MODELING SOVEREIGN RISKS: FROM A HYBRID MODEL TO THE GENERALIZED DENSITY APPROACH

Motivated by the European sovereign debt crisis, we propose a hybrid sovereign default model that combines an accessible part taking into account the evolution of the sovereign solvency and the impact of critical political events, and a totally inaccessible part for the idiosyncratic credit risk. We obtain closed‐form formulas for the probability that the default occurs at critical political dates in a Markovian setting. Moreover, we introduce a generalized density framework for the hybrid default time and deduce the compensator process of default. Finally, we apply the hybrid model and the generalized density to the valuation of sovereign bonds and explain the significant jumps in long‐term government bond yields during the sovereign crisis.     

A Dynamic Analysis of Fixed- and Adjustable-Rate Mortgage Terminations

This paper provides a side-by-side comparison of loan-level statistical models for fixed- and adjustable-rate mortgages. Multinomial logit models for quarterly conditional probabilities of default and prepayment are estimated. We find that the estimated impacts of embedded option values for prepayment and default are generally quite similar across both FRM and ARM loans, providing additional empirical support for the basic predictions of the options theory. We also find that differences in estimates of conditional probabilities of prepayment and default associated with mortgage age, origination period, original LTV, and relative loan size, indicate the continued significance of these other economic and demographic factors for empirical models of mortgage terminations.     

对远期外汇合约信用风险的监管

随着远期外汇合约近几年来在我国的逐步推行,外汇市场活跃的同时也增加了外汇交易的信用风险,。要实现外汇市场的有序开放和稳定发展,就必须对其实行有效的风险管理,这包括交易主体对信用风险的识别,处置和外部监管。     

DEFAULT RISK AND DIVERSIFICATION: THEORY AND EMPIRICAL IMPLICATIONS

Recent advances in the theory of credit risk allow the use of standard term structure machinery for default risk modeling and estimation. The empirical literature in this area often interprets the drift adjustments of the default intensity's diffusion state variables as the only default risk premium. We show that this interpretation implies a restriction on the form of possible default risk premia, which can be justified through exact and approximate notions of "diversifiable default risk." The equivalence between the empirical and martingale default intensities that follows from diversifiable default risk greatly facilitates the pricing and management of credit risk. We emphasize that this is not an equivalence in distribution, and illustrate its importance using credit spread dynamics estimated in Duffee (1999) . We also argue that the assumption of diversifiability is implicitly used in certain existing models of mortgage-backed securities.     

用违约距离判别信用风险:一个实证研究

本文选取了在中国A股市场上市的4家具有一定代表性的ST公司和4家对照公司，并通过计算从2003年到2005年的静态违约距离和不变增长率假设下的违约距离，发现后者比前者具有更好的判别能力；同时对影响违约距离大小的输入变量进行了敏感性分析，发现违约距离对股票收益波动率的变化最为敏感，因而精确计算波动率是关键。     

高校学生伤害事故的法律责任及处理和预防

学生伤害事故在高校办学过程中是很难避免的客观事实，困扰着高校工作，影响着高校教育教学秩序。从法律视角对高校学生伤害事故进行了界定，明确了学生伤害事故的违约责任和侵权责任，提出高校学生伤害事故责任竞合应采取允许竞合模式，同时，对高校学生伤害事故提出了处理和防范的原则和措施。     

Forecasting recovery rates on non-performing loans with machine learning

We compare the performance of a wide set of regression techniques and machine-learning algorithms for predicting recovery rates on non-performing loans, using a private database from a European debt collection agency. We find that rule-based algorithms such as Cubist, boosted trees, and random forests perform significantly better than other approaches. In addition to loan contract specificities, predictors that refer to the bank recovery process — prior to the portfolio’s sale to a debt collector — are also shown to enhance forecasting performance. These variables, derived from the time series of contacts to defaulted clients and client reimbursements to the bank, help all algorithms better identify debtors with different repayment ability and/or commitment, and in general those with different recovery potential.     

考虑违约距离的上市公司危机预警模型研究

在上市公司财务危机预警中,违约距离起着重要的不可替代的作用,仅考虑财务指标并不足以完全解释企业财务危机发生的原因.文章应用Merton模型对2002～2004年ST公司和相应配对公司的危机发生之前的违约距离进行了研究,发现危机公司违约距离在危机发生前第三年明显低于正常公司的相应值,违约距离比传统财务指标能更早地预警到企业财务危机的发生.结合违约距离因素的危机预警模型能更明显地提高模型的危机判断正确率.