以Noncausal Cauchy AR(1) with Gaussian Component分析台灣股價指數

過去實證研究多以時間序列模型搭配 GARCH 模型針對台灣股價指數進行分析。然而，Gourieroux and Zakoian(2017) 提出，當一時間序列具有泡沫現象時，noncausal Cauchy AR(1) process 是可能的優選模型。此外，Sarno and Taylor(1999) 的研究認為，台灣股價指數具有泡沫現象，故我們以 noncausal Cauchy AR(1) with Gaussian component 分析台灣股價指數，進而判斷其泡沫效果係來自 noncausal linear process 之 local explosive，並根據 noncaus...

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Bibliographic Details
Main Author:	温元駿
Language:	中文
Published:	國立政治大學
Subjects:	台灣股價指數泡沫效果 Noncausal Cauchy AR(1) with Gaussian component Taiwan stock price index Bubble effect
Online Access:	http://thesis.lib.nccu.edu.tw/cgi-bin/cdrfb3/gsweb.cgi?o=dstdcdr&i=sid=%22G1042580031%22.

id	ndltd-CHENGCHI-G1042580031
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spelling	ndltd-CHENGCHI-G10425800312017-07-05T03:30:11Z 以Noncausal Cauchy AR(1) with Gaussian Component分析台灣股價指數 Apply noncausal Cauchy AR(1) with Gaussian component to Taiwan Stock Price Index 温元駿台灣股價指數泡沫效果 Noncausal Cauchy AR(1) with Gaussian component Taiwan stock price index Bubble effect Noncausal Cauchy AR(1) with Gaussian component 過去實證研究多以時間序列模型搭配 GARCH 模型針對台灣股價指數進行分析。然而，Gourieroux and Zakoian(2017) 提出，當一時間序列具有泡沫現象時，noncausal Cauchy AR(1) process 是可能的優選模型。此外，Sarno and Taylor(1999) 的研究認為，台灣股價指數具有泡沫現象，故我們以 noncausal Cauchy AR(1) with Gaussian component 分析台灣股價指數，進而判斷其泡沫效果係來自 noncausal linear process 之 local explosive，並根據 noncausal Cauchy AR(1) 與 Gaussian component 之係數變動，捕捉泡沫效果之形成與來源。 Most of the previous studies focused on analyzing Taiwan Stock Price Index using time series models with GARCH effects. However, Gourieroux and Zakoian (2017) have demonstrated that noncausal Cauchy AR(1) process may be a possible model in which the bubbles are observed. Besides, according to the studies of Sarno and Taylor (1991), some bubbles exactly existed in Taiwan Stock Price Index before 1990. Accordingly, this study aims at investigating the possible bubbles in Taiwan Stock Price Index from 2005 to 2015 by employing noncausal Cauchy AR(1) with Gaussian component method. As a result, we find out he bubbles which modeled by the noncausal linear process are local explosive. And based on the changes of the coefficients from noncausal Cauchy AR(1) and Gaussian component, this study successfully captures the form of bubbles. 國立政治大學 http://thesis.lib.nccu.edu.tw/cgi-bin/cdrfb3/gsweb.cgi?o=dstdcdr&i=sid=%22G1042580031%22. text 中文 Copyright © nccu library on behalf of the copyright holders
collection	NDLTD
language	中文
sources	NDLTD
topic	台灣股價指數泡沫效果 Noncausal Cauchy AR(1) with Gaussian component Taiwan stock price index Bubble effect Noncausal Cauchy AR(1) with Gaussian component
spellingShingle	台灣股價指數泡沫效果 Noncausal Cauchy AR(1) with Gaussian component Taiwan stock price index Bubble effect Noncausal Cauchy AR(1) with Gaussian component 温元駿以Noncausal Cauchy AR(1) with Gaussian Component分析台灣股價指數
description	過去實證研究多以時間序列模型搭配 GARCH 模型針對台灣股價指數進行分析。然而，Gourieroux and Zakoian(2017) 提出，當一時間序列具有泡沫現象時，noncausal Cauchy AR(1) process 是可能的優選模型。此外，Sarno and Taylor(1999) 的研究認為，台灣股價指數具有泡沫現象，故我們以 noncausal Cauchy AR(1) with Gaussian component 分析台灣股價指數，進而判斷其泡沫效果係來自 noncausal linear process 之 local explosive，並根據 noncausal Cauchy AR(1) 與 Gaussian component 之係數變動，捕捉泡沫效果之形成與來源。 === Most of the previous studies focused on analyzing Taiwan Stock Price Index using time series models with GARCH effects. However, Gourieroux and Zakoian (2017) have demonstrated that noncausal Cauchy AR(1) process may be a possible model in which the bubbles are observed. Besides, according to the studies of Sarno and Taylor (1991), some bubbles exactly existed in Taiwan Stock Price Index before 1990. Accordingly, this study aims at investigating the possible bubbles in Taiwan Stock Price Index from 2005 to 2015 by employing noncausal Cauchy AR(1) with Gaussian component method. As a result, we find out he bubbles which modeled by the noncausal linear process are local explosive. And based on the changes of the coefficients from noncausal Cauchy AR(1) and Gaussian component, this study successfully captures the form of bubbles.
author	温元駿
author_facet	温元駿
author_sort	温元駿
title	以Noncausal Cauchy AR(1) with Gaussian Component分析台灣股價指數
title_short	以Noncausal Cauchy AR(1) with Gaussian Component分析台灣股價指數
title_full	以Noncausal Cauchy AR(1) with Gaussian Component分析台灣股價指數
title_fullStr	以Noncausal Cauchy AR(1) with Gaussian Component分析台灣股價指數
title_full_unstemmed	以Noncausal Cauchy AR(1) with Gaussian Component分析台灣股價指數
title_sort	以noncausal cauchy ar(1) with gaussian component分析台灣股價指數
publisher	國立政治大學
url	http://thesis.lib.nccu.edu.tw/cgi-bin/cdrfb3/gsweb.cgi?o=dstdcdr&i=sid=%22G1042580031%22.
work_keys_str_mv	AT wēnyuánjùn yǐnoncausalcauchyar1withgaussiancomponentfēnxītáiwāngǔjiàzhǐshù AT wēnyuánjùn applynoncausalcauchyar1withgaussiancomponenttotaiwanstockpriceindex
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以Noncausal Cauchy AR(1) with Gaussian Component分析台灣股價指數

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