The Bank of England just published a research paper examining how High-Frequency Trading impacts Market Efficiency. High-frequency trading (HFT), where automated computer traders interact at lightning-fast speed with electronic trading platforms, has become an important feature of many modern financial markets. The rapid growth, and increased prominence, of these ultrafast traders have given rise to concerns regarding their impact on market quality and market stability. These concerns have been fuelled by instances of severe and short-lived market crashes such as the 6 May 2010 ‘Flash Crash’ in the US markets. One concern about HFT is that owing to the high rate at which HFT firms submit orders and execute trades, the algorithms they use could interact with each other in unpredictable ways and, in particular, in ways that could momentarily cause price pressure and price dislocations in financial markets.
Using a unique data set on the transactions of individual high-frequency traders (HFTs), we examine the interactions between different HFTs and the impact of such interactions on price discovery. Our main results show that for trading in a given stock, HFT firm order flows are positively correlated at high-frequencies. In contrast, when performing the same analysis on our control sample of investment banks, we find that their order flows are negatively correlated. Put differently, aggressive (market-“taking”) volume by an HFT will tend to lead to more aggressive volume, in the same direction of trade, by other HFTs over the next few minutes. For banks the opposite holds, and a bank’s aggressive volume will tend to lead to aggressive volume in the opposite direction by other banks. As far as activity across different stocks is concerned, HFTs also tend to trade in the same direction across different stocks to a significantly larger extent than banks.
We find that HFT order flow is more correlated over time than that of the investment banks, both within and across stocks. This means that HFT firms tend more than their peer investment banks to buy or sell aggressively the same stock at the same time. Also, a typical HFT firm tends to simultaneously aggressively buy and sell multiple stocks at the same time to a larger extent than a typical investment bank. What does that mean for market quality? A key element of a well-functioning market is price efficiency; this characterises the extent to which asset prices reflect fundamental values. Dislocations of market prices are clear violations of price efficiency as they happen in the absence of any news about fundamental values.
Given the apparent tendency to commonality in trading activity and trading direction among HFTs, we further examine whether periods of high HFT correlation are associated with price impacts that are subsequently reversed. Such reversals might be interpreted as evidence of high trade correlations leading to short-term price dislocations and excess volatility. However, we find that instances of correlated trading among HFTs are associated with a permanent price impact, whereas instances of correlated bank trad- ing are, in fact, associated with future price reversals. We view this as evidence that the commonality of order flows in the cross-section of HFTs is the result of HFTs’ trades being informed, and as such have the same sign at approximately the same time. In other words, HFTs appear to be collectively buying and selling at the “right” time. The results are also in agreement with the conclusions of Chaboud, Chiquoine, Hjalmarsson, and Vega (2014), who find evidence of commonality among the trading strategies of algorithmic trades in the foreign exchange market, but who also find no evidence that such commonality appears to be creating price pressures and excess volatility that would be detrimental to market quality.
A final caveat is in order. The time period we examine is one of relative calm in the UK equity market. This means that additional research on the behaviour of HFTs, particularly during times of severe stress in equity and other markets, would be necessary in order to fully understand their role and impact on price efficiency.
DFA’s perspective is a little different. The underlying assumption in the paper is that more transactions gives greater market efficiency, and therefore HFT is fine. We are not so sure, as first the market efficiency assumption should be questioned, second it appears those without HFT loose out, so are second class market participants – those with more money to invest in market systems can make differentially more profit. This actually undermines the concept of a fair and open market. We think HFC needs to be better controlled to avoid an HFC arms race in search of ever swifter transaction times. To an extent therefore, the paper missed the point.
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