隨著電腦科技的日新月異， 金融市場也發生了翻天覆地的變化。近年來，高頻交易異軍突起，叱吒證券市場，不僅引起了監管者的注意，更吸引了學術界對它的討論與研究。本研究參考Hagstromer and Norden (2013)的方法，將高頻交易者分為造市商策略者和投機交易者。本文發現臺灣期貨市場上確實存在至少兩種不同類型的高頻交易者，並且他們在市場中的行為特徵各不相同。造市商策略者會在前期委託簿深度比較淺的時候下一些最佳買賣報價或者最佳買賣報價之間的限價單，或者在前期報酬為正的時候提高自己委託單的強度。但是投機交易者的行為則正好相反。這說明，我們的分類方式能夠有效的區分出兩種高頻交易者。本文的重點之一是觀察高頻交易對市場逆選擇成本的影響。通過實證分析，本文發現，在臺灣市場上，2011之前，兩種類型的高頻交易皆增加市場逆選擇成本。而在2011年之後，造市商策略者的參與似乎降低了逆選擇成本，而投機交易者的活動依舊增加逆選擇成本。以臺灣市場2009年提高揭示速度為事件做事件研究發現，揭示速度提高後高頻交易對市場逆選擇成本問題的負面影響明顯降低。這說明提高市場的透明度有助於減緩高頻交易對市場的負面影響。

With the development of technology, financial markets have been changing rapidly in recent years. High frequency trading has caught the attention of monitors as well as researchers. This study follows the method of Hagstromer and Norden (2013) to subgroup HFTs into market makers and opportunistic HFTs. We find that there exists at least two kinds of HFTs in the Taiwan futures market and they behave differently in some way. For market makers, they would increase the aggressiveness of their orders when the depth is shallow and the prior period’s return is positive. However, opportunistic HFTs act in the opposite way. Moreover, from the empirical research event study, we find that before 2011 both types of HFTs increase the problem of adverse selection, while after 2011, market makers play a positive role in improving liquidity, but opportunistic HFTs still decrease it. For the event study, we find HFTs reduce their negative impact on adverse selection. It may be that the more quickly the exchange displays the information, the less information asymmetry. Since HFTs lost some of their advantage, the fast traders are not able to use information to adverse select other investors as before. We believe that improving the transparency of the market, can reduce the negative impact of HFTs on market quality.

摘要 ii
ABSTRACT iii
I. INTRODUCTION 1
1.1 Background Information 1
1.2 Research Purpose 3
1.3 Research Structure 3
1.4 Research Contribution 4
II. LITERATURE REVIEW 5
2.1 The definition of HFT 5
2.1.1 Identifying HFTs 5
2.1.2 The classification of HFTs 6
2.2 High frequency trading and liquidity 8
2.2.1 The model of high frequency trading 8
2.2.2 The empirical results of high frequency trading and liquidity 11
III. METHODOLOGY 15
3.1 Data 15
3.2 High frequency traders 16
3.2.1 Identification of high frequency traders 16
3.2.2 Distinguish market maker or opportunistic HFTs 17
3.3 Regressions and variables 18
IV. EMPIRICAL RESULTS 23
4.1 Descriptive statistics 23
4.2 HFTs vs. Non-HFTs 23
4.3 HFT Market makers and opportunistic HFTs 29
4.4 High frequency trading and liquidity 35
V. CONCLUSION 38
REFERENCES 40

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