This paper was commissioned by Deutsche Börse and aims to provide up-to-date background information on HFT from a European perspective. Some of the main findings are that 1) HFT is not a trading strategy but a technical means to implement established trading strategies; 2) HFT is a natural evolution of the securities markets instead of a completely new phenomenon, and 3) any assessment of HFT based strategies has to take a functional rather than an institutional approach because HFT is applied by different groups of market players. 

This paper examines the question of whether algorithmic trading improves market quality by analyzing electronic message traffic at the New York Stock Exchange as a proxy for changes in the supply of liquidity. The paper finds that for large stocks in particular, automated trading narrows spreads, reduces adverse selection, and reduces trade-related price discovery. The findings indicate that automated trading improves liquidity and enhances the informativeness of quotes.

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Recent concern over “high frequency trading” (HFT) has called into question the fairness of the practice. What does it mean for a financial market to be "fair"? We first examine how high frequency trading is actually used. High frequency traders are often implementing traditional beneficial strategies such as market making and arbitrage, although computers can also be used for manipulative strategies as well. We then examine different notions of fairness. Procedural fairness can be viewed from the perspective of equal opportunity, in which all market participants are treated alike. The same rules apply to HFT as to other traders. Another approach to fairness is in the equality of outcomes. Many HFT strategies are beneficial to other market participants, so one cannot categorically denounce the practice as unfair. Other strategies, for both high and low frequency trading, are not. It is thus important to distinguish between the technology and the use of the technology to make judgments on fairness.

This paper studies market activity in the “millisecond environment,” where computer algorithms respond to each other almost instantaneously. Using order-level NASDAQ data, we find that the millisecond environment consists of activity by some traders who respond to market events (like changes in the limit order book) within roughly 2-3 milliseconds, and others who seem to cycle in wall-clock time (e.g. access the market every second). We define low-latency activity as strategies that respond to market events in the millisecond environment, the hallmark of proprietary trading by a variety of players including electronic market makers and statistical arbitrage desks. We construct a measure of low-latency activity by identifying “strategic runs,” which are linked submissions, cancellations, and executions that are likely to be parts of a dynamic strategy. We use this measure to study the impact that low-latency activity has on market quality both during normal market conditions and during a period of declining prices and heightened economic uncertainty. Our conclusion is that increased low-latency activity improves traditional market quality measures such as short-term volatility, spreads, and displayed depth in the limit order book.

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This paper examines the impact of high frequency traders on equities markets by analyzing trading data provided by Nasdaq OMX for a sample group of 120 U.S. stocks. The paper finds that HFT firms participate in 77% of all trades in 120 stocks traded on Nasdaq OMX’s U.S. equity market and that they tend to engage in a price-reversal strategy, buying after price declines and selling after price gains. The paper finds no evidence suggesting that HFT firms withdraw from markets in bad times or that they engage in abnormal front-running of large non-HFT trades. The paper finds instead that HFT trading provides liquidity, both in terms of quoting the tightest pricing and depth of book. The paper also finds through a number of statistical tests that HFT trading contributes to price discovery and reduces volatility. The paper estimates that the 26 HFT firms in the sample earn approximately $3 billion in profits annually from $30 trillion in trading activity in U.S. equity markets.

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For more information about this publication, please see links below.
http://www.theifm.org/index.cfm?inc=rfm.inc
http://business.kent.edu/rfm
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