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研究生:杜秉倫
研究生(外文):Ping-Lun Tu
論文名稱:應用不對稱GARCH模型於台灣股票市場之研究
論文名稱(外文):A Study of Applying Asymmetric GARCH Model to Taiwan Stock Market
指導教授:林楚雄林楚雄引用關係
指導教授(外文):Chu-Hsiung Lin
學位類別:碩士
校院名稱:國立高雄第一科技大學
系所名稱:財務管理所
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:69
中文關鍵詞:不對稱GARCH模型星期效應不對稱均數回復
外文關鍵詞:Asymmetric GARCH Modelday-of-the-week Effects
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Black(1976)發現股價報酬上具有強烈的不對稱性,由於GARCH模型無法描述波動不對稱,因此不對稱GARCH模型比GARCH模型估計波動更為精確。所以本文以不對稱GARCH模型為實證方法,針對兩個主題進行探討。第一個主題為SIMEX台指期貨交易對台灣股市星期效應與波動行為的影響;而第二個主題是台灣股票報酬短期均數不對稱回復之研究。
在第一個主題中,本文應用GJR GARCH模型為實證模型。主要分析在1993年1月5日到2000年12月30日SIMEX台指期貨引進前後時期,台灣股市星期效應與波動行為變化的情形並討論其原因。實證研究發現SIMEX台指期貨交易之前,台灣股票市場存在星期二為負報酬的星期效應,然而在SIMEX台指期貨交易之後,台灣股票市場呈現星期一與星期二為負報酬的星期效應現象,與其他國家研究結果不相同。本文分析現貨市場出現星期一為負報酬的原因,可能為現貨市場和SIMEX台指期貨存在雙向因果關係與高度的連動性,因此在期貨市場上存在星期一為負報酬的現象下,導致現貨市場產生星期一為負報酬的星期效應。其次,SIMEX台指期貨上市前後時期,現貨市場的條件波動結構發生改變,但並沒有增加現貨市場資訊流動的速度和品質。此外,現貨市場波動的不對稱性並不因為期貨市場的引進而減弱或消失,因此本文認為市場動態性之觀點並不能完全解釋台灣股票市場波動的不對稱性。不能完全解釋台灣股票市場波動的不對稱性。
在第二個主題中,本文應用不對稱非線性平滑轉換GARCH模型、門檻轉換GARCH模型和平滑轉換GARCH模型為實證模型,設計其條件平均數方程式以分析台灣股票市場是否存在股價報酬均數不對稱回復的現象及探討其成因,並利用條件變異數方程式以捕捉較精確台灣股市報酬波動特性。本研究樣本期間為1986年1月4日到2001年10月26日的週資料。實證結果發現台灣股票市場短期股價報酬存在均數不對稱回復的現象,隱含買進未預期下跌的股票獲取異常報酬的速度會快於賣出未預期上漲的股票所獲取異常報酬的速度。此外,當股價發生壞消息後,報酬呈現負相關,且預期未來波動風險和其風險貼水之間呈現負向關係,顯示投資人在短期間對股價有不理性預期而產生錯誤評價行為,因此實證發現過度反應假說可以解釋台灣股票市場股價報酬均數不對稱回復的現象。根據三個不對稱GARCH模型對台灣股票市場波動行為比較結果,本研究實證結果發現不對稱非線性平滑轉換GARCH模型、門檻轉換GARCH模型以及平滑轉換GARCH模型在解釋台灣波動行為的能力皆差不多。
Black(1976) confirmed that stock market volatility is asymmetric in its response to news。The GARCH model doesn’t allow good news and bad news to have a different impact on volatility, so we adopt the asymmetric GARCH model instead of GARCH model. The article researches two subjects, one named Day-of-the-Week Effects and Behavior of Volatility in Taiwan Stock Market:Before and After the Periods on SIMEX Index Future Trading and the other named a study on the asymmetric mean reverting of short-horizon stock returns in Taiwan.
In the first subject, we use GJR GARCH model. This subject analyses the impact of SIMEX Taiwan index future on daily return seasonality and volatility on Taiwan from January 5, 1993 to December 30, 2000. This subject indicates that low returns are observable in the Taiwan stock market on Tuesday before SIMEX index future listing. After SIMEX index future listing, the empirical result that Monday and Tuesday have negative return in the cash market is different from other countries. We also find Monday have negative return in the future market. The aim of this subject investigates explanations for the existence of anomalies. We find the day-of-the-week phenomenon in the Taiwan stock market, which would be regarded as weekend effect of the SIMEX index future. Next, SIMEX index future trading has significant effect on the spot market volatility. But it doesn’t improve the quality and speed of information to spot market and make market more efficient. Besides, this subject thinks that market dynamics doesn’t explain the reason of the asymmetric response of volatility to news in Taiwan market completely.
In the second subject, we use Asymmetric Nonlinear Smooth-Transition GARCH model、Smooth-Transition GARCH model and Threshold-Switching GARCH model to design mean equation to analyze asymmetric mean reverting of short-horizon stock returns in Taiwan and to utilize variance equation to capture the characteristics of the Taiwan stock return’s volatility. Using capital market weekly data from January 4, 1986 to October 26, 2001, we find strong evidence of asymmetric mean reverting in Taiwan stock market. It implies that anomalous return following unexpected price drop tend to gain more quickly than it does following unexpected price rise. Moreover, we find that the relationship between future volatility and risk premium is negative when a negative return shock is realized. The findings support the market overreaction hypotheses. The asymmetry is due to the mispricing behavior on the part of investors who overreact to certain market news. Besides, the empirical results are shown that Asymmetric Nonlinear Smooth-Transition GARCH Model is similar to Smooth-Transition GARCH Model and Threshold-Switching GARCH Model in capturing the behavior of volatility.
中文提要………………………………………………..Ⅰ
英文提要………………………………………………..Ⅲ
謝詞……………………………………………………. Ⅴ
目錄……………………………………………………..Ⅵ
表目錄…………………………………………………..Ⅷ
圖目錄…………………………………………………..Ⅹ
第一章 緒論……………………………………………….1
第二章 台灣股市星期效應與波動行為之分析:
SIMEX台指期貨交易前後時期……………...........3
第一節 前言…………………………………………..3
第二節 文獻回顧……………………………………..4
第三節 研究方法……………………………………..10
第四節 實證結果與分析……………………………..13
第五節 小節……………………………………… 22
第三章 台灣股票報酬短期均數不對稱回復之研究...27
第一節 前言………………………………………... 27
第二節 文獻回顧……………………………………..30
第三節 研究方法…………………………………… 35
第四節 實證結果與分析……………………………..46
第五節 小節………………………………………... 52
第四章 結論…………………………………………...60
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