This paper provides a comprehensive analysis of excess returns specific to corporate bonds. We construct a measure of excess returns that uses synthetic Treasury securities with identical cash flows as benchmarks, thereby fully removing interest rate effects and isolating the component of returns specific to corporate bonds. Using a monthly sample from 2002 to 2024, we find that, in addition to being lower on average, the corporate-bond-specific excess return differs significantly in the cross section from both the standard excess return based on T-bills and the duration-adjusted return. We further examine the effects of a broad set of bond-level characteristics and systematic risk factors on bond excess returns. Together, these findings provide a foundational benchmark for future research on corporate bond returns.

Serving on the official unsecured creditors' committee (UCC) of a bankrupt firm provides hedge funds with access to material nonpublic information (MNPI), which can facilitate their informed trading across firms and asset markets. We find that hedge funds increase equity turnover and execute more large trades in the quarters following UCC membership. In contrast, hedge funds do not exhibit such trading behavior after accessing public information about bankrupt firms or holding the bankrupt firm's debt without committee involvement. Importantly, these large trades often target firms with close economic ties to the bankrupt entity. Returns from these MNPI-driven trades are substantial.

I study whether workplace smoking bans change how bond investors assess firm risk. Using staggered state adoption across U.S.\ states from 2002 to 2012 and a heterogeneity-robust difference-in-differences design, I find that smoking bans increase six-month cumulative abnormal bond returns by about 90 basis points. The average effect is only the starting point: the response is much larger for speculative-grade issuers and firms with low interest coverage, indicating that investors reprice the policy where downside operating risk matters most for debt values. Mechanism tests point most clearly to improved operating performance and lower worker turnover, while broader financial-constraint, liquidity, and duration channels remain close to zero. Alternative estimators, placebo diagnostics, and geographic spillover checks all support the interpretation that workplace smoking bans trigger targeted credit-risk reassessment rather than a generic regional shock. My findings connect public-health regulation to capital-market outcomes and show how non-financial policy shocks can reveal economically meaningful information about corporate credit risk.

This study examines the economic consequences of China’s Three-Red-Lines policy, introduced in 2021 to cap real estate developers' leverage by imposing strict thresholds on debt ratios and liquidity. Developers breaching these thresholds experienced sharp declines in financing, land acquisitions, and financial performance. Privately owned developers(POE) are hit harder than state-owned firms (SOE), with larger drops in sales and higher default risk. Using granular project-level data, we show that the policy reduces developer sales primarily by curtailing new-project supply: breached developers launch fewer projects. On the demand side, homebuyers reallocate purchases from privately owned developers to SOEs, further widening the POE-SOE gap. The policy also reduced local governments’ land-transfer revenues and increased reliance on local government financing vehicles (LGFVs) for land purchases. These LGFV-acquired parcels exhibit very low subsequent development rates, which may increase local governments’off-balance-sheet debt risks.

In the realm of financial stability, accurate credit default discrimination models are crucial for policy-making and risk management. This paper introduces a robust model that enhances credit default discrimination through a sophisticated integration of a filter-wrapper feature selection strategy, instance selection, and an updated version of majority voting. We present a novel approach that combines individual and ensemble classifiers, rigorously tested on datasets from Chinese listed companies and the German credit market. The results highlight significant improvements over traditional models, offering policymakers and financial institutions a more reliable tool for assessing credit risks. The paper not only demonstrates the effectiveness of our model through extensive comparisons but also discusses its implications for regulatory practices and the potential for adoption in broader financial applications.

Traditional decision tree models, which rely exclusively on numerical variables, often encounter difficulties in handling high-dimensional data and fail to effectively incorporate textual information. To address these limitations, we propose the Integrated Multivariate Segmentation Tree (IMST), a comprehensive framework designed to enhance credit evaluation for small and medium-sized enterprises (SMEs) by integrating financial data with textual sources. The methodology comprises three core stages: (1) transforming textual data into numerical matrices through matrix factorization; (2) selecting salient financial features using Lasso regression; and (3) constructing a multivariate segmentation tree based on the Gini index or Entropy, with weakest-link pruning applied to regulate model complexity. Experimental results derived from a dataset of 1,428 Chinese SMEs demonstrate that IMST achieves an accuracy of 88.9%, surpassing baseline decision trees (87.4%) as well as conventional models such as logistic regression and support vector machines (SVM). Furthermore, the proposed model exhibits superior interpretability and computational efficiency, featuring a more streamlined architecture and enhanced risk detection capabilities.

Purpose The study investigates the impact of government intervention policy of capital markets (“National Team”) on firms’ sustainable management, i.e., green mergers and acquisitions (GMAs) in China, aiming to understand how such interventions influence corporate investment activities amidst a growing focus on green transition. Design/methodology/approach The research employs a dynamic analysis of quarterly data from Chinese companies (2014 Q1 to 2022 Q4), utilizing identified strategies, such as double machine learning-DID and multiple panel data regressions to assess the effects of government intervention on GMAs, and examines potential economic channels like liquidity, market stabilization, and informativeness. Findings The study finds that increased government intervention via direct stock purchases significantly boosts both the number and amount of GMAs, with economic significance of 23% and 45%, respectively. It identifies liquidity, market stability, and informativeness efficiency as underlying economic channels for this effect. Practical implications The findings suggest that government interventions can enhance corporate investment in green sectors, guiding firms to align strategies with sustainability goals. This can inform policymakers regarding the effectiveness of direct stock purchases in fostering a green economy, especially for large emerging countries. Social implications By promoting GMAs, government interventions contribute to green innovation and energy transition, ultimately benefiting society through enhanced environmental sustainability and compliance with eco-friendly regulations. Originality/value This research uniquely documents the direct effects of government stock purchases on corporate green financial activities, particularly GMAs, in a Chinese context characterized by tight credit, thereby expanding the understanding of government intervention in emerging markets.

We construct the most comprehensive bankruptcy database of Chinese firms to date and document significant real effects arising from the establishment of specialized bankruptcy courts. Specifically, the recovery rate for unsecured creditors increases by 38.6 percentage points after the reform. This improvement is not driven by shorter case durations or lower direct bankruptcy costs, as intuition might suggest. Instead, it results primarily from greater efficiency in the discovery and disposal of assets during bankruptcy proceedings. The reform also increases the likelihood of reorganization and promotes capital infusion in such cases. Higher recovery rates generate broader spillovers: reductions in non-performing loans, expansion of unsecured lending by local banks, relaxation of firms’ financial constraints, shifts in capital structure and investment, and greater public willingness to file for bankruptcy when distressed.

This paper studies the economic impact of introducing a personal bankruptcy regime, using China’s recent pilot reforms as a natural experiment. We exploit the staggered rollout of personal bankruptcy frameworks across Chinese cities and construct a novel dataset of bankruptcy case filings, combined with survey-based measures of credit access and official firm registration records. Our difference-in-differences estimates show that the reforms significantly improve small business credit access - business loan take-up increases by 1.3 % (21% relative to pre-reform mean), with no offsetting rise in interest rates. Effects are concentrated among non-corporate firms, firms with less employees and female entrepreneurs. Moreover, the reform is also associated with a 9.7% increase in new firm registrations. To interpret these findings, we develop a simple but novel theoretical model in which personal bankruptcy reduces the downside risk of entrepreneurial failure while preserving creditor recoveries. These findings underscore how debtor protection policies, when designed to reduce enforcement costs without expanding exemption rights, can enhance credit supply and entrepreneurial activity.

Using a sample of 501 Chinese non-financial firms listed on the Hong Kong Stock Exchange from 2008 to 2020, we find that both foreign exchange (FX) derivatives and foreign currency (FC) debt significantly reduce firms’ probability of default. We further observe that larger, non-state-owned enterprises (SOEs), Hong Kong-headquartered firms, firms operating after China’s 2015 exchange rate reform and firms under high trade policy uncertainty (TPU) are more likely to use both FX derivatives and FC debt concurrently, thereby diversifying their strategies for managing default risk. Our analysis indicates that these tools reduce firms’ default risk primarily by improving firms’ profitability, raising their likelihood of obtaining credit ratings, and increasing their use of interest rate derivatives. Importantly, we reveal that FX derivatives and FC debt act as substitutes in mitigating firms’ default risk. Notably, this substitution effect is more pronounced for larger, non-SOEs, Hong Kong-headquartered firms, firms operating after exchange rate reform and firms facing high TPU. Finally, we find that using FX derivatives significantly dampens firms’ investment, which may explain why Chinese firms tend to prefer FC debt to manage their default risk.