本研究主要是探討選擇權成交量與期貨價格變動之關係，檢定Schlag and Stoll (2005) 的三個假說：完全效率市場假說（perfect market hypothesis）、資訊假說（information hypothesis）及流動性假說（liquidity hypothesis）。採用2005年一整年期貨與選擇權之日內資料，將同一日內樣本資料區分成盤前、盤中與盤後三個交易時段，另外亦將同一週內區分成不同交易日（週一至週五），藉由一般化自我相關條件異質變異模型(GARCH)，得出下列三個實證結果： / 1. 日內未區分交易時段下，拒絕完全效率市場假說及資訊假說，淨買權或是正向選擇權成交量對於期貨價格有正向之影響，淨賣權或是負向選擇權成交量對於期貨價格則有負向之影響，且選擇權成交量對於期貨價格變動之同步價格效果在接下來的六分鐘內反轉。無法拒絕流動性假說。 / 2. 日內區分交易時段、但週內不區分不同交易日下，無論盤前、盤中及盤後，皆拒絕完全效率市場假說及資訊假說，而不拒絕流動性假說。 / 3. 日內區分交易時段、且週內區分不同交易日下，週內各交易日盤前與盤中時段，皆拒絕完全效率市場及資訊假說，而無法拒絕流動性假說；而週內盤後時段結果則相對複雜，值得進一步討論。

本文係利用高頻資料研究股票指數期貨的到期日效應，考量到中國的衍生性商品起步甚晚，相關研究不如台灣來的多，因此選取中國的滬深300股指期貨市場作為本研究的主題，希望能夠為後續有興趣的研究者提供參考。但是因為中國市場的資料取得不易，本文所使用的樣本資料只為期兩年，選取2010年4月16日到2012年4月20日的滬深300股指期貨的1分鐘高頻數據作為原始數據。 本文目的在於研究滬深300股指期貨經由考慮成交量、價格反轉以及波動度的到期日效應，實證結果發現在期貨到期日當天與隔一天的某些交易時段明顯存在著型0、型I與型II價格反轉，成交量檢驗指出，到期日成交量明顯大於非到期日成交量，波動度異常檢驗顯示，到期日收盤前五分鐘的波動度有異常放大的現象。本文的實證結果部分，利用模擬投資策略去檢驗價格反轉在經濟上是否有意義，發現價格反轉不只是在統計上顯著，同樣也是具有經濟意義的，但是把資料依據時間區分為前後兩部分並做檢驗之後也發現，這種經濟意義會隨著時間而呈現遞減的狀態。 / The central idea of this thesis is studying expiration effects of stock index futures. As we know, China stock index futures market, which is also known as CSI 300 Index futures market, is experiencing its early stage with fewer related studies comparing to Taiwan stock futures market. In order to provide research references for succeeding researchers interested in CSI 300 Index futures market. However, having difficulties collecting high frequency market data from CSI 300 Index futures market, we use only two years data from the beginning of CSI 300 Index futures market. The main purpose of this thesis is to study the expiration effect of CSI 300 Index futures by from three aspects, price reversals, volume effects and abnormal return volatility. The empirical results shows that type 0, type I and type II existed in several trading hours in both the expiration day and the next trading day. Second, it indicated that the trading volume in expiration days is significantly larger than in non-expiration days. Third, the empirical result also pointed out that magnified return volatilities existing in five minutes before market closes on the expiration day. Moreover, we used simulated investment strategies as analysis tools and found that price-reversal effect is significant on economical basis. However, we discovered that the level of these effects is declining gradually from the beginning to the end of data period.

第一章 台灣與美國股市價量關係的分量迴歸分析 摘要 本文利用分量迴歸來觀察台灣和美國股市報酬率和成交量的價量關係。實證結果發現兩地股市的價量關係截然不同。台灣股市的報酬率與成交量之間具有正向關係，呈現「價量齊揚」和「價跌量縮」的現象，而前者效果通常較顯著；但報酬率接近最大漲幅限制時，報酬率與成交量之間並無顯著關係，報酬率接近最大跌幅限制時，「價跌量縮」的現象甚至更強。相對於台灣，美國股市的報酬率與成交量則出現「價量齊揚」與「價量背離」互相對稱的 “V” 字關係。就實證方法而言，傳統以 OLS 方法估計的迴歸模型並無法得到上述的實證結果。進一步的分析顯示，融券成數的高低以及平盤以下不得放空等規定都是造成台灣股市出現「價跌量縮」的可能原因。 第二章 股市價量關係的分量迴歸分析 (二) 摘要 本章利用分量迴歸觀察包括台灣在內的亞洲新興工業國家與成熟股市的價量關係。實證結果顯示，亞洲新興工業國家和日本股市「價量齊揚」的效果較強，其中香港、南韓和新加坡呈現較弱的「價量背離」現象，因此價量之間有不對稱的 “V” 字關係；而日本股市則呈現「價跌量縮」，與第一章分析的台灣股市價量關係相似。在成熟股市的價量關係中，英國金融時報指數、美國道瓊工業指數和德國股價指數皆呈現對稱的 “V” 字關係，與美國US指數的價量關係相似。亞洲地區的國家在1997下半年到1998上半年普遍經歷了一場金融風暴，本文進一步的分析發現在這場風暴期間，亞洲地區除了台灣以外，日本、香港、南韓與新加坡都出現較強的「價量齊揚」與「價量背離」，這種現象可能肇因於投資人認為風暴期間的股價報酬率風險較高，遂使得股價報酬率對成交量的反應較為敏銳。相對而言，歐美地區的國家，受到亞洲金融風暴的影響較小，所以整體的價量關係在亞洲金融風暴期間並無重大改變。本章的結果都是透過分量迴歸所獲得。 第三章 股市價量因果關係的分量迴歸分析 摘要 本文依據分量迴歸設計 Granger 因果關係的新檢驗方法，並依此方法來檢驗幾個股市價量之間的因果關係。本文分析的股市包括日本、英國與美國等世界前三大股市，以及合稱亞洲四小龍的台灣、香港、南韓與新加坡等新興工業國家或地區的股市。實證結果顯示：除了台灣股市以外，其他的股市皆呈現 “V” 字的跨期價量關係。其中英國、美國、香港和新加坡股市的跨期價量關係大體呈現正向「價量齊揚」與負向「價量背離」互相對稱的 “V” 字關係，而日本和南韓股市則是「價量齊揚」較強的不對稱 “V” 字關係。此一結果表示這些股市的價量之間都存在分配上的 Granger (1969) 因果關係。但若以均數迴歸來衡量跨期價量關係，則所有股市都呈現不顯著的跨期價量關係，也就是傳統文獻上所謂價量之間沒有 Granger 因果關係。本文所提出的 Granger 因果關係之分量迴歸分析，可以觀察到整個條件分配中各分量的因果關係，為分配上的 Granger 因果關係提供一個較完整的檢驗方法。 / We examine the relationship between the stock return and trading volume in the Taiwan and U.S. Stock Exchanges using quantile regression. The empirical results show that the return-volume relations in these two exchanges are quite different. For Taiwan data, there are significant positive return-volume relations across quantiles, showing that a large positive return is usually accompanied with a large trading volume and a large negative return with a small trading volume, yet the effect of former is stronger. However, such relations change when returns approach the price limits. We also find that for U.S. data, return-volume relations exhibit symmetric V-shapes across quantiles, showing that a large return (in either sign) is usually accompanied with a large trading volume. On the other hand, linear regressions estimated by the ordinary least square method are unable to reveal such patterns. Further investigation shows that various restrictions on short sales in the Taiwan Stock Exchange may explain the difference between the return-volume relations in Taiwan and U.S. data.

傳統貨幣需求函數的估計，使用的影響因素包括物價、所得及利率。但是近年股市的蓬勃發展，對貨幣需求造成了一定程度的影響。 Friedman 就股市對貨幣需求的影響提出 4 大效果，分別是交易效果、資產組合調整效果、財富效果及替代效果。其中替代效果為負，其他的效果為正。然而並非只有股市會對貨幣需求造成影響，貨幣需求同樣會影響股市。本文採用 Johansen Procedure 估計法，首先建立一般的貨幣需求模型，使用的雙變數包括貨幣需求、物價、所得及利率，實證結果確定這些變數存在 2 條共積關係，一是貨幣需求共積方程式，一是物價共積方程式。然後我們將股市成交量放入，同樣確定這些變數間具有 2 條共積關係。 Johansen Procedure 有 5 種模型，分別適用於不同的情況，我們要事先由資料來判斷使用哪一個模型並不容易，因此本文採用了多項標準，包括共積係數符號及其大小、向量誤差修正模型誤差項常態性與序列相關檢定、重要統計值(RSS、AIC、SC)等，用來作為選擇最適模型的依據。經由實證結果我們發現，不論是否加入股市成交量，模型三都是最適當的模型，也就是資料有不為零的平均數與線性趨勢，但共積方程式只有截距項。 就貨幣需求共積方程式殘差對各變數的影響來看，M1A 與 M1B 的連續增加，都會使股市成交量擴大，而 M1B 的連續增加還會形成物價上漲的壓力。而就物價共積方程式殘差對各變數的影響來看，解釋上較不容易。這可能是因為台灣地區物價長期處於穩定，加上台灣股市受到心理及消息面的影響性很大，要用總體變數作一個完整的解釋並不十分容易。雖然如此，貨幣市場與股票市場間的互動仍然極具有研究價值。 / Traditionally, when estimating the money demand, we use price index, income, and interest rate as its influcing factors. But the stock market that is booming these years has made certain influence on money demand. Milton Friedman pointed out that there are 4 effects that stock market can influcnce money demand. They are trading effect, portfolio reconstruction effect, wealth effect, and subsitution effect. Among these effects, subsitution effect has negative influence on money demand and other 3 effects have positive influence on mondy demand. However, not only does the stock market has influence on mondy demand, money demand also has influence on stock market. In my thesis, I applied Johansen Procedure estimation method. First, I established a traditional model on money demand. The variables I used including money demand, price index, income, and interest rate. From the empirical outcome we are sure that there are 2 cointegration equations among these variables.One is the money demand cointegration equation and the other is the price cointegration equation. Next we add the stock trading volume to the model. We also make sure that there are 2 cointegration relationships among them. There are 5 models in Johansen Procedure estimation method, and they are applied in different situations. It is not easy to decide which model to apply in advance. So in the thesis, we used many criteria, including the value and the sign of the coefficients, the the serial correlation and the normality test of the residuals from the vector error correction model, and important statistics(RSS, AIC, SC) to decide which model to apply. According to the empirical outcome, whether stock trading volume is included, model 3, which is there are means and linear trend in data but the cointegration equation only has intercept is the proper model we selected. About the residuals from the money demand cointegration quation's influence on variables, we find that the continuous increase in M1A and M1B will make enlarge the stock trading volume. Besides, the coutinuous increase in M1B will cause the price to raise. And about the residuals from the price cointegration equation's influence on variables, it is a little bit difficult to interpret. Maybe it is because the price is very stable in Taiwan and the stock market in Taiwan is affected by psychology side and information side easily. So it is not easy to use the macro economic variables to interpret fully. Althought it is the case, the interaction between the money market and the stock market still worth researching.