公司多元化对证券分析师关注度的影响——基于证券分析师决策行为视角的经验分析

本文基于证券分析师的决策行为,采用中国证券市场的相关数据,研究了上市公司多元化水平与证券分析师关注度之间的关系.本文的研究发现,公司的多元化水平越高,证券分析师对其关注度越低,其原因在于随着公司多元化水平的提高,证券分析师获取公司信息所需付出的成本也相应提高,而信息成本的提高往往会驱使证券分析师放弃关注这样的公司;进一步的研究发现,相关多元化的公司相对于非相关多元化的公司更受证券分析师的青睐,其原因在于相关多元化的公司由于公司业务之间具有相关性,证券分析师获取的信息和应用的技术都具有共通性,这会减少证券分析师的成本.     

基于策略信息传递的外部董事占优型董事会投资决策机制研究

以中央企业的董事会结构改革为背景,以外部董事占优型董事会为研究对象,基于策略信息传递博弈理论,对信息不对称条件下董事会的项目投资额决策进行建模,运用最优化方法和数值分析手段,探讨外部董事占优型董事会的投资决策机制和微观治理行为.研究结果表明,外部董事占优可在董事会的投资(尤其是大项目的投资)决策过程中起到监督制衡内部董事的作用;内部董事在信息揭示增加的期望利润能够弥补其私人利益损失时进行信息传递,从而促进外部董事监督职能的发挥和投资绩效的改善;提高外部董事的咨询职能和知情概率对内部董事的信息揭示有激励作用,而内部董事的代理成本和外部董事的监督成本对内部董事的信息揭示有抑制作用,进而制约外部董事的职能发挥.这些结论对于外部董事的选聘和配套制度的完善具有重要的参考意义.     

新兴技术创新速度分析——一种实物期权方法

在创新采纳成本随时间下降的情况下,采用实物期权方法通过采纳企业投资决策对创新提供方的期望净收益的影响, 研究在快速变化的环境下最优的新兴技术创新速度.假设技术进步状态服从泊松过程,分析了创新采纳企业的3种投资策略.进一步通过比较创新提供方的期望净收益值的变化得到了最优的创新速度.最后,通过数字释例分析了几个重要参数的变化对创新提供企业期望净收益的影响.     

环状区域的车辆路径方案生成系统及优化模型

针对顾客满足环状区域分布的车辆路径问题(VRP),以大幅度地缩减问题求解的状态空间为突破口,引入人工智能和运筹学理论,提出求解这类特殊车辆路径问题的两阶段方法.第1阶段考虑行车时间和车载容量,提出带有控制策略的深度优先搜索算法自动生成备选的车辆路径方案集合.第2阶段将此备选方案集合归结为整数规划模型.采用VB6.0编程语言构建了车辆路径方案生成系统,并实现该系统与运筹学求解软件lindo的集成.通过案例验证了上述方法及自动求解系统的有效性.该项研究为解决环状配送区域的车辆路径问题这一难题提供了新方法.     

Which Factors are Risk Factors in Asset Pricing? A Model Scan Framework

Abstract

A key question for understanding the cross-section of expected returns of equities is the following: which factors, from a given collection of factors, are risk factors, equivalently, which factors are in the stochastic discount factor (SDF)? Though the SDF is unobserved, assumptions about which factors (from the available set of factors) are in the SDF restricts the joint distribution of factors in specific ways, as a consequence of the economic theory of asset pricing. A different starting collection of factors that go into the SDF leads to a different set of restrictions on the joint distribution of factors. The conditional distribution of equity returns has the same restricted form, regardless of what is assumed about the factors in the SDF, as long as the factors are traded, and hence the distribution of asset returns is irrelevant for isolating the risk-factors. The restricted factors models are distinct (nonnested) and do not arise by omitting or including a variable from a full model, thus precluding analysis by standard statistical variable selection methods, such as those based on the lasso and its variants. Instead, we develop what we call a Bayesian model scan strategy in which each factor is allowed to enter or not enter the SDF and the resulting restricted models (of which there are 114,674 in our empirical study) are simultaneously confronted with the data. We use a Student-t distribution for the factors, and model-specific independent Student-t distribution for the location parameters, a training sample to fix prior locations, and a creative way to arrive at the joint distribution of several other model-specific parameters from a single prior distribution. This allows our method to be essentially a scaleable and tuned-black-box method that can be applied across our large model space with little to no user-intervention. The model marginal likelihoods, and implied posterior model probabilities, are compared with the prior probability of 1/114,674 of each model to find the best-supported model, and thus the factors most likely to be in the SDF. We provide detailed simulation evidence about the high finite-sample accuracy of the method. Our empirical study with 13 leading factors reveals that the highest marginal likelihood model is a Student-t distributed factor model with 5 degrees of freedom and 8 risk factors.     

On the confusion matrix in credit scoring and its analytical properties

Abstract

Confusion Matrix is an important measure to evaluate the accuracy of credit scoring models. However, the literature about Confusion Matrix is limited. The analytical properties of Confusion Matrix are ignored. Moreover, the concept of Confusion Matrix is confusing. In this article, we systematically study Confusion Matrix and its analytical properties. We enumerate 16 possible variants of Confusion Matrix and show that only 8 are reasonable. We study the relationship between Confusion Matrix and 2 other performance measures: the receiver operating characteristic curve (ROC) and Kolmogorov-Smirnov statistic (KS). We show that an optimal cutoff score can be attained by KS.     

工科化学教学与学生问题意识培养

培养学生的问题意识对于激发学生的学习兴趣和动机,提高学习的效率,培养创造型人才具有重要意义。本文探索在工科化学教学中学生问题意识的培养。     

计算地基板挠度的一种边界元法

利用汉克尔变换推导了弹性半空间地基板挠度的基本解;然后建立了其挠度的边界积分方程;讨论了均质弹性半空间地基上夹住过板,简支边板的挠度边界积分方程;建立了边界值的一般代数方程组;并给出了算例。     

不同子宫切口对观赏犬术后繁殖力影响的研究

将83只难产剖腹的小型观赏犬随机分为作子宫角基部切口的对照组和作子宫体背侧切口的试验组。剖腹切开子宫取胎后施以相同的术后护理,观察术后发情,及时配种,追访产仔情况。结果发现:试验组比对照组受孕早和窝产数都高,分别为显著差异(P<0.05)和极显著差异(P<0.01)。说明通过改进剖腹产手术的切口部位可确保母犬剖腹产术后繁殖力。     

分析传动误差的时序模型法

介绍了齿轮传动链误差的时序建模及其几种典型时序谱估计的比较,并提出一种适于表示传动误差的时序模型。