跳到正文
← 返回论文列表与筛选
阅读说明

本页整理公开书目信息,不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成,未完成全文核验,可能有误;具体假设、证明与结论请核对原文。摘要保留来源文本,未经模型改写。

DOI 首次登记不等于接收或发表日期。部分更正、评论等条目没有独立摘要;缺少可靠材料时保留待补状态。

引用量采用 OpenAlex 单条关联记录,不合计多个记录;关联记录可能包含正式发表版本,不等于此版本单独引用。缺失不视为零,引用指标不代表论文质量。

关注作者按书目中的完整姓名匹配,同名和姓名变体需人工辨别。相关论文先按共享细分方向和具体方法排列,再参考通用方法与发表日期。

分类依据与纠错

AI 根据所提供的论文材料归类:摘要直接以金融波动为对象,研究多状态 GARCH、不对称性及波动动态。

反馈分类问题

正在核对关联版本…

代码、数据与补充材料

正在核对对应版本的资源…

关注这篇论文的作者
Alvaro Veiga

用灵活系数 GARCH(1,1) 模型刻画金融波动的多重状态

研究问题
如何用多于两个状态的 GARCH 模型刻画金融波动的符号与幅度不对称及间歇动态,并兼顾状态选择、平稳性与估计?
方法与思路
作者构建灵活系数多状态 GARCH(1,1) 模型,以序贯检验确定状态数,给出平稳性限制及准最大似然渐近理论,并开展模拟和实证。
材料陈述的贡献
摘要称,模型允许超过两个极限状态,局部爆炸状态可与整体严格平稳、遍历并存;高斯误差模拟也可产生高峰度和 Taylor 效应。
阅读关注点
应核对状态数检验如何处理识别问题、整体平稳性条件、准最大似然所需假设,以及模拟特征与实证拟合证据的对应关系。
阅读边界
所给 Crossref 摘要未列出所谓较弱条件及实证样本,也未量化检验表现;模型的比较优势与其他版本变化不能据此确认。

原文摘要

In this paper a flexible multiple regime GARCH(1,1)-type model is developed to describe the sign and size asymmetries and intermittent dynamics in financial volatility. The results of the paper are important to other nonlinear GARCH models. The proposed model nests some of the previous specifications found in the literature and has the following advantages. First, contrary to most of the previous models, more than two limiting regimes are possible, and the number of regimes is determined by a simple sequence of tests that circumvents identification problems that are usually found in nonlinear time series models. The second advantage is that the novel stationarity restriction on the parameters is relatively weak, thereby allowing for rich dynamics. It is shown that the model may have explosive regimes but can still be strictly stationary and ergodic. A simulation experiment shows that the proposed model can generate series with high kurtosis and low first-order autocorrelation of the squared observations and exhibit the so-called Taylor effect, even with Gaussian errors. Estimation of the parameters is addressed, and the asymptotic properties of the quasi-maximum likelihood estimator are derived under weak conditions. A Monte-Carlo experiment is designed to evaluate the finite-sample properties of the sequence of tests. Empirical examples are also considered.

笔记与分组
相关领域论文