行业财务信息的业绩预测能力研究

不同的行业特征会使行业间的企业财务信息呈现不同的特点。实证结果显示:基于行业财务 信息的业绩预测的效果比不区分行业的预测效果好;而预测效果的好坏则与行业内部的竞争 结构有关。     

对我国商品房价格的走势分析——以郑州市为个案

房价收入比的大小是影响房地产价格的关键，也是房地产是否出现拐点的判断依据。郑州市的数据分析显示，其商品房价格及房地产行业呈健康发展趋势，居民能够承受目前的住房压力，房地产行业与我国经济发展相适应。价格保持相对稳定是房地产业安全运行的关键，我国应该出台更具体的政策保持其健康发展。     

国内大中型客车市场需求预测

为从理论上探析大中型客车市场需求问题,运用图表分析法和直线趋势预测法分析了近几年中国大中型客车市场的销售情况和市场特点,同时预测2008年大中型客车的市场需求。分析认为：在公交优先政策的实施、旅游业的快速发展等一系列相关因素影响下,大中型客车市场将稳步发展,但竞争也会日趋激烈。分析结果表明：大中型客车企业应当建立完善的销售网络和售后服务体系,生产适销对路的产品,努力拓展海外市场。     

Forecasting mortality rates via density ratio modeling

The authors propose a semiparametric approach to modeling and forecasting age‐specific mortality in the United States. Their method is based on an extension of a class of semiparametric models to time series. It combines information from several time series and estimates the predictive distribution conditional on past data. The conditional expectation, which is the most commonly used predictor in practice, is the first moment of this distribution. The authors compare their method to that of Lee and Carter.     

Bias Reduction through First-order Mean Correction, Bootstrapping and Recursive Mean Adjustment

Standard methods of estimation for autoregressive models are known to be biased in finite samples, which has implications for estimation, hypothesis testing, confidence interval construction and forecasting. Three methods of bias reduction are considered here: first-order bias correction, FOBC, where the total bias is approximated by the O(T^-1) bias; bootstrapping; and recursive mean adjustment, RMA. In addition, we show how first-order bias correction is related to linear bias correction. The practically important case where the AR model includes an unknown linear trend is considered in detail. The fidelity of nominal to actual coverage of confidence intervals is also assessed. A simulation study covers the AR(1) model and a number of extensions based on the empirical AR(p) models fitted by Nelson & Plosser (1982). Overall, which method dominates depends on the criterion adopted: bootstrapping tends to be the best at reducing bias, recursive mean adjustment is best at reducing mean squared error, whilst FOBC does particularly well in maintaining the fidelity of confidence intervals.     

Risk of Error and the Kappa Coefficient of a Binary Diagnostic Test in the Presence of Partial Verification

The accuracy of a binary diagnostic test is usually measured in terms of its sensitivity and its specificity, or through positive and negative predictive values. Another way to describe the validity of a binary diagnostic test is the risk of error and the kappa coefficient of the risk of error. The risk of error is the average loss that is caused when incorrectly classifying a non-diseased or a diseased patient, and the kappa coefficient of the risk of error is a measure of the agreement between the diagnostic test and the gold standard. In the presence of partial verification of the disease, the disease status of some patients is unknown, and therefore the evaluation of a diagnostic test cannot be carried out through the traditional method. In this paper, we have deduced the maximum likelihood estimators and variances of the risk of error and of the kappa coefficient of the risk of error in the presence of partial verification of the disease. Simulation experiments have been carried out to study the effect of the verification probabilities on the coverage of the confidence interval of the kappa coefficient.     

Inference in the presence of ranking error in ranked set sampling

The author proposes inference techniques for ranked set sample data in the presence of judgment ranking errors. He bases his analysis on the models of Bohn & Wolfe (1994) and Frey (2007a, b), of which parameters are estimated by minimizing a distance measure. He then uses the fitted models to calibrate confidence intervals and tests. He shows the validity of his approach through simulation and illustrates its application through the construction of distribution‐free confidence intervals for the median area of apple tree leaves covered by a spray.     

基于灰色-马尔柯夫模型的西安房地产市场分析

如何定量科学地预测房地产市场和走势,面对未知的市场,政府如何调控市场?开发商如何定位新项目?应用灰色系统与随机过程两种数学方法,在对房地产各指标的预测中,建立相应的灰色-马尔柯夫预测模型,并对西安市2006年的房地产走势做出预测。预测结果是2006年西安市普通住宅均价应在3200元/平方米左右,表现出稳中有升的趋势。     

中国股票市场信息披露与传导机制的研究——基于报价价差成分的分析

信息披露与传导机制是解释股价波动性动态特性的最本质原因。上市公司发布的定期报告是投资者最主要的信息来源。利用事件分析的方法，从微观信息的角度实证分析上市公司年报公布的发布对市场微观结构的影响，利用股票买卖报价价差成分中的信息不对称成分来检验我国股票市场的公共信息私有化及内幕交易问题，并提出应加强信息披露的监管和内幕交易的监管，以完善我国信息披露传导机制。     

邓小平社会主义本质论的逻辑内涵、解释与预测功能

文章通过比较邓小平对社会主义本质论概括与马克思对未来社会主义社会基本特征描述的逻辑推演,发现两者之间是一脉相承的,都是运用生产力与生产关系的基本原理,特别是生产资料所有制理论来分析社会形态本质特征的。邓小平对社会主义本质论的概括比马克思对未来社会主义的特征描述更具有针对性、现实性和指导性;邓小平社会主义本质论的科学性体现在它对当今的所有制和收入分配改革仍然具有很强的解释和预测功能。