Temporal Aggregation of GARCH Process: An Empirical Study of the Stock Markets in Greater China

碩士 === 真理大學 === 管理科學研究所 === 93 === This study is to investigate volatility-clustering and the parameters consistency between implied estimates on the temporal aggregation and direct estimates of GARCH(1,1) models at four frequencies(daily, weekly, bi-weekly and monthly) written on Greater China Stoc...

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Main Authors: Ching-Lian Lai, 賴警聯
Other Authors: Chung-Chu Chuang
Format: Others
Language:zh-TW
Published: 2005
Online Access:http://ndltd.ncl.edu.tw/handle/09850273815529921880
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spelling ndltd-TW-093AU0004570012016-06-13T04:17:01Z http://ndltd.ncl.edu.tw/handle/09850273815529921880 Temporal Aggregation of GARCH Process: An Empirical Study of the Stock Markets in Greater China GARCH過程的跨時加總:大中華經濟圈股票市場的實證 Ching-Lian Lai 賴警聯 碩士 真理大學 管理科學研究所 93 This study is to investigate volatility-clustering and the parameters consistency between implied estimates on the temporal aggregation and direct estimates of GARCH(1,1) models at four frequencies(daily, weekly, bi-weekly and monthly) written on Greater China Stock markets. The resultant shows the data generating process of the daily stock indices of Greater China are close to IGARCH model. There are not consistent between the direct estimates and the implied estimates based on the daily frequency data other then Shanghai A stock index. In addition, the parameters sum of conditional heteroscedasticiity function tend to zero as aggregation level m approach to infinity, and conditional heteroscedasticity almost disappears. Chung-Chu Chuang 莊忠柱 2005 學位論文 ; thesis 82 zh-TW
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language zh-TW
format Others
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description 碩士 === 真理大學 === 管理科學研究所 === 93 === This study is to investigate volatility-clustering and the parameters consistency between implied estimates on the temporal aggregation and direct estimates of GARCH(1,1) models at four frequencies(daily, weekly, bi-weekly and monthly) written on Greater China Stock markets. The resultant shows the data generating process of the daily stock indices of Greater China are close to IGARCH model. There are not consistent between the direct estimates and the implied estimates based on the daily frequency data other then Shanghai A stock index. In addition, the parameters sum of conditional heteroscedasticiity function tend to zero as aggregation level m approach to infinity, and conditional heteroscedasticity almost disappears.
author2 Chung-Chu Chuang
author_facet Chung-Chu Chuang
Ching-Lian Lai
賴警聯
author Ching-Lian Lai
賴警聯
spellingShingle Ching-Lian Lai
賴警聯
Temporal Aggregation of GARCH Process: An Empirical Study of the Stock Markets in Greater China
author_sort Ching-Lian Lai
title Temporal Aggregation of GARCH Process: An Empirical Study of the Stock Markets in Greater China
title_short Temporal Aggregation of GARCH Process: An Empirical Study of the Stock Markets in Greater China
title_full Temporal Aggregation of GARCH Process: An Empirical Study of the Stock Markets in Greater China
title_fullStr Temporal Aggregation of GARCH Process: An Empirical Study of the Stock Markets in Greater China
title_full_unstemmed Temporal Aggregation of GARCH Process: An Empirical Study of the Stock Markets in Greater China
title_sort temporal aggregation of garch process: an empirical study of the stock markets in greater china
publishDate 2005
url http://ndltd.ncl.edu.tw/handle/09850273815529921880
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AT làijǐnglián garchguòchéngdekuàshíjiāzǒngdàzhōnghuájīngjìquāngǔpiàoshìchǎngdeshízhèng
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