The big xyt Microbites series is for those who are unfamiliar with the European market structure or need a refresher. In this third episode we look at dark trading in Europe and the unique rules that limit the activity. We recommend that you read the previous episodes if you are unfamiliar with any of the terms used here. View the article
Those of you who keep a close eye on market microstructure will be well aware of a dress rehearsal for “non equivalence” in July 2018 when all Swiss trading was banned on competing venues. Overnight the primary SIX exchange was responsible for 98.8% of turnover in the top 20 Swiss equities (two dual listed stocks ABB Ltd and Lafarge Holcim Ltd were exceptions). Before this the primary had around 70% of market share. This was fairly typical for the primary/MTF split for Lit and Dark volumes as competition evolved post-MiFID regulatory changes.
In our second episode on the European market structure landscape, we describe the grandly named “Multilateral Trading Facilities” (MTFs) and compare them to the better known national stock exchanges.
There was always bound to be some post Brexit ‘fallout’. Unsurprisingly there was plenty of market commentary last week, however we wanted to wait for the dust to settle before we made any of our own observations. You will find it reassuring to know that your suspicions are correct. We can confirm that turnover on Multilateral Trading Facilities (MTFs) shifted to EU venues as investors in EU stocks followed the expected migratory route. If a European alternative existed, the flow migrated there, away from the UK entity (*see the outlier in the footnote below).
In 2020, we took to trading from our bedrooms, garden sheds and conservatories, learned how to download several hundred video conferencing packages, set up a home-school on the kitchen table, and went to work in our pyjamas. As we couldn’t go out on New Year’s Eve to watch the fireworks, we stayed in and prepared our 2020 survey of European equity market volumes and other statistics.
As our 12 Days of Trading campaign 2020 draws to a close, we know you like a festive finale. A global view of equity data allows us to zoom in on specific regions or individual markets. So, just like Santa, you can see everything. In another demonstration of how smart analytics can be powered by a global vault of data, we switched on the lights for the top 30 Nasdaq stocks since the beginning of September. This year’s Christmas tree is constructed with Nasdaq analytical branches.
It’s been a turbulent year for the airlines, and just as the arrival of vaccines seemed to clear away some of the clouds, they’ve been hit by a blizzard of travel restrictions. In today’s 12 Days of Trading post we look at easyJet, a UK travel sector mid cap stock, as an example of how liquidity analysis can inform trading tactics during times of volatility. easyJet’s shares seemed to be on a smooth climb out just a few weeks ago before suffering a 13% price drop over the weekend, most of which has been recovered at the time of writing.
There may be several arguments about inclusion rules and timing and certainly when a stock with a Price /Earnings ratio of 1260 joins an index where the average P/E is 36 it is likely to cause waves rather than ripples. We knew it was going to be big…but this exceeded expectations. For a stock that trades huge volumes anyway the Tesla volumes on Friday were staggering. We can see on our first chart that $200bn traded on that one day. To put that in context, the biggest day in Europe since MiFIDII across ALL stocks was €132bn.
It would be remiss of us not to comment on some observations on market quality as a result of the macro surprises experienced this year. There was a lovely correlation between volatility/uncertainty and market quality during 2020. “Lovely” to behold, but unfortunately, expensive for many end investors. It would seem that the market is intended to be fair to all participants but some thrive more in choppy seas. We see the first evidence of this in Exhibit A today.
Having a team of super smart data scientists who use a consistent methodology on a well curated data set can bring enormous benefits when exploring new ideas. The deployment of new business logic to discover fresh insights can be applied historically as well as going forwards. This provides immediate context for those impatient to see if a trend is present.
