非线性协整时间序列的非参数方法及其应用研究
作者：舒晓惠 著
出版时间：2019年版
内容简介
本书主要研究了非线性协整理论的非参数检验与估计两个领域，包括非线性存在性、混沌与分形特征、非线性非平稳检验及非线性协整检验与估计等；梳理了这两个领域的研究脉络和框架。对我国货币各变量序列，以及我国与靠前股市指数序列应用所给出的非线性协整理论的非参数方法进行了非线性存在性检验、混沌与分形特征检验、存在非线性的非平稳检验以及非线性协整检验与估计，得出了较此前学者们应用线性协整理论相关方法更一般的结论。本书不仅可以丰富和完善协整关系模型的理论和方法，而且有助于决策者更准确地把握经济和金融变量之间的相互作用和演化关系，更好地制定经济和金融政策进行宏观调控。
目录
目 录 第1章 绪 论······························································································ 1 1.1 研究背景························································································· 1 1.2 研究的目的和意义············································································ 2 1.3 研究现状与文献综述········································································· 3 1.4 本书章节安排及创新之处································································· 11 第2章 单位根与线性协整理论概述······························································· 14 2.1 单位根过程···················································································· 14 2.2 单位根检验···················································································· 17 2.3 协整及其表述定理··········································································· 23 2.4 协整的估计与检验··········································································· 28 第3章 时间序列的非线性存在性检验···························································· 35 3.1 非线性的定义················································································· 35 3.2 非线性检验的方法··········································································· 35 3.3 Monte Carlo仿真模拟······································································ 43 3.4 我国股市的非线性存在性分析·························································· 45 第4章 非线性非平稳时间序列的混沌与分形特征检验····································· 50 4.1 混沌与分形理论简介······································································· 50 4.2 混沌与分形理论在经济中的应用综述················································· 57 4.3 时间序列中是否存在混沌的非参数检验方法······································· 58 4.4 Monte Carlo仿真模拟······································································ 67 4.5 我国沪深股票指数的混沌与分形特征的实证研究································ 74 第5章 非线性时间序列的非平稳检验···························································· 78 5.1 基于长记忆性、混合性概念的非平稳检验方法···································· 79 5.2 推广的单位根检验··········································································· 83 5.3 货币需求函数各变量的单位根秩检验与全距检验······························· 102 第6章 非线性协整的非参数检验方法·························································· 107 6.1 推广的E-G两步法········································································· 107 6.2 非线性协整的秩检验理论······························································· 108 6.3 记录数协整检验（Record Counting Cointegration Test, RCC）············· 125 6.4 中国与国际股市的非线性协整研究·················································· 128 第7章 非线性协整模型构造与估计的非参数方法·········································· 149 7.1 ACE算法（Alternating Conditional Expections, ACE）······················· 149 7.2 局部核权*小二乘法······································································ 152 7.3 基于神经网络的非线性协整模型估计方法········································ 153 7.4 Monte Carlo仿真实验研究····························································· 172 7.5 实证研究······················································································ 179 第8章 总结与展望···················································································· 186 8.1 本书所做的主要工作······································································ 186 8.2 不足之处······················································································ 186 8.3 进一步研究展望············································································ 187 附 录········································································································ 189 Gauss程序集程序段····················································································· 222 参考文献···································································································· 223 后 记········································································································ 237
