IBKR Quant Blog


How Algo Trading Reacts to Market Stress

By Quantpedia

A recent academic research looks at effects of algorithmic trading during turbulent times:

Authors: Breedon, Chen, Ranaldo, Vause
Title: Judgement Day: Algorithmic Trading Around the Swiss Franc Cap Removal
Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3126136

A key issue raised by the rapid growth of computerised algorithmic trading is how it responds in extreme situations. Using data on foreign exchange orders and transactions that includes identification of algorithmic trading, we find that this type of trading contributed to the deterioration of market quality following the removal of the cap on the Swiss franc on 15 January 2015, which was an event that came as a complete surprise to market participants. In particular, we find that algorithmic traders withdrew liquidity and generated uninformative volatility in Swiss franc currency pairs, while human traders did the opposite. However, we find no evidence that algorithmic trading propagated these adverse effects on market quality to other currency pairs.

Notable quotations from the academic research paper:

"We analyse the role of AT in foreign exchange (FX) markets in a period containing the 15 January 2015 announcement by the Swiss National Bank that it had discontinued its policy of capping the value of the Swiss franc against the euro. 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. In particular, we study the contribution of AT and human traders to two important dimensions of market quality, namely liquidity and price efficiency. Our analysis is based on a unique dataset with a detailed identification of AT obtained from EBS Market, which is the leading platform for electronic spot FX trading in many of the major currencies.

A detailed understanding of AT in distressed situations is important for at least two reasons. 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. Second, the resilience of an exchange system depends on the behaviour of different types of market participant and their reciprocal influence on each other. 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. To shed light on this key issue for financial stability, we analyse whether human traders and AT substitute for or complement each other in supplying and consuming liquidity.

We proceed in three steps. First, we describe the EBS Market platform and our sample of data from it. Second, we perform an in-depth analysis of market liquidity and price movements by decomposing order flow, effective spreads and intraday volatility by type of trader. This enables us to highlight the contribution of AT and human traders to liquidity provision and consumption, transaction costs and realised volatility. Third, we study the contribution to efficient pricing of AT and human traders."


To learn more about this study and findings, view the full article on Quantpedia website:



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