On the invertibility of EGARCH(p,q)

Of the two most widely estimated univariate asymmetric conditional volatility models, the exponential GARCH (or EGARCH) specification is said to be able to capture asymmetry, which refers to the different effects on conditional volatility of positive and negative effects of equal magnitude, and leverage, which refers to the negative correlation between the returns shocks and subsequent shocks to volatility. However, the statistical properties of the (quasi-)maximum likelihood estimator (QMLE) of the EGARCH(p, q) parameters are not available under general conditions, but only for special cases under highly restrictive and unverifiable sufficient conditions, such as EGARCH(1,0) or EGARCH(1,1), and possibly only under simulation. A limitation in the development of asymptotic properties of the QMLE for the EGARCH(p, q) model is the lack of an invertibility condition for the returns shocks underlying the model. It is shown in this article that the EGARCH(p, q) model can be derived from a stochastic process, for which sufficient invertibility conditions can be stated simply and explicitly when the parameters respect a simple condition.¹¹Using the notation introduced in part 2, this refers to the cases where α ≥ |γ| or α ≤ ? |γ|. The first inequality is generally assumed in the literature related to the invertibility of EGARCH. This article provides (in the Appendix) an argument for the possible lack of invertibility when these conditions are not met. This will be useful in reinterpreting the existing properties of the QMLE of the EGARCH(p, q) parameters.     

Quantile regression for robust inference on varying coefficient partially nonlinear models

In this paper, we propose a robust statistical inference approach for the varying coefficient partially nonlinear models based on quantile regression. A three-stage estimation procedure is developed to estimate the parameter and coefficient functions involved in the model. Under some mild regularity conditions, the asymptotic properties of the resulted estimators are established. Some simulation studies are conducted to evaluate the finite performance as well as the robustness of our proposed quantile regression method versus the well known profile least squares estimation procedure. Moreover, the Boston housing price data is given to further illustrate the application of the new method.     

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。     

区间灰数序列的白化方法及其性质研究

由于灰代数运算体系尚不完善,难以有效构建基于灰数序列的灰色模型,而传统灰数序列的白化方法又将导致信息损失,故在不破坏区间灰数独立性及信息完整性的前提下,设计一种区间灰数序列白化处理的新方法,重点研究白化序列与原区间灰数序列在平移变换及倍乘变换过程中的数据特点;同时将白化序列成功地应用于区间灰数预测及关联分析模型的构建。这一研究成果对拓展灰色模型的适用范围具有重要意义。     

试析湖南现代话剧作家的审美倾向

湖南现代话剧作家由于受到湖湘文化的影响,在剧本创作中表现出“以刺世事”和“凭心而言”的审美倾向。湖南现代话剧作家关心时政、“以刺世事”的积极面世的创作倾向的形成得益于在湖南成长过程中接受的新式教育和亲戚朋友爱国思想的熏陶;他们擅于捕捉生活中的浪漫与诗情的“凭心而言”创作姿态的形成则离不开孩提时在湖湘故土养成的“诗心”主体。历史的、民族的群体实践以及社会、文化的遗传因子对湖南剧作家审美心理的形成产生了潜隐却是重要的作用。     

个体特质、组织理性与新闻从业人员的选题偏好

新闻从业人员的选题偏好既可能受到个人特质的主动性影响,又有可能受到组织的影响.我国媒体具有意识形态的宣传组织以及产业属性的市场组织双重性质,这种双重属性使得媒体从业人员有着不同的目标诉求,遵循不同的行动逻辑.通过对70名新闻从业人员的实证调研,验证了在突发事件的报道中,不同媒体从业人员存在差异性新闻选择偏好,并认为这些差异性新闻选择偏好是由于遵循组织理性行动逻辑的结果,而与个人特质没有统计性相关.     

外出务工对民族混居农村的影响——来自内蒙古翁牛特旗农村的调查

摘要：近20年来,“农民工”已经成为中国城乡经济活动中的重要组成部分和社会现象,上亿农民进城务工与生活不仅极大促进了城市经济的发展,调整了城市人口的年龄结构,推进了中国城市化进程,同时也有力地改善了农民家庭的收入。但目前学界的研究偏于宏观分析和对“迁入地”的调查,对“迁出地”的调查相对较少。本文以内蒙古自治区半农半牧区的26个自然村的户访问卷调查数据为基础,分析了当地外出务工人员的基本情况、结构性特征及务工活动对当地农户收入的贡献,有助于我们更加深入细致地认识和理解农村的外出务工现象及其对农民生活的影响。     

我国城市房屋拆迁问题与其纠偏机制选择

某些违法违规的城市房屋拆迁行为,给社会和民众的各方面都造成了一定危害。引发收地拆迁的内在原因是多方面的,应对症下药,予以彻底治理。但根本上讲,只有从经济层面扼住额外利益驱动这个基本源头,在具体操作中让利于民,充分压缩利益组合集团拆迁开发的利润空间,设置起客观的硬性约束机制,才可能遏止狂收乱拆的不良倾向,从而维护国民的合法物权及住宅权,引导房地产开发和城市建设正常发展。     

Surrogate models in ill-conditioned systems

Ridge versions of an ill-conditioned system are alleged to “act more like an orthogonal system” than the system itself. Alternatives, called surrogates and based on the conditioning of linear systems, are shown to yield smaller expected mean squares than OLS, and uniformly smaller residual sums of squares than ridge. Ridge and surrogate solutions are compared on several marques of orthogonality to include conditioning of dispersion arrays, variance inflation factors, isotropy of variances, and sphericity of contours of the estimators. For these, ridge typically exhibits erratic divergence from orthogonality as the ridge scalar evolves, often reverting back to OLS in the limit. In contrast, surrogate solutions converge monotonically to those from orthogonal systems. Invariance considerations constrain the computations to models in canonical form. Case studies serve to illustrate the central issues.     

Interim analysis of clinical trials based on urn models

Clinical trials usually involve efficient and ethical objectives such as maximizing the power and minimizing the total failure number. Interim analysis is now a standard technique in practice to achieve these objectives. Randomized urn models have been extensively studied in the literature. In this paper, we propose to perform interim analysis on clinical trials based on urn models and study its properties. We show that the urn composition, allocation of patients and parameter estimators can be approximated by a joint Gaussian process. Consequently, sequential test statistics of the proposed procedure converge to a Brownian motion in distribution and the sequential test statistics asymptotically satisfy the canonical joint distribution defined in Jennison & Turnbull (Jennison & Turnbull 2000. Group Sequential Methods with Applications to Clinical Trials, Chapman and Hall/CRC). These results provide a solid foundation and open a door to perform the interim analysis on randomized clinical trials with urn models in practice. Furthermore, we demonstrate our proposal through examples and simulations by applying sequential monitoring and stochastic curtailment techniques. The Canadian Journal of Statistics 40: 550–568; 2012 © 2012 Statistical Society of Canada