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An academic study[37] found that, for large-cap stocks and in quiescent markets during periods of "generally rising stock prices", high-frequency trading lowers the cost of trading and increases the informativeness of quotes;[38] however, it found "no significant effects for smaller-cap stocks"[39], and "it remains an open question whether algorithmic trading and algorithmic liquidity supply are equally beneficial in more turbulent or declining markets...algorithmic liquidity suppliers may simply turn off their machines when markets spike downward."[40]
In September 2011, Nanex, LLC (a high-frequency trading software company) published a report stating the contrary. They looked at the amount of quote traffic compared to the value of trade transactions over 4 and half years and saw a 10-fold decrease in efficiency.[41] Many discussions about HFT focus solely on the frequency aspect of the algorithms and not on their decision-making logic (which is typically kept secret by the companies that develop them). This makes it difficult for observers to pre-identify market scenarios where HFT will dampen or amplify price fluctuations. The growing quote traffic compared to trade value could indicate that more firms are trying to profit from cross-market arbitrage techniques that do not add significant value through increased liquidity when measured globally.
More fully automated markets such as NASDAQ, Direct Edge, and BATS, in the US, have gained market share from less automated markets such as the NYSE. Economies of scale in electronic trading have contributed to lowering commissions and trade processing fees, and contributed to international mergers and consolidation of financial exchanges.
The speeds of computer connections, measured in milliseconds or microseconds, have become important.[42][43] Competition is developing among exchanges for the fastest processing times for completing trades. For example, in 2009 the London Stock Exchange bought a technology firm called MillenniumIT and announced plans to implement its Millennium Exchange platform[44] which they claim has an average latency of 126 microseconds.[45] Since then, competitive exchanges have continued to reduce latency, and today, with turnaround times of three milliseconds available, are useful to traders to pinpoint the consistent and probable performance ranges of financial instruments. These professionals are often dealing in versions of stock index funds like the E-mini S&Ps because they seek consistency and risk-mitigation along with top performance. They must filter market data to work into their software programming so that there is the lowest latency and highest liquidity at the time for placing stop-losses and/or taking profits. With high volatility in these markets, this becomes a complex and potentially nerve-wracking endeavor, in which a small mistake can lead to a large loss. Absolute frequency data play into the development of the trader's pre-programmed instructions.[46]
Spending on computers and software in the financial industry increased to $26.4 billion in 2005.[47]
The brief but dramatic stock market crash of May 6, 2010 was originally alleged to have been caused by high-frequency trading.[48] However, CME Group, a large futures exchange, stated that, insofar as stock index futures traded on CME Group were concerned, its investigation had found no support for the notion that high-frequency trading was related to the crash, and actually stated it had a market stabilizing effect.[49] This conclusion is contradicted in a report on the Flash Crash by the U.S. Securities and Exchange Commission and the Commodity Futures Trading Commission, wherein regulators stated that the actions of high-frequency trading firms on May 6, 2010 contributed to volatility during the crash.[9][10][11][12][13][14][15][16] Despite the original perception that high-frequency traders typically cause no market price impact,[7] and have a stabilizing effect in times of volatility,[7][36][49] and some suggestions that they may actually have been a major factor in minimizing and partially reversing the Flash Crash,[50] later reports determined that high-frequency trading had significant price impact and a destabilizing role during the Flash Crash, helping to drive prices down.[9][10][11][12]
