A Discrete Variable Chain Graph for Applicants for Credit

A bank offering unsecured personal loans may be interested in several related outcome variables, including defaulting on the repayments, early repayment or failing to take up an offered loan. Current predictive models used by banks typically consider such variables individually. However, the fact that they are related to each other, and to many interrelated potential predictor variables, suggests that graphical models may provide an attractive alternative solution. We developed such a model for a data set of 15 variables measured on a set of 14 000 applications for unsecured personal loans. The resulting global model of behaviour enabled us to identify several previously unsuspected relationships of considerable interest to the bank. For example, we discovered important but obscure relationships between taking out insurance, prior delinquency with a credit card and delinquency with the loan.     

The Volatility of Realized Volatility

In recent years, with the availability of high-frequency financial market data modeling realized volatility has become a new and innovative research direction. The construction of “observable” or realized volatility series from intra-day transaction data and the use of standard time-series techniques has lead to promising strategies for modeling and predicting (daily) volatility. In this article, we show that the residuals of commonly used time-series models for realized volatility and logarithmic realized variance exhibit non-Gaussianity and volatility clustering. We propose extensions to explicitly account for these properties and assess their relevance for modeling and forecasting realized volatility. In an empirical application for S&P 500 index futures we show that allowing for time-varying volatility of realized volatility and logarithmic realized variance substantially improves the fit as well as predictive performance. Furthermore, the distributional assumption for residuals plays a crucial role in density forecasting.     

义务教育财政体制变迁的经济学分析——从城乡义务教育发展不平衡角度

改革开放以来我国义务教育财政体制多次发生了变化,对义务教育的发展起了非常大的推动作用。但该体制依然存在一些问题,比较突出的是城市和农村关系失衡。在运用制度变迁理论分析义务教育财政体制变迁内在逻辑的基础上,提出了解决城市和农村关系失衡的方法。     

互联网金融纠纷解决与商事仲裁的运用

互联网金融作为新兴的金融创新模式,是传统金融服务体系的重要补充。基于互联网行业与金融行业相结合的特性,互联网金融面临着因技术安全与违约风险而引发的诸多复杂且多元化的纠纷。从解纷机制考量,商事仲裁的运用与互联网金融纠纷的特点相契合,具有纠纷解决专业化、效率化以及纠纷认可与执行广泛性的特点。对此,充分发挥商事仲裁的积极效用,无疑将促进我国互联网金融纠纷的顺利解决,从而维护互联网金融市场的稳定与发展。     

高职金融学投资理财专业设置的可行性分析

为了发挥学院优势,满足市场要求,分析了投资理财专业设置的可行性。对该专业的定位、市场需求情况、课程设置及培养目标进行了探讨。     

发挥农业政策性金融作用，服务社会主义新农村建设

2006年,中央一号文件明确指出,建设社会主义新农村是我国现代化建设进程中的重大历史任务,新农村建设需要巨大的资金投入,作为我国唯一的农业政策性金融机构的农业发展银行,肩负着为新农村建设提供资金的历史任务。然而,目前的农业政策性金融还存在一些缺陷,满足不了新农村建设的需求,我们需要改革农业政策性金融,使其更好地为社会主义新农村建设服务。     

我国中期财政问题浅析

本文对我国的中期财政问题进行了简要分析。     

A NOTE ON THE USE OF SELECTED NONFINANCIAL RATIO VARIABLES TO PREDICT SMALL-BUSINESS LOAN PERFORMANCE*

Small business loan applications have not been evaluated successfully by traditional methods. This paper explores the possibility of using three types of nonfinancial ratio variables (owner, firm, and loan characteristics) to predict whether a small business will pay off or default its loan. The owner and loan variables were better predictors of loan success than the firm variables.     

美国医疗援助制度中的联邦——州财政权责关系

美国的医疗援助制度（Medicaid）是专向负担不起卫生保健费用的贫困、老年、残疾等弱势群体提供医疗保健等服务的福利项目。该制度采取联邦与州共担资金的筹资模式。但在具体管理上．联邦政府只负责制定宏观的指导原则。而州政府负责具体实施和管理。本文试图通过对联邦与各州的权责分配、联邦与州在医疗援助计划中的相互关系、以及联邦对州医疗援助拨款比例等方面做出具体分析：探讨美国医疗援助制度在实现各州资金公平分配、有效控制医疗费用等方面的成果和经验：并对我国的医疗援助制度提出相关政策建议,以利于我国医疗救助制度的改革与完善．     

日韩文化与金融融合发展经验及其对上海的启示

与日韩两国相比,上海文化与金融融合发展起步晚,但起点高、步子实、进度快。中共十八届三中全会以来,上海将文化与金融融合发展作为重点工作推进,以国际视野、创新方式和落细落小落实举措,着力推动上海文化与金融融合发展并取得显著进展。学习和借鉴日韩两国经验,最重要的是坚持政府融合主导,发挥市场融合优势,激活社会融合主体,创新开放融合方式,合力推动融合发展。