本研究從時間序列的角度出發，利用高頻率的日內資料，接著再使用橫斷面分析方式去檢驗出台灣股市當日沖銷交易、市場波動度及流動性此三個變數在電子、金融及傳產類股中，彼此互動、影響的關係，當中並透過門檻向量自我迴歸模型 (Threshold Vector Autoregressive Model；TVAR )加以分析與討論，本研究資料以台灣證券交易所 2007 年 1 月 2 日至 2008 年 9 月 30 日，共計 451 個交易日之研究樣本，並進一步分析於此三大類股中在門檻效果下的關係。
根據本研究實證結果發現，於電子及傳產類股中，當於體制一(上)時，當日沖銷交易活動與股市波動度存在顯著正相關之影響力，即表示此二類股當波動度位於門檻值上時，愈多的當日沖銷交易會導致股市產生更多的波動，且波動亦與當日沖銷交易活動間存在正向回饋效果，顯示當沖者偏好高波動度的標的股票，當日沖銷交易對股市流動性之影響則有顯著正相關，即表示此二類股當波動度位於門檻值上時，愈多的當日沖銷交易導致其買賣價差縮小，提升市場之流動性，顯示當沖者亦會選擇流動性較佳的股票來進行交易；金融類股於體制一(上)時，當日沖銷交易是單向領先及預測市場波動度與流動性的，這可能是由於台灣股市金融標的股票之組成特性所導致，因其股性屬於穩定較不活潑型，故股價震盪幅度亦較小，而且根據高風險高報酬的財務觀點，金融類股較不適合當日沖銷交易此種投機意味濃厚之交易行為模式，因此較不易吸引當沖者的進場交易。綜合來說，當日沖銷交易、市場波動度及流動性，於體制一(上)之相互影響效果以電子類股最為顯著，其次為傳產類股，金融類股之表現則較不強烈。
於體制二(下)發現不論是電子、金融或傳產類股皆為低關聯性，顯示其變數間彼此是不具有領先及預測的關係存在的，故當波動度位於門檻值下時，於電子、金融與傳產類股來說，由於其價格的波動太低，以至於無法滿足當沖者的高風險高報酬期待，進而減少交易。
實證結果顯示，台灣股市之當日沖銷交易、波動度與流動性之間確實存在門檻效果，其影響程度則隨著各類股性質之不同而隨之改變。

The research employs high frequency of intraday data to examine relationships among day-trading, volatility and liquidity with electronic, financial and traditional industrial listed companies. The methodology used Threshold Vector Autoregressive Model, TVAR . The data of the research employed is from January 2,2007 to September 30,2008 in Taiwan Stock Exchange.
The empirical results reveal that under regime 1,day-trading and volatility exhibit highly positive correlation between electronic and traditional industrial listed companies, indicating that the higher day-trading frequency, the higher the degree of volatility in the stock market when the degree of volatility is above the threshold. Meanwhile, day-trading has high positive correlation with liquidity of the stock market if day-traders prefer high volatility stocks. In other words, the day-traders would rather trade the stock with higher degree of liquidity, since when the degree of volatility of electronic and traditional industrial listed companies is above threshold, the more day-trading frequency would cause bid-ask spread shrinking and enhance the liquidity of the stock market. the day-trading of financial listed companies exhibit one-way leading effect to predict both volatility and liquidity. These phenomenon could possibly be caused by the characteristics of financial listed companies, e.g. stability and less bouncing in price. Therefore, financial listed companies are less attractive to day-trader since day-trading usually stands for a risky strategy. In summary, electronic listed companies have the highest relationships among day-trading, volatility and liquidity, the next is traditional industrial listed companies. Financial listed companies have the least relationships among day-trading, volatility and liquidity.
The empirical results also reveal that under regime 2, the variables of electronic, financial or traditional industrial listed companies are neither leading nor predicting each other. Therefore, when the degree of volatility is under the threshold, for the financial, electronic, and traditional industrial listed companies, day-trader are not interested in trading since low volatility of price hardly satisfies their expectation to meet with higher risk premium. 
The empirical results reveal that certain threshold effect do exist among day-trading, volatility and liquidity in Taiwan Stock Market. But the degree of influence will depend on the characteristics of each stock.

論文內容目錄
 第一章  緒論	1
第一節 研究背景與動機	1
第二節 研究目的	2
第三節 研究架構	4
第四節 研究流程	5
 第二章  文獻回顧	6
第一節 我國當日沖銷交易制度之變革及相關規定	6
第二節 當日沖銷交易對市場波動度之文獻探討	8
第三節 當日沖銷交易對市場流動性之文獻探討	14
 第三章  研究方法	18
第一節 變數說明與定義	20
第二節 單根檢定	22
第三節 門檻迴歸模型	30
第四節 當日沖銷比例、波動度、流動性之因果關係	38
 第四章  實證結果	40
第一節 資料說明與處理	40
第二節 單根檢定	49
第三節 門檻向量自我迴歸模型結果分析	51
第四節 當日沖銷比例、波動度、流動性之因果關係結果分析	72
 第五章  結論	78
 參考文獻	81

表目錄
【表 2 1】國外當日沖銷交易影響市場波動度之相關文獻彙總表	12
【表 2 2】國內當日沖銷交易影響市場波動度之相關文獻彙總表	13
【表 2 3】國外當日沖銷交易影響市場流動性之相關文獻彙總表	16
【表 2 4】國內當日沖銷交易影響市場流動性之相關文獻彙總表	17
【表 3 1】ADF單根檢定統計量	27
【表 4 1】所有上市股分類	41
【表 4 2】本研究樣本之產業分類比重	43
【表 4 3】電子類股敘述統計表	47
【表 4 4】金融類股敘述統計表	48
【表 4 5】傳產類股敘述統計表	48
【表 4 6】電子類股單根檢定結果	49
【表 4 7】金融類股單根檢定結果	50
【表 4 8】傳產類股單根檢定結果	50
【表 4 9】電子類股門檻檢定表(波動度)	52
【表 4 10】金融類股門檻檢定表(波動度)	58
【表 4 11】傳產類股門檻檢定表(波動度)	59
【表 4 12】門檻效果統計表	61
【表 4 13】向量自我迴歸模型最適落後期數選取表	62
【表 4 14】電子類股體制一(上)TVAR檢定表	64
【表 4 15】電子類股體制二(下) TVAR檢定表	66
【表 4 16】金融類股體制一(上) TVAR檢定表	67
【表 4 17】金融類股體制二(下) TVAR檢定表	68
【表 4 18】傳產類股體制一(上) TVAR檢定表	69
【表 4 19】傳產類股體制二(下) TVAR檢定表	71
【表 4 20】電子類股體制一(上)因果關係檢定	72
【表 4 21】電子類股體制二(下)因果關係檢定	73
【表 4 22】金融類股體制一(上)因果關係檢定	74
【表 4 23】金融類股體制二(下)因果關係檢定	74
【表 4 24】傳產類股體制一(上)因果關係檢定	75
【表 4 25】傳產類股體制二(下)因果關係檢定	76
【表 4 26】三變量TVAR模型估計結果表	77

圖目錄
【圖 1 1】研究流程	5
【圖 4 1】金融類股當日沖銷比率	46
【圖 4 2】電子類股當日沖銷比率	46
【圖 4 3】傳產類股當日沖銷比率	47

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