BoE Paper Cites Opposite Impacts of Human and Automated FX Traders

A new working paper from the Bank of England analyses the role of automated trading (AT) in FX markets in a period containing the 15 January 2015 announcement by the Swiss National Bank that it had removed its EUR/CHF floor and finds that while AT “generated uninformed volatility”, human traders did the opposite.

“This ‘Swiss franc event’ represents a natural experiment as one of the largest shocks to the FX market in recent years and probably the most significant ‘black swan’ event in the period in which AT has been a prominent force in FX markets,” the paper states.

The study looks at the contribution of automated and human traders in providing liquidity and bringing price efficiency, based upon a dataset from EBS Market.

“A detailed understanding of AT in distressed situations is important for at least two reasons,” the paper says. “First, a better comprehension of whether AT is beneficial or detrimental for market quality in extreme situations would help inform the ongoing reform of trading venues, as pursued by Regulation NMS in the United States and MiFID I and II in Europe.

“Second, the resilience of an exchange system depends on the behaviour of different types of market participant and their reciprocal influence on each other,” it continues. “For instance, a tendency of AT to offer liquidity in calm markets and withdraw it in distressed situations could lead less sophisticated agents to become reliant on high levels of market liquidity only to find it in short supply when they most needed it.

“If these adverse consequences of AT were predominant or not offset by other traders, then AT could represent a systemic threat to the whole trading system,” it adds. “To shed light on th s key issue for financial stability, we analyse whether human traders and AT substitute for or complement each other in supplying and consuming liquidity.”

The paper says it delivers two important findings. First, in reaction to the Swiss franc event, its argues that AT tended to consume liquidity and reinforce the price disruption.

Opposite and offsetting patterns apply for human traders, however, who, the paper finds, supported market quality by providing liquidity and aiding price discovery. Interestingly, the paper confirms observations on the day that the mayhem was limited to Swiss franc markets by finding that the market quality degradation coming from AT was concentrated in the shocked FX rate (EUR/CHF) and, to a lesser extent, USD/CHF. “Non-CHF currency pairs were essentially unaffected,” the paper states. “This suggests that AT models were somewhat compartmentalised, which, along with human trading, helped to sustain market quality beyond the CHF currency pairs.”

The paper finds that there was a noticeable withdrawal of EUR/CHF bids that could have been the SNB signalling its withdrawal just prior to the announcement, however it says that it took 44 seconds for the market to react and for the cross to significantly weaken – helped by there being, for a few seconds, no bids to by euro “at any price”

In something of an understatement, the paper states, “We take the delayed response to the announcement as further evidence that it was not anticipated.”

The paper shows that bank AIs consumed liquidity at extreme prices (prices significantly different to those of immediately preceding trades) on a number of occasions, notably between 9.31 and 9.36, and as such, over 75% of the cumulative appreciation of the franc in the 20 minutes to 9.50 was attributable to bank AIs, which accounted for 61% of the volume of liquidity-consuming trades. Bank AIs accounted for an even larger share of the realised variance of the EUR/CHF rate at this time, and also provided liquidity for some of the extreme-price trades. “That bank AIs both consumed and provided liquidity at extreme prices may reflect the diverse set of traders from whom these trades may originate,” the paper states. “This includes not only the different banks but also their various clients.

“In addition, a roughly equal number of extreme-price trades were accommodated by human traders,” it adds. “Indeed, human traders accounted for a significantly higher share of liquidity-providing trades (50%) than they did for liquidity-consuming trades (19%) during the 20 minutes to 9.50 when the Swiss franc appreciated sharply.

Summarising conditions, the paper notes that computers traded “with the wind”, while human traders tended to trade against –this probably signifies those bids placed by traders who were convinced the market had over-reacted to the event, especially as it fell below 0.90 from the original 1.20 floor.

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Colin Lambert

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