Apply noncausal Cauchy AR(1) with Gaussian component to Taiwan Stock Price Index

Apply noncausal Cauchy AR(1) with Gaussian component to Taiwan Stock Price Index

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碩士 === 國立政治大學 === 經濟學系 === 105 === 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 obs...

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Main Author: 温元駿
Other Authors: 徐士勛
Format: Others
Language:zh-TW
Online Access:http://ndltd.ncl.edu.tw/handle/phzkmj
id ndltd-TW-105NCCU5389023
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spelling ndltd-TW-105NCCU53890232018-05-13T04:29:21Z http://ndltd.ncl.edu.tw/handle/phzkmj Apply noncausal Cauchy AR(1) with Gaussian component to Taiwan Stock Price Index 以Noncausal Cauchy AR(1) with Gaussian Component分析台灣股價指數 温元駿 碩士 國立政治大學 經濟學系 105 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. 徐士勛 學位論文 ; thesis 39 zh-TW
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 碩士 === 國立政治大學 === 經濟學系 === 105 === 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.
author2 徐士勛
author_facet 徐士勛
温元駿
author 温元駿
spellingShingle 温元駿
Apply noncausal Cauchy AR(1) with Gaussian component to Taiwan Stock Price Index
author_sort 温元駿
title Apply noncausal Cauchy AR(1) with Gaussian component to Taiwan Stock Price Index
title_short Apply noncausal Cauchy AR(1) with Gaussian component to Taiwan Stock Price Index
title_full Apply noncausal Cauchy AR(1) with Gaussian component to Taiwan Stock Price Index
title_fullStr Apply noncausal Cauchy AR(1) with Gaussian component to Taiwan Stock Price Index
title_full_unstemmed Apply noncausal Cauchy AR(1) with Gaussian component to Taiwan Stock Price Index
title_sort apply noncausal cauchy ar(1) with gaussian component to taiwan stock price index
url http://ndltd.ncl.edu.tw/handle/phzkmj
work_keys_str_mv AT wēnyuánjùn applynoncausalcauchyar1withgaussiancomponenttotaiwanstockpriceindex
AT wēnyuánjùn yǐnoncausalcauchyar1withgaussiancomponentfēnxītáiwāngǔjiàzhǐshù
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