How European Market State Developed during COVID-19

The European market moved from a passive state of tighter spreads, lower volumes and longer resting times during January and early February to a much more aggressive state in late February and March through April.

As a result of COVID-19 and its immeasurable impact on the global economy, we have seen unprecedented levels of volatility and volumes in the equities market. Overall trading volumes on primary exchanges have risen sharply, 2-3 times above pre-COVID-19 levels, while spreads have widened significantly and daily intraday volatility spiked at 25% price swings.

In this animation, we look at the 200 most liquid stocks for Europe across the 4 biggest markets, France, Germany, Switzerland and the UK. The effect of COVID-19 volatility on Europe in aggregate mirrors the impact seen in the US. As with the US, European stocks moved from a passive state, with longer resting times, tighter spreads and lower volumes executed, to a more aggressive state during the height of the COVID-19 crisis. Towards the end of April, market state reverted back to longer order resting time and lower volumes, however spreads remained wide even into the start of May.

Examining the data on a country level, bubbles are clustering per market, top Swiss equities (depicted in orange) which had a longer average resting time than German stocks before the crisis, continued to do so throughout the crisis, suggesting a less fundamental change in market state than the German or British markets.

The different markets show bubbles repartition along straight lines with the same slope in that log-log plot - in that respect the data presented here is less noisy than what we had observed in the US. Those straight lines in a log-log plot, suggest a power law relation between the number of executions and the resting time of the orders. Therefore one can infer, should such an observation be made at an early enough stage, a level of predictability about the direction of travel of market state. A widening of spreads, coupled with shorter average resting times, can be indicative of a market state where traders are happy to take slippage to better position themselves against wider market swings.

Notes: The Y-axis represents the average order resting time The X-axis represents the number of executions The bubble size represents bid-offer spreads

Aggressive market states, such as those depicted by our plot, should prove rich pickings for market participants who have the technology and data architecture in place to identify and capitalise on wider spreads and higher volumes. Sudden market swings, which seem unpredictable to the naked eye, uncover themselves through access to granular market data & analytics and the tools to analyse them.