基于CPV模型的房地产信贷信用风险的度量和预测

本文基于CPV模型,对房地产信贷风险进行了度量与预测.结果表明,该模型在度量和预测房地产信贷违约率方面具有较好的效果.房地产信贷的违约率和宏观经济状况紧密相连,当经济状况恶化,房地产信贷违约率上升,当经济状况好转,房地产信贷违约率下降.分别从国家宏观经济、房地产行业状况、房地产企业状况三个层面选择出三个宏观经济因素指标--综合领先指标、国房景气指数和企业景气指数进行研究,结果表明,对于研究房地产信贷的信用风险来说它们是较好的指标,尤其是综合领先指标.     

龙永煤田仁盘西矿区构造特征及找煤预测

文章通过对矿区构造特征分析,认为矿区中西部大面积分布泥盆统桃子坑组(D3tz)、下石炭统林地组(C1l)等老地层,呈上覆现象,其老地层下应赋存有二叠系煤系地层并蕴藏着丰富的煤炭资源,前景较好,可作为煤炭勘查的后备基地。     

A Model Forecasting Risk for Emerging Market Currencies

In this paper, we propose a risk forecasting model for emerging market currencies. Our model is based on the Markov regime switch which is constructed by exploiting daily equity market information, and we show that our model outperforms the existing model using macroeconomic information. We evaluate it by the performance measures, the goodness-of-fit and the Wilcoxon rank-sum test.     

Forecasting the Adoption of GM Oilseed Rape: Evidence from a Discrete Choice Experiment in Germany

This paper explores farmers’ willingness to adopt genetically modified (GM) oilseed rape prior to its commercial release and estimates the ‘demand’ for the new technology. The analysis is based upon choice experiments with 202 German arable farmers. A multinomial probit estimation reveals that GM attributes such as gross margin, expected liability from cross pollination, or flexibility in returning to conventional oilseed rape significantly affect the likelihood of adoption. Neighbouring farmers’ attitudes towards GM cropping and a number of farmer and farm characteristics were also found to be significant determinants of prospective adoption. Demand simulations suggest that adoption rates are very sensitive to the profit difference between GM and non‐GM rape varieties. A monopolistic seed price would substantially reduce demand for the new technology. A monopolistic seed supplier would reap between 45% and 80% of the GM rent, and the deadweight loss of the monopoly would range between 15% and 30% of that rent. The remaining rent for farmers may be too small to outweigh possible producer price discounts resulting from the costs of segregating GM and non‐GM oilseed rape along the supply chain.     

Analyst following and count-data econometrics

This paper reexamines the determinants of the number of analysts following a firm using econometric models based on count distributions. We replicate Bhushan's (1989) analyst-following study to demonstrate the effects of using count-data econometrics, in lieu of OLS, in studying phenomena where the dependent variable ranges among nonnegative integers. In contrast with the original paper, our findings indicate the number of institutional investors is inversely related with analyst following. We also provide econometric evidence to support the preferred use of the negative binomial model in estimating cross-sectional, analyst-following regressions.     

Using Leading Indicators to Forecast U.S. Home Sales in a Bayesian Vector Autoregressive Framework

This article uses Bayesian vector autoregressive models to examine the usefulness of leading indicators in predicting U.S. home sales. The benchmark Bayesian model includes home sales, price of homes, mortgage rate, real personal disposable income, and unemployment rate. We evaluate the forecasting performance of six alternative leading indicators by adding each, in turn, to the benchmark model. Out-of-sample forecast performance over three periods shows that the model that includes building permits authorized consistently produces the most accurate forecasts. Thus, the intention to build in the future provides good information with which to predict U.S. home sales. Another finding suggests that leading indicators with longer leads outperform the short-leading indicators.     

On the Predictability of the Stock Market Volatility: Does History Matter?

This study compares the performance of the ISD, the GARCH (1,1) , the historical volatility estimates and of two lagged trading volume measures for predicting the Swiss Stock Market Index's (SMI) volatility. The ISD has a superior daily informational content than the GARCH (1,1) estimate and retains unbiased but decreasing explanatory power over up to 20 days ahead horizons. Mean and spread daily volume measures play a significant correcting role when forecasting stock market volatility over daily and longer intervals respectively and clearly dominate the GARCH (1,1) forecasts. Their significance emphasises heterogeneous horizon traders' influence on the SMI volatility time series properties     

连锁超市配送中心过节囤货问题探讨

随着物流业和连锁超市的发展，配送中心在连锁超市中的地住越来越重要。由传统仓库向配送中心的改变是一个痛苦的过程，而这个痛苦的过程的表现之一就是文中的“过节囤货系列问题”。本文通过分析过节囤货问题的危害及其原因，并结合我国连锁超市的实际情况，提出了解决该问题的方案。     

我国石油消费市场回顾及发展趋势预测

文章回顾了近年来我国原油、成品油的消费状况和进出口状况，对与石油市场相关的各个行业的发展动态进行了分析。预测未来10-15年全国成品油消费总量增幅将继续维持平缓增长势头。由于乙烯和对二甲苯需求量的稳步增长，对化工轻油的需求量将会继续增加。建议在原油加工量一定的情况下，应将有限的石油资源优先保证化工产业发展，抓紧实施石油替代和燃料多元化战略，加快替代燃料的开发，尽量减少交通用油的比重。     

我国主要石化产品需求预测及供求结构分析

运用改进了的弹性法对乙烯和乙烯为主要原料的石化产品的市场需求进行了预测，并且对乙烯等石化产品的生产－消费结构进行了系统分析，为我国石化产业结构调整和发展提供了具体建议和对策。