive impact on credit bond spreads. Informed trading leads to an increase in credit bond spreads by amplifying bond illiquidity. The amplifying effect of informed trading on credit bond spreads is stronger for bonds with high illiquidity. The amplifying effect of informed trading on credit bond spreads will be stronger in private enterprises, enterprises with low information transparency, and high debt ratios. This study reveals the risk nature of informed trading in China's interbank bond market, which helps to deepen the understanding and management of the bond market.

What drives liquidity in the Chinese credit bond markets?

We study the drivers and pricing of liquidity in the Chinese credit bond markets. We document that the liquidity and liquidity effects priced into yield spreads differ significantly across the four major credit bond categories and the two parallel trading venues: the interbank over-the-counter and exchange markets. We analyze the levels of liquidity and the pricing of liquidity effects into credit bond yield spreads using three counterfactuals: a collateral shock to repo eligibility, a crackdown on agent-holding activities, and four liberalization shocks on foreign investment. We identify the bond risk and macroeconomic channels as significant influences on liquidity effects but not the information channel. Our empirical findings are robust to a battery of tests.

Exploring the mechanism of regional ecological legal governance's impact on corporate bond credit spreads

This study selects corporate bonds publicly issued in China's exchange market from 2012 to 2022 as the core analysis objects, aiming to deeply dissect the mechanism of how the regional ecological legal system affects corporate bond credit spreads. The research findings indicate that the establishment of intermediate environmental courts has effectively reduced investors' risk premiums for enterprises. Meanwhile, in the context of the establishment of these courts, environmental regulations have become a key factor in lowering corporate risk premiums, exerting a significant mediating effect.

Does the impact of credit rating downgrade on bond returns vary by region: Empirical evidence from China

Utilizing trading data from corporate and enterprise bonds that experienced credit rating downgrades between 2012 and 2022, this study employs event study methodology and regression analysis to examine the regional differences in the impact of credit rating downgrades on bond pricing and the mechanisms behind these effects. The study found that, during the window period when the bond credit rating is downgraded, there is a significant difference in the cumulative abnormal return of bonds between the eastern and non-eastern regions. Heterogeneity analysis indicates that bonds with higher credit ratings and those issued by non-state-owned enterprises are more significantly affected by credit rating downgrades. This study provides empirical evidence of regional disparities in the impact of credit rating downgrades, and proposes a theoretical mechanism whereby differences in the degree of marketization influence these effects through varying expectations of government implicit guarantees. The findings offer a theoretical foundation for optimizing decision-making by participants in the Chinese bond market.

Emerging Stock Market Integration and Corporate Bond Credit Spreads

ABSTRACT Stock market integration into the world financial markets has been a common and important practice in emerging countries over the past several decades. Relying on the staggered inclusion of China A-shares into MSCI indexes, we employ a difference-in-differences analysis and find that bond credit spreads of firms significantly decrease after the firms’ stock securities are included in the MSCI indexes. We also find that stock market integration reduces credit spreads by improving the stock liquidity, firm reputation, and alleviating information asymmetry. The effect is more pronounced among firms with greater financial constraints or higher performance volatility. Overall, our study provides evidence that emerging stock market integration can generate bond market benefits for firms.

Air pollution and issuance credit spread of municipal investment bond

This paper explores the impact of city-level air pollution on the financing costs of local and regional governments (LRGs) in China. The empirical results demonstrate that cities with poor air quality face higher credit spreads on bonds issued by local financing platforms (LFPs), underscoring the critical role of air quality in determining LRGs financing costs. Air pollution negatively affects the credit rating of municipal investment bonds and increases fiscal pressure on LRGs. However, when LRGs invest more in environmental protection, reduce reliance on tax revenue, enforce stricter environmental regulations, and implement auditing policy for natural resources management, the adverse effect of air pollution on bond credit spreads are mitigated. This study enriches the research on whether and how air pollution affects bond issuance pricing and provides insights into strategies for reducing LFPs financing costs and addressing LRGs debt crises.

A novel URP-CNN model for bond credit risk evaluation of Chinese listed companies

The effective identification of bond credit risk is critical for maintaining stability in the bond market and safeguarding investor rights. This paper proposes a URP-CNN model for evaluating bond credit risk of Chinese listed companies. This model effectively combines the unique advantages of the Unthresholded Recurrence plot in extracting and representing spatial domain association information, along with the powerful performance of Convolutional Neural Networks in image feature extraction and classification tasks, thus demonstrating outstanding overall performance in tackling the complex task of predicting default of listed company bonds. The research results show that the URP-CNN model constructed in this paper improves accuracy by 1 %–10 % and F1 score by 10 %–30 % compared to other methods, ensuring accurate identification of non-defaulting enterprises while effectively reducing Type II-Error occurrence rates. Furthermore, the combination of URP method and machine learning models significantly enhances model effectiveness. Compared to single models, models combined with the URP method show varying degrees of improvement in accuracy and F1-score numerical indicators.

Corporate climate risk and bond credit spreads

This study analyzes the impact of corporate climate risk on bond credit spreads using data from Chinese A-listed companies during 2007–2022. Utilizing textual analysis of annual reports, we construct firm-level climate risk indicators and identify a significant positive association between corporate climate risk and bond credit spreads, particularly for state-owned enterprises and high carbon-emitting companies. Mechanism analysis shows that heightened climate risk leads to higher operational risk and information opacity, indicating that greater investor compensation was required. These results provide new empirical evidence and insights into the factors influencing corporate bond financing costs.

The Influence of Liquidity on Bond Credit Ratings: Evidence from The Indonesian Corporate Bond Market

This study examines the effectiveness of various liquidity proxies in distinguishing between Investment Grade (IG) and High Yield (HY) bonds within the Indonesian corporate bond market. Utilizing logistic regression models across a dataset of 30,738 observations for IG bonds and 176 observations for HY bonds, we evaluated the impact of six liquidity proxies: Range Measure (RG), Hui Heubel ratio (HH), Market Share (MS), Interquartile Range (IR), Imputed Roundtrip Cost (IRC), and Trading Volume (TV). The findings reveal that the Imputed Roundtrip Cost (IRC) is the most reliable indicator of liquidity, demonstrating a significant negative relationship with the likelihood of a bond being classified as IG. This suggests that higher IRC values, which represent higher transaction costs, are associated with lower liquidity. In contrast, the other proxies, including the Hui Heubel ratio, did not show consistent or significant impacts in line with the hypotheses. The study concludes that IRC is the best measure for assessing liquidity in the Indonesian corporate bond market.

Social media and cost of debt financing: Evidence from stock forum text analysis

AbstractIn this article, we examine whether and how small investors’ social media activity is associated with subsequent bond credit spreads. We use extensive data from posts/comments on social media 30 days before the bond issuance announcement date to identify their implied power and find that the more posts/comments, the smaller the bond issuance spreads. We further find that information quality improvement of posts increases this negative relation between social media activity and bond cost, and that posts directly related to issuers’ fundamentals and/or debt financing drive our main results. Additional tests show that the effect is more salient when there is a greater demand for information quality or when macroeconomic conditions worsen.

Economic policy uncertainty and volatility of corporate bond credit spread: Evidence from China and the United States

In the prevailing situation of economic instability, it is customary for governments to enact economic policies aimed at influencing the decision-making processes of corporations. Nevertheless, the uncertainty surrounding economic policies inevitably impacts the capital structure of firms, consequently giving rise to fluctuations in corporate bond credit spreads through various transmission channels. Therefore, this study examines the impact of economic policy uncertainty (EPU) on the volatility of corporate bond credit spread in China and the United States (U.S.) from January 2014 to July 2021. Developing a one-sided filtering single-factor and multi-factor GARCH-MIDAS model in which monthly EPU and daily corporate bond credit spread are used as variables with different frequencies, the total volatility of corporate bond credit spread is decomposed into long- and short-term volatility components. Utilising the EPU data, encompassing indices delineating EPU in the U.S. (Baker et al., 2016) and China (Huang and Luk, 2020), alongside the corporate bond credit spreads in both the Chinese and American markets, we find that the level and volatility of EPU positively impact the long-term volatility of corporate bond credit spread with different ratings. Moreover, the EPU level contributes to more than 12% to the total volatility of corporate bond credit spread in the Chinese samples and more than 4.31% in the U.S. samples. While the variance of EPU contributes to over 5.19% to the total volatility of corporate bond credit spread in the U.S. samples, which is more than that of the Chinese samples.

New Regulation on Membership and Investor Shares in Credit Unions. Comparative Interpretation of Polish Law on Credit Unions

This paper analyses the 2023 amendment to the Act on Credit Unions of 9 November 2009 using dogmatic and comparative methods. First, the author considers membership of partnerships in credit unions in the context of the requirement of a common bond for membership. Second, the author analyses the legal status of investor shares, conditions of dividend payment on their basis, as well as their termination. In conclusion, the author indicates that Polish regulation on membership of partnerships requires establishing multiple common bond credit unions and that restrictions for holders of investor shares in credit unions are similar in Poland and the UK.

Predicting Credit Bond Default with Deep Learning: Evidence from China

Predicting Credit Bond Default with Deep Learning: Evidence from China

The Moderating Role of Leverage on Corporate Bonds Yield

This study aims to identify the effect of bond credit rating, firm size, profitability, and liquidity on the yield to maturity (YTM) of listed Indonesian corporate bonds, with leverage ratio as a moderating variable. A panel data multi-linear regression with the fixed effect estimator was used to investigate the YTM of 25 listed corporate bonds from 2019 to 2021. The sample data comprise complete financial reports published in the Indonesia Stock Exchange (IDX) market and operations in the non-financial sector to increase the accuracy of information obtained. The results show that profitability proxied to return-on-asset (ROA) and firm size positively affect the YTM, while the liquidity ratio proxied to the current ratio (CR) had a negative influence. As a moderating variable, leverage proxied to the debt-to-equity ratio (DER) positively moderates the effect of CR, DER negatively moderates the effect of ROA and DER cannot moderate the bond’s credit rating to influence the YTM. However, the bond’s credit rating does not affect the YTM. The analysis of corporate bonds is a relatively uncommon study in Indonesia, and significant implicating for policymakers, underscoring the importance of meticulous management of CR and DER, which can decrease the YTM.

Forecasting default risk of Chinese real estate credit bonds based on Bagging algorithm

In recent years, with Chinese rapid economic upgrading, it has also made the property industry more and more prosperous. However, due to the imbalance between supply and demand in China's real estate industry in recent years has led to an overly rapid rise in property prices, the risk of a real estate market bubble has increased, and many real estate companies have gradually defaulted on their bonds. Against this background, the aim of this paper is to construct a bond default prediction model using the Bagging algorithm in machine learning to predict the default risk of real estate bonds. And the results were also compared with Logistic model and SVM model, eventually it was found that Bagging algorithm can improve the prediction results more effectively. It is possible to identify real estate companies that may default on their bonds in advance, reducing investor losses, strengthening the risk prevention awareness of debt issuers, contributing to the healthy and stable development of real estate.

Information processing costs and credit ratings: evidence from investor interactive platforms in China

We examine the impact on bond credit ratings of reduced information processing costs from two investor interactive platforms in China, i.e. ‘Easy Interaction’ and ‘e-Interaction’. These online platforms provide investors with a channel to directly communicate with listed companies and learn much of corporate operations. Replies and explanations from management assist investors in integrating disclosed information and reducing information processing costs. The reduced costs likely impose reputational concerns on credit rating agencies (CRAs), leading to more stringent rating standards and less rating inflation. We find that more interactions result in lower credit ratings of corporate bonds. This effect is more pronounced for bonds rated by global-partnered CRAs and bonds whose issuers have higher information complexity, and less pronounced for bonds whose issuers have official consultation websites. Further analyses show that reduced information processing costs are associated with more information contents in rating downgrades and timelier ratings. Our findings provide evidence for the disciplinary effect of reduced processing costs on CRA behavior.

The impact of quality of investor protection disclosures on credit risk premium

The bond prospectus is an important source of disclosure for bond information, in which the quality of investor protection-related text conveys the issuer’s efforts on investor protection and risk management. We try to find out whether reader-friendly prospectus make investors process information more easily, which finally leads to lower credit premium. This study innovatively explores the impact of investor protection-related text quality on bond credit risk premiums, using a total of 6,025 Chinese listed corporate bonds from 2006 to 2022 as a sample for regression. The results show that the higher the Fog Index of investor protection disclosure, the higher the bond credit risk premium; the higher the boilerplate of investor protection disclosure, the lower the bond credit risk premium. Meanwhile, we further find the positive moderating effect of option-embedded bonds in the above relationships, and conclude that option-embedded bonds have stronger relationships between bond credit risk premiums and boilerplate or Fog Index than normal bonds. This study holds significant reference value for regulators to formulate policies and standardize information disclosure to ensure investors’ rights and interests.

IMPACTS OF NEW MONETARY POLICY TOOLS, BOND CREDIT SPREADS ON CORPORATES GREEN INNOVATION AND SUSTAINABILITY

IMPACTS OF NEW MONETARY POLICY TOOLS, BOND CREDIT SPREADS ON CORPORATES GREEN INNOVATION AND SUSTAINABILITY

MIȘCAREA COOPERATISTĂ INTERBELICĂ. STUDIU DE CAZ: OLTENIA

After 1919, the importance of bond credit cooperatives increased. For both the small rural producer and the civil servant, the people bank remained the most advantageous credit institution. In the first post-war decade, the most popular banks were in the Old Kingdom, and they had to be reinvigorated on the one hand, and, on the other hand, strengthened through attracting new funds. In the interwar period, the credit cooperatives from Oltenia granted loans, especially to those who used them for productive purposes: buying animals and land, purchasing tools and seeds, etc. After 1934, we noticed a huge demand for credit from the peasants, however, the central institutions asked for caution in contracting new debts, in order to avoid the situations encountered during the years of economic crisis.

Sustainability and credit spreads in Japan

Does the market value the environmental, social, and governance (ESG) performance of firms in corporate bond credit spreads? In this study, we construct the firm-level corporate bond credit spread based on the ‘bottom-up’ approach and examine the relationship between corporate ESG performance and credit spreads. Our results indicate that the ESG performance significantly decreases the credit spreads and the effects of ESG performance increase with the recognition of the importance of ESG investing regardless of the pillar. Furthermore, our analysis suggests differential trends across the issuing firms’ credit quality. Specifically, the ESG performance has a much higher impact on the credit spreads for lowly-rated firms, implying that the information on higher ESG scores could be a stronger signal for higher sustainability for those firms that are considered to have higher default risk from the financial information. Within the E, S, and G pillars, the resource use category, human rights category, and management category respectively show the most prominent annual lowering effects.