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系統識別號 U0002-0901200814360500
中文論文名稱 資產報酬在偏態GED分配下之跳躍模型比較
英文論文名稱 A comparison of GARCH –Jump Models with Skewed Generalized Error Distribution for Asset Returns
校院名稱 淡江大學
系所名稱(中) 財務金融學系碩士在職專班
系所名稱(英) Department of Banking and Finance
學年度 96
學期 1
出版年 97
研究生中文姓名 陳俊吉
研究生英文姓名 Chun-Chi Chen
學號 794490390
學位類別 碩士
語文別 中文
口試日期 2007-12-29
論文頁數 59頁
口試委員 指導教授-李命志
共同指導教授-鄭婉秀
委員-俞海琴
委員-邱建良
委員-姜淑美
中文關鍵字 GARCH-JD  ARJI  高狹峰  跳躍  SGED  概似比率檢定 
英文關鍵字 GARCH-JD  ARJI  Leptokurtosis  Jump  SGED  LR test 
學科別分類
中文摘要 本研究以跳躍擴散模型(GARCH-JD)及Chan and Maheu(2002)的ARJI模型,探討資產報酬為SGED分配下,美國及金磚四國(巴西、俄羅斯、印度及中國;BRICs)等五個國家之股價指數日報酬率是否存在跳躍的現象與是否具備高峰、厚尾及波動叢聚等特性,並以概似比率檢定檢驗模型的配適性,最後再分析模型在成熟市場與新興市場上,對於統計特性捕捉能力的優劣性。
實證結果發現這五個國家的條件報酬分配普遍存在高狹峰及波動叢聚的現象,但俄羅斯在GARCH-JD及ARJI模型上及中國在GARCH-JD模型上無法捕捉到偏態特性。跳躍分析過程中,發現除了巴西之外,均能捕捉到顯著的跳躍現象,跳躍過程具備了與時俱變的特徵,跳躍參數中觀察到各國股價的波動有必要考量跳躍的現象,當資產報酬設定為SGED分配時,在捕捉統計特性上更具效率。ARJI模型在SGED分配假設下發現成熟市場在消化前期對於當期股價報酬率的影響是較具效率的,但前期不可預期的價格波動對於成熟市場當期的影響卻較新興市場來得強烈。最後從概似比率檢定觀察到所有國家使用SGED模型來估計的結果均較常態分配的模型有顯著的配適度,整體而言,ARJI模型捕捉統計特性的能力優於GARCH-JD模型,且ARJI模型運用於新興市場較之運用於成熟市場有更好的解釋能力。
英文摘要 This paper adopts the GARCH jump model and ARJI model of Chan and Maheu(2002) that combine the skewed generalized error distribution of asset returns, in order to examine the jump, leptokurtosis and volatility clustering for the rates of returns of America and BRICs. We also employ likelihood ratio test for testing goodness of different models. In conclusion, we analyze different models’ capture ability for statistic features of mature market and emerging markets.
The empirical results indicated that the five countries exist heavy tail and volatility clustering, but GARCH-JD and ARJI model with Russia and GARCH-JD with China can’t capture skewness. We also find these countries’ stock returns except Brazil with the two models have significant characteristic of jumping and jump process is provided with time varying. It’s better efficient when we assume that asset returns obey SGED. The ARJI model with SGED of asset returns develop that the diminishing efficiency for mature markets is faster then emerging markets while the earlier stage’s returns affect it at present. But mature markets’ nonpredictive volatility in early days for effecting upon at once is stronger then emerging markets. In the end, the likelihood ratio test demonstrate that these countries using SGED have more significant goodness of fit then using normal distribution. Totally, the ARJI model captures statistical property’s ability surpasses the GARCH-JD model and the ARJI model utilizes to the emerging markets compared with utilizes has the better explanation ability to the mature market.
論文目次 目 錄
第壹章 緒論……………………………………………………… 1
第一節 研究背景與動機……………………………………… 1
第二節 研究目的……………………………………………… 3
第三節 研究架構……………………………………………… 5

第貳章 相關理論與文獻回顧…………………………………… 6
第一節 相關理論……………………………………………… 6
第二節 國內外文獻回顧……………………………………… 8

第參章 研究方法…………………………………………………11
第一節 單根檢定…………………………………………………11
第二節 ARCH檢定…………………………………………………16
第三節 GED分配………………………………………………… 19
第四節 GARCH(1,1)模型…………………………………………22
第五節 GARCH-JD模型……………………………………………24
第六節 ARJI模型…………………………………………………26
第七節 ARJI-SGED模型………………………………………… 29
第八節 概似比率檢定……………………………………………32

第肆章 實證分析…………………………………………………33
第一節 資料來源整理……………………………………………33
第二節 基本統計特性分析………………………………………36
第三節 單根檢定…………………………………………………37
第四節 ARCH檢定…………………………………………………43
第五節 實證結果分析……………………………………………44

第伍章 結論………………………………………………………52

參考文獻……………………………………………………………55


表 次
【表3.1】SGT家族機率密度函數表………………………………21
【表4.1】各國家股價指數報酬率基本統計量………………… 36
【表4.2】各國家股價指數報酬率選取最適落階期準則……… 38
【表4.3】各國家股價指數報酬率ADF單根檢定(水準項)………40
【表4.4】各國家股價指數報酬率ADF單根檢定(差分項)………40
【表4.5】各國家股價指數報酬率PP單根檢定(水準項)……… 40
【表4.6】各國家股價指數報酬率PP單根檢定(差分項)……… 41
【表4.7】ARCH效果檢定………………………………………… 43
【表4.8】美國S&P500指數(SPX)模型估計………………………47
【表4.9】巴西聖保羅BOVESPA指數(IBOV)模型估計……………48
【表4.10】俄羅斯莫斯科ASP綜合指數(ASPGEN)模型估計…… 49
【表4.11】印度孟買SENSEX30指數(SENSEX)模型估計…………50
【表4.12】中國上海證交所綜合指數(SHCOMP)模型估計………51


圖 次
【圖3.1】SGT家族的族譜…………………………………………20
【圖4.1】美國之S&P500指數(SPX)走勢圖………………………34
【圖4.2】巴西聖保羅BOVESPA指數(IBOV)走勢圖………………34
【圖4.3】俄羅斯莫斯科ASP綜合指數(ASPGEN)走勢圖…………34
【圖4.4】印度孟買SENSEX30指數(SENSEX)走勢圖…………… 35
【圖4.5】中國上海證交所綜合指數(SHCOMP)走勢圖………… 35
【圖4.6】美國之S&P500指數(SPX)報酬走勢圖…………………41
【圖4.7】巴西聖保羅BOVESPA指數(IBOV)報酬走勢圖…………41
【圖4.8】俄羅斯莫斯科ASP綜合指數(ASPGEN)報酬走勢圖……42
【圖4.9】印度孟買SENSEX30指數(SENSEX)報酬走勢圖……… 42
【圖4.10】中國上海證交所綜合指數(SHCOMP)報酬走勢圖……42
參考文獻 一、中文部份
李命志、洪瑞成、劉洪鈞,「厚尾GARCH模型之波動性預測能力比較」,輔仁管理管刊,第14卷第2期,2007年,頁47-72。
李彥賢、姜淑美、邱建良,「亞洲金融風暴對台灣股匯市影響:跳躍-擴散模型應用」,朝陽商管評論,第5卷第1期,2006年,頁1-22。
林丙輝、葉仕國,「台灣股票價格非連續跳躍變動條件異質變異之研究」,證券市場發展季刊,第4期,1999年,頁61-92。
林楚雄、劉維琪、吳欽杉,「GJR與Volatility-Switching GARCH模型的比較:台灣股票市場條件波動不對稱的研究」,中國財務學會暨財務金融學術論文研討會論文集,1999年。
邱哲修、林卓民、洪瑞成、徐明傑,「價格不連續下的最適避險策略-ARJI模型之應用」,計量管理期刊,第2卷第2期,2005年,頁189-206。
洪瑞成、劉洪鈞,「厚尾GARCH模型之波動性預測績效」,計量管理期刊,第3卷第2期,2005年,頁161-174。
黃博怡、邱哲修、林卓民、陳建宏,「短期利率之動態條件變異與預測績效之探討」金融風險管理季刊,第1卷第2期,2005年,頁17-32。
蘇欣玫、鄒易凭、鄭婉秀,「美國存託憑證與其標的股票之波動性-跳躍與門檻自我迴歸模型之應用」,輔仁管理評論,第14卷第2期,2007年,頁27-45。

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