股票股利变化市场反应的实证研究

对公司分配方案中股票股利发生变化时股票收益率的研究,显示证券市场对股票股利分配方案发生变化时有一定反应,但与国外成熟资本市场的反应并不一致,说明我国证券市场距离国外成熟资本市场还有一定差距,证券市场信息披露制度尚不规范。     

中国股票市场效率的实证研究

处于二元转型期的中国股票市场,功能定位不完全合理,结构性矛盾突出。行政导向性强,是一个不完全市场。市 场仍处于非弱效率状态。利用1999-2000年中国股票市场的时间序列数据进行的自相关系数检验和游程检验.证实了中国 股票市场非弱有效性的判断。     

基于利润的股票定价模型研究

股息现值模型 (Gordon model)、税后利润再投资有限增长模型 (Gordon and Gordon m odel)以及简化后的税后利润再投资有限增长模型 (Morris m odel)都无法为亏损公司的股票定价。根据弱有效市场假设 ,提出基于净利润的股票定价模型。该模型允许公司未来几年把全部或部分利润投资于盈利项目。利用该模型投资者可以计算不同类型上市公司股票的投资价值     

管理育人的关键是高效服务与优化管理--建设既安身又安心的大学生公寓

结合高校学生公寓社会化管理的实际情况,探讨在高校后勤社会化管理进程中,如何更新观念,高效服务与优化管理并重,实现管理育人.     

Robust sparse regression and tuning parameter selection via the efficient bootstrap information criteria

There is currently much discussion about lasso-type regularized regression which is a useful tool for simultaneous estimation and variable selection. Although the lasso-type regularization has several advantages in regression modelling, owing to its sparsity, it suffers from outliers because of using penalized least-squares methods. To overcome this issue, we propose a robust lasso-type estimation procedure that uses the robust criteria as the loss function, imposing L₁-type penalty called the elastic net. We also introduce to use the efficient bootstrap information criteria for choosing optimal regularization parameters and a constant in outlier detection. Simulation studies and real data analysis are given to examine the efficiency of the proposed robust sparse regression modelling. We observe that our modelling strategy performs well in the presence of outliers.     

侵权干涉与效率违约的比较——以引诱违约情形的经济分析为中心

效率违约理论认为在引诱违约的情况下,违约能够导致资源流向更高价值的用途,并且减少了交易成本。研究表明,上述两个假设都不能成立。而且由于补偿不充分,效率违约还导致了过多的违约。相反,侵权干涉规则保证了资源流向更高价值的用途,并降低了交易成本,而且避免了过多的违约。     

Bayesian Conditional Mean Estimation in Log‐Normal Linear Regression Models with Finite Quadratic Expected Loss

Log‐normal linear regression models are popular in many fields of research. Bayesian estimation of the conditional mean of the dependent variable is problematic as many choices of the prior for the variance (on the log‐scale) lead to posterior distributions with no finite moments. We propose a generalized inverse Gaussian prior for this variance and derive the conditions on the prior parameters that yield posterior distributions of the conditional mean of the dependent variable with finite moments up to a pre‐specified order. The conditions depend on one of the three parameters of the suggested prior; the other two have an influence on inferences for small and medium sample sizes. A second goal of this paper is to discuss how to choose these parameters according to different criteria including the optimization of frequentist properties of posterior means.     

Bayesian estimation of the efficient frontier

In this paper, we consider the estimation of the three determining parameters of the efficient frontier, the expected return, and the variance of the global minimum variance portfolio and the slope parameter, from a Bayesian perspective. Their posterior distribution is derived by assigning the diffuse and the conjugate priors to the mean vector and the covariance matrix of the asset returns and is presented in terms of a stochastic representation. Furthermore, Bayesian estimates together with the standard uncertainties for all three parameters are provided, and their asymptotic distributions are established. All obtained findings are applied to real data, consisting of the returns on assets included into the S&P 500. The empirical properties of the efficient frontier are then examined in detail.     

均值—条件风险价值模型有效前沿分析——以含无风险资产和持有期为研究视角

从有效投资组合的角度构建持有期下含有无风险资产的均值—条件风险价值模型,用Lagrange乘子法对该模型求解,可得到:一定条件下,新模型的有效前沿与均值—方差模型有效前沿是一致的;且当借贷利率不同时,新模型的有效前沿可以根据组合预期收益率与借贷利率的不同关系,由线段、双曲线以及射线三个部分组合而成。     

行为金融学的发展与探索

本文通过对行为金融相关文献的回顾 ,指出了当前研究的不足 ,并探索了行为金融理论的发展需要解决的难题及未来研究的方向。同时 ,本文指出了行为金融理论作为一门独立学科应具备的基本条件 ,为行为金融理论整合为一门学科提出了自己的意见