中国的金融市场开发与借款证券化

在当今社会，市场对金融运行的压力越来越大，传统的融资方式已难以满足投资者的需要。一种新的金融形式——贷款证券化，使资金拥有者可以通过这一渠道将资金转移到贷款者手中。通过这种形式，可以很好地解决当今社会许多融资难的问题。目前，这种融资形式正在引起我国许多业界人士的注意，这种形式如果能够在我国的金融体系中得到完善，将会极大地促进我国的经济建设，也能很好地解决我国投融资体系中存在的诸多现实问题。     

国家助学贷款的风险与防范

国家助学贷款是一个政治、福利、教育、金融概念的混合体。本文主要从国家助学贷款发放的现状、存在的问题人手，提出了应加强维护信用制度的法律建设；创建良好的社会信用环境；改进管理制度与操作模式；加强各部门的协调与沟通等防范措施。     

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。     

国家助学贷款：问题与建议

1996年高校招生实行并轨 ,高等教育收费制度的改革已日趋明朗 ,随着扩大招生、收费制度的改革 ,迎面而来的是逐年增多的贫困生 ,为了扩大教育消费、为了不让贫困生辍学 ,政府出台了国家助学贷款政策。实施几年来 ,显现出诸多问题 ,给全面落实带来了困难。目前国家助学贷款在重点院校进展顺利 ,而在普通院校及中小型院校进展缓慢 ,必须加以研究与解决     

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.     

制度环境的改善与我国房贷证券化的推进

实行房贷证券化,能够积极有效地推动银行和金融市场的发展,增强国家宏观政策施行的效果,从而促进经济社会的发展。借鉴美国等模式的经验,推进我国房贷证券化,需要构建适合我国MBS发展模式及其体制建设,为住房抵押贷款证券化提供发展空间,创造发展环境。     

应用期权方法构建商业银行贷款利率模型

以分析公司普通股所具有的看涨期权特性为出发点，以Black—Scholes看涨期权定价模型为基础，根据不同企业资本结构和资产回报风险的差别，构造了一个商业银行基本贷款利率模型。从期权角度来设计贷款利率模型，除考虑了企业的经营风险因责外，还同时考虑了企业融资结构所带来的财务风险，能更加全面地反映出商业银行贷款的保障程度。     

产权制度下商业银行不良资产博弈

银行的改革进行了二十几年,虽然取得了阶段性的成果,但却没有从本质上解决银行的巨额不良资产问题。本文通过建立两阶段的动态博弈模型,分析了政府与国有银行之间的利益博弈行为,阐明国有银行不良资产之所以仍然不断涌现,是由于政府对银行产权份额的过多控制而导致的。在此基础上,提出了推进彻底的银行产权制度改革、完善银行的法人治理结构的建议,以便从根本上减少银行的不良资产。     

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.