我国商业银行风险防范模型的建立与分析

随着我国金融体制改革的日益深化,商业银行风险也日趋增大,因此,有必要建立健全商业银行金融风险防范模型.本文首先探讨了如何建立商业银行流动性业务风险测控模型,即流动性资产余额的确定;然后探讨了我国商业银行资产负债业务风险测控缺口管理模型、证券业务风险测控模型、国际业务风险测控模型和商业银行中间业务风险测控模型;最后,在以上各微观业务模型的基础上探讨了建立商业银行风险综合测控模型系统,以从总体上监测及防范商业银行金融风险.本文所建立的风险模型涵盖了商业银行的主要经营业务,可以有效监控并防范我国商业银行的各类金融风险,提高其抵御风险的能力.     

我国商业银行操作风险度量模型与实证分析

2000年以来我国商业银行频繁发生一些涉案金额巨大、情节恶劣的操作风险案例,给商业银行造成了巨额的经济损失,严重影响了商业银行的社会形象.近几年我国商业银行加强了对操作风险的管理.我国商业银行操作风险度量模型选择的构建要以操作风险的特征和我国商业银行具体情况为基础.本文描述了操作风险的定义及其特征,并通过对招商银行和深圳发展银行的操作风险状况采用收入模型进行实证分析,证明了我国商业银行运用模型进行量化管理的可行性.     

关于应用RAROC模型评价商业银行内控管理效果的研究

RAROC模型是国际通用的银行业风险收益评价方法.能够反映风险因素调整后经济资本的盈利水平,合理的分析和评估商业银行内控管理水平和成效.本文提出应用RAROC模型技术,旨在为商业银行及其监管部门引进新的管理理念,完善内控评价体系,促进商业银行规避风险,解决商业银行经营绩效考核中风险控制与赢利之间的矛盾.应用RAROC模型,对于我同商业银行加强风险控制,选择内控评价机制的创新路径,具有重要的现实意义及理论价值.     

基于收入模型的我国商业银行操作风险实证研究

本文选用适合我国商业银行实际情况的收入模型,利用2009年-2013年的面板数据对16家上市商业银行的操作风险进行度量;为了解不同产权下的商业银行操作风险差异,本文又进一步将这16家上市商业银行按国有商业银行、股份制商业银行和城市商业银行三种类别分别进行了操作风险度量与比较.研究发现:收入模型在一定程度上可反映出商业银行操作风险大小;这三类银行中,城市商业银行操作风险最小,国有商业银行较大,股份制商业银行操作风险最大.研究成果有利于商业银行有针对性的选择操作风险度量模型和管理策略.     

基于价值链的商业银行核心竞争力影响要素研究

从商业银行价值链的角度出发,根据商业银行的资源要素、能力要素和环境要素可以建立商业银行核心竞争力影响要素分析模型.运用这一模型分析商业银行核心竞争力影响要素与商业银行核心竞争力之间的关系,对提高我国商业银行的国际竞争力具有重要的意义.     

数据包络分析法在我国商业银行效率研究中的运用

本文将数据包络分析法引入我国商业银行的效率研究,建立了基于DEA的商业银行效率评价模型,并应用该模型对我国四大国有商业银行与十大股份制商业银行2002年的经营效率进行了比较.研究结果表明,四大国有商业银行的效率显著低于十大股份制商业银行;我国商业银行总体处于DEA无效率,其很大程度上是缘于规模无效率.规模不当已成为制约我国商业银行经营效率提高乃至持续发展的症结所在,而要解决这一问题的关键在于妥当处理商业银行发展过程中所必须面临的技术提升与规模扩张之间的关系.     

基于商业银行特殊性的价值增值指标构建及实证研究

本文基于商业银行特殊性,对EVA计算模型中的各个关键要素进行了相应调整,构建出适合我国商业银行自身特点的商业银行EVA（CBEVA）计算模型,并采用实证分析方法对模型的有效性进行检验.结论表明CBEVA指标与商业银行在资本市场的表现更加一致,可以用来实施更加精确的业绩评价和经济资本管理.     

内蒙古商业银行房地产贷款风险的实证研究

运用CPV模型探究宏观经济变量和房地产信贷违约率的关系,证明CPV模型可以预测商业银行房地产贷款的违约率.为减少商业银行风险损失,建议构建商业银行内部的风险管理衡量模型,完善房地产业的监管制度、改善行业风险评估体制,加强银行内部信贷管理制度、严控信贷发放流程,加强复合型风险管理人才的培养.     

预期信用损失模型对银行资本计提的结构性影响研究——基于50家上市商业银行的实证分析

预期信用损失模型是一项新的贷款损失准备计提方法,对其经济后果的评估非常重要.关于预期信用损失模型的实施对我国商业银行资本计提的具体影响,目前还缺乏深入系统的研究.本文结合我国50家上市商业银行的公开数据,从监管资本、会计损益和资本计提前瞻性的角度分析了预期信用损失模型对我国商业银行资本计提的影响.研究结果表明:总体影响上,商业银行的贷款损失准备计提金额显著增加,利润波动增强,对资本充足率带来一定冲击;从不同特征商业银行看,小型商业银行、使用权重法商业银行、城市商业银行和H股上市商业银行受到的影响更为严重;从资本计提的前瞻性看,贷款损失准备的前瞻性得到加强,顺周期性效应得到一定程度缓解,但并不能完全消除.     

对完善我国商业银行风险管理的思考——基于"多维度风险度量模型"的分析

商业银行风险种类繁多,且各种风险相互联系,传统的风险管理模式在解决此类问题时常常出现捉襟见肘的现象. "多维度"风险管理在全面考虑商业银行所面临的各种风险的基础上对其进行了综合评价.本文借用"多维度"风险度量模型对国内某商业银行近些年的风险状况进行了分析,并认为"多维度"风险度量模型有利于完善我国商业银行风险管理.     

Diversification disasters

The recent financial crisis has revealed significant externalities and systemic risks that arise from the interconnectedness of financial intermediaries’ risk portfolios. We develop a model in which the negative externality arises because intermediaries’ actions to diversify that are optimal for individual intermediaries may prove to be suboptimal for society. We show that the externality depends critically on the distributional properties of the risks. The optimal social outcome involves less risk-sharing, but also a lower probability for massive collapses of intermediaries. We derive the exact conditions under which risk-sharing restrictions create a socially preferable outcome. Our analysis has implications for regulation of financial institutions and risk management.     

非金融企业杠杆率与银行信用风险关系研究

本文立足于重庆市非金融企业杠杆率的测算,采用描述性统计分析、变异系数法、向量自回归模型分析等分析方法,重点分析了重庆市非金融企业杠杆率的发展情况及非金融企业杠杆率与商业银行信用风险之间的关系。研究结果表明：重庆市非金融企业杠杆率总体稳定可控,但部分行业风险不容忽视;去杠杆短期内会增加商业银行信用风险,长期有助于化解金融风险;去杠杆对商业银行不良率攀升的影响较为显著。据此,根据研究结论提出了相应的对策建议。     

宏微观分析相结合的信贷风险预测模型研究

我国现有的信贷风险评估方法存在宏微观分析结合不紧密以及风险评估不全面的问题.本文在基于财务分析的企业风险评估模型基础上,构建了宏微观分析相结合的信贷风险预测模型.建模的主要工作包括:选择反映行业信贷风险的指标与反映宏观经济变化的指标;确定反映宏观经济变化的指标与反映行业信贷风险指标之间的函数关系;依据以上的关联函数和宏观经济指标预测值,计算行业信贷风险调整系数;据此对属于该行业的企业即期信贷风险指标进行调整,对企业的信贷风险进行前瞻性预测.作者还利用证券市场数据检验了上述模型的准确性,结果表明模型可以有效预测企业未来的信贷风险.     

A new mixture cure model under competing risks to score online consumer loans

In credit scoring, survival analysis models have been widely applied to answer the question as to whether and when an applicant would default. In this paper, we propose a novel mixture cure proportional hazards model under competing risks. Most existing mixture cure models either do not consider competing risks or generally assume that a subpopulation of subjects is immune to any risk from all the competing risks. Compared with existing models, the proposed model is more flexible since it assumes that a subpopulation of subjects is immune to a subset of risks instead of being immune to all the risks. To estimate model parameters, we derive the likelihood function of the proposed model, based on which an expectation maximization estimation algorithm is developed. A simulation algorithm is designed to simulate time-to-event observations from the proposed model, and simulation studies are conducted to verify the proposed methodology. A real world example of credit scoring for online customer loans based on the proposed model is demonstrated.     

The Financial Modeling of Property-Casualty Insurance Companies

This paper describes a financial model currently being used by a major U.S. multiline property-casualty insurer. The model, which was first developed for solvency monitoring purposes, is now being employed for a variety of internal management purposes as well, including (1) the allocation of equity to corporate units, thereby allowing measurements of profitability by business segment and policy year, as well as analysis of the progression of “free surplus,” (2) the analysis of major risks–such as inflation risks, interest rate risks, and reserving risks–that have heretofore been difficult to quantify, and (3) consideration of varying scenarios on the company’s financial performance, both of macroeconomic conditions as well as of the insurance environment.

Many aspects of financial modeling do not differ significantly between life and property-casualty insurers, and these are not discussed in the paper. Rather, the paper focuses on the following topics:

1. Surplus allocation and profitability: how economic surplus and the returns on this surplus are determined by line of business, separately for new business and for the runoff of existing business, and how the progression of free surplus is viewed.

2. Multifaceted risks: how to model risks that affect multiple components of the insurer’s operations, such as economic risks and financial risks. The multiple effects of macroeconomic conditions and changing inflation rates on workers’ compensation claim frequencies and severities complicate the basic interest rate path modeling of life insurance products and annuity contracts.

3. Scenario building: how to construct scenarios of macroeconomic conditions or industry cyclical movements to test the resilience of the company to changing external conditions.     

地方政府财政风险:表现形式、成因与防范

财政是政府实现其职能的重要手段和经济基础.目前我国财政状况相当严峻,财政风险已逐渐凸现.与中央政府相比,我国地方政府运行困难更大,而与之相伴的财政风险的危害也更大,并且具有向上级传导风险的特性,从而有可能给国家公共财政体系带来各类风险.本文试图从我国地方财政风险的表现形式入手,探索其形成的深层原因,并提出了防范地方财政风险的制度、政策建议.     

商业银行贷款定价策略和模型设计

建立完善贷款定价体系对商业银行适应利率市场化、增强抵御利率风险具有重大意义。本文从贷款定价理论及其对商业银行重要意义入手,分析我国商业银行贷款定价的现状和难点。作者参照西方发达国家商业银行贷款定价模式,提出了我国商业银行建立完善贷款定价体系的策略和测算模型,即要综合考虑客户的信用风险、综合收益、筹资成本和营运成本以及货币信贷市场变化等因素,从而建立以成本精算、风险量化为基础的价格领导定价测算模型,最后依据客户综合贡献度、计结息周期和利率浮动周期进行修正,最终建立起以市场为导向,以弥补成本为前提,以客户盈利能力为参数的贷款定价机制。     

Law of large numbers and large deviations for dependent risks

We analyse the mathematical structure of models for large risk portfolios, especially for credit risk models. These risk portfolios are modelled using a multivariate mixture model for the dependence structure between the risks. The dependence structures are characterized by latent variables Θ, which play the role of systematic risks. We show that, depending on the choice of the distribution of Θ, there are different asymptotic behaviours for the aggregated risk portfolio, namely law of large numbers/central limit theorem behaviour and large deviation behaviour.     

Value at risk and efficiency under dependence and heavy-tailedness: models with common shocks

This paper presents an analysis of diversification and portfolio value at risk for heavy-tailed dependent risks in models with multiple common shocks. We show that, in the framework of value at risk comparisons, diversification is optimal for moderately heavy-tailed dependent risks with common shocks and finite first moments, provided that the model is balanced, i.e., that all the risks are available for portfolio formation. However, diversification is inferior in balanced extremely heavy-tailed risk models with common factors. Finally, in several unbalanced dependent models, diversification is optimal, even though there is extreme heavy-tailedness in common shocks or in idiosyncratic parts of the risks. Analogues of the obtained results further hold for efficiency comparisons of linear estimators in random effects models with dependent and heavy-tailed observations.     

Complete Versus Incomplete Insurance Contracts under Adverse Selection with Multiple Risks

This article extends the standard adverse-selection model for competitive insurance markets, which assumes a single source of risk, to the case where individuals are subject to multiple risks. We compare the following market situations—the case where insurers can offer comprehensive policies against all sources or risks (complete contracts) and the case where different risks are covered by separate policies (incomplete contracts). In the latter case, we consider whether the insurer of a particular risk has perfect information regarding an individual's coverage against other sources of risks. The analysis emphasizes the informational role of bundling in multidimensional screening. When the market situation allows bundling, it is shown that in equilibrium the low-risk type with respect to a particular source of risk does not necessarily obtain partial coverage against that particular risk.