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研究生:張維敉
研究生(外文):Wee-Bee Teo
論文名稱:金融危機與風險外溢─DCC模型之應用
論文名稱(外文):Financial Crisis and Risk Spillover: An Application of The DCC Model
指導教授:周冠男周冠男引用關係徐之強徐之強引用關係
指導教授(外文):Robin ChouChih-Chiang Hsu
學位類別:碩士
校院名稱:國立中央大學
系所名稱:財務金融研究所
學門:商業及管理學門
學類:財務金融學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:83
中文關鍵詞:風險值風險外溢DCC模型金融危機
外文關鍵詞:Financial CrisisRisk SpilloverDCC modelValue at Risk
相關次數:
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此篇研究主要利用Engle(2001)提出之DCC-多變量GARCH模型探討亞洲金融危機時期,亞洲國家,包括印尼、日本、馬來西亞、菲律賓、韓國、台灣與泰國等匯率市場和股票市場彼此間的動態條件相關性。
  亞洲金融危機於1997年7月泰銖大貶而掀開序幕,其影響快速的蔓延至東南亞各國。雖然傳遞至各國的速度與各國受影響的程度皆不一樣,但是最終影響了全球的經濟以及造成一些新興國家的經濟嚴重衰退。因此,亞洲金融危機使得經濟學者對各金融市場間的關係的評估不在只是著重在國際面,而也開始著重在一個國家裡各個市場的相關性。然而,針對過去一些金融危機(financial crisis)的研究多數著重在報酬率(一階動差)的探討,如匯市報酬率和股市報酬率之間的相關性,較少研究波動性(二階動差)的變化與影響。然而,在財務理論上,不論在資產評價或動態避險等,波動性扮演著很重要的角色。隨著時間的不同,各市場間的波動變化皆不一樣,進而影響市場間波動之相關性也隨著時間之不同而不同。因此,採用固定相關係數來衡量不同市場彼此間的影響似乎易造成高估或低估彼此間的相關性,尤其在波動性發生劇烈變化之時,進而影響避險效果或風險值(Value at Risk,VaR)之計算。
  
本論文之研究結果主要發現市場之間有資訊或波動外溢之現象。波動性之蔓延,使市場彼此間變異與波動相關性皆受到影響,尤其在亞洲金融風暴期間,市場間之波動相關性皆發生明顯正相關之變化。此外,隨著投資種類與投資市場的多樣化及規避風險重要性之提高,採用固定相關係數來衡量市場間之相關性與投資組合之風險值計算,會造成高估或低估的情況,尤其在市場波動劇烈變動時期。
Financial Crisis and Risk Spillover: An Application of the DCC Model
In this paper, we apply the Dynamic Conditional Correlation Multivariate GARCH (DCC MV-GARCH) model, proposed by Engle (2001), to investigate the effects of risk-spillover between currency and equity markets during the Asian crisis. We consider seven Asian countries including ndonesia, Japan, Malaysia, Philippines, South Korea, Taiwan, and Thailand.

The Asian crisis began in July 1997 with the devaluation of the Thai baht and it spread out quickly through East Asia. Although each country experienced the crisis with differing intensity and duration, eventually the global economy is affected by this crisis and causing several emerging countries experience deep recessions.

Many economists have evaluted the relationships among international financial markets and also the intermarket dependencies within each country since the Asian crisis. Studies of Asian crisis mostly focus on the first moment (return), however, volatility (the second moment) plays a key role in many areas of finance, especially in asset pricing and dynamic hedging strategies. For example, volatility and the dynamic correlation among markets play a central role as the selection of investment assets and markets and the importance of dynamic hedging are increasing. The hypothesis of a constant correlation of volatility among markets is likely to be incorrect because the correlation will likely to be more volatile as market volatility fluctuates. Thus, there would be bias if we simply use constant correlation to measure the correlation between markets. Especially when the market volatility is unstable, it would also affect the dynamic hedging effect and the calculation of VaR (Value at Risk).
Our results show that there are volatility spillovers among markets. The dynamic correlations among markets are positively related during the Asian crisis. We find that the assumption of a constant correlation would introduce biases in the calculation of correlation among markets and in the estimation of VaR.
第一章 緒論…………………………………….……………..…….1
1.1 研究動機…………………………………………………….1
1.2 研究目的………………………………….…………………2
1.3 研究方法………………………………………………….. 3
1.4 研究結果………………………………………………….3
1.5 研究架構…………………………………….………………4
第二章 文獻回顧……………………………………..…………….. 5
2.1 波動性之動態模型之相關文獻……………………………. 5
2.2 ARCH模型在財務上的應用…………….. …………………7
2.3 波動性之相關研究………………………………………....9
2.4 亞洲金融危機之相關研究………………………………….11
第三章 理論模型與實證方法……………………….………….14
3.1 理論模型……………………………………………………..14
3.2 兩階段估計方法……………………………...…………….. 15
3.3 假設檢定……..,…………………………………………….. 16
第四章 實證結果分析……………………………………...……..18
4.1 資料來源與資料處理.…..…………………………………….…18
4.1.1 資料來源…………………………………………………19
4.1.2 資料處理…………………………………………………19
4.2 股匯市報酬率敘述計…………………………..……………...19
4.3 各市場間之波動動態相關性變化…………………………….22
4.3.1 各國彼此間的匯率市場波動相關性…………………….23
4.3.2 各國彼此間股市波動相關性變化和各國彼此間匯市波動相關性變化與股市波動相關性變化之比較………31
(1) 各國彼此間的股票市場波動相關性…………………31
(2) 不同國家兩市場分別波動相關性之比較……………33
4.3.3 各別國家裡股匯市之間的波動相關性 ………….…….42
第五章 DCC模型之應用-VaR……………………..………………..52
5.1 VaR之簡述……………………………………………..….……52
5.2 VaR不同計算方式之比較………………………..…..……..52
第六章 結論與未來研究建議……………….……………….…58
6.1 結論……………………..……………………….……………..58
6.2 未來研究建議………………………………………..…….….60
參考文獻………………………………………………..…………..…61
附錄1:虛無假設檢定…………………………………………………64
附錄2:DCC參數之估計…………………………………………....65
附錄3:各國匯率市場之間的波動相關性…………………..………66
附錄4:各國股票市場之間的波動相性……………….……….…69
附錄5:泰國和各國彼此間分別在兩市場的相關性變化………72
附錄6:回饋測試(back-testing)………………………………76
表格與圖表
表 1:各國股價指數………………………………………………..…...18
表 2:各國於亞洲金融風暴前後之匯率政策………………………..….19
表 3:各國股市與匯市之敘述統計……………………………………...20
表 4:同一國家不同市場所選擇的模型……………………………….…23
表 5:泰株大貶對各國匯市間的波動相關性影響與發生時點………….28
表 6:各國和其他國家匯市間呈正╱負相關的組合.…28
表 7:各國在1150觀察值的標準殘差……………………………………..29
表 8:泰株大貶對各國股市間的波動相關性影響與發生時點……………32
表 9:各國和其他國家股市間呈正╱負相關的組合………………….…33
表 10:各國和泰國股市間在1151觀察值左右時的波動相關性………….34
表 11:各國彼此間匯市和股市分別波動相關性………………………..35
表 12:在1151左右,股市和匯市分別波動相關性發生情況………….40
表 13:受亞洲金融風暴影響,股市和匯市分別波動相關性發生情況…..41
圖1:各國匯市和股市之報酬率………………………………………….…22
圖2:印尼匯市和股市間的波動相關性…………………………………...43
圖3:日本匯市和股市間的波動相關性…………………………………….44
圖4:馬來西亞匯市和股市間的波動相關性……………………………...45
圖5:菲律賓匯市和股市間的波動相關性………………………………...46
圖6:韓國匯市和股市間的波動相關性………………………………….…48
圖7:台灣匯市和股市間的波動相關性………………………………….…49
圖8:泰國匯市和股市間的波動相關性…………………………………...50
圖9 :信賴水準95%、常態分配下之風險值………………………………..52
圖 10:日本股市和匯市1994年4月到1997年6月投資期間的風險值….53
圖 11:日本股市和匯市1997年7月至1999年12月投資期間的風險值..54
圖 12:馬來西亞和泰國股市1994年4月至1997年4月投資期間的風險值………………………………………………………………….56
圖13:馬來西亞和泰國股市1997年5月至1999年底投資期間的風險值…57
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