财务困境预警模型与银行信贷风险的识别与防范

当前商业银行信贷风险管理主要采用的是6C法和五级分类法,这类方法具有主观性、短期性和单一性等缺点,不能为银行提供及时准确的决策信息。鉴于此,本文在企业财务困境预警模型的基础上建立了商业银行对企业的财务预警模型—Logit模型,该模型以企业的现金流量好坏作为信贷评级依据,以各类财务指标作为预警指标。研究结果表明:在企业发生财务困境的前一两年,该模型具有很好的预测效果,能够有效地为商业银行识别出有问题的企业,从而降低商业银行的不良贷款的形成。     

商业银行不良贷款的宏观经济影响因素分析

商业银行不良贷款总额一直在高位徘徊,成为制约中国商业银行发展的重要因素之一.通过收集2004年1季度～2009年1季度的最新数据,运用相关分析、共线性诊断、主成分回归分析等方法建立模型,探讨宏观经济因素对商业银行不良贷款的影响和贡献率.由实证结论发现:宏观经济因素与不良贷款余额负相关;社会消费品零售总额、进出口总额对降低商业银行不良贷款的贡献度最大,每增加1%会导致不良贷款平均降低0.0249%和0.0248%;宏观经济因素对降低不良贷款有正向促进作用,因此,在操作层面上可通过扩大内需、改善商业银行的外部信用环境等措施间接降低商业银行的不良贷款.     

浅析商业银行不良贷款及其处置措施

商业银行不良贷款的形成,长期制约着商业银行的正常运营。因此,降低不良贷款成为商业银行当前的首要任务。本文对商业银行不良资产形成原因进行了比较全面的阐述,阐明了控制不良贷款增长的主要措施。     

基于KMV模型的小微企业信用风险预警研究

随着我国经济增速的放缓,商业银行的不良贷款余额和不良贷款率呈现出双升的趋势,信用风险成为了银行面临的首要风险。实践证明,风险预警对防范信用风险、控制不良贷款具有重要意义。当前在多数商业银行的授信客户结构中,小微企业的授信占据了主要地位,开发专门针对小微企业的预警模型具有现实意义。本文选取了78家公司作为样本,构建了KMV信用风险预警模型。实证研究证明：该模型能够有效识别出有问题的企业,降低商业银行不良贷款的形成。     

浅析商业银行不良贷款及其处置措施

商业银行不良贷款的形成,长期制约着商业银行的正常运营.因此,降低不良贷款成为商业银行当前的首要任务.本文对商业银行不良资产形成原因进行了比较全面的阐述,阐明了控制不良贷款增长的主要措施.     

商业银行信用风险预警模型的实证研究

选择深沪两市40家上市公司作为样本,对基础财务指标采用相关分析法和逻辑回归法进行筛选,构建信用风险预警模型.实证研究表明:该模型能够有效地为商业银行识别出有问题的企业,从而降低商业银行不良贷款的形成.     

当前商业银行不良贷款的特征与对策研究

本文从国内商业银行资产质量管理现状出发,立足当前经济形势分析商业银行不良贷款上升的诱发因素,在对不良贷款演变历史的比较分析中,预测商业银行资产质量变化趋势,在此基础上探讨商业银行防控内外部风险,化解不良贷款的相关对策,旨在提高商业银行可持续发展能力,促进国民经济健康平稳发展.     

商业银行贷款集中度对不良贷款率的影响

采用行业集中度、地区集中度和客户集中度三个变量来测算国有商业银行、股份制商业银行和城市商业银行三类银行的贷款集中度,并通过建立回归模型对比分析这三类银行的贷款集中对不良贷款率的影响。研究结果表明,商业银行的贷款集中与不良贷款率正相关,各类商业银行的贷款集中程度与不良贷款的相关程度不同,其中贷款集中度对国有商业银行资产质量的影响要大于股份制商业银行,降低贷款集中度是遏制不良贷款的有效方法。     

国家控股商业银行不良贷款成因及对策探讨

我国的国家控股商业银行在金融业中起着举足轻重的作用。国家控股商业银行由于不良贷款规模较大，不良率较高，正常经营受到严重影响，如不及时处理，将引发流动性风险。为及时有效地防范不良贷款，本文针对国家控股商业银行不良贷款的发展现状，揭示不良贷款成因，阐述适合国家控股商业银行防范不良贷款的对策，为国家控股商业银行降低不良贷款提供借鉴之处。     

试论商业银行贷款风险的成因及规避对策

金融业是高风险行业之一，银行贷款业务存在着极大的风险。从当前看，商业银行的收益绝大部分仍是依靠贷款资产获取，而目前商业银行的信贷资产质量低下，不良贷款总量和比例不断攀升，居高不下，其中大部分商业银行的不良贷款比例在20％－40％左右，有些行甚至达到了40％－50％。如此庞大惊人的不良贷款，已危及到商业银行的生存与发展，因此，分析商业银行不良贷款形成的原因，寻找规避贷款风险的对策，已成我国商业银行非常迫切的工作，分析我国商业银行不良贷款的现状，既有其形成的客观原因，也有商业银行自身的主观原因，本拟浅析其原因和对策，以便在今后的工作中能更好地做好贷款存量的清收与盘活工作，优化增量，从而切实扭转不良贷款现状，降低和化解风险，提高信贷资产质量。     

The financial distress pricing puzzle in banking firms

This paper examines whether the financial distress pricing puzzle observed for non-financial firms is also observed for financial firms and how this puzzle differs according to the extent of short-sale constraints. By using the eight distress measures developed for financial firms, we find that there is a strong negative relation in the cross-section between financial distress and subsequent bank stock returns, regardless of adjustment for risk. However, this distress pricing puzzle is statistically significant only for high short-sale constrained banks, but not for low short-sale constrained banks. Thus, short-sale constraints are at least one non-risk attribute that causes the distress pricing puzzle for financial firms. We also find that despite its simple form, compared to the other complex distress measures, non-performing loans (NPLs) are the most informative in predicting future bank stock returns as well as bankruptcy and failure.     

Deflation,bank credit growth,and non-performing loans: Evidence from Japan

In this paper, I examine the link between bank credit growth and non-performing loans in an economy with deflationary pressures. Using panel OLS regressions and two-step GMM regressions, I find evidence for the time-varying relationship between bank credit growth and non-performing loans in a sample of 82 publicly listed commercial banks in Japan during the period 1993–2013. I show that bank credit growth positively correlates with non-performing loans prior to the onset of the global financial crisis of 2007 but negatively correlates with non-performing loans afterwards. I find evidence to support the notion that large banks drive the observed effects of credit growth on non-performing loans. In addition, credit growth and non-performing loans have no effect on profitability. Overall, the findings suggest that while the increase in the supply of bank loans increases the level of non-performing loans, it does not lead to higher profitability.     

后危机时代商业银行不良资产形成因素的实证研究——基于江西省数据的经验分析

2009年,我国信贷高增长引致未来银行不良资产大量积聚的潜在风险引起了各方关注。在后金融危机背景下,研究商业银行不良贷款的现状,发掘不良贷款存在的根源,对信贷风险管理具有重要的现实意义。本文在回顾以前研究成果的基础上,试图以更加全面的视角,从宏观经济金融环境、宏观调控政策以及银行业运行情况等三个方面深入分析商业银行不良资产的影响因素。文章运用协整分析、格兰杰因素检验和脉冲响应模型对资产价格、固定资产投资、通胀率、存款准备金率、基准利率、银行利润等指标与不良贷款率（或不良贷款余额）的因果关系、影响程度进行了实证分析。结果表明,宏观经济金融形势的变化和货币政策调整都是影响不良贷款变化的重要原因,而不良贷款率的变化对商业银行利润影响明显。     

Derivatives holdings and systemic risk in the U.S. banking sector

This paper studies the impact of the banks’ portfolio holdings of financial derivatives on the banks’ individual contribution to systemic risk over and above the effect of variables related to size, interconnectedness, substitutability, and other balance sheet information. Using a sample of 95 U.S. bank holding companies from 2002 to 2011, we compare five measures of the banks’ contribution to systemic risk and find that the new measure proposed in this study, Net Shapley Value, outperforms the others. Using this measure we find that banks’ aggregate holdings of five classes of derivatives do not exhibit a significant effect on the bank’s contribution to systemic risk. On the contrary, the banks’ holdings of certain specific types of derivatives such as foreign exchange and credit derivatives increase the banks contributions to systemic risk whereas holdings of interest rate derivatives decrease it. Nevertheless, the proportion of non-performing loans over total loans and the leverage ratio have much stronger impact on systemic risk than derivatives holdings. Therefore, the derivatives’ impact plays a second fiddle in comparison with traditional banking activities related to the former two items.     

How to explain non-performing loans by many corporate governance variables simultaneously? A corporate governance index is built to US commercial banks

This paper aims to combine the principal component analysis and GMM dynamic panel data methods in order to estimate the effect of corporate governance system on non-performing loans. The first method is meant to construct a corporate governance index for US commercial banks. The second one allows us to study the relation between the built index and non-performing loans. The advantage of the combination of these methods is reducing the number of corporate governance variables into a single one and ensuring the consistency of GMM estimates, given that a high number of variables leads to an increase in the number of GMM instruments, which in turns results in biased estimators. Applying these methods to US commercial banks, for a period including the financial crisis years, we find that small banks are characterized by a sound corporate governance system that reduces their non-performing loans. In opposition, the corporate governance fails to protect medium and large US commercial banks from excessive risk-taking that damages their loans’ quality and even leads to enormous losses especially during the global financial crisis.     

银行业危机:金融泡沫视角的分析

自20世纪80年代以来,银行业危机爆发越显频繁。然而,通过对银行业危机内部形成机理分析可以发现,银行业危机的爆发其实是伴随着金融泡沫的形成与破灭这一过程的。在金融泡沫的形成过程中,银行往往会给一些高风险行业发放贷款,从而增加银行经营风险;而在金融泡沫破灭之后,这将直接或间接地导致银行产生大量的不良贷款,从而使银行业危机最终爆发。因此,我国应尽快化解国有商业银行的不良资产;完善银行微观治理结构;建立和完善金融监管机制。     

集团化运作与企业财务风险——基于中国上市集团公司的经验证据

集团公司已成为我国重要的企业组织形态。本文运用1998—2006年期间沪、深两地上市公司样本数据,从财务风险的角度探讨了集团化运作的经济后果。本文研究发现,企业的集团化运作不但显著加大了企业财务风险,而且集团化运作后企业发生财务困境的概率也大为提高。本研究在丰富企业理论、组织行为理论以及公司财务理论的同时,对于集团公司加强财务风险管理,对于银行等主要债权人和政府监管部门提升金融风险监控意识,均具有一定的启示意义。     

商业银行信用风险评估的生存分析模型及实证研究

企业发生财务危机,不能归还到期贷款是商业银行信贷资产的主要风险来源,商业银行如何构建恰当的信用风险评估模型来预测企业的财务危机,从而避免这类信用风险的出现就显得尤为重要。本文以我国上市公司为研究对象,结合杜邦分析法建立了基于生存分析的信用风险评估模型,模型对于随机选取的预测样本,其提前1年、2年和3年的预测准确率分别达到86%、72%和68%。通过与Altman模型、Ohlson模型预测结果的比较和鲁棒性检验的结果发现,该模型同时具有可以使用时间序列、无需样本配对、中远期预测能力强和高鲁棒性的特点,这些特点特别对于商业银行中长期信贷风险管理具有较高的应用价值。     

Ability of accounting and audit quality variables to predict bank failure during the financial crisis

We examine the ability of selected accounting and audit quality variables measured in a period prior to the financial crisis (i.e., the four quarters of 2006), to predict banks that subsequently failed during the financial crisis. We employ two sets of samples from the US: a troubled banks sample that includes banks that failed in or after 2007 as well as banks classified as being troubled based on profitability, loan quality, and balance sheet position in 2007, and a full sample that includes all banks with available required data. Using the troubled banks sample, we identify six reliable predictors of bank failure: auditor type, auditor industry specialization, Tier 1 capital ratio, proportion of securitized loans, growth in loans, and loan mix. For the larger full sample of banks, we identify the following ten predictors of bank failure: auditor type, Tier 1 capital ratio, proportion of securitized loans, nonperforming loans, loan loss provisions, growth in commercial loans, growth in real estate loans, growth in overall loans, loan mix, and whether the bank is a public bank.     

LTV policy as a macroprudential tool and its effects on residential mortgage loans

Since the early 2000s, macroprudential policy has increasingly become part of the regulatory and supervisory framework. Likewise, the housing market has been at the center of the debate on systemic financial risk prevention. Among macroprudential tools, the purpose of the loan-to-value (LTV) ratio is to constrain mortgage loan creation. This paper is unique in that it analyzes the effectiveness of LTV on mortgage lending moderation using a large sample of more than 4000 banks from 46 countries. The analysis suggests mortgage loans have been successfully curbed in countries with a LTV policy. Size and non-performing loans are the two key characteristics to the effectiveness of LTV. When nonlinearities are considered, the average effect of LTV can be very large; however, it becomes much less effective with large banks and banks with bad loans. Our results suggest the inclusion of other macroprudential tools may have complementary effects to LTV, and for large size banks in particular.