ARFIMA approximation and forecasting of the limiting aggregate structure of long‐memory process

This article studies Man and Tiao's (2006) low‐order autoregressive fractionally integrated moving‐average (ARFIMA) approximation to Tsai and Chan's (2005b) limiting aggregate structure of the long‐memory process. In matching the autocorrelations, we demonstrate that the approximation works well, especially for larger d values. In computing autocorrelations over long lags for larger d value, using the exact formula one might encounter numerical problems. The use of the ARFIMA(0, d, d?₁) model provides a useful alternative to compute the autocorrelations as a really close approximation. In forecasting future aggregates, we demonstrate the close performance of using the ARFIMA(0, d, d?₁) model and the exact aggregate structure. In practice, this provides a justification for the use of a low‐order ARFIMA model in predicting future aggregates of long‐memory process. Copyright © 2008 John Wiley & Sons, Ltd.     

从产学研结合谈高职院校品牌的创建

高职教育发展比较迅速,规模和结构日趋完善,但目前还没有形成一批象本科院校那样的品牌高职院校。从市场需求和竞争来看,实施高职院校品牌战略,关系到高职院校的自身生存和今后发展。作者从产学研结合角度就人才培养、科学研究和社会服务等方面探讨高职院校的品牌建设。     

基于时间序列的灰色预测技术在估产模型中的应用

在建立估产模型过程中，引进基于时间序列的灰色预测技术，通过对样本点建立基于时间序列的灰色预测模型和常规的多元线性回归气象模型的分析比较，试图找到一种计算简单，数据要求少而精度较高，时效性较好的建模方法，为时间序列预测在农作物估产方面的应用作出一点探索。     

Optimal sampling frequency for volatility forecast models for the Indian stock markets

This paper evaluates the performance of conditional variance models using high‐frequency data of the National Stock Index (S&P CNX NIFTY) and attempts to determine the optimal sampling frequency for the best daily volatility forecast. A linear combination of the realized volatilities calculated at two different frequencies is used as benchmark to evaluate the volatility forecasting ability of the conditional variance models (GARCH (1, 1)) at different sampling frequencies. From the analysis, it is found that sampling at 30 minutes gives the best forecast for daily volatility. The forecasting ability of these models is deteriorated, however, by the non‐normal property of mean adjusted returns, which is an assumption in conditional variance models. Nevertheless, the optimum frequency remained the same even in the case of different models (EGARCH and PARCH) and different error distribution (generalized error distribution, GED) where the error is reduced to a certain extent by incorporating the asymmetric effect on volatility. Our analysis also suggests that GARCH models with GED innovations or EGRACH and PARCH models would give better estimates of volatility with lower forecast error estimates. Copyright © 2008 John Wiley & Sons, Ltd.     

Dynamic density forecasts for multivariate asset returns

We propose a simple and flexible framework for forecasting the joint density of asset returns. The multinormal distribution is augmented with a polynomial in (time‐varying) non‐central co‐moments of assets. We estimate the coefficients of the polynomial via the method of moments for a carefully selected set of co‐moments. In an extensive empirical study, we compare the proposed model with a range of other models widely used in the literature. Employing a recently proposed as well as standard techniques to evaluate multivariate forecasts, we conclude that the augmented joint density provides highly accurate forecasts of the ‘negative tail’ of the joint distribution. Copyright © 2010 John Wiley & Sons, Ltd.     

语义取象对词义组合与发展的影响

词的所指对象依照认知经验会在人的心目中形成一定的心理意象,可以称之为"语义取象"。通过对"嘴、口、脸、面"的词义分析发现:受深层认知因素的制约,两个词即使词汇意义大致相当,但它们在人们认知体系中有不同的意象和各自突显的特征,这深刻影响着词的组合和词义的发展,对词义系统的自我调控与平衡是极有利的。聚焦于词的语义取象,能够获得词义分析的新视角,能够为词义的组合和发展趋势提供解释,也为同义词的辨析提供新思路。     

中国共产党对马克思主义结合中国实际逻辑进路的选择

在马克思主义与中国实际结合的过程中,存在着＂四化＂即马克思主义中国化、马克思主义化中国、中国化马克思主义、中国马克思主义化。在结合的过程中,中国共产党选择了一条沿着＂马克思主义化中国——马克思主义中国化——中国化马克思主义——中国马克思主义化＂的逻辑进路,表现为对马克思主义摹写——建构——运用的过程。其实质是理论——实践——理论——实践的逻辑发展过程。这条与＂实践——理论——实践＂道路相悖的道路选择既有符合中国社会实际的方面,但也给中国社会的发展带来了一些问题。     

探讨在需求分析理论框架下实现高职英语教材的优化整合

在需求分析理论和教材调整、取舍理论的指导下,结合南京工业职业技术学院(国家首批示范高职院)长期以来高职公共英语教材选用和使用的具体情况,采用问卷调查和访谈的方式,探讨教材优化整合的新思路——构建高职英语教材体系。     

汉字的视觉语言表现

汉字本身具有很高的审美性与观赏性,充分运用了平衡、对称、和谐等形式美法则,汉字以字形和字意的内在组合关系作为视觉信息传达的媒介来进行个性化的设计,充分体现了现代汉字强烈的视觉冲击力,使人们在获得信息的同时得到审美体验。     

基于回归分析与三次指数平滑的组合预测

组合预测是把几种单一的预测方法进行组合后得到更好的预测结果的方法.文章根据国家财政用于科学研究支出的统计数据,运用回归预测与三次指数平滑预测,而后求出组合预测的权重,最后得出更优的预测结果.