中国、香港与美国股票市场波动传导的时延分析

金融风险传导的控制是金融风险管理中非常重要的内容,对金融市场波动传导的规律性进行研究具有重要的理论意义和实践价值。基于时间序列高阶谱分析的时延估计方法分析非高斯性、非线性的股票指数时间序列,可以确定各股票市场波动传导的具体领先——滞后时间和相互间的影响强度。研究结果表明,内地股票市场和香港股票市场波动传导时滞很短;内地股票市场波动的原因主要来自内部,香港和美国股市的波动对内地的影响并不大。     

Competition in banking: A disequilibrium approach

The Rosse–Panzar revenue test for competitive conditions in banking is based on observation of the impact on bank revenue of variation in factor input prices. We identify the implications for the H-statistic of misspecification bias in the revenue equation, arising when adjustment towards market equilibrium is partial and not instantaneous. In simulations, fixed effects estimation produces a measured H-statistic that is severely biased towards zero. Empirical results for the banking sectors of the Group of Seven (G7) countries corroborate our principal finding, that a dynamic formulation of the revenue equation is required for accurate identification of the H-statistic.     

南京都市圈基本公共服务均等化时空演变及地域差异

通过构建基本公共服务均等化评价指标体系,运用核密度估计法和Dagum基尼系数探究2011—2020年南京都市圈基本公共服务均等化的时空演变以及地区差异特征。研究表明：在时序演变上,南京都市圈基本公共服务均等化水平不断提高,但是城市间差异仍然存在,呈现微弱的两极化特征;在空间分布上总体呈现中间高四周低的空间格局,苏皖两省内各城市各子维度均等化水平分界明显,具有典型的区域化特征;南京都市圈基本公共服务总体呈现均等化水平上升,区域总体差异逐渐缩小;南京市龙头作用发挥不足,是导致区域内差异存在的重要原因。因此,需加强南京都市圈内部分工协作,破除政策壁垒,推动南京市的带头作用,促进区域内基本公共服务均等化发展。     

Nonparametric efficiency analysis: A multivariate conditional quantile approach

This paper focuses on nonparametric efficiency analysis based on robust estimation of partial frontiers in a complete multivariate setup (multiple inputs and multiple outputs). It introduces α-quantile efficiency scores. A nonparametric estimator is proposed achieving strong consistency and asymptotic normality. Then if α increases to one as a function of the sample size we recover the properties of the FDH estimator. But our estimator is more robust to the perturbations in data, since it attains a finite gross-error sensitivity. Environmental variables can be introduced to evaluate efficiencies and a consistent estimator is proposed. Numerical examples illustrate the usefulness of the approach.     

On estimating the reliability after sequentially estimating the mean: The exponential case

Sequential estimation problems for the mean parameter of an exponential distribution has received much attention over the years. Purely sequential and accelerated sequential estimators and their asymptotic second-order characteristics have been laid out in the existing literature, both for minimum risk point as well as bounded length confidence interval estimation of the mean parameter. Having obtained a data set from such sequentially designed experiments, the paper investigates estimation problems for the associatedreliability function. Second-order approximations are provided for the bias and mean squared error of the proposed estimator of the reliability function, first under a general setup. An ad hoc bias-corrected version is also introduced. Then, the proposed estimator is investigated further under some specific sequential sampling strategies, already available in the literature. In the end, simulation results are presented for comparing the proposed estimators of the reliability function for moderate sample sizes and various sequential sampling strategies.     

Varying Coefficient Regression Models: A Review and New Developments

Varying coefficient regression models are known to be very useful tools for analysing the relation between a response and a group of covariates. Their structure and interpretability are similar to those for the traditional linear regression model, but they are more flexible because of the infinite dimensionality of the corresponding parameter spaces. The aims of this paper are to give an overview on the existing methodological and theoretical developments for varying coefficient models and to discuss their extensions with some new developments. The new developments enable us to use different amount of smoothing for estimating different component functions in the models. They are for a flexible form of varying coefficient models that requires smoothing across different covariates' spaces and are based on the smooth backfitting technique that is admitted as a powerful technique for fitting structural regression models and is also known to free us from the curse of dimensionality.     

空间目标的联合矩阵束极点估计

极点作为谐振区雷达目标的最主要电磁特性,具有很大的空间目标识别前景。但是在使用频域观测数据提取目标极点时,存在虚假极点和估计精度问题。针对上述问题,首先通过加窗和截断改进了后时响应信号的获取流程,抑制了虚假极点影响;然后采用最小描述长度法（MDL）估计极点个数,避免了定阶错误引起的虚假极点;最后采用联合矩阵束法估计极点,有效减少了单角度数据估计极点时存在的遗漏极点和虚假极点问题。FEKO软件验证表明,所提算法具有更高的精度和抗噪能力。     

软件项目进度估算的模糊方法

软件项目进度的估算是软件项目管理的重要组成部分,当开发新型项目时,由于没有历史经验,精确的甚至基于概率的估算方法都比较困难,而且可信度也较低,文章采用了模糊-概率的方法来进行进度的估算,在模糊运算中采用基于卷积的模糊算子,该算子具有扩散性较低的特点。     

长春市中心区人口疏散规模估算评析与调控策略工程

分析了长春市中心区人居环境现状特征,以此为基础,从三个不同的角度,估算了人口疏散的规模,探讨了人口疏散的时空阶段及相应的调控对策。