上市公司审计收费影响因素的实证研究

本文利用我国深沪两市A股上市公司2003年年报中披露的数据,对可能影响我国上市公司年度审计费用的主要因素,运用多元线性回归进行实证分析。研究结果发现,上市公司资产总额、纳入合并报表的控股子公司数目、其他应收款占总资产的比例、公司和事务所是否位于经济发达地区和董事会规模与年度审计费用显著正相关,而独立董事人数与年度审计费用显著负相关;应收账款占总资产的比例、存货占总资产的比例、审计意见、当年和前一年度的盈利状况等因素对年度审计费用的影响并不显著。因此,我国上市公司审计费用主要由审计的产品费用所决定,从而会计师事务所的审计收费主要反映了现实的审计成本,而审计风险等潜在风险成本并没有在审计收费中体现出来。     

Three Corrected Score Tests for Generalized Linear Models with Dispersion Covariates

We develop three corrected score tests for generalized linear models with dispersion covariates, thus generalizing the results of Cordeiro , Ferrari and Paula (1993) and Cribari-Neto and Ferrari (1995) . We present, in matrix notation, general formulae for the coefficients which define the corrected statistics. The formulae only require simple operations on matrices and can be used to obtain analytically closed-form corrections for score test statistics in a variety of special generalized linear models with dispersion covariates. They also have advantages for numerical purposes since our formulae are readily computable using a language supporting numerical linear algebra. Two examples, namely, iid sampling without covariates on the mean or dispersion parameter oand one-way classification models, are given. We also present some simulations where the three corrected tests perform better than the usual score test, the likelihood ratio test and its Bartlett corrected version. Finally, we present a numerical example for a data set discussed by Simonoff and Tsai (1994) .     

基于主成分分析的多元线性回归用水量模型研究——以安徽省为例

用水量的准确预测对水资源规划具有重要意义。根据统计资料,选取了八项主要影响用水量变化的指标。按照主成分分析法原理,运用少数综合因子对影响用水量变化的原有八项指标进行了综合和简化,并研究其贡献率及综合效应;分析了用水量增长的特点,选用Logistic方程对综合因子进行回归分析;结合多元线性回归方法,建立了安徽省用水量模型;拟合结果表明,模型具有较高的精度;运用该模型,对安徽省2010年的用水量进行了预测;为水资源规划与管理提供参考依据。     

An effective going concern prediction model for the sustainability of enterprises and capital market development

The purpose of this study is to construct a two-stage effective and innovative going concern prediction model to predict going concern doubt for the sustainability of enterprises and capital market development. Samples of this study are the companies listed on the Taiwan Stock Exchange or the Taipei Exchange, totalling 196 companies and including 49 companies with going concern doubt and 147 normal companies (with no going concern doubt). The data are taken from the Taiwan Economic Journal (TEJ) and the Market Observation Post System during the period from 2001 to 2016 (totalling 16 years). This study adopts a two-stage way to construct the going concern prediction models. In Stage I, the traditional statistical method of stepwise regression (SR) and the data mining technique artificial neural network (ANN) are applied to select the important variables. In Stage II, two decision tree algorithms (data mining techniques): classification and regression tree (CART) and C5.0 are used to establish the prediction models. The results show that the SR + CART model has the highest going concern prediction accuracy, with an overall accuracy of 87.42%.     

灰色预测算法在物流园区需求预测中的应用

对物流园区需求预测进行了系统分析,介绍了灰色预测算法,和物流园区腹地划分方法;结合连云港港口物流园区需求预测的实例进一步阐述了灰色预测算法在物流园区需求预测中的应用.     

Portfolio Optimization under Lower Partial Risk Measures

Portfolio management using lower partial risk (downside risk) measures is attracting more attention of practitioners in recent years. The purpose of this paper is to review important characteristics of these riskmeasures and conduct simulation using four alternative measures, lower semi-variance, lower semi-absolute deviation, first order below targetrisk and conditional value-at-risk.We will show that these risk measures are useful to control downside risk whenthe distribution of assets is non-symmetric. Further, we will propose a computational scheme to resolve the difficultyassociated with solving a large dense linear programming problems resulting from these models. We will demonstrate that this method can in fact solve problems consisting of10⁴ assets and 10⁵ scenarios within a practical amount of CPU time.     

油气勘探目标的经济评价

勘探目标经济评价要坚持常规经济评价和风险评价相结合，在用多种方法合理预测经济评价参数，充分考虑各种风险因素的基础上，认真做好风险评价研究，提高勘探目标经济评价的可靠性。     

集值函数及向量值函数的两类线性算子逼近

本文得到了利用插值型线性算子列及积分型算子列逼近连续集值函数及连续向量值函数的收敛逼近阶。     

我国股份制商业银行薪酬激励有效性研究

我国股份制商业银行薪酬激励存在一些不足，原因在于薪酬激励的自身因素和薪酬环境因素两方面。自身因素主要包括忽视长期行为激励、缺乏同业竞争优势、轻视普通员工激励；环境因素主要有银行治理结构不完善、市场非充分有效、法规制度不健全等。本文通过对商业银行高管人员及普通员工的薪酬与业绩相关性进行实证检验，认为我国商业银行薪酬激励基本上是有效的，但是其有效性并不十分理想。据此，本文提出了提升我国商业银行薪酬激励有效性的具体建议：从微观层面看，优化薪酬激励机制：从中观层面看，强化商业银行治理结构；从宏观层面看，改善外部相关环境。