航班动态定价机制下的机票价格序列变点估计

文章旨在研究受航空业动态定价机制影响下的机票价格序列变点估计模型,文中分析了机票价格u8序列数据的结构特点,提出了可用于高噪声数据环境下、阶梯状、带明显多变点的多阶段序列变点估计框架,该框架中级联组合了DBSCAN算法、EM-高斯混合模型聚类、凝聚层次聚类算法和基于乘积划分模型的变点估计方法等多种成熟的数据分析方法,通过对“北京-昆明”航线航班的实证分析,验证了数据分析框架的有效性和普遍适用性。     

双重视角下的中国经济周期混频测度

本文同时在混频动态因子模型截距和方差项引入马尔科夫区制转换过程,从经济增长速度和波动强度的双重角度对我国经济周期不同阶段间的运行特征进行详细考察。研究表明,我国经济周期呈现出明显不同的阶段性特征;不同状态间的转移概率存在非对称性;新常态背景下经济运行继续保持微波化的平稳运行态势是大概率事件。此外,本文提取的一致景气指数与我国实际季度GDP增长率的走势基本一致,能较为准确地反映各个时期的经济形势。     

Long memory in intertrade durations,counts and realized volatility of NYSE stocks

We study the persistence of intertrade durations, counts (number of transactions in equally spaced intervals of clock time), squared returns and realized volatility in 10 stocks trading on the New York Stock Exchange. A semiparametric analysis reveals the presence of long memory in all of these series, with potentially the same memory parameter. We introduce a parametric latent-variable long-memory stochastic duration (LMSD) model which is shown to better fit the data than the autoregressive conditional duration model (ACD) in a variety of ways. The empirical evidence we present here is in agreement with theoretical results on the propagation of memory from durations to counts and realized volatility presented in Deo et al. (2009).     

刘易斯拐点对甘肃地区“民工荒”现象的验证分析

近年甘肃地区出现了＂民工荒＂现象,是否意味着刘易斯拐点的到来？通过对二元经济模型和刘易斯拐点的理论进行重新梳理,确定拐点的判断标准,即劳动力转移引起农业部门制度工资上涨,进而引起工业部门实际工资上涨。结合甘肃地区实际情况进行分析结果表明,甘肃地区出现的＂民工荒＂不能认为是刘易斯拐点的到来。解决＂民工荒＂的对策应该是改善农民工就业环境;加大就业技能培训,提高农民工科技文化素质;提供优惠政策,鼓励农民工回乡创业。     

以跨文化视角审视纳博科夫的文学世界

俄裔美籍双语作家、文艺评论家兼诗人弗拉基米尔·纳博科夫,在20世纪世界文学史上占有重要的位置.他一生辗转迁居,造就了他跨国界、跨民族、跨语言、跨文化的多彩文学艺术个性,即在浓郁的俄罗斯文化背景上叠印了英美社会现实的缩影.跨文化的创作就需要我们用跨文化的视角去审视、去衡量、去解读,这样才能给予他合理而正确的评价,也才能真正走入纳博科夫具有多彩艺术个性的文学世界.     

"点"、"线"、"面"的缺失与突破

从上世纪90年代以来,文艺理论与批评陷入了"精神疲软"和"话语城堡"之中,失去了原创性,其主要原因不仅在于失去了对于文化之根--"元点"的追寻,在历史线索方面有所迷失,而且远离了具体的文艺创作实践,使文艺理论与批评失去了原生的动力与活力.     

全球化背景下的中国文学思想体系

全球化的困惑使我们进入了一个杂话语的时代,但是每一种话语都深深地打着不同学科背景的烙印。作为一名人文知识分子,应该以"中国现代人"的生存困境为基点,打破各种人为的学科界限,以便获得触类旁通、交相深化的学术发现。     

An investigation of the spatial correlations for relative purchasing power in Baden–Württemberg

The relative purchasing power—i.e., the purchasing power per inhabitant—is one of the key characteristics for businesses deciding on site selection. Apart from that it also plays a major role in regional planning, pricing policy and market research. In this study we investigate the spatial correlations for relative purchasing power of the townships in Baden–Württemberg. In particular, changes in relative purchasing power are analysed for three different time intervals, 1987–1993, 1993–1998 and 1998–2004, by means of distance-dependent characteristics like the mark–correlation function, the Simpson indices α(r) and β(r) and by tests on random labelling. It is shown that there are positive correlations for small distances between different townships but that these positive correlations become weaker over the years until they are almost nonexistent (in the sense that hypotheses of random labelling are no longer rejected). A conclusion from this loss of spatial correlations with time is that the relative purchasing power might become more and more purely random. This means that the relative purchasing power in a township is less and less influenced by the relative purchasing power of townships nearby. We further analysed these changes in the Bodensee–Oberschwaben and Stuttgart regions to compare the development of the relative purchasing power in both urban and rural environments. This analysis was done in close cooperation with W. Brachat–Schwarz and W. Walla of the Statistical Office of Baden–Württemberg. S.E. is supported by a grant of the graduate college 1100 at Ulm University.     

A Note on Continuous Spatial-Temporal Dynamics of Stochastic Processes

We propose a general form to analyze the space-time interdependency of continuous space-time stochastic processes. We present a new space-time approach based on the intensity function of the underlying point process. These formulations can be, to some extent, analytically solved to obtain explicit formulae of interest. We define a general function that controls the space-time interaction and allows for closed forms depending on the particular choice of several mathematical tools playing a role in this interaction function. In particular, we make use of copulas and Laplace transforms to provide interesting examples of the dynamics of the random intensity function and, in turn, of the number of points contained in a given region.     

A Monte Carlo method for filtering a marked doubly stochastic Poisson process

The author provides an approximated solution for the filtering of a state-space model, where the hidden state process is a continuous-time pure jump Markov process and the observations come from marked point processes. Each state k corresponds to a different marked point process, defined by its conditional intensity function λ _k (t). When a state is visited by the hidden process, the corresponding marked point process is observed. The filtering equations are obtained by applying the innovation method and the integral representation theorem of a point process martingale. Since the filtering equations belong to the family of Kushner–Stratonovich equations, an iterative solution is calculated. The theoretical solution is approximated and a Monte Carlo integration technique employed to implement it. The sequential method has been tested on a simulated data set based on marked point processes widely used in the statistical analysis of seismic sequences: the Poisson model, the stress release model and the Etas model.