中国共产党坚持胸怀天下的内在逻辑、世界意义与实践要求

坚持胸怀天下是中国共产党百年辉煌成就的重要历史经验,贯穿中国共产党的百年奋斗历史征程,体现了一个马克思主义政党致力于全人类解放的宽广胸怀、雄心壮志、坚定信念和战略思维方式,彰显了中国共产党的使命自觉和责任担当。中国共产党坚持胸怀天下具有深刻的内在逻辑,包含了党对中华优秀传统文化的继承和弘扬的历史逻辑,包含了党对马克思主义理论的坚持和发展的理论逻辑,涵盖了党对无产阶级历史使命的担当和作为的价值逻辑。坚持胸怀天下体现了党的全球视野,具有深厚的世界意义,有助于推动回答世界之问“世界怎么了、我们怎么办”,有助于推动回答时代之问“人类向何处去”,有助于推进世界的和平与发展。同时,坚持胸怀天下在新时代要求推动建设新型国际关系,坚决维护公平公正的国际秩序,关切人类前途命运,推动构建人类命运共同体,创造人类文明新形态,引领和推动人类现代化进程。     

认知纬度解释图式在听力理解过程中的作用

图式理论对英语听力教学的积极作用已经越来越得到公认,国内不少学者对图式的应用价值问题予以了探讨。文章先将对图式及图式理论做较为系统的介绍,再对图式在听力理解中的作用做心理认知纬度的说明,并且对如何在听力教学中发挥图式作用提出自己的建议。期望在日常英语听力教学中运用图式的可操作性得以增强,从而使听力理解的实际效果得以改进。     

从有效市场假说到分形市场假说

介绍了有效市场假说理论的形成与发展以及有效市场假说所引发的争论。阐述了分形市场假说的基本理念,并对我国证券市场(以上海证券市场为例)的分形结构进行了实证分析。结果表明:中国证券市场具有明显的分形特征和持续性,股票的收益率不符合随机游走过程。股票收益率序列不是独立的,具有约62周的长期记忆性。     

Time varying long memory parameter estimation for locally stationary long memory processes

The semiparametric estimators of time varying long memory parameter are investigated for locally stationary long memory processes. The GPH estimator and the local Whittle estimator are considered. Under some mild regularity assumptions, the weak consistency and the asymptotic normality of the estimators are obtained. The finite sample performance of the estimators is discussed through a small simulation study.     

Statistical properties of detrended fluctuation analysis

The main goal of this work is to consider the detrended fluctuation analysis (DFA), proposed by Peng et al. [Mosaic organization of DNA nucleotides, Phys. Rev. E. 49(5) (1994), 1685–1689]. This is a well-known method for analysing the long-range dependence in non-stationary time series. Here we describe the DFA method and we prove its consistency and its exact distribution, based on the usual i.i.d. assumption, as an estimator for the fractional parameter d. In the literature it is well established that the nucleotide sequences present long-range dependence property. In this work, we analyse the long dependence property in view of the autoregressive moving average fractionally integrated ARFIMA(p, d, q) processes through the analysis of four nucleotide sequences. For estimating the fractional parameter d we consider the semiparametric regression method based on the periodogram function, in both classical and robust versions; the semiparametric R/S(n) method, proposed by Hurst [Long term storage in reservoirs, Trans. Am. Soc. Civil Eng. 116 (1986), 770–779] and the maximum likelihood method (see [R. Fox and M.S. Taqqu, Large-sample properties of parameter estimates for strongly dependent stationary Gaussian time series, Ann. Statist. 14 (1986), 517–532]), by considering the approximation suggested by Whittle [Hypothesis Testing in Time Series Analysis (1953), Hafner, New York].     

Piecewise FARIMA models for long-memory time series

We consider the problem of modelling a long-memory time series using piecewise fractional autoregressive integrated moving average processes. The number as well as the locations of structural break points (BPs) and the parameters of each regime are assumed to be unknown. A four-step procedure is proposed to find out the BPs and to estimate the parameters of each regime. Its effectiveness is shown by Monte Carlo simulations and an application to real traffic data modelling is considered.     

Obtaining prediction intervals for FARIMA processes using the sieve bootstrap

The sieve bootstrap (SB) prediction intervals for invertible autoregressive moving average (ARMA) processes are constructed using resamples of residuals obtained by fitting a finite degree autoregressive approximation to the time series. The advantage of this approach is that it does not require the knowledge of the orders, p and q, associated with the ARMA(p, q) model. Up until recently, the application of this method has been limited to ARMA processes whose autoregressive polynomials do not have fractional unit roots. The authors, in a 2012 publication, introduced a version of the SB suitable for fractionally integrated autoregressive moving average (FARIMA (p,d,q)) processes with 0<d<0.5 and established its asymptotic validity. Herein, we study the finite sample properties this new method and compare its performance against an older method introduced by Bisaglia and Grigoletto in 2001. The sieve bootstrap (SB) method is a numerically simpler alternative to the older method which requires the estimation of p, d, and q at every bootstrap step. Monte-Carlo simulation studies, carried out under the assumption of normal, mixture of normals, and exponential distributions for the innovations, show near nominal coverages for short-term and long-term SB prediction intervals under most situations. In addition, the sieve bootstrap method yields better coverage and narrower intervals compared to the Bisaglia–Grigoletto method in some situations, especially when the error distribution is a mixture of normals.     

First‐order bias correction for fractionally integrated time series

Most of the long memory estimators for stationary fractionally integrated time series models are known to experience non‐negligible bias in small and finite samples. Simple moment estimators are also vulnerable to such bias, but can easily be corrected. In this article, the authors propose bias reduction methods for a lag‐one sample autocorrelation‐based moment estimator. In order to reduce the bias of the moment estimator, the authors explicitly obtain the exact bias of lag‐one sample autocorrelation up to the order n⁻¹. An example where the exact first‐order bias can be noticeably more accurate than its asymptotic counterpart, even for large samples, is presented. The authors show via a simulation study that the proposed methods are promising and effective in reducing the bias of the moment estimator with minimal variance inflation. The proposed methods are applied to the northern hemisphere data. The Canadian Journal of Statistics 37: 476–493; 2009 © 2009 Statistical Society of Canada     

Refined Inference on Long Memory in Realized Volatility

There is an emerging consensus in empirical finance that realized volatility series typically display long range dependence with a memory parameter (d) around 0.4 (Andersen et al., 2001; Martens et al., 2004). The present article provides some illustrative analysis of how long memory may arise from the accumulative process underlying realized volatility. The article also uses results in Lieberman and Phillips (2004, 2005) to refine statistical inference about d by higher order theory. Standard asymptotic theory has an O(n^-1/2) error rate for error rejection probabilities, and the theory used here refines the approximation to an error rate of o(n^-1/2). The new formula is independent of unknown parameters, is simple to calculate and user-friendly. The method is applied to test whether the reported long memory parameter estimates of Andersen et al. (2001) and Martens et al. (2004) differ significantly from the lower boundary (d = 0.5) of nonstationary long memory, and generally confirms earlier findings.     

新传播媒介铸牢中华民族共同体意识的功能

由传播技术迭代与革命而衍生的新传播媒介,为当前铸牢中华民族共同体意识提供了一种重要载体。当前,以铸牢中华民族共同体意识为目标,新传播媒介应承担起强化各民族历史记忆,培育各民族公民意识,增进各民族国家认同等主要功能。在现实生活中,充分发挥新传播媒介这三种功能,可以分别为铸牢中华民族共同体意识奠定心理基础、身份基础、政治基础。同时,我们还应当看到新传播媒介是一把双刃剑,规制其负面影响是正确运用新传播媒介的必要前提。