Show simple item record

dc.contributor.advisor王学新
dc.contributor.author李亚日
dc.date.accessioned2018-12-05T01:43:32Z
dc.date.available2018-12-05T01:43:32Z
dc.date.issued2017-11-01
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/170242
dc.description.abstract时间序列模型在经济、金融、统计、计量经济学等众多领域中都有着非常广泛的应用。其中,GARCH模型也经常被用来研究金融市场中产品价格的波动情况。但是,在这些应用中,人们往往会忽略判断模型能否成立时的一些重要假设,比如检验ARMA模型的混成检验统计量在假设残差不相关时服从卡方分布,而这些假设条件的忽略很有可能造成对模型的构造造成一定的影响。所以,将假设条件放松为不相关序列是必要并且具有一定是现实意义。 本文采用的方法主要是Wang在2016年针对弱残差时间序列提出的简易混成检验模型。这一新的混成检验通过残差自相关系数的转换,使得检验结果在弱残差的情况下依然有效,并且避免了选择参数的问题,为标准混...
dc.description.abstractModels for time series are quite popular in Economics, Finance, Statistics and Econometrics and GARCH models are usually used to study the volatility in financial market. However, people sometimes would ignore the important assumptions when using the models, which is likely to have an inverse effect on modelling. For example, the Portmanteau test follows a chi squared distribution, under the assum...
dc.language.isozh_CN
dc.relation.urihttps://catalog.xmu.edu.cn/opac/openlink.php?strText=56960&doctype=ALL&strSearchType=callno
dc.source.urihttps://etd.xmu.edu.cn/detail.asp?serial=61184
dc.subject弱GARCH模型
dc.subject混成检验
dc.subject时间序列
dc.subjectWeak GARCH models
dc.subjectPortmanteau test
dc.subjectTime series
dc.title简易混成检验在弱GARCH模型的应用
dc.title.alternativeA Simple Portmanteau Test for Weak GARCH Models
dc.typethesis
dc.date.replied2017-04-28
dc.description.note学位:经济学硕士
dc.description.note院系专业:王亚南经济研究院_西方经济学
dc.description.note学号:27720141152742


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record