Let and f:Xn→Xn be a continuous map. If f is a second descendible map, then P(f) is closed if and only if one of the following hold: 1);2) For any z ε R (f), there exists a yεw (z,f) ∩ P(f) such that every point o...Let and f:Xn→Xn be a continuous map. If f is a second descendible map, then P(f) is closed if and only if one of the following hold: 1);2) For any z ε R (f), there exists a yεw (z,f) ∩ P(f) such that every point of the set orb (y,f) is a isolated point of the set w (z,f);3) For any z ε R(f), the set w (z,f) is finite;4) For any z ε R(f), the set w' (z,f) is finite. The consult give another condition of f with closed periodic set other than [1].展开更多
本文在α-混合序列假设下,基于半参数变系数模型研究条件期望分位数风险价值(expectile-based value at risk,EVaR)的风险度量.此模型不仅考虑了风险因素的影响,还可以动态描述风险影响及交互效应.同时,EVaR比经典的风险在险价值(quanti...本文在α-混合序列假设下,基于半参数变系数模型研究条件期望分位数风险价值(expectile-based value at risk,EVaR)的风险度量.此模型不仅考虑了风险因素的影响,还可以动态描述风险影响及交互效应.同时,EVaR比经典的风险在险价值(quantile-based value at risk,QVaR)具有更直观、更易于计算的良好性质,而且对于资产分布的尾部损失更加敏感,在度量极端风险情形下,相对于QVaR更为有效和方便.本文采用三阶段估计的方法,分别对变系数部分和常系数部分的参数进行估计,并且给出3个阶段中每个估计的相合性和渐近正态性.为了节省计算时间,提高计算效率,本文采用一步估计的算法,减少迭代所需的时间.由于时间序列样本是非独立样本,建立这些统计量的大样本性质时带来了更大的困难.有别于独立同分布的观察数据,本文利用大小块分割方法发展α-混合序列的极限理论,获得了基于金融时间序列数据建立的模型参数和非参数估计的统计渐近性质.在数值模拟中,本文给出3个模型假设下变系数曲线估计和常系数估计的结果,无论是估计的精确度还是估计的稳健性,模拟结果都表明本文所提出的估计方法有优良的性质.实例则展示了本文所提出模型在上证指数的实际应用.展开更多
The authors define and study topological pre-image entropy for the non-autonomous discrete dynamical systems given by a sequence {fi}i=1^∞ of continuous self-maps of a compact topological space. The basic properties ...The authors define and study topological pre-image entropy for the non-autonomous discrete dynamical systems given by a sequence {fi}i=1^∞ of continuous self-maps of a compact topological space. The basic properties and the invariant with respect to equiconjugacy of pre-image entropy for the non-autonomous discrete dynamical systems are obtained.展开更多
文摘Let and f:Xn→Xn be a continuous map. If f is a second descendible map, then P(f) is closed if and only if one of the following hold: 1);2) For any z ε R (f), there exists a yεw (z,f) ∩ P(f) such that every point of the set orb (y,f) is a isolated point of the set w (z,f);3) For any z ε R(f), the set w (z,f) is finite;4) For any z ε R(f), the set w' (z,f) is finite. The consult give another condition of f with closed periodic set other than [1].
文摘本文在α-混合序列假设下,基于半参数变系数模型研究条件期望分位数风险价值(expectile-based value at risk,EVaR)的风险度量.此模型不仅考虑了风险因素的影响,还可以动态描述风险影响及交互效应.同时,EVaR比经典的风险在险价值(quantile-based value at risk,QVaR)具有更直观、更易于计算的良好性质,而且对于资产分布的尾部损失更加敏感,在度量极端风险情形下,相对于QVaR更为有效和方便.本文采用三阶段估计的方法,分别对变系数部分和常系数部分的参数进行估计,并且给出3个阶段中每个估计的相合性和渐近正态性.为了节省计算时间,提高计算效率,本文采用一步估计的算法,减少迭代所需的时间.由于时间序列样本是非独立样本,建立这些统计量的大样本性质时带来了更大的困难.有别于独立同分布的观察数据,本文利用大小块分割方法发展α-混合序列的极限理论,获得了基于金融时间序列数据建立的模型参数和非参数估计的统计渐近性质.在数值模拟中,本文给出3个模型假设下变系数曲线估计和常系数估计的结果,无论是估计的精确度还是估计的稳健性,模拟结果都表明本文所提出的估计方法有优良的性质.实例则展示了本文所提出模型在上证指数的实际应用.
基金the National Natural Science Foundation of China under Grant Nos.10661001 and 10761007Natural Science Foundation of Jiangxi under Grant No.2007GZS2398partly by Nanchang University Science Foundation under Grant No.Z-03713
文摘The authors define and study topological pre-image entropy for the non-autonomous discrete dynamical systems given by a sequence {fi}i=1^∞ of continuous self-maps of a compact topological space. The basic properties and the invariant with respect to equiconjugacy of pre-image entropy for the non-autonomous discrete dynamical systems are obtained.
