“传染病”视角下“××门”扩散的模型研究

近年来,由于英汉两种语言的接触而产生的词项借用“××门”不断在新闻媒体和网络上涌现,并以惊人的速度扩散.文章统计了2005-2010年“××门”在中国网络媒体上的使用频率,基于模因论理论,同时借鉴生物传染病的数学模型研究了“××门”的扩散规律,建立了一个简单的“××门”扩散的数学模型,以期对语言接触、扩散与变异等语言动态变化规律研究提供理论分析依据.     

基于动态Panel Data模型的上市公司区域治理效率研究

本文在中国大陆地区910家上市公司样本数据基础上,利用动态Panel Data模型对中国上市公司地区治理效率进行了实证研究.我们发现,中国上市公司的治理效率在不同的区域之间存在着较大的差异.本文认为,造成上市公司治理效率存在地区性差异的主要原因是由于我国各地区在市场化进程中出现的地区发展差异,上市公司治理效率的地区性差异是我国证券市场的一个重要特征,把握这个特征对制定和完善具有针对性的上市公司治理法规和政策有着积极的意义.     

广告竞争模型中的混沌同步特性分析

提出一个基于V - W销售广告反应模型的二维离散广告竞争动态模型. 在两家卖主竞 争的市场中,企业可以生产相互替代的商品,运用广告促销吸引顾客,提高销量. 在V - W模型 的基础上,把广告投入作为控制量,采用线性反馈控制,通过数学分析和数值计算,得出模型中 两个状态变量在一定参数下混沌同步. 并且对混沌同步的稳定性进行了分析     

The dynamic development of gender variability

We diagram and discuss theories of gender identity development espoused by the clinical groups represented in this special issue. We contend that theories of origin relate importantly to clinical practice, and argue that the existing clinical theories are under-developed. Therefore, we develop a dynamic systems framework for gender identity development. Specifically, we suggest that critical aspects of presymbolic gender embodiment occur during infancy as part of the synchronous interplay of caregiver-infant dyads. By 18 months, a transition to symbolic representation and the beginning of an internalization of a sense of gender can be detected and consolidation is quite evident by 3 years of age. We conclude by suggesting empirical studies that could expand and test this framework. With the belief that better, more explicit developmental theory can improve clinical practice, we urge that clinicians take a dynamic developmental view of gender identity formation into account.     

教育动态论的哲学观照

教育是一个动态的发展过程,具有不可逆转的动态规律。教育又是一个系统的动态结构,既有整体的联系又有具体的动态结构的联系。教育的动态发展是由社会价值主体的需要来决定,并受社会发展的制约,社会的发展决定教育的发展也决定教育的形式。     

动态语境与话语选择

语境与话语分析的研究从传统单一的语境特征描述开始,经历了从一元到多元的发展过程,但都没有突破静态的研究,即只强调话语的情景场所,而忽视了话语参与者在每个话轮情景中的改变。Sperber和Wilson提出的关联理论从理据上阐明了动态语境研究的合理性,注重话语理解过程的语境变化。本文立足于认知语言学理论,通过研究动态的语境观察对话语选择的影响,从实践上证明话语的选择取决于不断变化着的语境,这也为话语人际意义的研究提供了更直接的分析途径。     

Some Properties of Order Statistics When the Sample Size Is Random

ABSTRACT

The study of r-out-of-n systems is of utmost importance in reliability theory. In this note, we study closure of different partial orders under the formation of r-out-of-N and (N ? s)-out-of-N systems when the number of components N, forming the system, is a random variable having support {k, k + 1,…}, where k is a fixed positive integer, r ∈ {1,…, k} and s ∈ {0, 1,…, k ? 1}. This generalizes quite a few results already known in the literature. We also study the closure of different partial orders when two systems are formed out of different random number of components.     

The Neutrality Properties of Competing Relative Price Models: Tests Using Linear Feedback

This article uses a variant of Geweke's (1982) linear feedback measure to test common characterizations of monetary neutrality implicit in classes of relative price models. The neutrality properties are defined in terms of relative price changes' response to monetary policy shocks in a system including average price changes, an interest rate, and industrial production growth. The magnitude and patterns of monetary feedback found in U.S. relative price data provide no support for any of the structurally neutral models.     

Stochastic Spanning

ABSTRACT

This study develops and implements methods for determining whether introducing new securities or relaxing investment constraints improves the investment opportunity set for all risk averse investors. We develop a test procedure for “stochastic spanning” for two nested portfolio sets based on subsampling and linear programming. The test is statistically consistent and asymptotically exact for a class of weakly dependent processes. A Monte Carlo simulation experiment shows good statistical size and power properties in finite samples of realistic dimensions. In an application to standard datasets of historical stock market returns, we accept market portfolio efficiency but reject two-fund separation, which suggests an important role for higher-order moment risk in portfolio theory and asset pricing. Supplementary materials for this article are available online.     

Forecast Evaluation in the Presence of Unobserved Volatility

Abstract

A number of volatility forecasting studies have led to the perception that the ARCH- and Stochastic Volatility-type models provide poor out-of-sample forecasts of volatility. This is primarily based on the use of traditional forecast evaluation criteria concerning the accuracy and the unbiasedness of forecasts. In this paper we provide an analytical assessment of volatility forecasting performance. We use the volatility and log volatility framework to prove how the inherent noise in the approximation of the true- and unobservable-volatility by the squared return, results in a misleading forecast evaluation, inflating the observed mean squared forecast error and invalidating the Diebold–Mariano statistic. We analytically characterize this noise and explicitly quantify its effects assuming normal errors. We extend our results using more general error structures such as the Compound Normal and the Gram–Charlier classes of distributions. We argue that evaluation problems are likely to be exacerbated by non-normality of the shocks and that non-linear and utility-based criteria can be more suitable for the evaluation of volatility forecasts.