证券市场个人投资者过度自信实证研究

采用Odean模型对我国证券市场上个人投资者过度自信倾向进行了实证研究,并进一步对不同年龄、性别、开户时间、交易频率投资者的过度自信倾向差异进行了研究和对比。结果表明:我国证券市场上个人投资者普遍存在过度自信倾向,且男性较女性更倾向过度自信,年龄、开户时间和交易频率不同也会对投资者的过度自信倾向产生不同程度的影响。     

决策双系统理论在促销决策研究中的运用

决策双系统理论为系统审视促销决策提供了基础。从直觉启发式来看,消费者往往会借助自己认为更有把握的象征性信息或刻板印象进行促销决策,并且过度关注品牌和价格信息。从直觉偏误来看,消费者在收集和接收促销信息时容易夸大感知利得,忽略有可能存在的风险,并且倾向于寻找支持其想法的证据,而不关注或很少关注否定其观点的证据。从决策特征来看,消费者既会受到不同促销信息框架的影响,也会受到群体以及其他人的影响。从认知闭合需要与认知主观能动性来看,不同消费者的促销决策质量存在着明显的差异。从时间压力来看,随着机会时间的减少,会引起消费者不做后悔的强度的增长。未来可综合促销特征、个体认知特质及直觉启发式对促销决策进行更深入地探索。     

创业认知研究综述

认知研究是近年来在国际创业领域的一个重要研究取向,对于更全面认识创业过程有积极的意义.创业认知有五个重要领域需要梳理：创业意向的研究现状和理论模型;认知启发式研究在创业心理研究中的潜在价值;与创业有关的一些认知偏差变量;架构和前景理论在创业研究中的应用;自我效能感与内在动机两个认知变量在创业研究中的应用.     

Bootstrap variance and bias estimation in linear models

Let θ be a nonlinear function of the regression parameters and θ be its estimator based on the least-squares method. This paper studies the bootstrap estimators of the variance and bias of θ. The bootstrap estimators are shown to be consistent and asymptotically unbiased under some conditions. Asymptotic orders of the mean squared errors of the bootstrap estimators are also obtained. The bootstrap and the classical linearization method are compared in a simulation study. Discussions about when to use the bootstrap are given.     

A Note on Derived Means of Scaled Data

Details are given of the procedures for calculating derived means of square-root and log transformed variables from un-subdivided and layered samples. A method for determining approximate confidence limits of the derived means is also described. The temporal distribution of nematodes in grass herbage is given as an example to illustrate the procedures used.     

Using a correlated probit model approximation to estimate the variance for binary matched pairs

A correlated probit model approximation for conditional probabilities (Mendell and Elston 1974) is used to estimate the variance for binary matched pairs data by maximum likelihood. Using asymptotic data, the bias of the estimates is shown to be small for a wide range of intra-class correlations and incidences. This approximation is also compared with other recently published, or implemented, improved approximations. For the small sample examples presented, it shows a substantial advantage over other approximations. The method is extended to allow covariates for each observation, and fitting by iteratively reweighted least squares.     

Exact Bounds for the Bias of Trimmed Means

Trimmed means remove outliers but affect the estimation efficiency in uncontaminated samples. This paper provides and analyses sharp upper and lower bounds on the bias in the non–parametric estimation of population means by various trimmed means in different scale units. It also presents sharp evaluations of expected trimmed means by the expectations of properly truncated parent distributions.     

A New Kernel Distribution Function Estimator Based on a Non-parametric Transformation of the Data

Abstract.  A new kernel distribution function (df) estimator based on a non-parametric transformation of the data is proposed. It is shown that the asymptotic bias and mean squared error of the estimator are considerably smaller than that of the standard kernel df estimator. For the practical implementation of the new estimator a data-based choice of the bandwidth is proposed. Two possible areas of application are the non-parametric smoothed bootstrap and survival analysis. In the latter case new estimators for the survival function and the mean residual life function are derived.     

Estimating precision,repeatability, and reproducibility from Gaussian and non- Gaussian data: a mixed models approach

Quality control relies heavily on the use of formal assessment metrics. In this paper, for the context of veterinary epidemiology, we review the main proposals, precision, repeatability, reproducibility, and intermediate precision, in agreement with ISO (international Organization for Standardization) practice, generalize these by placing them within the linear mixed model framework, which we then extend to the generalized linear mixed model setting, so that both Gaussian as well as non-Gaussian data can be employed. Similarities and differences are discussed between the classical ANOVA (analysis of variance) approach and the proposed mixed model settings, on the one hand, and between the Gaussian and non-Gaussian cases, on the other hand. The new proposals are applied to five studies in three diseases: Aujeszky's disease, enzootic bovine leucosis (EBL) and bovine brucellosis. The mixed-models proposals are also discussed in the light of their computational requirements.     

合福铁路浅埋偏压隧道溜坍分析及整治方案研究

以合福铁路客运专线浅埋偏压隧道为例，对其溜坍事故原因进行分析，研究提出施工整治方案并对实施效果进行评价。首先,通过现场调研与有限元模拟对事故原因进行分析，结果显示,该隧道施工过程受力复杂，软弱围岩自稳性差，洞口临时支护不足及施工期发生强降雨是本次事故的主要原因。然后，结合工程实际和有限元模拟结果提出了加强支护、减少开挖步长等具体整治措施。后续施工中隧道围岩变形收敛较快，洞口稳定得到有效控制，开挖进展顺利，表明该整治方案合理可行。研究思路和方法可为同类工程施工和事故处理提供参考。