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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 雷立芬(Li-Fen Lei) | |
dc.contributor.author | Wei-Chen Liao | en |
dc.contributor.author | 廖偉真 | zh_TW |
dc.date.accessioned | 2021-06-08T06:57:09Z | - |
dc.date.copyright | 2009-07-23 | |
dc.date.issued | 2009 | |
dc.date.submitted | 2009-07-18 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/25927 | - |
dc.description.abstract | 台灣股市的快速成長加上政府對於外資管制的鬆綁,以及列入摩根史坦利新興市場指數後,愈來愈多投資者關注台灣股票市場發展,使得台灣股市波動性加劇,因而波動性議題越形重要。Andersen與Bollerslev(1997)指出,若使用較低頻資料無法正確反應出市場動態關係,因此建議使用高頻日內分鐘資料來分析。由於股票報酬波動是金融商品 (包括衍生證券) 的評價、投資組合選擇與資產管理很重要的依據,然而不同觀察頻率會有不同研究結果。為了使投資人在能做出正確判斷,最適頻率的選擇就變得格外重要。
本研究運用GARCH、TGARCH及EGARCH三種模型分析不同觀察頻率(五分鐘、十分鐘、三十分鐘、六十分鐘及日資料)GARCH效果變化,以便待出最適預測台灣股價加權指數的觀察頻率。資料選取期間為2006年1月2日至2008年12月31日。 經由實證結果發現,五分鐘觀察頻率模型預測能力最佳,即最能捕捉金融資產波動現象,日資料預測能力最差。因此,未來在探討台灣股票波動性時建議使用高頻五分鐘資料來探討。此外,加入落後一期交易量及落後一期交易量與報酬率交乘項的模型會使得波動持續性下降,亦交易變數可以增加模型解釋能力。 從三種GARCH模型比較發現,TGARCH與EGARCH模型配適能力較一般GARCH模型好,且不對稱效應皆很顯著,顯示台灣市場存在波動不對稱現象,因此未來在探討股票波動性時,需考慮波動不對稱效果。 | zh_TW |
dc.description.abstract | Abstract
The paper evaluates the performance of conditional variance models using high-frequency data of the TAIEX and attempts to determine the optimal sampling frequency for the best daily volatility forecast. In this paper, we use GARCH, T-GARCH and E-GARCH model to measure and also add volume and interaction term. Form the analysis, is found that sampling at 5 minutes gives the best forecast for volatility. Our analysis also suggests that volume and interaction term would give better estimates of volatility with lower forecast error estimate. | en |
dc.description.provenance | Made available in DSpace on 2021-06-08T06:57:09Z (GMT). No. of bitstreams: 1 ntu-98-R96627019-1.pdf: 1579847 bytes, checksum: 87cdfb7d41ee37113e670dc145f07ae5 (MD5) Previous issue date: 2009 | en |
dc.description.tableofcontents | 目錄
謝辭 i 摘要 ii Abstract iii 表目錄 vi 圖目錄 vii 附表目錄 viii 附圖目錄 ix 第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的與論文架構 4 第二章 文獻回顧 6 第一節 股價報酬波動性 6 第二節 股價與交易量關係 8 第三章 理論架構 11 第一節 GARCH模型 11 第二節 模型階次認定與診斷 14 第三節 ARCH效果檢定與模型參數估計 15 第四節 模型配適能力檢定 18 第五節 實證模型設定 19 第四章 實證結果與分析 25 第一節 資料來源與整理 25 第二節 單根檢定 28 第三節 條件平均數方程式之ARMA模型診斷 29 第四節 ARCH效果檢定 32 第五節 實證模型估計 34 第六節 模型預測能力分析 47 第五章 結論 50 參考文獻 53 附錄 58 | |
dc.language.iso | zh-TW | |
dc.title | 不同樣本頻率之股市波動性估計 | zh_TW |
dc.title | Estimation of Stock Volatility
Using Different Sample Frequency | en |
dc.type | Thesis | |
dc.date.schoolyear | 97-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 郭震坤(Jen-Kuen Guo),官俊榮(Jiun-Reng Guan) | |
dc.subject.keyword | 高頻資料,交易量,GARCH模型,TGARCH模型,EGARCH模型, | zh_TW |
dc.subject.keyword | high frequency data,volume,GARCH,TGARCH,EGARCH, | en |
dc.relation.page | 82 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2009-07-20 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 農業經濟學研究所 | zh_TW |
顯示於系所單位: | 農業經濟學系 |
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