Olympic news and attitudes towards the Olympics: a compositional time-series analysis of how sentiment is affected by events

Sentiment affects the evolving economic valuation of companies through the stock market. It is unclear how ‘news’ affects the sentiment towards major public investments like the Olympics. In this paper we consider, from the context of the pre-event stage of the 30th Olympiad, the relationship between attitudes towards the Olympics and Olympic-related news; specifically the bad news associated with an increase in the cost of provision, and the good news associated with Team Great Britain's medal success in 2008. Using a unique data set and an event-study approach that involves compositional time-series analysis, it is found that ‘good’ news affects sentiments much more than ‘bad’, but that the distribution of such sentiment varies widely. For example, a much more pronounced effect of good news is identified for females than males, but ‘bad’ news has less of an impact on the young and older age groups.     

波动率的持续性：基于GARCH模型的成交量解释

文章将成交量变量合理地分解为由好、坏消息分别引致的两部分,结合GARCH模型,研究了成交量对波动率持续性的解释,并得出如下结论:成交量变量对波动率的持续性具有一定的解释力;信息对波动率的影响具有不对称性,坏消息比好消息的影响大;将成交量分解成由好、坏消息分别引致的两部分之后,能够更进一步地解释波动率的持续性。     

浅析我国国有商业银行 不良资产形成的原因及对策

 我国国有商业银行不良资产和不良资产率都在下降,但主要是受政府干预和主导,而不良资产的化解更需依靠金融市场。本文探讨了我国国有商业银行不良资产形成原因,既有国有银行自身的原因,也有政府干预的因素,同时受社会信用环境、金融监管等因素影响,并探寻了防范和解决不良资产的对策。     

Gosset,Fisher, and the t Distribution

Bias has different sources. Measurement errors create “bad” data and biased estimates. But selection biases occur even with “good” data and can be both subtle and large in magnitude.

Selection biases are not easily detected by internal examination of the data. Detection is more likely by comparison with external data sources.     

中国煤炭企业的全要素生产率增长

 本文通过Malmquist-Luenberger 指数将污染物及矿难作为“坏”产出纳入到全要素生产率的分析框架,测算了中国1998～2009 年30家大型煤炭企业的全要素生产率增长,并对影响全要素生产率增长的因素进行了实证分析。结果显示：“坏”产出约束下大多数企业的全要素生产率出现了负增长,但平均来讲企业的生产技术是显著进步的;在考虑环境污染及安全生产规制的两种不同情形下,分别有14家和16家企业发生过生产可能性边界的移动;技改和安全投入、管理效率以及滞后一期的技术无效率等因素与生产率指数呈显著的正相关关系,单位GDP煤炭消耗总量以及资本-劳动比与生产率指数呈显著的负相关关系,生产率指数与人均GDP呈“U”型关系。     

Zero acceptance number quick switching system for compliance sampling

The zero acceptance number plan is invariably used for compliance sampling and safety inspection of products. The disadvantage of such a plan is that its discriminating power between good and bad lots is poor. This paper presents a quick switching system that has zero acceptance numbers, with a provision for the resubmission of lots not accepted during normal inspection. The proposed system is found to require a smaller average sample size, and possesses greater discriminating power.     

Constructing optimal projection designs

ABSTRACT

The early stages of many real-life experiments involve a large number of factors among which only a few factors are active. Unfortunately, the optimal full-dimensional designs of those early stages may have bad low-dimensional projections and the experimenters do not know which factors turn out to be important before conducting the experiment. Therefore, designs with good projections are desirable for factor screening. In this regard, significant questions are arising such as whether the optimal full-dimensional designs have good projections onto low dimensions? How experimenters can measure the goodness of a full-dimensional design by focusing on all of its projections?, and are there linkages between the optimality of a full-dimensional design and the optimality of its projections? Through theoretical justifications, this paper tries to provide answers to these interesting questions by investigating the construction of optimal (average) projection designs for screening either nominal or quantitative factors. The main results show that: based on the aberration and orthogonality criteria the full-dimensional design is optimal if and only if it is optimal projection design; the full-dimensional design is optimal via the aberration and orthogonality if and only if it is uniform projection design; there is no guarantee that a uniform full-dimensional design is optimal projection design via any criterion; the projection design is optimal via the aberration, orthogonality and uniformity criteria if it is optimal via any criterion of them; and the saturated orthogonal designs have the same average projection performance.     

An evaluation of the trimmed mean approach in clinical trials with dropout

The trimmed mean is a method of dealing with patient dropout in clinical trials that considers early discontinuation of treatment a bad outcome rather than leading to missing data. The present investigation is the first comprehensive assessment of the approach across a broad set of simulated clinical trial scenarios. In the trimmed mean approach, all patients who discontinue treatment prior to the primary endpoint are excluded from analysis by trimming an equal percentage of bad outcomes from each treatment arm. The untrimmed values are used to calculated means or mean changes. An explicit intent of trimming is to favor the group with lower dropout because having more completers is a beneficial effect of the drug, or conversely, higher dropout is a bad effect. In the simulation study, difference between treatments estimated from trimmed means was greater than the corresponding effects estimated from untrimmed means when dropout favored the experimental group, and vice versa. The trimmed mean estimates a unique estimand. Therefore, comparisons with other methods are difficult to interpret and the utility of the trimmed mean hinges on the reasonableness of its assumptions: dropout is an equally bad outcome in all patients, and adherence decisions in the trial are sufficiently similar to clinical practice in order to generalize the results. Trimming might be applicable to other inter‐current events such as switching to or adding rescue medicine. Given the well‐known biases in some methods that estimate effectiveness, such as baseline observation carried forward and non‐responder imputation, the trimmed mean may be a useful alternative when its assumptions are justifiable.     

统计教育现状分析与思考

近几年统计教育规模不断下降的状况已引起人们的高度重视和思考。形成目前状况的原因,既有诸如统计法规宣传不力、人才质量与社会需求相背离、统计数据质量不高等外部原因,也有教育自身在教育模式、教育结构、教育功能、教育标准、教育资源、教学过程等方面存在的问题。我们只有理性地看待统计教育发展现状,认真分析其产生原因,逐个剖析,深入挖掘,抓住主要矛盾,加大改革力度,采取有利措施,才能促进统计教育健康稳步地发展。     

深沪股指收益率波动研究

文章选取沪、深两市1991年1月1日至2005年2月18日的股票指数作为样本,运用EGARCH(1,1)模型,研究指数日收益率波动的性质特征,并探讨了不同阶段股市对利好消息和利空消息的反映。结果表明:不同阶段的指数收益率序列具有结构特征,各阶段沪、深两市指数收益率均与滞后一阶高度相关,且两市指数收益率均具有信息不对称效果。     

基于“奖优罚劣”线性变换算子的区间数多目标灰色局势决策方法

针对多目标决策值为区间数的规范化问题,提出一种具有奖优罚劣特性的[-1,1]线性变换算子,规范化处理原始决策信息,将其运用到目标权重确定,且属性值为区间数的多目标灰色局势决策中,给出了基于"奖优罚劣"算子的区间数多目标灰色局势决策方法,并以空舰导弹设计方案的选择作为应用案例,结果表明该方法操作方便、计算简单、易于实现,可以为一些具有区间值的不确定决策问题提供一种有效、科学、实用的方法。     

环境约束下的工业全要素生产率增长——基于Malmquist-Luenberger指数的行业面板数据分析

目前,关于工业全要素生产率的研究多数只考虑如增加值之类的＂好＂产出,从而忽略了环境污染＂坏＂产出,故对工业发展效率的评价出现失真。鉴此,通过Malmquist-Luenberger指数重新测算考虑环境污染约束的工业全要素生产率增长,并寻找行业＂创新者＂,同时与不考虑环境污染约束的情况进行对比分析。实证研究发现：虽然忽略环境约束会低估技术效率水平和技术效率指数,但会高估技术进步指数和全要素生产率指数;行业＂创新者＂主要集中于制造业,尤其是环境污染较低的行业。     

Life: what is the chance that we are alone?

The Earth is full of life. If life evolved here, why not elsewhere? The Universe is a big place and our galaxy has many stars with planets. So are we alone? What is out there? And how do we know? Mark Burchell looks at the probability of life beyond our planet.     

A high breakdown,high efficiency and bounded influence modified GM estimator based on support vector regression

Regression analysis aims to estimate the approximate relationship between the response variable and the explanatory variables. This can be done using classical methods such as ordinary least squares. Unfortunately, these methods are very sensitive to anomalous points, often called outliers, in the data set. The main contribution of this article is to propose a new version of the Generalized M-estimator that provides good resistance against vertical outliers and bad leverage points. The advantage of this method over the existing methods is that it does not minimize the weight of the good leverage points, and this increases the efficiency of this estimator. To achieve this goal, the fixed parameters support vector regression technique is used to identify and minimize the weight of outliers and bad leverage points. The effectiveness of the proposed estimator is investigated using real and simulated data sets.     

Best ever athlete?

Who was the best athlete the modern world has ever seen? Must we refer to ancient history to decide? Joseph Hilbe looks at the contenders.     

基于随机森林模型的分类数据缺失值插补

缺失数据是影响调查问卷数据质量的重要因素,对调查问卷中的缺失值进行插补可以显著提高调查数据的质量。调查问卷的数据类型多以分类型数据为主,数据挖掘技术中的分类算法是处理属性分类问题的常用方法,随机森林模型是众多分类算法中精度较高的方法之一。将随机森林模型引入调查问卷缺失数据的插补研究中,提出了基于随机森林模型的分类数据缺失值插补方法,并根据不同的缺失模式探讨了相应的插补步骤。通过与其它方法的实证模拟比较,表明随机森林插补法得到的插补值准确度更优、可信度更高。     

Econometric Applications of the Forward Search in Regression: Robustness,Diagnostics, and Graphics

The article illustrates the use of the forward search to provide robust analyses of econometric data. The emphasis is on informative plots that reveal the inferential importance of each observation. The division of observations into “good” and “bad” leverage points is shown to be potentially misleading.     

Good item or bad—can latent class analysis tell?: the utility of latent class analysis for the evaluation of survey questions

Summary.  Latent class analysis has been used to model measurement error, to identify flawed survey questions and to estimate mode effects. Using data from a survey of University of Maryland alumni together with alumni records, we evaluate this technique to determine its usefulness for detecting bad questions in the survey context. Two sets of latent class analysis models are applied in this evaluation: latent class models with three indicators and latent class models with two indicators under different assumptions about prevalence and error rates. Our results indicated that the latent class analysis approach produced good qualitative results for the latent class models—the item that the model deemed the worst was the worst according to the true scores. However, the approach yielded weaker quantitative estimates of the error rates for a given item.     

The Langevin distribution on high dimensional spheres

The Langevin (or von-Mises) distribution L(μ,k,q) of a unit vector in Rq has been well studied for the cases of large samples (n? 8) and high concentrations (K? 8). Here we study it as q? 8. Interesting results are only obtained when we use L(μ,q^½,q).     

基于二元Logistic模型的农村劳动力转移培训需求意愿研究

通过对农村劳动力转移培训需求进行二元Logistic模型检验,发现女性、已婚、群众、转移时间长、目前工作状况不好,以及能对未来家庭生活有所改善等因素可以促进农村劳动力进行转移培训。对此,政府应加大对农村劳动力的培训力度,切实提高培训质量,推行培训与职业资格认证制度的结合。