通信经济发展与工业企业创新效率——基于Super-SBM与灰色关联分析

基于2011—2020年中国30个省(市、自治区)的大口径统计数据,先利用Super-SBM模型测度各地的工业企业创新效率,再利用灰色关联模型,分别计算电信产业和邮政产业与工业企业创新效率的关联系数。结果发现：2011—2020年各地工业企业创新效率值基本呈现出稳定的状态,效率值呈现出明显的东中西部空间分异情况,且东部的优势非常明显。邮政业的灰色关联系数值明显高于电信业,东中西部的灰色关联系数虽没有显现出太大的差别,但仍然可以看到,关联系数与经济发达程度成正比。因此,我国接下来不仅需要大力发展信息通信、移动物联网技术与产业,还要推动区域协调发展,优化省域通信技术与新经济地理的耦合。     

融资流动性与市场流动性

市场流动性刻画市场的交易能力,融资流动性反映投资者的融资能力,两种流动性及其相关程度是衡量金融市场健康发展的重要指标,为了控制与防范危机时期金融市场的风险,有必要准确分析和量化融资流动性与市场流动性的关系。以融资流动性和股票市场流动性为研究对象,以美国次级债危机作为研究背景,选择2000年1月3日～2008年4月30日作为样本区间,运用DCC-MVGARCH模型估计融资流动性与股票市场流动性之间的动态相关系数,并通过t检验对比金融危机前后两者之间动态条件相关系数的时间走势,以证实两种流动性在危机时期是否存在相互增强的促进作用。实证结果表明,危机爆发前,融资流动性与股票市场流动性的动态相关性较低,且相对稳定,但危机爆发后,两种流动性的相关性显著增强,且波动程度变大,呈现出流动性螺旋的现象。这一结论为危机中市场流动性突然消失提供了理论解释,并以此提出提升市场流动性的相关政策和建议。     

投资者情绪、平均相关性与股市收益

Pollet和Wilson的研究认为,股市平均相关性-收益关系比股市波动-收益关系能够更好的阐述总体风险-收益关系。本文研究了投资者情绪对股市平均相关性-收益关系的影响。实证结果表明,相比于股市波动,平均相关性对股市预期收益的解释能力明显增强,并且在低情绪期,平均相关性-收益之间的关系并不显著,而在高情绪期,平均相关性-收益关系被削弱为显著的负相关关系,这表明高情绪会削弱总体风险-收益关系。这一结论在随后的稳健性检验中被证明是稳健的。     

多标度条件下资本市场波动的级串方向和结构

对上证综指多标度条件下波动级串方向和结构的实证研究发现,在4days临界标度范围内,大小波动间互为因果;超出临界标度,大小波动间表现出单方向性特征.运用交叉相关系数和功率谱方法从相关性和能量耗散2个角度对多标度波动级串传递方向的分析同样显示,在101～103min的3个数量级广泛标度范围内,大波动对于小波动具有较强预测能力,波动级串结构表现出大波动影响小波动变化的单方向特征.在此基础上,提出了4类"递进"的资本市场波动级串模型及其运用于风险管理的基本思路.     

债券流动性与违约风险相关性溢价及实证研究

债券的流动性与违约风险都是影响债券溢价的重要因素,然而以往在违约风险最为突出的公司债券定价中却很少考虑两种风险相关性关系的影响,这与发达市场实证经验不符.在已有研究的基础上同时引入两种风险相关性,通过对Copula函数刻画的不同相关性结构情况下公司债券的收益率和风险变化分析,以及对中国短、中、长期公司债券市场数据的实证检验均发现,流动性与违约风险的相关性之间存在显著的正相关性,且对债券利差具有显著的影响和交互作用.     

基于多目标加权灰靶决策模型的节能服务公司选择研究

用能方对节能服务公司（Energy Service Company,ESCO）的选择关系到合同能源管理（Energy Performance Contracting,EPC）能否顺利实施。从用能方的角度,采用灰色系统理论中的多目标加权灰靶决策模型,对存在多决策目标的ESCO选择问题进行研究。通过层次分析法确定ESCO的11个决策目标的决策权数,根据综合效果测度值的比较,最终实现最优对策的选择。本文为用能方的ESCO选择问题提供了一种新的思路。     

Binary probability maps using a hidden conditional autoregressive Gaussian process with an application to Finnish common toad data

The Finnish common toad data of Heikkinen and Hogmander are reanalysed using an alternative fully Bayesian model that does not require a pseudolikelihood approximation and an alternative prior distribution for the true presence or absence status of toads in each 10 km×10 km square. Markov chain Monte Carlo methods are used to obtain posterior probability estimates of the square-specific presences of the common toad and these are presented as a map. The results are different from those of Heikkinen and Hogmander and we offer an explanation in terms of the prior used for square-specific presence of the toads. We suggest that our approach is more faithful to the data and avoids unnecessary confounding of effects. We demonstrate how to extend our model efficiently with square-specific covariates and illustrate this by introducing deterministic spatial changes.     

Correlation in a Bayesian framework

The authors consider the correlation between two arbitrary functions of the data and a parameter when the parameter is regarded as a random variable with given prior distribution. They show how to compute such a correlation and use closed form expressions to assess the dependence between parameters and various classical or robust estimators thereof, as well as between p‐values and posterior probabilities of the null hypothesis in the one‐sided testing problem. Other applications involve the Dirichlet process and stationary Gaussian processes. Using this approach, the authors also derive a general nonparametric upper bound on Bayes risks.     

Feature selection based on distance correlation: a filter algorithm

Feature selection (FS) is one of the most powerful techniques to cope with the curse of dimensionality. In the study, a new filter approach to feature selection based on distance correlation is presented (DCFS, for short), which keeps the model-free advantage without any pre-specified parameters. Our method consists of two steps: hard step (forward selection) and soft step (backward selection). In the hard step, two types of associations, between univariate feature and the classes and between group feature and the classes, are involved to pick out the most relevant features with respect to the target classes. Due to the strict screening condition in the first step, some of the useful features are likely removed. Therefore, in the soft step, a feature-relationship gain (like feature score) based on the distance correlation is introduced, which is concerned with five kinds of associations. We sort the feature gain values and implement the backward selection procedure until the errors stop declining. The simulation results show that our method becomes more competitive on several datasets compared with some of the representative feature selection methods based on several classification models.     

阅读能力与听解能力相关性刍议

听解与阅读都是获取信息的渠道,同时也是二语学习者学习英语的主要途径。从大学英语教学的现状出发,以普通非英语专业大学生的测试成绩验证阅读能力与听解能力之间的相关关系,分析心理语言学的理论基础,进而说明如何利用两者的相关关系来提高学习者的听解能力,并提出了几点看法。