Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/111376| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | 徐士勛 | zh_TW |
| dc.contributor.author | 温元駿 | zh_TW |
| dc.creator | 温元駿 | zh_TW |
| dc.date | 2017 | en_US |
| dc.date.accessioned | 2017-07-24T04:16:28Z | - |
| dc.date.available | 2017-07-24T04:16:28Z | - |
| dc.date.issued | 2017-07-24T04:16:28Z | - |
| dc.identifier | G1042580031 | en_US |
| dc.identifier.uri | http://nccur.lib.nccu.edu.tw/handle/140.119/111376 | - |
| dc.description | 碩士 | zh_TW |
| dc.description | 國立政治大學 | zh_TW |
| dc.description | 經濟學系 | zh_TW |
| dc.description | 104258003 | zh_TW |
| dc.description.abstract | 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。 | zh_TW |
| dc.description.abstract | 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. | en_US |
| dc.description.tableofcontents | 1 緒論 1\n2 文獻回顧 3\n3 研究模型 6\n3.1 穩定分配 (Stable distribution) 6\n3.2 橢圓分配 (Elliptical distribution) 7\n3.3 Noncausal linear AR(1) process 8\n4 估計方法 10\n4.1 泡沫效果 (Bubble Effect) 10\n4.2 Noncausal Cauchy AR(1) 之係數估計與其漸近性質 10\n4.3 NoncausalCauchylinearAR(1)processwithGaussianAR(1)component 13\n4.4 實證特徵函數 (empirical characteristic function, ECF) 估計 14\n4.4.1 獨立且同分配資料型態 15\n4.4.2 時間序列資料型態 15\n4.5 資料模擬 16\n5 實證分析 19\n5.1 資料基本分析與描述 19\n5.2 ACF 分析 21\n5.3 模型檢定 21\n5.4 參數估計 24\n5.5 分段估計 25\n6 結論 32\nA 一般動差估計法(generalizedmethodofmomentestimator, GMM\nestimator) 39 | zh_TW |
| dc.format.extent | 1019004 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.source.uri | http://thesis.lib.nccu.edu.tw/record/#G1042580031 | en_US |
| dc.subject | 台灣股價指數 | zh_TW |
| dc.subject | 泡沫效果 | zh_TW |
| dc.subject | Noncausal Cauchy AR(1) with Gaussian component | zh_TW |
| dc.subject | Taiwan stock price index | en_US |
| dc.subject | Bubble effect | en_US |
| dc.subject | Noncausal Cauchy AR(1) with Gaussian component | en_US |
| dc.title | 以Noncausal Cauchy AR(1) with Gaussian Component分析台灣股價指數 | zh_TW |
| dc.title | Apply noncausal Cauchy AR(1) with Gaussian component to Taiwan Stock Price Index | en_US |
| dc.type | thesis | en_US |
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| item.cerifentitytype | Publications | - |
| item.grantfulltext | open | - |
| item.openairetype | thesis | - |
| item.fulltext | With Fulltext | - |
| item.openairecristype | http://purl.org/coar/resource_type/c_46ec | - |
| Appears in Collections: | 學位論文 | |
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| 003101.pdf | 995.12 kB | Adobe PDF2 | View/Open |
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