本研究主要目的是為台灣期貨市場提出二種區分頻繁交易者的指標，其一為高刪改單量比率，其二為高委託次數者，以此探討期貨市場中頻繁與非頻繁交易投資人對市場流動性與報酬率之影響。我們以台灣期貨市場的台指期貨及小型台指期貨為研究標的，分別自各市場參與人中篩選出兩種頻繁交易人並將他們的委託單排除後算出委託不均衡，將其結果減去完整市場的委託不均衡，得到無頻繁交易者委託單時的市場委託不均衡與完整委託單下市場委託不均衡的差異，以此觀察頻繁交易者對市場流動性的貢獻情形。本文根據文獻回顧，將交易量、報酬率與波動度作為自變數，前述流動性貢獻作為因變數，以Tobit Model檢視它們之間的關係。結果驗證了屬於資訊擁有者的頻繁交易人是市場流動性的供給者，而非頻繁交易者則為市場流動性的需求者。其次，本研究欲探討頻繁交易者委託不均衡與市場報酬率、市場委託不均衡之間的時間序列關係，將各變數落後一至二分鐘之落後期數值與代表不同交易時段的虛擬變數納入VAR迴歸模型中，觀察兩兩間是否存在領先落後關係。檢驗結果顯示頻繁交易者的委託單不均衡與其落後期有顯著相關性，顯示頻繁交易人會依據前期下單決策調整當期下單方向；市場委託不均衡與頻繁交易者的委託不均衡間則無顯著領先落後關係。

The study aims to create indexes to indicate two groups of frequent traders in Taiwan futures exchange market. One is by observing order revision of each account, another is by order frequency. By separating frequent traders from the majority non-frequent traders, we are able to analyze their contributions to market liquidity and returns. The research is focusing on Taiwan Stock Index Futures and Mini-Taiwan Stock Index Futures. Due to the fact that they are the most frequently traded products and the most discussible subjects in both empirical and academic research of Taiwan futures exchange market.
We take order imbalance as the index of market liquidity. In order to measure the contribution of frequent traders to market liquidity, we calculate the market order imbalance of each product; then we calculate the order imbalance without orders made by the frequent traders; finally, we acquire a new index measuring the liquidity contribution of each trader group by subtracting the former from the latter. Base on the discovery of previous studies, trading volume, return rate and validity have influence on liquidity. Our study extends the observations by implying the three variables as independent variables and the liquidity contributions of frequent traders as dependent variable into TOBIT model. To examine if the correlation exists in the orders of frequent traders. The regression analysis confirms that frequent traders are the suppliers of market liquidity while non-frequent traders are the demanders. Finally, we also examine order imbalances of the two frequent trader groups and their relationships with market order imbalance and market return while taking each of their lag values into account. We do a sequence of time-series analysis by using VAR model. The results show that order imbalance of frequent traders has significant relationship with its lag values which implies frequent traders tend to make orders base on their previous order strategies. Meanwhile, there’s neither significant relation between order imbalance of frequent traders and market order imbalance nor significant relation with the lag values of market order imbalance.

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