“The real voyage of discovery consists, not in seeking new landscapes, but in having new eyes.” – Marcel Proust (1923)
“Develop your senses — especially learn how to see. Realize that everything connects to everything else.” — Leonardo Da Vinci (~1500)
If you – like the precious thousands of other professionals, mostly notably from the high-performance end of the global trading spectrum, who will venture this way – have come this far in search of Alphacution’s unique brand of irreverent spin on Virtu’s 3rd quarter earnings announcement, then you are about to miss most of the intelligence that is on offer from the growing portfolio of evidence that we are assembling here.
Yes, our modeling and charting and narratives surrounding this latest catalyst from Virtu – along with its and others’ exploits in this rare corner of the financial world – can be found here and throughout our Feed. But, for those who choose to stretch their go-to frame of perspective, there is much more going on here than initially meets the eye…
What is actually going on here is the birth of a new dataset – and, eventually, with the application of some process automation and scaling to our research methodology, the potential for a new data feed. At that point, a regular flow of aggregated data would then fuel regular updates to a series of financial ecosystem “maps,” as if that apparatus was this industry’s very first version of a 3D printer. What is currently of value primarily in the form of strategic navigational intelligence today would then become much more valuable as a form of tactical navigational intelligence – and frankly, become valuable to a broader suite of products and services beyond these maps.
Dare I say, like the aggregation and distribution of the first market-oriented datasets by Michael Bloomberg or the exploitation of those first market-oriented datasets by Jim Simons (founder of Renaissance Technologies), the focus of this project might appear to be rather timely, particularly given that we live in an era when the topic of alternative data is in vogue.
However, unlike the relatively limited use cases of many new alternative data sources and data feeds that, for example, use satellites to track global shipping flows, or social platforms to track increasingly specific user preferences, or even the Internet of Things (IoT) data to parse energy usage patterns through a web of connected appliances, the datafeed we speak of here would be relevant to the entire community players with a direct or indirect economic connection to the financial industry; a very large audience.
Now, all of this assumes that Alphacution is able to convince you of something that I see clearly, but that many – perhaps, most – of you cannot see yet at all. It is at this crossroad, that we continue to leverage interest in and curiosity about firms like Virtu and its peers and competitors – and what its newsworthy evolution may foreshadow for the consecutive rings of players that form the remainder of the global asset management world, namely prop shops, hedge funds, traditional asset managers, and their stakeholders.
As has been said many times within our library of posts: All data has direct observational value as well as contextual value. What follows is a bit of the direct observational value. The contextual value – a blunt hint of which I’ve laid out above – is yours to marinate in for the time being.
The chart below is the Q3-2018 update to a template that was first published here and then again most recently here. It includes the single additional data point that may have triggered the recently announced ITG acquisition.
Here’s why, in a nutshell:
The difference between Virtu’s quarterly net trading income for Q3-2018 and pro-forma Q3-2017 is 2.0%. (That difference is 2.8% if we use adjusted net trading income.) And, the difference between quarterly average volatility (as measured by VIX) for Q3-2018 (of 12.86) and Q3-2017 (of 10.94) is 17.6%
So, given that we have established that volatility is the primary driver of trading income in this space, it does seem puzzling that a quarter vs. quarter increase in volatility of nearly 20% only yields a 2% improvement in net trading income – and especially because we established here that the KCG algorithms – which we must assume have been ever so meticulously ported over to the Virtu infrastructure – proved more responsive to volatility.
Now, we don’t need to think too hard to figure that something else might be going on here: Chances are that the algos are working just fine. Either there has been a shift in competitive dynamics (which could certainly happen when you risk the information leakage from slashing ~500 bright individuals from their jobs), or perhaps there has been some adverse shifting in the costs of trading, as we recently showcased, in part, in the post “Robinhood and Payments for Order Flow” – but, I don’t think that’s it since a cursory review of the disclosures does not indicate any major shifts in trading costs.
Though the hot era of the trading technology arms race has long since cooled – and perhaps forgotten by many – the right ear to the right ground would hear about renewed progress in speed. It is here that we return to the value of contextual data (sooner than I thought!): When we add up the possibilities of increased progress with speed, plus risks of information leakage, plus the fact that there are a scant few players in a position to make a dent, there is only one answer: Citadel.
Anyone care to make an alternate case?
P.S. – A more comprehensive analysis of Virtu + ITG is forthcoming…
As always, if you value this work: Like it, share it, comment on it – or discuss amongst your colleagues – and then send us email@example.com.
As our “feedback loop” becomes more vibrant – given input from clients and other members of our network, especially around new questions to be answered – the value of this work will accelerate.
Don’t be shy…