Model of counterparty risk with geometric attenuation and valuation of CDS

To investigate the impact of microstructure interdependency of a counterparty explicitly, a geometric function is introduced in one firm's default intensity to reflect the attenuation behavior of the impact of its counterparty firm's default. The general joint distribution and marginal distributions of default times are derived by employing the change of measure. The fair premium of a vanilla CDS (credit default swap) is obtained in continuous and discrete contexts, respectively. The swap premium in a discrete context is similar to the accumulated interest during the period between two payment days, and the short rate is the swap rate in a continuous context.

Semi-analytical Formula for Pricing Bilateral Counterparty Risk of CDS with Correlated Credit Risks

Based on the framework of [7], we discuss pricing bilateral counterparty risk of CDS, where each individual default intensity is modeled by a shifted CIR process with jump （3CIR＋＋）, and the correlation between the default times is modeled by a copula function. We present a semi-analytical formula for pricing bilateral counterparty risk of CDS, which is more convenient to compute through calculating multiple numerical integration or using Monte-Carlo simulation without simulating default times. Moreover, we obtain simpler formulae under FGM copulas, Bernstein copulas and CA＇B copulas, which can be applied for speeding up the computation and reducing the pricing error. Numerical results under FGM copulas and CA＇B copulas show that our method performs better both in computation speed and accuracy.

PRICING CATASTROPHE OPTIONS WITH COUNTERPARTY CREDIT RISK IN A REDUCED FORM MODEL

In this paper, we study the price of catastrophe Options with counterparty credit risk in a reduced form model. We assume that the loss process is generated by a doubly stochastic Poisson process, the share price process is modeled through a jump-diffusion process which is correlated to the loss process, the interest rate process and the default intensity process are modeled through the Vasicek model： We derive the closed form formulae for pricing catastrophe options in a reduced form model. Furthermore, we make some numerical analysis on the explicit formulae.

Valuation of Credit Default Swap with Counterparty Default Risk by Structural Model

This paper provides a methodology for valuing a credit default swap (CDS) with considering a counterparty default risk. Using a structural framework, we study the correlation of the reference entity and the counterparty through the joint distribution of them. The default event discussed in our model is associated to whether the minimum value of the companies in stochastic processes has reached their thresholds (default barriers). The joint probability of minimums of correlated Brownian motions solves the backward Kolmogorov equation, which is a two dimensional partial differential equation. A closed pricing formula is obtained. Numerical methodology, parameter analysis and calculation examples are implemented.

A dynamic credit risk assessment model with data mining techniques:evidence from Iranian banks

Giving loans and issuing credit cards are two of the main concerns of banks in that they include the risks of non-payment.According to the Basel 2 guidelines,banks need to develop their own credit risk assessment systems.Some banks have such systems;nevertheless they have lost a large amount of money simply because the models they used failed to accurately predict customers’defaults.Traditionally,banks have used static models with demographic or static factors to model credit risk patterns.However,economic factors are not independent of political fluctuations,and as the political environment changes,the economic environment evolves with it.This has been especially evident in Iran after the 2008-2016 USA sanctions,as many previously reliable customers became unable to repay their debt(i.e.,became bad customers).Nevertheless,a dynamic model that can accommodate fluctuating politicoeconomic factors has never been developed.In this paper,we propose a model that can accommodate factors associated with politico-economic crises.Human judgement is removed from the customer evaluation process.We used a fuzzy inference system to create a rule base using a set of uncertainty predictors.First,we train an adaptive network-based fuzzy inference system(ANFIS)using monthly data from a customer profile dataset.Then,using the newly defined factors and their underlying rules,a second round of assessment begins in a fuzzy inference system.Thus,we present a model that is both more flexible to politico-economic factors and can yield results that are max compatible with real-life situations.Comparison between the prediction made by proposed model and a real non-performing loan indicates little difference between them.Credit risk specialists also approve the results.The major innovation of this research is producing a table of bad customers on a monthly basis and creating a dynamic model based on the table.The latest created model is used for assessing customers henceforth,so the whole process of customer assessment need not be repeated.We assert that this model is a good substitute for the static models currently in use as it can outperform traditional models,especially in the face of economic crisis.

Credit Risk （Based on Analysis of Financial Statements） as the Decisive Factor Influencing the Risk of Investors

Banks as the key subjects in the financing of investment have a strong influence on the risk of investors. Hence, the solvency of the bank is of crucial importance for the risk management in the investment process. Given the fact of underdevelopment of financial markets and the lack of trading activities in securities, it is evident that the investments of banks in the developing countries mostly include lending investments. Looking at the key categories of risk that influence the overall risk of the banking business in such conditions, it can be concluded that credit risk presents the dominant and decisive factor. The aim of the paper is to select the bank determinant key factors of credit risk and to determine the extent to which non-performing loans （NPL） of bank credits affect the solvency of banks, and therefore also the risk of investors. This selection of the main determinants will be based on the analysis of financial statements. This is essential, especially taking into account the impact of the global financial crisis and the increasingly frequent falling into insolvency customers. Finally, liquidity of customers is that of the bank, and it is crucial for investors to timely identify possible risks associated with bank loans in order to proactively manage risk investment.

The Empirical Estimation of the Influence of Credit Risk Determinants in Baltic States＇ Banking Sector

There have been investigated empirically the influence of macroeconomic and real estate market variables on the level of non-performing loans in the Baltic States. A secondary goal was to analyze the effect of constant loan portfolio growth on the level of non-performing loans in mentioned countries and to define the type of influence of the variables （i.e., long-term or short-term）. The research indicates that all variables except the growth rate of the real estate market （RRE） have long-term influence on the level of non-performing loans. RRE has short-term influence and variables influence is associated with the development of another variables. The influence of RRE played an important role, but it was not as crucial as it has been previously assumed. If a respective credit risk management is applied, the influence of RRE is to be eliminated. The research results indicate that the most significant reason for the growth of non-performing loans for the Baltic States presented by rapid growth of aggregated loan portfolio and unemployment rate. The increasing influence of rapid loan portfolio growth proves the assumption that banks＇ credit risk management policies underestimated the changes in the macroeconomic variables during the analyzed period. The changes in the real GDP had initial influence on the economic situation deterioration for Baltic States.

The Impact of Bank-Specific and Macroeconomic Factors on Non-performing Loans in Sri Lankan Commercial Banks

The main purpose of this study is to ascertain the effect of bank-specific and macroeconomic factors on non-performing loans in systemically and non-systemically important commercial banks in Sri Lanka over 10 year’s period from 2004 to 2013.Also,the study examines the impact of civil war that prevailed in the country for 30 years on the ex-post credit risk of the banking sector.The study employed panel data methodology to investigate the effect of bank-specific and macroeconomic factors on non-performing loans.Panel unit root test has been undertaken in order to test the stationary of the variables.Hausman test and Wald coefficient restriction test were used to select the appropriate model out of pooled,random,and fixed effect.A dummy variable panel regression model adopted to study the war effect,considering 2009 as the structural year.Findings revealed that return on assets as a proxy for bank efficiency has a significant negative influence,while non-interest income as a proxy for income diversity is positively correlated with non-performing loans of systemically important banks.Both real gross domestic products and lending rates were highly significant in both bank types.On contrary with literature,growth in bank branches is negatively correlated.Public banks do not account for higher level of non-performing loans compared to their private counterpart.Finally,it was identified that civil war had an effect on the level of non-performing loans in commercial banks.The research would have benefited if the analysis is carried out among classified types of loans offered by commercial banks.Future researchers should involve in identifying the most significant contributing loan type to the non-performing loans and its determinants.This study is one of the few studies which have investigated the causes of non-performing loans in the commercial banking industry in Sri Lanka.The analysis of civil war and its impact on non-performing loans is the first study of that nature to be conducted in the context.

区块链在“三社”共生系统中的作用分析

传统“三社”共生系统因信用社放贷风险、专业社和供销社之间的交易对手风险而难以形成稳定共生系统。区块链技术通过减小信息不对称、建立风险处理机制保障合同执行来应对这两种风险。为确定区块链如何通过降低两种风险为“三社”共生创造价值,构建有无采用区块链的“三社”共生系统模型,并比较有无采用区块链的均衡结果。研究发现:采用区块链可以促使“三社”共生系统农产品产量和利润增加。在信息透明共享机制下,信用社放贷行为与专业社生产行为形成闭环牵制机制,使农业生产更加接近市场需求。通过区块链构建风险处理机制,将促进“三社”共同应对风险,实现风险损失最小化。供销社始终能通过区块链技术获益,而专业社大多数情况下可以从中受益,这取决于市场需求的稳定性。因此,区块链技术应在市场稳定性差和农业自然风险发生频繁的地区优先推广。

Analytical Expressions to Counterparty Credit Risk Exposures for Interest Rate Derivatives

This paper proposes an approximate analytical solution method to calculate counterparty credit risk exposures.Compared with the Standard Approach for measuring Counterparty Credit Risk and the Internal Modeling Method provided by Basel Committee,the proposed method significantly improves the calculation efficiency based on sacrificing a little accuracy.Taking Forward Rate Agreement as an example,this article derives the exact expression for Expected Exposure.By approximating the distribution of Forward Rate Agreement’s future value to a normal distribution,the approximate analytical expression for Potential Future Exposure is derived.Numerical results show that this method is reliable and is robust under different parameters.

商业银行供应链金融的风险及防范——基于交易对手信用风险的视角

中小企业的"融资困境"是制约我国中小企业发展的紧迫问题。供应链金融作为商业银行新兴业务,拓宽了中小企业的融资渠道。与传统信贷方式不同,供应链金融建立在应收账款抵押的基础上,因此供应链金融中存在交易对手信用风险。指出并介绍供应链金融业务特有的交易对手信用风险,并结合合俊集团案例进行阐述,进一步提出建立供应链金融风险预警系统和设立供应链金融风险基金对交易对手信用风险进行管控。

论中央交易对手与交易对手信用风险管理

场外衍生产品交易被认为是导致美国次贷危机的重要因素之一。次贷危机后,各国金融监管当局以及国际金融组织都加强了对场外衍生产品的风险管理,其中,交易对手信用风险是防范的重点。由于中央交易对手的特点,使其能够在场外衍生产品的交易对手信用风险管理中发挥重大作用。本文厘清了中央交易对手的概念、类型和发展历程,阐述了其在场外衍生产品交易对手信用风险管理中的作用及需要关注的问题,并给出了结论与展望。

考虑交易对手间三种违约相关情景下的CDS定价——基于单因子Copula模型的模拟

2008年金融危机中暴露出的交易对手违约相关风险,不仅使作为信用违约互换(CDS)交易对手方的Lehman Brothers,Bear Sterns和AIG等金融机构遭受了巨额损失,而且增加了金融市场的系统性风险。因此,考虑交易对手违约相关风险对合理定价CDS至关重要。基于单因子Copula模型框架,数值模拟分析了交易对手间3种不同违约相关情景下的CDS定价,在统一的框架内创新性地解决了信用保护卖方、买方和参考资产方的违约相关情况、违约强度、支付频率及回收率等因素对CDS定价的影响。结果表明:(1)保护卖方和参考资产方形成的违约相关对CDS定价的影响要强于交易三方违约相关的影响,各情景下的CDS价格明显不同;(2)随着保护买方支付频率的增加,3种情景下的CDS价格均逐渐降低;(3)参考资产方回收率的增加,会降低不同情景下的CDS价格且差异明显。

系统信用事件与信用违约互换估值研究

本文以系统信用事件为载体,研究了双边交易对手风险下信用违约互换(credit default swap,CDS)的估值,研究表明:1)完备的信用事件组将形成一个信用风险系统,并可作为CDS估值的基础;2)在CDS估值中,买方违约的可能性是不可以忽略的.如果忽略,将产生一个错误的定价,并且这个错误的定价将低于真实价值而使信用保护的卖方受到损失;3)CDS交易中的替换成本是不可以忽略的,由于替换成本的存在,CDS合约的价值会发生超常变化,其变化幅度取决于合约当前的市场价格;4)CDS合约价格对参考资产信用价差十分敏感,信用价差的变化,将会显著改变合约的价格.

美国应对金融危机的货币政策及其效应评析

尽管美国金融危机的货币表象为流动性枯竭、金融市场混乱,但金融危机的真实根源却在于交易中的对手风险。因此,虽然美联储采取了扩张性货币政策和创新的金融工具,增加金融市场的流动性,但这些政策只能在短期内抑制经济衰退,并不能真正地消除金融危机,反而还可能延缓甚至恶化金融危机。

考虑对手方违约风险首次违约互换合约的定价

研究对手方违约风险的首次违约互换合约的定价问题.通过双曲衰减的违约相关模型来刻画资产池中两个资产之间的相互依赖性结构,利用总的违约时间构建方法,建立了考虑对手方违约风险的首次违约互换合约的数学模型,得到了合约的定价公式,并进行了风险分析.

金融风险管理的新挑战及次贷危机的启示

本文从实践角度讨论当前金融危机形势下所面临的信贷危机以及未来经济之不确定性的挑战:金融衍生品之估价与风险的问题。本文的重点研究是关于管理风险的市场风险衡量原则和所面临的挑战。然后结合美国财务会计准则第157号与国际财务报告准则第7号(SFAS157/IFRS7)"公允价值计量准则"中的关键概念"不履行风险"与"交易对手风险"以及相对应的市场风险概念与信贷风险因子,讨论衍生品价值计量及相应对冲帐户的挑战。最后简要论述市场风险管理及相关对冲避险策略,并建议采取系列应对措施。

商业银行市场风险的若干思考

此次国际金融危机表明,传统的市场风险理论与管理模式可能已不能适应金融市场业务的发展需要。本文重新审视了市场风险的内容与实质,认为波动性风险只是市场风险最基本的特征。实际上,市场风险的发生和变化是与信用风险、流动性风险、操作风险等紧密交织在一起的,并包含了各类风险之间的相互影响。此外,本文还讨论了如何科学计量市场风险,提出了若干能够有效应用于我国商业银行市场风险管理的措施和对策。

论银行业衍生产品交易对手信用风险管理

银行是场外衍生产品市场的主要参与者。在从事场外衍生产品业务时,银行会面临一种特殊的风险———交易对手信用风险。美国次贷危机中,交易对手信用风险的破坏性体现得尤为明显,使参与其中的银行承受了巨大损失。本文厘清了衍生产品交易对手信用风险的定义及特征,总结了全球及中国的衍生产品交易对手信用风险现状,介绍了国外银行业的风险管理经验,最后,提出了我国银行业应采取的风险管理措施。

美国中小银行救助机制对我国的启示——对包商银行事件的思考

2019年上半年,中国银保监会宣布接管包商银行,这一事件是20年来金融监管机构再度出手整治问题商业银行。包商银行事件打破原有的同业刚兑预期,使得金融市场面临着短期流动性冲击。包商银行事件作为一个特殊个案,尽管其体量与规模无法影响到整个银行系统的根基,但可被视为金融供给侧改革过程中的一次风险压力测试,虽然短期内难免对中小银行具有负面影响,但却进一步加速了中小银行改革的步伐。与包商银行被接管导致我国银行同业市场违约风险上升并加剧同业市场运转困难这一结果不同的是,美国的银行业拥有单个银行常态化破产以及退出的成熟经验。本文通过对比我国及美国中小银行救助机制,提出我国要借鉴美国中小银行市场化退出的监管经验,在金融供给侧改革框架内设计我国中小银行救助机制。