信贷融资中农村社会资本的信用价值

农业和农村经济发展面临巨大的信贷约束,究其原因,信用资源的匮乏是影响农村经济组织信贷融资的重要因素。而农村社会资本具有经济担保作用,从社会资本视角,对农村信贷融资的信用保障机制进行深入研究,探究农村社会资本的资金调配功能,通过农村社会资本的信用价值及其局限性分析,寻求农村金融体系重构的有效路径。     

关于构建我国保险信用评级制度的思考

保险信用评级制度是为市场参与者提供服务的一种机制,虽然保险信用评价制度已有近百年的历史,但是在中国等发展中国家,信用评级机构还比较少,信用评级制度急需完善。文中从各个方面讨论和思考了我国保险信用评级制度的构建问题,对我国保险信用评级制度起了一定的推动作用。     

Credit default swaps and sovereign debt markets

This study investigates the link between the price discovery dynamics in sovereign credit default swaps (CDS) and bond markets and the degree of financial integration of emerging markets. Using CDS and sovereign bond spreads, the price discovery mechanism was tested using a vector error correction model. Financial integration is measured using news-based methods. We find that sovereign CDS and bond markets are co-integrated. In five out of seven sovereigns (71%), the bond market leads in price discovery by adjusting to new information regarding credit risk before CDS. In 29% of times, CDS markets are the source of price discovery. We also find a positive correlation of 0.67 between the degree of financial integration and the bond market information share. The evidence suggests that changes in sovereign credit risk and bond yields are significantly influenced by common external (global) factors, while country-specific factors play an insignificant role.     

Credit ratings of Chinese online loan platforms based on factor scores and K-means clustering algorithm

The rapid development of Chinese online loan platforms (OLPs), as well as their risks, has attracted widespread attention, increasing the demand for a complete credit rating mechanism. The present study establishes a credit rating indicator system for 130 mainstream Chinese OLPs that combines 12 quantitative metrics of online loan operations similar to commercial bank credit rating indicators, including platform transaction volume and average expected rate of return. We also consider two qualitative indicators of online loan background, namely platform background and guarantee mode, that reflect Chinese characteristics. Subsequently, a factor analysis was conducted to reduce the 14 indicators’ dimensions. The loads of the rating indicators in the resulting rotating component matrix were refined into an OLP operation scale factor, fund dispersion factor, security factor, and profitability factor. Finally, a K-means clustering algorithm was employed to cluster the factor scores of each OLP, thereby obtaining credit rating results. The empirical results indicate that the proposed machine learning–based credit rating method effectively provides early warnings of problem platforms, yielding more accurate credit ratings than those provided by two mainstream online loan rating websites in China, namely, Wangdaitianyan and Wangdaizhijia.     

Asset sale,debt restructuring,and liquidation

This paper considers a dynamic model in which shareholders of a firm in distress have a choice of whether the firm proceeds to debt restructuring or direct liquidation at an arbitrary time. In the model, we show the following results. Fewer asset sales, lower financing, debt renegotiation, and running costs, a lower premium to the debt holders, a lower cash flow volatility, and a higher initial coupon increase the shareholders׳ incentive to choose debt restructuring to avoid full liquidation. In the debt renegotiation process, the shareholders arrange the coupon reduction and use equity financing to retire a part of the debt value to the debt holders. The timing of debt restructuring always coincides with that of liquidation without debt renegotiation. Most notably, the shareholders do not prefer asset sale in debt restructuring even if they face high financing costs. The possibility of debt renegotiation in the future increases the initial leverage ratio in the optimal capital structure.     

Prices,debt and market structure in an agent-based model of the financial market

We develop an agent-based model in which heterogeneous and boundedly rational agents interact by trading a risky asset at an endogenously set price. Agents are endowed with balance sheets comprising the risky asset as well as cash on the asset side and equity capital as well as debt on the liabilities side. A number of findings emerge when simulating the model: we find that the empirically observable log-normal distribution of bank balance sheet size naturally emerges and that higher levels of leverage lead to a greater inequality among agents. Furthermore, greater leverage increases the frequency of bankruptcies and systemic events. Credit frictions, which we define as the stickiness of debt adjustments, are able to explain a key difference in the relation between leverage and assets observed for different bank types. Lowering credit frictions leads to an increasingly procyclical behavior of leverage, which is typical for investment banks. Nevertheless, the impact of credit frictions on the fragility of the model financial system is complex. Lower frictions do increase the stability of the system most of the time, while systemic events become more probable. In particular, we observe an increasing frequency of severe liquidity crises that can lead to the collapse of the entire model financial system.     

上市公司的信用行为及其市场反应

以1993—2012年在上海证券交易所和深圳证券交易所主板市场交易的所有非金融企业为样本,对公司的信用行为及其市场反应进行实证研究。结果发现:公司信用行为深受宏观经济政策的影响;商业信用的供给和需求与短期银行信用、长期银行信用显著负相关;商业信用需求与商业信用供给显著正相关;公司价值与商业信用供给显著正相关,与商业信用需求显著负相关,与短期银行信用需求和长期银行信用需求显著负相关;此外,宏观经济周期、企业的经济性质、公司规模、资本结构、成长性等因素对公司的信用行为和公司价值具有显著影响。     

Forecasting US bond default ratings allowing for previous and initial state dependence in an ordered probit model

In this paper we investigate the ability of a number of different ordered probit models to predict ratings based on firm-specific data on business and financial risks. We investigate models which are based on momentum, drift and ageing, and compare them with alternatives which take the initial rating of the firm and its previous actual rating into account. Using data on US bond issuing firms, as rated by Fitch, over the years 2000 to 2007, we compare the performances of these models for predicting the ratings both in-sample and out-of-sample using root mean squared errors, Diebold-Mariano tests of forecast performance and contingency tables. We conclude that both initial and previous states have a substantial influence on rating prediction.     

会计信息质量与中小板企业信贷融资可获性——基于公司内部治理结构角度的实证研究

本文以2004年至2007年中小板上市企业为研究对象,分别从盈余管理程度和会计稳健性水平两个维度来考察中小板企业的会计信息质量与信贷决策之间的关系,结果发现:会计信息质量不是银行信贷决策考虑的主要因素。表明我国银行信贷决策中亦没有将债务人的内部治理结构纳入考虑范畴。     

Government debt,learning and the term structure

Does a change in the public׳s holdings of government debt affect the term structure of interest rates? Empirical analysis using a VAR model indicates that a rise in these holdings of the real debt-to-GDP ratio increases both the three-month and ten-year U.S. nominal yields in a statistically significant manner. The maturity composition of debt is also found to matter: innovations in holdings of long-term debt affect the term structure, while increases in short-term debt affect inflation expectations. These effects of changes in holdings of debt on the yield curve can be derived in a general equilibrium model in which the government issues exponentially-maturing riskless debt, financed by lump-sum taxes, and the optimizing agents are adaptive learners. On calibrating the average maturity of debt in the model to match that of U.S. Treasury debt since the 1980s, I find that positive innovations in government debt lead to increases in asset yields. This is because agents do not learn the principle of Ricardian equivalence exactly, and perceive increases in holdings of government bonds as a rise in their net wealth. Imposing rational expectations on the agents eliminates this channel, and changes in holdings of government debt have no effect on yields. The learning model also implies that as the real debt-to-GDP ratio increases, and the average maturity of debt becomes longer, the agents become less likely to learn that Ricardian equivalence holds.     

使用信用违约互换产品化解信贷集中风险

信贷集中风险已经成为我国银行业亟待解决的问题,本文在分析了我国银行业信贷集中风险的现状和危害后,提出了使用信用违约互换产品化解银行信贷集中风险的建议。并对信用违约互换产品的基本原理以及在我国的实施方法提出了建议。     

资本结构决策理论及其存在的问题分析

本文资本结构理论论进行了综合研究与评述,并对资本结构定量决策的每股收益分析法和比较资金成本法,对资本结构理论及目前资本结构定量决策方法存在的问题作了全面的分析研究,以其对企业财务管理理论研究与教学参考。     

Moral hazard,debt overhang and capital structure

This paper investigates the impact of managerial moral hazard on the debt overhang of a firm by constructing a contingent claims model in which the manager faces costly effort. Using a calibrated capital structure model, we show that the costs of debt overhang become more serious in the presence of managerial moral hazard. Such costs even account for more than half of the total agency costs at a high level of cash flow. Moreover, in contrast to the results of Hackbarth and Mauer (2012), our model predicts a U-shaped relationship between the leverage ratio and investment opportunities of a firm, which is caused by managers’ moral hazard. Finally, by considering this moral hazard, we also show the coexistence of low leverage ratios and high credit spreads, which explains the phenomenon of “low debt levels and high credit spreads” observed in practice.     

Is there valuable private information in credit ratings?

Credit rating agencies (CRAs) contend their ratings contain a quantitative assessment based on hard information, and a qualitative adjustment based on private information. We study if the qualitative portion of ratings, generated with the companies’ own private information, contains valuable information for equity investors. We generate predicted ratings based on hard information alone and form portfolios of stocks based on the difference between observed and predicted ratings. Over a sample from 1998 to 2018, we find that stock portfolios formed on the basis of private information generate 2% to 4% in annual risk-adjusted returns. We also find that companies with positive private information have better future accounting performance. Our results suggest that CRAs bring valuable information to the market and investors could benefit from it.     

信用突变下商业银行信用风险预警模型及应用

在信用突变环境下,传统的基于模糊评价技术的信用风险预警模型存在较大的功能局限性。对此,文章运用偏好信息熵与物元可拓理论相融合的偏好熵权物元可拓方法,构建了基于偏好熵权物元可拓的商业银行信用风险预警模型,并进行了预警模型的实证分析。文章认为,基于偏好熵权物元可拓的信用风险预警模型的优势在于,通过偏好信息熵与物元可拓理论相融合的偏好熵权物元可拓方法,使得信用突变下信用风险的预警结果具有较好的平滑性与客观性,此外,该模型的综合关联度预警功能,提高了信用风险预警结果的精确度,很好地解决了信用突变下商业银行信用风险的预警问题。     

信息不对称下保险信用缺失分析及防范

当前，保险信用缺失已成为制约保险市场进一步发展的瓶颈。文中从投保人、保险人的逆向选择及道德风险三个方面阐述了保险信用缺失的原因，同时提出了健全我国保险信用体系的对策。     

Powerful CEOs,debt financing,and leasing in Chinese SMEs: Evidence from threshold model

This study investigates the impacts of CEO power on firm financing policies (i.e. debt financing and operating leasing) using the Caner and Hansen (2004) instrumental variable threshold regressions approach. The sample consists of a panel of 297 Chinese listed small and medium sized enterprises (SMEs) over the period 2009–2012. The empirical results indicate that there are threshold effects in the CEO power-debt relationship and CEO power-operating lease relationship. In particular, we find that firms tend to use more debt financing (and operating leasing) when CEO power index below a certain threshold level; beyond the threshold level, CEO tends to manipulate firm capital structure to pursue their own interests, thus using less debt financing and operating leasing. In addition, our estimation results suggest a positive relationship between debt and operating leases when CEO power is smaller than certain threshold, while it becomes negative if the power index exceeds the threshold level.     

Capital accumulation and regulation

This paper sets up a dynamic model that analyzes a bank's capital decision and the impact of this decision on her default risk and lending that affects aggregate output in the economy under regulation. The model shows that even though capital regulation may reduce the default risk of the bank, it may lead to credit crunch, hence the ensuing decline in output in the real sector. Furthermore, it appears that the risk-based capital requirement changes the composition of both liability and asset of the bank's balance sheet.     

Comparing debt characteristics and LGD models for different collections policies

This paper discusses the similarities and differences in the collection process between in-house and 3rd party collection. The objective is to show that, although the same type of modelling approach to estimating the Loss Given Default (LGD) can be used in both cases, the details will be significantly different. In particular, the form of the LGD distribution suggests that one needs to split the distribution in different ways in the two cases, as well as using different variables. The comparisons are made using two data sets of the collection outcomes from two sets of unsecured consumer defaulters.