Resistance to high-frequency trading: the debate, the evidence and the market designs it produced
High-frequency trading (HFT) uses computers, fast data feeds and physical proximity to exchanges to trade in microseconds. For some, it is the modern form of market making that has made trading cheaper for everyone. For others, it is an arms race that extracts profits from slower investors and makes markets fragile. The resistance to HFT has produced lawsuits, books, regulations and even new exchanges. This article sets out the debate and what research has found.
What HFT firms do
High-frequency trading is not a single strategy but a style: very short holding periods, high order volumes, many cancellations, and positions usually flat by the end of the day. Its main strategies include:
- Electronic market making: posting buy and sell quotes and earning the spread, while managing inventory risk.
- Arbitrage: exploiting brief price differences between related instruments, such as an index future and its constituent stocks, or the same stock on different exchanges.
- Directional short-term trading: predicting very short-term price moves from order flow and order book data.
Speed matters because the first firm to update its quotes or to act on an arbitrage wins. Firms rent rack space next to exchange servers (co-location), buy direct data feeds and have even built microwave networks between Chicago and New York because signals travel faster through air than through fibre.
The case against
- Latency arbitrage: faster traders can see price changes on one venue and trade on another before slower participants' quotes are updated, picking off stale orders.
- Phantom liquidity: quotes that disappear when large investors try to trade against them.
- Fragility: automated liquidity providers can withdraw simultaneously in stress, amplifying moves.
- Wasteful arms race: money spent shaving microseconds benefits the fastest firm rather than society.
- Manipulation: practices such as spoofing, placing orders intended to be cancelled to move prices, are illegal and have been prosecuted.
The Flash Crash
On 6 May 2010, U.S. stock indices fell around 5 to 6 per cent within minutes and then largely recovered. Some individual stocks traded at a penny or at 100,000 dollars. The joint report of the SEC and the CFTC, published in September 2010, traced the trigger to a large automated sell order in E-mini S&P 500 futures, executed without regard to price or time, during an already stressed market. High-frequency traders initially absorbed some of the selling but then traded aggressively among themselves and reduced their liquidity provision. The event led to market-wide circuit breakers and "limit up-limit down" rules for individual stocks.
Flash Boys and the speed bump
Michael Lewis's 2014 book Flash Boys brought the latency arbitrage debate to a wide audience. It told the story of the founders of IEX, a trading venue designed to neutralise some speed advantages. IEX's best-known feature is a "speed bump": incoming and outgoing messages pass through a coil of fibre optic cable that delays them by 350 microseconds, giving the venue time to update its pegged orders before faster traders can react to price changes elsewhere. After a contested process, the SEC approved IEX as a national securities exchange in June 2016. Other venues have since introduced their own forms of delay.
Redesigning the auction
Economists Eric Budish, Peter Cramton and John Shim (2015) argued that the arms race is a design flaw of continuous limit order books, in which time is treated as infinitely divisible and the fastest order always wins. They proposed frequent batch auctions: collecting orders over short intervals, such as a tenth of a second, and executing them together at a single price. Within an interval, speed would no longer confer priority, and competition would shift from speed to price. Batch auctions remain a proposal for most continuous markets, though variants exist in certain venues and in opening and closing auctions.
The case for, and the evidence
Defenders of HFT point to the long decline in bid-ask spreads and trading costs since the early 2000s, when electronic market makers replaced human specialists and floor traders. Several empirical studies support part of that view. Hendershott, Jones and Menkveld (2011) found that the rise of algorithmic trading on the NYSE improved liquidity and the informativeness of quotes, especially for large stocks. Brogaard, Hendershott and Riordan (2014) found that HFT firms on average traded in the direction of permanent price changes and against transitory ones, contributing to price discovery.
Other research is more critical: studies of latency arbitrage, such as Aquilina, Budish and O'Neill (2022) using London Stock Exchange message data, estimated that speed races account for a meaningful share of trading volume and impose a cost equivalent to a small "tax" on trading. Both things can be true: HFT can narrow spreads in normal times while extracting rents from speed and contributing to instability in stress.
Regulation
Regulators have responded with targeted rules rather than bans: the SEC's Market Access Rule requiring pre-trade risk controls (2010); circuit breakers after the Flash Crash; the European Union's MiFID II regime from 2018, which requires firms engaged in high-frequency algorithmic trading to be authorised, store order records and test their algorithms; and enforcement against spoofing under the U.S. Dodd-Frank Act. Some countries have introduced financial transaction taxes or order-to-trade ratio limits.
What it means for slower investors
For most long-term investors, trading costs are lower than they were before electronic markets, and the main practical defences against speed-based disadvantages are simple: use limit orders, avoid trading at the open and close in illiquid names unless through the auctions, and for large orders, use execution algorithms or brokers that measure execution quality. For researchers building automated systems, the lesson is that a strategy whose edge depends on speed is competing against firms that have spent heavily on it.
Sources
- U.S. CFTC and SEC (2010). Findings Regarding the Market Events of May 6, 2010.
- Budish, E., Cramton, P. and Shim, J. (2015). The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response. Quarterly Journal of Economics, 130(4), 1547–1621.
- Hendershott, T., Jones, C. and Menkveld, A. (2011). Does Algorithmic Trading Improve Liquidity? Journal of Finance, 66(1), 1–33.
- Brogaard, J., Hendershott, T. and Riordan, R. (2014). High-Frequency Trading and Price Discovery. Review of Financial Studies, 27(8), 2267–2306.
- Aquilina, M., Budish, E. and O'Neill, P. (2022). Quantifying the High-Frequency Trading "Arms Race". Quarterly Journal of Economics, 137(1), 493–564.
- U.S. Securities and Exchange Commission (2016). Order granting IEX's application for registration as a national securities exchange, Release No. 34-78101.
- Lewis, M. (2014). Flash Boys: A Wall Street Revolt. W. W. Norton.