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

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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Bibliographic Details
Main Author: 温元駿
Other Authors: 徐士勛
Format: Others
Language:zh-TW
Online Access:http://ndltd.ncl.edu.tw/handle/phzkmj
Description
Summary: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.