本研究以台灣期貨交易所2008年1月2日至2009年9月30日的期貨資料為主，以大型台股期貨、小型台股期貨、電子期貨及金融期貨為主要研究樣本，使用向量自我迴歸模型來探討當日沖銷交易、波動度、流動性及效率性，等四種變數之間的關聯性分析，以探討本研究各種不同期貨商品之間其影響效果是否相同。
　　根據本研究實證結果顯示，當日沖銷對大型台股期貨及小型台股期貨的波動度、流動性及效率性具有顯著的正面影響效果，此結果顯示當日沖銷會對期貨市場造成較大的波動，從而吸引偏好短線交易的當沖交易人進入市場。此外，愈多的當沖交易，亦會造成買賣價差縮小，造成交易人的交易成本下降，此乃因相對價差下降，從而提升市場的流動性，顯示當沖交易人偏好流動性較高的商品進行交易。當沖交易的熱絡，會造成短期價格的波動相較於長期價格波動來的劇烈，因此短時間期貨市場的流動性會越高，效率性也會提升。
　　本研究亦發現在台灣期貨市場裡，在大型台股期貨、小型台股期貨、電子期貨及金融期貨裡，波動度及流動性之間存在內生關係，彼此之間具有可預測的功能，顯示前期報酬的波動提高會造成當期流動性上升，而市場若處於流動性高檔，也就是交易量大增之時，此時就會使投資人進場投資，造成擴大期貨市場波動度之功能。至於效率性，研究顯示在大型台股期貨及小型台股期貨裡，發現當日沖銷交易會造成效率性提高，至於在電子期貨及金融期貨兩種期貨商品裡，則無此情況發生。

In this study, the data of Taiwan Futures Exchange (TAIFEX) dated from 2008/1/2 to 2009/9/30, main TAIEX futures, small TAIEX futures, electronic futures and financial futures are the main research samples. Using Vector Autoregression to explore the relationship among day trade, volatility, liquidity and efficiency to analyze its effect is the same between four various futures commodity.
　　The results show that there is a significant positive effect on the large TAIEX futures and small TAIEX futures volatility, liquidity and efficiency. It indicates that day trade will cause greater fluctuations in order to attract the preference for short-term trader to enter the market. In addition, the more day trader, the narrower the bid-ask spread, and the transaction costs decreased so as to enhance the liquidity of the market. It seems that the traders prefer the transactions which are more liquid. High volume hedge transactions will cause the severe fluctuations of short-term price compared to the long-term price. Therefore, the liquidity in short futures market will not only be higher, but also be efficiency.
　　It also found that the volatility and liquidity exists endogenous relationship in large TAIEX Futures, Mini TAIEX futures, electronic futures and financial futures. Besides, from this evidence we acquired the predictable function when the early return volatility increases will cause increased current liquidity. In addition, if it exits high liquid in frequency trading market, the investors will get into the market and it will expand futures market volatility. As for efficiency, it shows that day trading in the large TAIEX futures and small TAIEX futures will increase the efficiency, but not in the electronic futures and financial futures.

目錄
目錄	V
 第一章　緒論	1
第一節 研究背景與動機	1
第二節 研究目的	3
第三節 研究架構	6
 第二章　文獻探討	8
第一節 當日沖銷交易與市場波動度之相關探討	8
第二節 當日沖銷交易與市場流動性之相關探討	10
第三節 當日沖銷交易與市場效率性之相關探討	13
 第三章　研究方法	15
第一節 研究資料來源與介紹	15
第二節 研究變數定義及說明	18
第三節 單根檢定	22
第四節 向量自我迴歸模型	25
第五節 因果關係、衝擊反應與變異數分解	27
 第四章　實證結果與分析	34
第一節 台灣指數期貨及市場績效變數之敘述統計分析	34
第二節 台灣指數期貨及市場績效變數之單根檢定分析	36
第三節 市場績效變數間向量自我迴歸模型分析	38
第四節 市場績效變數間因果關係、衝擊反應及變異數分解分析	49
 第五章　結論	75
第一節 研究結論	75
第二節 研究限制與建議	77
 參考文獻	79

表目錄
【表 3-1】期貨商品內容簡介	17
【表 4-1】大型台股期貨敘述統計量（單位：%）	35
【表 4-2】小型台股期貨敘述統計量（單位：％）	36
【表 4-3】電子期貨敘述統計量（單位：%）	36
【表 4-4】金融期貨敘述統計量（單位：%）	36
【表 4-5】台灣各類期貨指數LLC單根檢定結果	37
【表 4-6】大型台股期貨、小型台股期貨IPS單根檢定結果	37
【表 4-7】電子期貨、金融期貨IPS單根檢定結果	38
【表 4-8】向量自我迴歸模型最適落後期數SIC表	39
【表 4-9】大型台股期貨向量自我迴歸實證結果	41
【表 4-10】小型台股期貨向量自我迴歸實證結果	43
【表 4-11】電子期貨向量自我迴歸實證結果	46
【表 4-12】金融期貨向量自我迴歸實證結果	48
【表 4-13】大型台股期貨因果關係實證檢定	50
【表 4 14】小型台股期貨因果關係實證檢定	51
【表 4-15】電子期貨因果關係實證檢定	52
【表 4-16】金融期貨因果關係實證檢定	53
【表 4-17】大型台股期貨變數間衝擊反應實證分析	55
【表 4-18】小型台股期貨變數間衝擊反應實證分析	58
【表 4-19】電子期貨變數間衝擊反應實證分析	61
【表 4-20】金融期貨變數間衝擊反應實證分析	64
【表 4-21】大型台股期貨變數間變異數分解實證分析	67
【表 4-22】小型台股期貨變數間變異數分解實證分析	69
【表 4-23】電子期貨變數間變異數分解實證分析	71
【表 4-24】金融期貨變數間變異數分解實證分析	73
【表 5-1】四變數之因果關係表	77

圖目錄
【圖 1-1】大型台股期貨及小型台股期貨之逐年每日平均交易量	4
【圖 1-2】電子期貨及金融期貨之逐年每日平均交易量	4
【圖 1-3】研究架構流程圖	7
【圖 4-1】大型台股期貨四變數衝擊反應分析圖	56
【圖 4-2】小型台股期貨四變數衝擊反應分析圖	59
【圖 4-3】電子期貨四變數衝擊反應分析圖	62
【圖 4-4】金融期貨四變數衝擊反應分析圖	65

1.	林蒼祥、顧廣平 (2008)，期交所股價指數期貨契約最後結算價與最後結算日決定方式之研究，台灣期貨交易所委託專題研究計畫報告。
2.	Adrian, T. and J. Rosenberg (2008) , “Stock Returns and Volatility:Pricing the Short-Run and Long-Run Components of Market Risk, ” Journal of Finance , Vol. 63, pp. 2997-3030.
3.	Amilhud, Yakov and Mendelson (1991) , “Volatility, Efficiency and Trading : Evidence from the Japanese Stock Market, ” Journal of Finance ,Vol. 46 , pp. 1765-1789.
4.	Andrade , S. C., C. Chang and M. S. Seasholes (2008) , “ TradingImbalances, Predictable Reversals, and Cross-Stock Price Pressure, ”Journal of Financial Economics, Vol. 88 , pp. 406-423.
5.	Bae,S. C., T. H. Kwon , J.W. Park, (2004) , “ Futures Trading, Spot Market Volatility, and Market Efficiency: The Case of The Korean Index Futures Market, ” The Journal of Futures Market , Vol. 24(12) , pp. 1195-1228.
6.	Bae, K. H., K. Chan, and Y. L. Cheung, (1998) , “The Profitability of Index Futures Arbitrage: Evidence from Bid-Ask Quotes, ”Journal of Futures Markets,Vol. 18 , pp.743-763.
7.	Barber, B. M. and T. Odean (2001) , “ The Internet and the Investor,” Journal of Economic Perspectives , Vol. 15 (1), pp. 41-54.
8.	Barber, B. M. , Yi-Jane Lee, Yu-Jane Liu,and T. Odean (2003) , “ Who Gains from Trade?Evidence from Taiwan, ” Working paper , University of Califorlinia.
9.	Barber, B. M., Yi-Jane Lee, Yu-Jane Liu,and T. Odean (2004) , “Do Individual Day Traders Make Money?Evidence from Taiwan, ” Working paper, University of Califorlinia.
10.	Battalio, R. H., H. Brian, and R. Jennings (1997) , “ SOES Trading and Market Volatility, ” Journal of Financial and Quantitative Analysis, Vol. 32 (2), pp. 225-238.
11.	Chang, R. P., S. T. Hsu, N. K. Huang and S. G. Rhee (1999) , “ The Effects of Trading Method on Volatility and Liquidity: Evidence from the Taiwan Stock Exchange,” Journal of Business Finance and Accounting , Vol. 26 , pp.137-170.
12.	Chung , J. M., H. Choe and B.C. Kho (2009) , “ The Impact of Day-Trading on Volatility and Liquidity, ” Asia-Pacific Journal of Financial Studies , Vol. 38 (2) , pp. 237-275.
13.	Dickey ,D. A. and W. A. Fuller, (1979) , “Distribution of the Estimators for AutoregressiveTime Series with a Unit Root, ” Journal of the American Statistical Association , Vol. 74 , pp. 427-31.
14.	Draper, P., and J. K. W. Fung. (2002) , “ A Study of Arbitrage Efficiency Between The Ftse-100 Index Futures and Options Contract, ” Journal of Futures Markets , Vol. 22(1) pp. 31-58.
15.	Fleming, J., B. Ostdiek, and R. E Whaley. (1996) ,“ Trading Costs and the Relative Rates of Price Discovery in Stock, Futures, and Options Markets,”Journal of Futures Markets, Vol. 16 , pp. 353-387.
16.	Fung, J. K. W., and A. K. W. Fung, (1997) ,“ Mispricing of Futures Contacts: A Study of Index Futures Versus Index Options Contracts, ”Journal of Derivatives , pp. 37-44.
17.	Grossman, S. J. (1988) , “ Program Trading and Market Volatility: A Report on Interday Relationships, ”Financial Analysts Journal, Vol. 44(4) , pp. 18-28.
18.	Harris,J. and P.Schultz (1998) , “ The Trading Profits of SOES Bandits, ” Journal of Financial Economics , Vol. 50 , pp. 39-62.
19.	Hasbrouck, J. , and R. A. Schwartz (1988) , “ Liquidity and Execution Costs in Equity Markets, ” Journal of Portfolio Management , Vol .14 , pp. 10-16.
20.	Herbst, A. F. and E. D. Maberly (1990) , “ Stock Index Futures, Expiration-Day Volatility, and the Special Friday Opening:a Note,” Journal of Futures Markets , Vol. 10(3) , pp. 323-325.
21.	Kawamoto,K.,and S. Hamori (2011) , “ Market Efficiency among Futures with Different Maturities: Evidence From The Crude Oil Futures Market, ” Journal of Futures Markets,Vol. 31(5), pp. 487-501.
22.	Koski , J. Lynch, E. M. Rice, and A. Tarhouni (2004) , “ Noise Trading and Volatility: Evidence from Day Trading and Message Boards, ” Working Paper.
23.	Kyrolainen, Petri (2008) , “ Day Trading and Stock Price Volatility, ” Journal of Economics and Finance,Vol. 32(1), pp. 75–89.
24.	Lee, J. H., and N. Nayar, (1993) ,“ A Transactions Data Analysis of Arbitrage between Index Options and Index Futures, ”Journal of Futures Markets , Vol. 13(8), pp. 889-902.
25.	Cheng Lee-Young, Z. Yan, Y. Zhao and W. F. Chang (2012) , “ Short Selling Activity, Price Efficiency and Fundamental Value of IPO Stocks, ”Pacific-Basin Finance Journal, Vol. 20 , pp. 809-824.
26.	Linnainmaa, Juhani. (2003) , “ The Anatomy of Day Traders, ” UCLA working Paper.
27.	Malkiel (1999) , “Day Trading and Its Dangers, ” The Wall Street Journal ,
28.	Panago M. and A. Roell, (1996) , “ Transparency and Liquidity: A Comparison of Auction and Dealer Markets with Informed Trading, ” Journal of Finance , Vol. 51, pp. 579-611
29.	Naidu and Rozeff (1994) , “ Volume , Volatility , Liquidity and Efficiency of Singapore Stock Exchange before and after Automation, ” Pacific-Basin Finance Journal,Vol. 2, pp. 23-42.
30.	Odean, Terrance (1998) , “ Volume, Volatility , Price, and Profit when all Traders are above Average, ” Journal of finance , pp. 1887-1934.
31.	Odean, Terrance (1999) , “ Do Investors Trade too much? ” American Economic Review, pp. 1279-1298.
32.	Petri Kyrolainen (2008) , “ Day Trading and Stock Price Volatility, ” Journal of Economics and Finance , Vol. 32, pp. 75-89.
33.	Robert T. D. and K. W. Marilyn (1999) , “The Impact of Trader Type on the Futures Volatility-Volume Relation, ”The Journal of Finance , Vol. 54(6), pp. 2297-2316.
34.	Schwartz, R.A. (1988) , “ A proposal to Stablize Price, ” The Journal of Portfolio Management , pp. 5-11.
35.	Sims, C. A. (1980), “ Macroeconomics and Reality, ” Econometrica, Vol.48, pp. 1-48
36.	Thomas H. M. and A. W. Robert , (1992) , “ An Analysis of Intraday Patterns in Bid-Ask Spreads for NYSE Stocks, ” The Journal of Finance , Vol. 47, pp. 753-765
37.	Vipul (2005) , “Futures and Options Expiration-Day Effects: The Indian Evidence, ” Journal of Futures Markets, Vol. 25(11) , pp. 1045-1065.