Does institutional quality matter for domestic bond market development?

This paper explores the dynamic and distributional association between natural gas prices (NGPs) and the green bond market in a sustainable development context. The analysis employs a Quantile-on-Quantile (QQ) approach on monthly data between 2013 and 2025 to capture nonlinear and asymmetric interactions as well as state-dependent interactions between the two markets under varying market conditions. The findings indicate a bilateral intricate relationship. In the short run, NGP rises are likely to have a negative impact on green bond performance, indicating cost impacts and macro-financial risk in traditional energy markets. In the long run, the development of NGP becomes progressively shaped by the rise of sustainable finance together with the stepwise transformation of energy systems toward low-carbon configurations, ultimately bringing about a structural decline in fossil fuel dependence. In contrast, it is observed that the increase in the green bond market has a short-to-medium-term positive impact on NGP, which highlights the significance of natural gas as a transitional fuel in the energy transition. On the whole, the results indicate that, although green bonds are important in supporting sustainable development goals, their interplay with transitional energy markets like natural gas is nonlinear and changes over time. These findings provide key indications on how financial strategies can be realigned to accord with long-term sustainability goals.

In general, issues of organising trading and increasing transparency in the financial market, and in particular in the government bond market, are of paramount importance. Consequently, international organisations that regulate the securities market are developing specific standards and rules on these issues. These issues are of particular importance due to their significant impact on liquidity, efficiency, and risk in the market. From the perspective of public debt management policy, the latter are also of significance. The purpose of this analysis is to propose key areas for developing and improving this system in the Republic of Armenia. These recommendations are based on a study of international norms and experience in organising the secondary market for government bonds and transparency systems.

Abstract Current research on corporate bond default identification in China faces several challenges, including imbalanced default samples, complex hyperparameter configurations, and limited interpretability of the identification model. To tackle these issues, this study employs an interpretable machine learning framework, leveraging its efficient data-processing capabilities. Using samples of Chinese defaulted bonds from 2014 to 2024, the framework first applies the Synthetic Minority Over-sampling Technique (SMOTE) to alleviate classification bias resulting from sample imbalance. Subsequently, the Light Gradient Boosting Machine (LightGBM) is employed for feature selection and default bond identification, while the multi-objective optimization algorithm Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to optimize the hyperparameters of the LightGBM, thereby improving the model’s generalization capability. Finally, the SHapley Additive exPlanations (SHAP) method is adopted to interpret the marginal contributions of default factors to the identification outcomes. Experimental results show that the proposed model achieves an average identification accuracy of over 82.88% across four different prediction windows, with an average efficiency metric of 93.54%. Moreover, SHAP analysis reveals that risk factors such as the cash asset ratio play a critical role in default identification within China’s bond market. These findings confirm that the proposed approach not only makes the decision-making process of key risk factors interpretable but also offers regulatory authorities a scientific basis for policymaking, thereby supporting the development of targeted regulatory frameworks and enabling proactive intervention in high-risk bonds.

We present a new approach to commodity pricing that enhances accuracy by integrating four distinct risk factors: the spot price, stochastic volatility, convenience yield, and stochastic interest rates. We build on Yan [Valuation of commodity derivatives in a new multi-factor model. Rev. Deriv. Res., 2002, 5, 251–271], the only model to our knowledge that incorporates all four sources of risk, and extend it by adding a more flexible correlation structure that captures state-dependent co-movements and time-varying risk premia. A further contribution is the explicit inclusion of the stochastic interest-rate factor within a unified Kalman-filter framework, which allows us to jointly filter the state variables and estimate model parameters using both commodity and bond market data. An empirical analysis of crude-oil futures shows that our four-factor model captures the complex dynamics of the futures term structure and consistently outperforms existing benchmarks.

Disclosing risks and the financial impact of environmental, social, and governance (ESG) risk factors is a growing concern for organizations around the world. In the United States, climate-related financial risk disclosure has historically been state-specific; however, federal policies that impact state and local governments are changing that dynamic. Specifically, the Municipal Securities Rulemaking Board (MSRB), the municipal bond market regulator, has considered additional rules for ESG disclosure in the tax-exempt municipal market, which would affect all state and local government borrowers. In this paper, we review fifty-four public comment letters on ESG practices in the municipal securities market that were submitted during the MSRB’s ninety-day comment period (December 2021–March 2022) to identify the major themes that encompass the opinions of issuers, investors, and other market participants. Using reflexive thematic analysis, we analyze these public comments, which enables us to better understand the challenges facing state and local governments, as well as regulators, in dealing with ESG risks. Results show that respondents’ primary concern is the disclosure criteria for ESG-related information. The analysis highlights the diverse set of stakeholders that participate in the regulatory process and how their concerns differ from those of the issuers. We find the role of financial intermediaries and data providers to be significant in the formulation of ESG policy.

ABSTRACT China's green credit market and green bond market are governed by distinct regulatory frameworks, with significant divergence in their treatment of heavily polluting industries. This study explores how such regulatory misalignment affects the environmental effectiveness of green bonds. Our findings indicate that heavily polluting firms, constrained by stricter green credit policies, often resort to using green bonds for regulatory arbitrage. Consequently, these firms achieve only minimal environmental improvements after issuing green bonds. In contrast, lightly polluting firms exhibit substantial enhancements in their environmental performance. At the city level, the emission reduction effect of green bonds issued by lightly polluting firms is greater than that of heavily polluting firms. By manually collecting data on the usage of bond proceeds, we identify evidence of greenwashing. Specifically, heavily polluting firms are more likely to divert funds toward non‐green expenditures and debt repayment, as compared to lightly polluting firms. These findings emphasise the crucial impact of an integrated regulatory framework on the effective implementation of green finance policies.

ABSTRACT This study utilizes the Time-Varying Parameter Vector Autoregression (TVP-VAR) model to explore the dynamic impact of climate policy uncertainty on the green bond market, focusing particularly on the comparison among the three major regional markets, namely the United States, Europe, and Asia. Our findings indicate an overall negative correlation between climate policy uncertainty and the performance of green bonds, with significant time-varying characteristics and regional disparities. Across all regions, short-term responses are pronounced, temperate in the medium term, and eventually diminish towards near stability in the long term. The US and European markets respond similarly to climate policy uncertainty with Europe’s response faster and more pronounced. Conversely, the Asian market demonstrates a more sensitive and volatile short-term reaction. The market responses during three critical periods: the Sino-U.S. trade war, the COVID-19 pandemic, and the Russia–Ukraine war, are also discussed. Lastly, the impulse response between the three bond markets demonstrates that global green bond markets are interconnected, with the US market exerting dominant spillover effects on Europe and Asia, while Asia’s influence on global green finance trends is relatively weaker. These findings provide crucial insights for policymakers, investors, and market regulators as they navigate the intricacies of climate-related financial markets.

ABSTRACT The credit spread of green bonds—the “green premium”—fundamentally reflects the market’s monetary valuation of environmental benefits as a key financing instrument for green projects. This study constructs an environmental information disclosure (EID) quality index through content analysis and the entropy method to empirically examine EID’s impact on credit spreads in primary and secondary markets using data from China’s green bond market (2016–2023). The findings reveal that: (1) high-quality EID significantly reduces credit spreads; (2) environmental regulation can weaken the effect of EID in reducing credit spreads; (3) investor subscription willingness in the primary market and liquidity risk expectations in the secondary market mediate the relationship between EID and credit spreads; (4) heterogeneity analysis indicates that labeled green bonds, non-listed firms, and first-time issuers benefit more prominently from EID in lowering credit spreads; and (5) high-quality EID can also reduce the pricing discrepancy between the primary and secondary markets. The results have significant policy implications for improving the green bond market pricing efficiency and advancing sustainable finance.

ABSTRACT This paper studies how partisan alignment between city leaders and state governors shapes information processing and bond pricing in the municipal bond market. Using a novel data set on 1,045 U.S. cities from 2005 to 2019, we show that cities with the same political affiliation as the state governor face 9 basis points lower borrowing costs than misaligned cities. The effect is stronger for riskier bonds, in states where governors hold greater authority, and for fiscally dependent cities. Aligned cities also receive more aid during fiscal distress. Partisan alignment shapes how investors interpret and respond to financial information: Nondisclosure and adverse audit findings raise borrowing costs primarily for misaligned cities, while penalties for aligned cities are markedly smaller.

Inter-industry credit risk contagion based on a multiplex network: Evidence from China's bond market

Do green bonds boost corporate investment efficiency? Evidence from China’s mandatory bond market

From bonds to boundaries: Bond market liberalization and corporate tax avoidance in China

Does bond market liberalization mitigate corporate risk-taking? Evidence from China

ABSTRACT This paper develops a multi-country dynamic general equilibrium model to quantify how capital account liberalization influences the internationalization of the Chinese renminbi (RMB). The model features two major economies: the United States and China, and a continuum of small open economies. We incorporate two types of capital controls: price-based (e.g. transaction costs) and quantity-based (e.g. foreign ownership quotas) into household portfolio choices, along with frictions in trade finance that generate collateral demand. After calibration, we uncover three key findings. First, price-based controls exhibit nonlinearity effect: small reductions have little effect until a critical threshold is passed, after which RMB usage rises sharply—by about 20% in the baseline case, and up to around 27% with a larger bond market. Second, quantity-based controls also show threshold effects, with full liberalization raising RMB usage by 8–15%, depending on RMB bond market size. Third, expanding the supply of RMB-denominated bonds substantially boosts global adoption. Doubling bond supply increases RMB internationalization by roughly 30% points under tight capital controls, and around 55% when paired with full liberalization. These findings highlight the importance of jointly reducing cost frictions and expanding asset availability.

ABSTRACT The relationship between ESG performance and equity pricing has attracted considerable scholarly attention, but comparable research examining its effect on bond pricing remains comparatively underexplored. We study the impact of issuer ESG performance on the bond pricing in the Chinese primary corporate bond market and discuss the interaction between ESG and traditional credit rating in bond pricing. Based on 12,821 corporate bonds issued by 2218 listed and non-listed companies in the exchange market from 2019 to 2023, we find that better ESG performance significantly reduces bond issuance spreads. Mechanism analysis reveals that ESG performance affects the pricing of corporate bond issuance through both the incremental information effect and the fundamental effect. In the extended study, with the abolition of mandatory bond rating requirements for issuance in 2021, we find that ESG can have a corrective effect on credit rating. We also provide preliminary evidence on the impact of incorporating ESG performance into credit rating methodologies. These findings offer practical insights for investors, firms, and policymakers aiming to integrate ESG into risk management and financing strategies.

The objective of this study is to examine the predictive relationship between the China stock market and the bond market. With the worsening economic environment entering 2024-2025, the stock-bond linkage mechanism has played an increasingly important role in financial forecasts. But through the current forecasts, it has been noticed that the forecasts often ignore the systematic connection of market information between the markets. The construction of the model was focused on a VAR model with the return of the stock market as an exogenous variable, which was contrasted with the traditional ARIMA model, and the nature of the connection between the two markets was evaluated through Granger causality test, variance decompositions, and impulse responses. The outcome of the test showed the superiority of the VAR model in terms of the key predictive accuracy of the forecast, especially regarding the declining trend of the bond market yields. Overall, the findings suggest that the stock market exhibits significant leading and explanatory power over the bond market, indicating that integrating cross-market information can enhance forecasting accuracy and provide more effective quantitative support for asset allocation and risk early warning by leveraging leading indicators from the stock market.

Purpose This paper examines the market for insurance risk transfer via catastrophe bonds (CAT bonds), with a particular focus on the issuer's change in shareholder value. It addresses two gaps in the existing literature. Firstly, changes in risk composition over time in the CAT bond market are analysed, including an examination of innovative CAT bonds that cover risks such as cyber-attacks. Secondly, it examines how the sponsor's shareholder value reacts to the issuance of a CAT bond. Design/methodology/approach An event study evaluates the impact of CAT bond issuances on the sponsor's shareholder value. It analyses 118 bonds issued under Rule 144A since 2016. This is followed by a cross-sectional analysis. Findings Our findings challenge the prevailing view in the existing literature, indicating that CAT bond announcements are typically met with a negative market reaction. This can be explained by two factors: the high costs associated with these instruments, which often exceed the actuarial price of the risk, and the negative perception of CAT bonds among potential investors. The cross-sectional analysis reveals a negative impact of the relative issuance size, the size of the issuer and the risk multiple, as well as a positive influence of the number of issuances, the trigger selection and the issuer’s overall performance. Originality/value This study offers a novel perspective by identifying a negative market reaction to CAT bonds. It deepens our understanding of how issuance characteristics interact with market responses and provides insight into the complexities of CAT bond issuances.

We examine how climate-related (transition and physical) risks impact European bond markets and inflation expectations, and identify their effects across distinct volatility regimes using a Markov-switching vector autoregression model. Our central finding is that the transmission of climate-related risk shocks is highly state-dependent and primarily affects short-term inflation expectations. Transition risks have a limited, disinflationary effect on short-term expectations, but only during low volatility periods. In sharp contrast, physical risks exert a destabilising, inflationary impact during high volatility periods, depressing bond returns and amplifying market stress. Additionally, we observe two more patterns: first, that long-term inflation expectations tend to remain largely anchored. Second, financial linkages and contagion tend to intensify in the high volatility state. Our findings matter for asset pricing and for monetary authorities. They support integrating climate-related risks into stability frameworks, as these shocks presumably intensify and complicate the trade-off between inflation-target credibility and financial stability.

ABSTRACT The link between corporate bond credit spreads and secondary market illiquidity in the cross section has grown stronger since 2005, resulting in a higher liquidity component in credit spreads. Using U.S. investor holdings data, we show that short‐term investors (e.g., mutual funds/exchange‐traded funds [ETFs]) increase trading activities in the secondary market, amplifying the effect of secondary market frictions on prices. We provide a model featuring heterogeneous investors with different trading needs and heterogeneous bonds to investigate the impact of the rapid‐growing mutual fund/ETF sector on the corporate bond market. We find the change in investor composition can quantitatively explain the aggregate trend.