鑒於ACD模型的日益發展，許多相關研究也迅速被廣泛討論。因此，本研究應用Fernandes and Grammig(2006)所發展的擴增型ACD族模型進行台灣股票交易資料的實證研究分析。本文實證研究結果發現價格時距呈現高度自我相關且存在日曆效應。參數估計結果顯示擴增型ACD族中各模型間確實存在差異性。此外，在各模型中條件價格時距皆具幾何遍歷性的馬可夫過程、嚴格定態及β-mixing呈指數遞減等特性。若由對數概似估計值、AIC值及SBIC值來衡量模型之配適效果，則以非對稱ACD模型，即模型中存在有非對稱性效果之衝擊反應函數的線性ACD模型表現為最佳。最後，無論在任何模型下其所有D-test值皆不顯著，顯示殘差假設為Burr分配是適當的分配假設。

As the ACD models develop over time, many related issues have been widely explored. In this study, we apply the augmented ACD family proposed by Fernandes and Grammig(2006) to empirically analyze the data from Taiwan equity market. The empirical results of this study indicate that the price durations exhibited high autocorrelation and weekend effect. The parameters estimated in this study indicate that there are substantial diversities between the models in augmented ACD family. Furthermore, in all specifications, the conditional price durations possess some properties, including geometrically ergodic Markov process, strict stationarity, geometric ergodicity and β-mixing property with exponential decay. Based on the values of log-likelihood function, AIC and SBIC, the asymmetric ACD model that exhibits the asymmetric effect by the shock impact curve of the liner ACD model has relatively better performance. Finally, the D-test values are not significant among all the models, revealing that the assumption of the Burr distribution of the error term is appropriate.

目錄

頁次
第壹章 緒論 1
第一節 研究背景及動機 1
第二節 研究目的 3
第三節 研究架構 5
第貳章 文獻回顧 7
第参章 研究方法 15
第一節 基本自我相關條件交易時距模型 15
第二節 擴增型自我相關條件交易時距模型 19
第三節 條件交易時距的高階動差與自我相關共變異數函數 28
第四節 Burr-ACD模型、診斷性檢定及模型設定檢定 34
第肆章 實證分析 42
第一節 資料來源與敘述統計 42
第二節 時距資料之週期性調整 48
第三節 對稱型ACD模型實證分析 52
第四節 非對稱型ACD模型實證分析 56
第五節 擴增型ACD族綜合實證分析 60
第伍章 結論與建議 62
參考文獻 64

圖目錄
頁次
圖 1 1 研究流程圖 6
圖 3 1 擴增型ACD族之衝擊反應函數圖 21
圖 4 1 聯電價格時距之累計分佈圖 43
圖 4 2 聯電價格時距日內走勢圖 44
圖 4 3 週一至週五之價格時距日內走勢圖 46

表目錄
頁次
表3 1 擴增型ACD族之分類 23
表3 2 擴增型ACD族之限制條件 27
表3 3 條件交易時距之高階動差與自我共變數函數的彙整 34
表4 1 聯電價格時距之敘述統計 42
表4 2 聯電價格累積變動達0.1元之次數 45
表4 3 擴增型ACD族價格時距參數估計值與殘差檢定值 52
表4 4 擴增型ACD族價格時距參數估計值與殘差檢定值 56

參考文獻
中文部份
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2.謝順峰(2003)，「小數化、市場流動性與交易時距」，國立中央大學財務金融研究所碩士論文
3.楊奕農(2005)，時間序列分析：經濟與財務上之應用，台北：雙葉書廊
4.謝佩吟(2006)，「探討極端金融波動發生時距之研究-以ACD 模型為研究方法」，國立交通大學經營管理研究所碩士論文



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