违约风险、银行信贷筛选与货币政策非对称效应

本文构建一个包含企业违约风险与银行信贷筛选的动态随机一般均衡模型,研究银行信贷筛选对货币政策宏观经济效应产生的影响。在参数校准的基础上,分析了货币政策冲击的长期效应与短期效应。研究结果显示：(1)无论是基于长期还是短期效应的角度,银行信贷筛选均显著抑制了扩张性货币政策对宏观经济产生的积极影响;(2)基于货币政策冲击的短期效应可以发现,银行信贷筛选降低了扩张性货币政策的实际效应,并且放大了货币政策对通胀的影响;(3)通过比较扩张性与紧缩性货币政策的脉冲响应可以发现,银行信贷筛选导致货币政策的宏观经济效应存在非对称性特征。福利分析的结果表明,相比无银行信贷筛选的情形而言,银行信贷筛选导致了整体社会福利的恶化。     

Default and Punishment in General Equilibrium1

We extend the standard model of general equilibrium with incomplete markets to allow for default and punishment by thinking of assets as pools. The equilibrating variables include expected delivery rates, along with the usual prices of assets and commodities. By reinterpreting the variables, our model encompasses a broad range of adverse selection and signalling phenomena in a perfectly competitive, general equilibrium framework. Perfect competition eliminates the need for lenders to compute how the size of their loan or the price they quote might affect default rates. It also makes for a simple equilibrium refinement, which we propose in order to rule out irrational pessimism about deliveries of untraded assets. We show that refined equilibrium always exists in our model, and that default, in conjunction with refinement, opens the door to a theory of endogenous assets. The market chooses the promises, default penalties, and quantity constraints of actively traded assets.     

Efficiency,Equilibrium, and Asset Pricing with Risk of Default

We introduce a new equilibrium concept and study its efficiency and asset pricing implications for the environment analyzed by Kehoe and Levine (1993) and Kocherlakota (1996). Our equilibrium concept has complete markets and endogenous solvency constraints. These solvency constraints prevent default at the cost of reducing risk sharing. We show versions of the welfare theorems. We characterize the preferences and endowments that lead to equilibria with incomplete risk sharing. We compare the resulting pricing kernel with the one for economies without participation constraints: interest rates are lower and risk premia depend on the covariance of the idiosyncratic and aggregate shocks. Additionally, we show that asset prices depend only on the valuation of agents with substantial idiosyncratic risk.     

信用风险的动态测量方法

本文提出了以市场波动性为基础的信用风险的一个动态量度框架.首先,通过把市场运动对信用暴露的影响量化,使得在信用风险的量度中融合了市场风险的因素,具有了动态的特征;其次,采用广义违约的概念,通过对基于历史数据的累计违约概率表进行拟合,得到了具有长期稳态的转移矩阵,由此得到的违约概率也具有动态属性;再次,根据有关金融产品优先级的历史数据,可以估计得到回收率;最后,把三者结合,得到了信用风险(信用损失)的动态量度,并对该量度框架的实际应用进行了探讨.     

信用风险模型比较分析

本文分析了现代信用风险模型迅速发展的主要原因,对主要派别的代表性模型用数学语言进行了总结,比较分析了各模型的原理及优缺点,并简要介绍了各模型的实证效果。     

风险相关性下的信用风险、市场风险和操作风险集成度量

商业银行各种风险之间相关性的存在,对其整体风险的度量产生重要影响。本文针对商业银行的信用风险、市场风险和操作风险这三类主要风险,在考虑相关性基础上给出了风险集成过程,通过copula函数和蒙特卡洛模拟方法计算了商业银行的整体风险,同时研究了风险分散化效应和在不同copula函数下整体风险的变化情况。最后以主流文献中的数据做了实证分析,结果显示本文提出方法能够很好的描述风险损失之间的相关性,同时在能够抵御相同风险的情况下考虑相关性下的在险值与简单相加得到的在险值相比要小,这能为银行业提高资金利用率提供了一定的理论和方法依据。     

基于copula函数族的信用违约互换组合定价模型

copula函数的出现解决了相关性结构不易刻画的难题,也为构建多元联合分布函数提供了切实可行的方法。在分析了不同copula函数的特点基础上并结合信用风险模型,本文建立了信用违约互换组合(Basket CreditDefault Swap)定价模型,并且给出了具体的计算步骤。本文揭示了信用违约互换组合为解决我国当前商业银行的不良贷款和流动性过剩问题提供了一个有效机制,模拟验证的结果显示模型的可实现性。     

基于信用风险度的商业银行风险评估模型研究

本文依据商业银行信用风险的内涵,结合信用风险的不确定性和相对性特征,提出以"信用风险度"作为系统的输出,并针对传统模式识别评估方法的不足,构建了基于补偿模糊神经网络的信用风险评估预测模型,为有效转变信用风险的分类评估模式、提供更为全面的信贷决策支持奠定了基础.实证结果表明,该模型是一种较为有效的评估方法.     

A Hint of Risk: Tradeoffs Between Quantitative and Qualitative Risk Factors

Risk-perception research plays an active role in discussions of risk-management alternatives. However, little guidance is provided regarding how public concerns should be weighed against other sources of cost and benefits. This paper reports the results of two experiments that measure tradeoffs among cost (in dollars), a quantitative risk measure (number of deaths or injuries), and several qualitative characteristics associated with perceived risk. Most subjects were willing to make the requested trade. However, the perceived risk information led others to reject the proposed technology.     

信贷风险管理系统的开发实践

信贷风险管理一直是金融界关注的焦点,而对处于新兴市场和转轨型经济环境下的我国商业银行而言,这个问题尤为重要。本文分析了如何利用计算机辅助进行信贷风险的管理,提出了具体的思路和方案。     

A Game Theory Approach for Assessment of Risk and Deployment of Police Patrols in Response to Criminal Activity in San Francisco

An efficient police patrol schedule must ensure the allocation of an appropriate number of officers sufficient to respond to the danger of criminal incidents, particularly in an urban environment, even when the available number of personnel is limited. This study proposes a framework that incorporates two game theory models designed for the allocation of police officers to patrol shifts. In the first step, the interactions of three factors between the criminal and the operation captain are modeled as a zero-sum, noncooperative game, after which a mixed strategy Nash equilibrium method is used to derive the risk value for each district to be patrolled. In the second step, the risk values are used to compute the Shapley value for all 10 districts, for three different threat levels. A fair allocation of police personnel based on the Shapley value is made with a minimum set of personnel deployment costs. The efficacy of the proposed method is verified using openly available data from the San Francisco City Police detailing incidents from the year 2016. The experimental results show that police planners can use this framework to quantitatively evaluate the criminal threat in each district when deciding upon the deployment of patrol officers for three shifts per day.     

Compressed Natural Gas Bus Safety: A Quantitative Risk Assessment

This study assesses the fire safety risks associated with compressed natural gas (CNG) vehicle systems, comprising primarily a typical school bus and supporting fuel infrastructure. The study determines the sensitivity of the results to variations in component failure rates and consequences of fire events. The components and subsystems that contribute most to fire safety risk are determined. Finally, the results are compared to fire risks of the present generation of diesel-fueled school buses. Direct computation of the safety risks associated with diesel-powered vehicles is possible because these are mature technologies for which historical performance data are available. Because of limited experience, fatal accident data for CNG bus fleets are minimal. Therefore, this study uses the probabilistic risk assessment (PRA) approach to model and predict fire safety risk of CNG buses. Generic failure data, engineering judgments, and assumptions are used in this study. This study predicts the mean fire fatality risk for typical CNG buses as approximately 0.23 fatalities per 100-million miles for all people involved, including bus passengers. The study estimates mean values of 0.16 fatalities per 100-million miles for bus passengers only. Based on historical data, diesel school bus mean fire fatality risk is 0.091 and 0.0007 per 100-million miles for all people and bus passengers, respectively. One can therefore conclude that CNG buses are more prone to fire fatality risk by 2.5 times that of diesel buses, with the bus passengers being more at risk by over two orders of magnitude. The study estimates a mean fire risk frequency of 2.2 x 10(-5) fatalities/bus per year. The 5% and 95% uncertainty bounds are 9.1 x 10(-6) and 4.0 x 10(-5), respectively. The risk result was found to be affected most by failure rates of pressure relief valves, CNG cylinders, and fuel piping.     

Improving Default Risk Prediction Using Bayesian Model Uncertainty Techniques

Credit risk is the potential exposure of a creditor to an obligor's failure or refusal to repay the debt in principal or interest. The potential of exposure is measured in terms of probability of default. Many models have been developed to estimate credit risk, with rating agencies dating back to the 19th century. They provide their assessment of probability of default and transition probabilities of various firms in their annual reports. Regulatory capital requirements for credit risk outlined by the Basel Committee on Banking Supervision have made it essential for banks and financial institutions to develop sophisticated models in an attempt to measure credit risk with higher accuracy. The Bayesian framework proposed in this article uses the techniques developed in physical sciences and engineering for dealing with model uncertainty and expert accuracy to obtain improved estimates of credit risk and associated uncertainties. The approach uses estimates from one or more rating agencies and incorporates their historical accuracy (past performance data) in estimating future default risk and transition probabilities. Several examples demonstrate that the proposed methodology can assess default probability with accuracy exceeding the estimations of all the individual models. Moreover, the methodology accounts for potentially significant departures from “nominal predictions” due to “upsetting events” such as the 2008 global banking crisis.     

基于违约风险的三叉树模型在可转债定价中的应用研究

本文考虑可转债券的违约风险,研究如何用违约风险下的三叉树模型对可转换债券进行定价。首先本文使用Black-Scholes公式测算企业在单位时间内的违约概率。其次,在计算可转债的债券价值时,将相似经营业绩和同等风险的企业债券收益率作为贴现率,计算现金流的现值,以反映相应的违约风险;在计算可转债看涨期权价值时,本文在三叉树模型中引入违约概率,重新计算调整后股票上涨、下跌的幅度和概率,得到基于违约风险的三叉树定价模型;最后对中国市场中实际的可转债——新钢转债进行了定价的计算,并对结果进行了探讨。     

CRMW风险缓释效用目标跟踪的债券投资组合优化策略研究

为缓释债券市场违约风险,央行着力推进信用风险缓释工具CRMW(信用风险缓释凭证)的发展,关于CRMW风险缓释能力度量及CRMW在债券投资组合中的应用成为了亟待解决的关键问题。为此,本文借鉴CVaR思想提出了“CRMW风险缓释效用”以度量CRMW对债券违约风险缓释能力,借助概率分位点理论定义债券的动态风险并制定了动态风险缓释跟踪目标,基于此跟踪目标探讨带有CRMW的债券投资组合优化策略问题。研究结果表明,在保证目标投资收益率的前提下,债券最优投资组合可达到风险缓释效用的目标,使其同时实现转移风险和保障收益的双重目的,且该投资组合优化策略表现出良好的抗风险性能。     

基于文本先验信息的贷款信用风险评估模型

本文利用现有信用风险研究所蕴含的信息,构建了一个新的贷款信用风险评估模型—PIPL。该模型先通过文本挖掘技术对现有研究进行文本信息搜集,得到关于信用风险指标的先验词频以体现指标的重要性,再通过惩罚变量选择法将先验词频量化为先验因变量,最后基于先验因变量和原始数据构建模型,并通过弹性网筛选风险指标。模拟分析显示PIPL模型能自动识别先验信息的质量,当先验信息质量高时,它赋予先验信息较高的权重,从而改进了指标选择和分类效果,当先验信息质量较低时,它能自动降低先验因变量在模型中的权重,表现出稳健的分类效果。实证分析从知网挖掘123篇文献获取文本信息,并以P2P网贷数据为例,发现PIPL模型通过先验信息提高了分类的准确性,并表现出了良好的稳健性。     

贷款风险管理中道德风险的防范模型

由于贷款风险管理中信息不对称性的存在,导致贷款道德风险的产生,加大了银行贷款风险。本文通过设置激励条件,构造出道德风险的防范模型,对于降低银行贷款风险具有重要参考价值。     

基于信用风险久期免疫的资产负债管理优化模型

用信用风险溢酬修正现金流的贴现率,构造了基于信用风险久期免疫条件;以组合收益最大为目标函数,建立了基于信用风险久期免疫的资产负债组合优化模型。本模型通过建立信用风险久期的免疫条件匹配银行的资产与负债,回避了利率风险和信用风险对银行所有者权益的影响;通过用反映违约风险的贴现率表述信用久期函数,揭示了信用风险对久期的影响;通过看跌期权公式建立了贴现率与违约风险的函数关系,揭示了违约风险对贴现率的影响。     

A Poultry-Processing Model for Quantitative Microbiological Risk Assessment

A poultry-processing model for a quantitative microbiological risk assessment (QMRA) of campylobacter is presented, which can also be applied to other QMRAs involving poultry processing. The same basic model is applied in each consecutive stage of industrial processing. It describes the effects of inactivation and removal of the bacteria, and the dynamics of cross-contamination in terms of the transfer of campylobacter from the intestines to the carcass surface and the environment, from the carcasses to the environment, and from the environment to the carcasses. From the model it can be derived that, in general, the effect of inactivation and removal is dominant for those carcasses with high initial bacterial loads, and cross-contamination is dominant for those with low initial levels. In other QMRA poultry-processing models, the input-output relationship between the numbers of bacteria on the carcasses is usually assumed to be linear on a logarithmic scale. By including some basic mechanistics, it is shown that this may not be realistic. As nonlinear behavior may affect the predicted effects of risk mitigations; this finding is relevant for risk management. Good knowledge of the variability of bacterial loads on poultry entering the process is important. The common practice in microbiology to only present geometric mean of bacterial counts is insufficient: arithmetic mean are more suitable, in particular, to describe the effect of cross-contamination. The effects of logistic slaughter (scheduled processing) as a risk mitigation strategy are predicted to be small. Some additional complications in applying microbiological data obtained in processing plants are discussed.     

重大灾害情境下感知风险对消费者信心的影响研究

以汶川地震的调研数据为基础,构建了重大灾害情境下的感知风险与消费者信心关系的理论模型。分析发现消费者信心各维度之间蕴含的相互关联,即重建和房地产发展信心对经济发展信心起显著正向影响,经济发展信心对生活质量信心具有正向影响。同时,发现地震感知风险对消费者信心、对经济发展信心具有直接负向影响,对重建和房地产发展信心没有产生显著影响,对生活质量信心的负向影响是通过经济发展信心间接实现的。