臺灣博碩士論文加值系統

為了瞭解波動度在市場中之預測性，本研究利用芝加哥選擇權交易所(Chicago Board Options Exchange, CBOE)，所推出之波動率指數編製方法，運用台灣、美國S&P500、美國那斯達克、美國道瓊工業指數、歐洲STOXX50、墨西哥、韓國、日本各個市場特性的不同所推出之VIX(Volatility Index，波動率指數)與其標的指數，使用報酬率與絕對日報酬之日資料，利用Hansen and Seo (2002)門檻誤差修正模型(Threshold Vector Error Correction Model; TVECM)以分析各指數之間領先落後關係。研究結果發現，報酬率資料在一般水準區中，VIX指數領先標的指數的國家為台灣、美國S&P500、美國那斯達克、美國道瓊指數、歐洲STOXX50，由此可知，這五個市場可以運用VIX指數來對標的指數進行預測。而日本不論是在一般水準或極端偏高區都是非常顯著，皆是標的指數領先波動率指數。而韓國與墨西哥則皆是標的指數與VIX指數互為領先的情況。在絕對日報酬方面，結果發現在一般水準區歐洲STOXX50為VIX指數領先標的指數，極端偏高區則是標的指數領先VIX指數。而墨西哥則是極端偏高區標的指數領先VIX指數。在日本與韓國方面，一般水準區為標的指數領先VIX指數，極端偏高區則是VIX指數與標的指數是相互領先的關係。

This study analyzes the causality relationship between volatility infex(VIX) and corresponding index by using Hansen and Seo(2002) TVECM model. We consider the VIX on TAIWAN, S&P500, NASDAQ, DJIA, EUROPE, MEXICO, KOSPI, NIKKEI. We find that, VIX leads corresponding index in normal regimes tor TAIWAN, S&P500, NASDAQ, DJIA, EUROPE. It means that VIX predicts the corresponding index. In JAPAN, the corresponding index cause VIX in either extreme or normal regimes. In KOREA and MEXICO, we find there are feedback on two variables. For the causality of corresponding index return volatility and VIX volatility, VIX volatility leads corresponding index return volatility. It means EUROPE and MEXICO, VIX volatility is predicted by corresponding index return volatility in extreme regime. However in normal regime, VIX volatility predicts the corresponding index return volatility only in EUROPE, but reverse relation is found in JAPAN and KOREA. Our findings should shed lights on implications on the causality of VIX and corresponding index.

中文摘要--------------------------------------------------I
英文摘要-------------------------------------------------II
謝詞----------------------------------------------------III
目錄----------------------------------------------------IV
表目錄--------------------------------------------------VI
圖目錄--------------------------------------------------VII
第一章 緒論------------------------------------------------1
第一節 研究背景與動機------------------------------------1
第二節 研究目的-----------------------------------------4
第三節 研究架構-----------------------------------------5
第二章 文獻探討---------------------------------------------6
第一節 CBOE波動度指數編製原理------------------------6
第二節 波動度模型預測能力---------------------------------9
第三節 文章小結----------------------------------------12
第三章 研究方法--------------------------------------------13
第一節 資料來源----------------------------------------13
第二節 CBOE新VIX指數編製公式-----------------------14
第三節 單根檢定----------------------------------------17
第四節 TVECM門檻向量誤差修正模型--------------------18
第五節 門檻檢定----------------------------------------21
第四章 實證分析--------------------------------------------23
第一節 敘述統計量---------------------------------------23
第二節 單根檢定----------------------------------------27
第三節 向量自我迴歸模型----------------------------------30
第四節 門檻向量誤差修正模型------------------------------32
第五節 二區域Granger causality檢測-----------------36
第五章 結論與建議-------------------------------------------40
參考文獻--------------------------------------------------42
附錄一----------------------------------------------------47
附錄二----------------------------------------------------50
表目錄
表3-1 研究樣本期間-----------------------------------------14
表4-1 敘述統計量表-----------------------------------------24
表4-2 波動率指數與標的指數單根檢定結果(報酬率)------------------28
表4-3 波動率指數與標的指數單根檢定結果(絕對日報酬)---------------29
表4-4 各指數最適落後期數之選取(報酬率)------------------------31
表4-5 各指數最適落後期數之選取(絕對日報酬)---------------------31
表4-6 門檻效果SupLM檢定結果(報酬率)--------------------------32
表4-7 門檻效果SupLM檢定結果(絕對日報酬)-----------------------34
表4-8 門檻向量誤差修正模型係數估計結果(報酬率)------------------36
表4-9 門檻向量誤差修正模型係數估計結果(絕對日報酬)---------------38
圖目錄
圖1-1 研究流程圖-------------------------------------------5
圖4-1 台灣標的指數與波動率指數之走勢圖------------------------25
圖4-2 S&P500標的指數與波動率指數之走勢圖---------------------25
圖4-3 那斯達克標的指數與波動率指數之走勢圖---------------------25
圖4-4 道瓊指數標的指數與波動率指數之走勢圖------------------26
圖4-5 歐洲標的指數與波動率指數之走勢圖------------------------26
圖4-6 墨西哥標的指數與波動率指數之走勢圖-----------------------26
圖4-7 韓國標的指數與波動率指數之走勢圖------------------------27
圖4-8 日本標的指數與波動率指數之走勢圖------------------------27

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6.盧陽正、魏君洪、魏裕珍、張健偉 (2006)，「韓國KOSPI200指數選擇權波動度指數與標的指數之不對稱非線性動態調整模式」，中華決策科學學會年會暨論文研討會。
7.蘇柏鈞 (2008)，「多、空頭市況下最適波動率模型的檢驗-以臺指選擇權為例」，中正大學財務金融研究所碩士論文。
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