隨著科技進步，電腦科技日新月異，過去以交易員在交易所內吶喊交易的情形已被網際網路與電腦取代。機構法人的交易模式也逐漸在轉變中，特別是美國股票市場近五年來經歷了大幅度的改變，演算法交易與高頻交易在美國股市的比重每年均以非常快的速度成長目前至少佔了七成的交易量。且許多學者發現這些以程式、電腦為基礎的交易方式能增加流動性、降低波動性，且能促進價格發現功能。
本研究以台灣股票市場2008年之日內資料進行實證研究，欲探討這股風潮對於台灣股票市場的影響。實證結果發現，市值、流動性、個股波動性越大，演算法交易比例越高。而演算法交易比例越大能提升流動性，但會增加個股波動性，在控制金融海嘯的影響後，仍有相同的結論。代表演算法交易者的交易行為對於市場品質的影響並不都是正向的，此結果可能與台灣特殊的交易機制或演算法交易在台灣的競爭度較低有關。在交易策略方面，發現外資的交易策略以動能策略為主，且同時考慮前期報酬、前期OIB。在刪單策略上，發現外資在前期報酬、OIB均為正或均為負時顯著會改下刪單，表示外資在這些情況下會更積極的改變委託單進行交易。
綜上所述，演算法交易者對於市場同時存在正向(流動性)與負向(波動性)影響。對於一般投資人而言，演算法交易的追漲殺跌策略可能會吸引其進場交易，但投資人若跟隨其一起進場交易不一定能討到好處，因為其交易策略可能僅是為了拉高價格出貨或壓低價格買進。對於監管機關而言，演算法交易者的交易行為應受到部分管制，監管機關或許可考慮加入類似韓國的斷路機制，特別是針對程式交易上的斷路機制。
關鍵字：演算法交易、高頻交易、日內、策略、流動性、波動性、市場品質

As science advances, computer technologies are developing rapidly in the past decades. The previous way of traders’ yelling for orders in the house of exchange has been replaced by the Internet and computers. The trading modes of institutional investors are transforming gradually, particularly the radical changes in the US stock market for the past 5 years. The transaction volume from high frequency trading and algorithmic trading is growing dramatically per year, accounting for at least 70% in the U.S. market. And many researchers find these trading methods based on the computer programs good in increasing liquidity, reducing volatility and facilitating price discovery.
By using intraday data of Taiwan stock market in 2008 to conduct empirical research, this study intends to analyze the effect of this trend on the TW stock market. Empirical results found that the greater the market capitalization, liquidity, stock volatility are, the higher the proportion of algorithmic trading will be, but which only exists in foreign institutional investors. On the other hand, the increase of the proportion of algorithmic trading can improve liquidity, meanwhile raise the volatility. The conclusion remains unchanged when applied to control the effect of financial tsunami. That means algorithmic trader’s behaviors are not always positive. This result could be related to the special transaction mechanism or lower competition of algorithmic trading in Taiwan. As to trading strategy, the result found that foreign institutional investors focus on momentum strategies, whereas particular dealers act for the sake of index arbitrage or hedge.
In summary, the algorithmic trader’s transaction bears positive (liquidity) and negative (volatility) impact on the market at the same time. For individual investors, algorithmic trading’s momentum strategy could appeal to them, but they may not make a profit from these trades, because this strategy could merely want to pull price higher and sell stock or the opposite. About regulators, algorithmic traders’ behavior should be regulated partly; regulatory authorities might also consider adding the circuit mechanism similar to South Koreas’, especially on the program trading.
Keywords: algorithmic trading, high frequency trading, intraday, strategy, liquidity, volatility, market quality

論文審定書 i
摘 要 ii
Abstract iii
第一章 緒論 1
第一節 研究動機與目的 1
第二節 研究貢獻 5
第三節 研究範圍、對象與限制 5
第四節 研究架構 5
第二章 文獻探討 6
第一節 委託單型態 7
第二節 市場品質 10
第三節 交易速度與交易環境 16
第四節 獲利性 19
第五節 對監管機關、交易所與投資人的影響 20
第六節 其他文獻 21
第三章 演算法交易與高頻交易的歷史發展與交易策略 23
第一節 演算法交易之定義 23
第二節 高頻交易之定義 24
第三節 演算法交易與高頻交易之歷史演進 24
第四節 演算法交易之現況 26
第五節 高頻交易之現況 27
第六節 演算法交易之策略 29
第七節 高頻交易之策略 31
第八節 小結 34
第四章 研究假說與方法 35
第一節 樣本描述 35
第二節 研究假說 44
第三節 研究方法 46
第五章 實證結果 54
第一節 敘述統計 54
第二節 市場品質 55
第三節 金融海嘯 61
第四節 交易策略 64
第六章 結論與後續研究建議 78
第一節 結論 78
第二節 後續研究建議 80
參考文獻 81
附錄一：文獻彙整表 87
附錄二：演算法交易之定義 90
附錄三：高頻交易之定義 93
附錄四：四種法人之日內資料敘述統計表 95
附錄五：各類法人之個別交易人下單次數排名表 96
附錄六：相關係數彙整表 97
附錄七-1：市場品質變數對AT代理變數之結果彙總表(自營商) 99
附錄七-2：市場品質變數對AT代理變數之結果彙總表(外資) 100
附錄八-1：AT代理變數對流動性變數之彙總表(自營商) 101
附錄八-2：AT代理變數對流動性變數之彙總表(外資) 102
附錄九-1：AT代理變數對波動性之彙總表(自營商) 103
附錄九-2：AT代理變數對波動性之彙總表(外資) 104
附錄十二：不同交易人之買單交易策略結果彙整表 105
附錄十三：不同交易人之賣單交易策略結果彙整表 106
附錄十四：不同交易人之刪單交易策略結果彙整表 107
附錄十五：HFT市占率 108

Prix, J., Loistl, O., & Huetl, M. (January 01, 2007). Algorithmic Trading Patterns in Xetra Orders. The European Journal of Finance, 13, 8, 717-739.
Bacidore, J., Battalio, R. H., & Jennings, R. H. (January 01, 2003). Order submission strategies, liquidity supply, and trading in pennies on the New York Stock Exchange.Journal of Financial Markets, 6, 3, 337.
Ahn, H.-J., Bae, K.-H., & Chan, K. (January 01, 2001). Limit Orders, Depth, and Volatility: Evidence from the Stock Exchange of Hong Kong. The Journal of Finance, 56, 2, 767-788.
Albert J. Menkveld(April 26, 2011), High Frequency Trading and The New-Market Makers
Aldridge, I. (2010). High-frequency trading: A practical guide to algorithmic strategies and trading systems. Hoboken, N.J: Wiley.
Alvaro Cartea, Jose Penalva(2011), Where is the Value in High Frequency Trading?, Working paper
Amihud, Y., 2002, Illiquidity and stock returns: Cross-section and time series effects, Journal of Financial Markets 5, 31–56.
Anand, A. and T. Martell (2001), “Informed limit order trading,” Working paper, School of Management, Syracause University.
Andrei Kirilenko Mehrdad Samadi Albert S. Kyle Tugkan Tuzun, The Flash Crash: The Impact of High Frequency Trading on an Electronic Market, Working paper, January 18, 2011
Andrew Lepone and Mitesh Mistry(2010), The New Breed of Market Participants: High Frequency Trading Evidence from the Australian Stock Exchange, Working paper, University of Sydney
Austin Gerig ,J. Doyne Farmer, Fabrizio Lillo(2011), How Prices Respond to Worked Orders , Working paper
Back K., C. H. Cao, and G. A. Willard (2000), “Imperfect competition among informed traders,” Journal of Finance 55, 2117-2155.
Bennett, P. and L. Wei (2006), ‘Market Structure, Fragmentation, and Market Quality’, Journal of Financial Markets, 9: 49-78.
Bernstein, P. L., 1987, “Liquidity, Stock Market, and Market Maker,” Financial Management, 16, 54-63.
Biais, B., Hillion, P., & Spatt, C. (January 01, 1995). An Empirical Analysis of the Limit Order Book and the Order Flow in the Paris Bourse. The Journal of Finance, 50, 5, 1655.
BMO Capital market(2009), The Impact of High Frequency Trading on the Canadian Market
Boehmer, E., 2005. Dimensions of execution quality: Recent evidence for US equity mar-
kets. Journal of Financial Economics 78 (3), 553–582.
Boulatov, Alex, and Martin Dierker, 2007, Pricing prices, Working paper, University of Houston.
Brogaard, Jonathan, 2010, High Frequency Trading and its Impact on Market Quality,Working paper.
Bruno Biais, Sophie Moinas, Thierry Foucault(October 2010), Equilibrium Algorithmic Trading, Working paper
Chaboud, Alain, Benjamin Chiquoine, Erik Hjalmarsson, and Clara Vega, 2009, Rise of the machines: Algorithmic trading in the foreign exchange market, Working paper, Federal Reserve Board.
Chordia, T., Roll, R., & Subrahmanyam, A. (August 01, 2011). Recent trends in trading activity and market quality. Journal of Financial Economics,101, 2, 243-263.
CIBC Whitepaper, High Frequency Trading: A Canadian Perspective, OCTOBER 20, 2009
CME Group , Algorithmic trading and market dynamics, July 2010
Copeland, T., and D. Galai, (1983). Information effects on the bid-ask spread. Journal of Finance, 38, 1456-1469.
David Easley, Maureen O’Hara and Liyan Yang, March, 2011, Differential Access to Price Information in Financial Markets, Working paper, Cornell University
Demsetz, H., 1968, “The Cost of Transaction.” Quarterly Journal of Economics 82, 33-53.
Domowitz, I., & Yegerman, H. (January 01, 2005). THE COST OF ALGORITHMIC TRADING: A FIRST LOOK AT COMPARATIVE PERFORMANCE. The Institutional Investor, 11, 30
Durbin, M. (2010). All about high-frequency trading. New York, NY: McGraw-Hill.
Easely, D., Hendershott, T., Ramadorai, T., 2007. The price of latency, Working paper.
Elvis Jarnecic and Mark Snape, An analysis of trades by high frequency participants on the London Stock Exchange, Working paper, 22 June 2010
Esser, Angelike, and Monch, Burkart, 2007 , The Navigation of an Iceberg：The Optimal Use of Hidden Orders. Finance Research Letters Volume 4, Issue 2 Pages 68-81.
Financial Times, Burton Malkiel, (December 14, 2009), High-frequency trading is a natural part of market evolution
Foster, F Douglas & Viswanathan, S, 1996. " Strategic Trading When Agents Forecast the Forecasts of Others," Journal of Finance, American Finance Association, vol. 51(4), pages 1437-78, September
Foster, F. Douglas & Viswanathan, S., 1994. "Strategic Trading with Asymmetrically Informed Traders and Long-Lived Information," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 29(04), pages 499-518, December.
Frank Zhang(December 2010), The Effect of High-Frequency Trading on Stock Volatility and Price Discovery, Working paper , Yale School of Management
Frey, Stefan, and Sandas, Patrik, 2008, Iceberg Orders and Compensation for Liquidity Provision. Working paper.
Garvey, R., & Wu, F. (November 01, 2010). Speed, distance, and electronic trading: New evidence on why location matters☆. Journal of Financial Markets, 13, 4, 367-396.
Glosten, Lawrence R., 1994, Is the electronic limit order book inevitable? Journal of Finance 49, 1127–1161.
Groth, Sven S., 2009, Further evidence on “Technology and liquidity provision: The blurring of Tradition Definitions,” Working paper, Goethe University, Frankfurt am Main
Gsell, Markus, and Peter Gomber, 2008, Algorithmic trading versus human traders—Do they behave different in securities markets? Working paper, Goethe University, Frankfurt am Main.
Handa, P., and Schwartz, R. A., 1996b, "Limit Order Trading," Journal of Finance 51,1835-1860.
Harris, L. and Hasbrouck, J., 1996, “Market vs. Limit Orders: the SuperDot Evidence on Order Submission Strategy,” Journal of Financial and Quantitative Analysis, 31, 219-232.
Harris, L., Sofiano, G.., and Shapiro J. E., 1994, “Program Trading and Intraday Volatility”. The Review of Financial Studies, 7, 4, pp.653-685.
Hasbrouck, J., & Saar, G. (M ay 01, 2009). Technology and liquidity provision: The blurring of traditional definitions. Journal of Financial Markets,12, 2, 143.
Hasbrouck, Joel, and Gideon Saar, February 2011 Low Latency Trading, Johnson School Re- search Paper Series 35.
Hendershott, T., & Moulton, P. C. (November 01, 2011). Automation, speed, and stock market quality: The NYSE's Hybrid. Journal of Financial Markets, 14, 4, 568-604.
Hendershott, T., Jones, C. M., & Menkveld, A. J. (February 01, 2011). Does algorithmic trading improve liquidity?. Journal of Finance, 66, 1, 1-33.
Hendershott, Terrence, and Ryan Riordan, 2009, Algorithmic trading and information, Working paper, University of California, Berkeley.
Jeff Castura, Robert Litzenberger, Richard Gorelick, Yogesh Dwivedi (August 30, 2010), Market Efficiency and Microstructure Evolution in U.S. Equity Markets: A High-Frequency Perspective, RGM Advisors, LLC
Jovanovic, Boyan, and Albert J. Menkveld, 2010, Middlemen in limit-order markets, Working paper, New York University, New York.
Kyle, Albert S., 1985, Continuous Auctions and Insider Trading, Econometrica 53, 1315–1335.
Laurent Grillet-Aubert(2010), Equity trading: A review of the economic literature for the use of market regulators,AMF
Lee, C., Mucklow, B., & Ready, M. (February 01, 1993). Spreads, depths, and the impact of earnings information: an intraday analysis. Review of Financial Studies, 6, 2, 345-374.
Lee, Charles M.C., and Mark J. Ready, 1991, Inferring trade direction from intraday data, Journal of Finance 46, 733–746.
Michael J. Mcgowan(2010), The rise of computerized high frequency trading: use and comtroversy, Workgin paper
Moallemi, Ciamac C., and Mehmet Saglam, 2010, The Cost of Latency, Working paper.
Netherlands Authority for the Financial Markets(AFM,2010), High frequency trading: The application of advanced trading technology in the European marketplace
Order Characteristics and Stock Price Evolution: Program Trading on the NYSE, Journal of Financial Economics, 41, 129-149 (1996).
Robert Jarrow, Philip Protter, A Dysfunctional Role of High Frequency Trading in Electronic Markets, Johnson School Research Paper, 2011
Rosenblatt Securities Inc(September 30, 2009) , Market Structure Analysis & Trading Strategy An In-Depth Look at High-Frequency Trading
Ryan Riordan , Andreas Storkenmaier,( March 29, 2011) Latency, Liquidity and Price Discovery, Karlsruhe Institute of Technology Working paper
Sal Arnuk and Joseph Saluzzi(December 4, 2009), Latency Arbitrage: The Real Power Behind Predatory High Frequency Trading, A Themis Trading LLC White Paper
Securities and Exchange Commission, 2010, Concept Release on Equity Market Structure (Release No. 34-61358).
Stoll, H. R(2006), "Electronic Trading in Stock Markets, "Journal of Economic Perspectives , vol.20 , p. 153–174.
U.S. Commodities Futures Trading Commission, and U.S. Securities and Exchange Commission, 2010, Findings regarding the market events of May 6, 2010,
Venkataraman, K., 2001. Automated versus floor trading: An analysis of execution costs
on the Paris and New York Exchanges. Journal of Finance 56 (4), 1445–1485.
Wang, F.A. (1998). Strategic trading, asymmetric information and heterogeneous prior beliefs. Journal of Financial Markets, Vol.1, pp.321–352.
游張松、張耀鴻(2009), 期貨交易之市場資料揭露速度與關鍵因素研究, 中華民國期貨業商業同業公會
蕭朝興、尤靜華、林庭宇（2009），「台灣股市投資人競價策略與價格. 優劣之比較」，中山管理評論，第17卷，第4期，927-969