Before we get into the weeds of quantum computing and M&A, for our fans of market data and regulation, Jo Wright has been covering movements toward a consolidated tape in Europe closely. Here, she looks at a recent EU-backed report that has presented what might be the most viable governance model yet for the controversial project.
Also, we’re just over two weeks away from Election Day in the United States. As we’ve learned numerous times before, preliminary polls don’t always reflect reality. Reb Natale looks at how advancements in modeling and the rise of alt data have made the process of prepping for a US presidential election more complex for portfolio managers, but hopefully more accurate.
Let’s Make a Deal
While the coronavirus has wreaked havoc on industries across the globe, the world of finance has largely survived the pandemic unscathed—while jobs have certainly and unfortunately been lost, 2008 and the resulting staff reductions from the Financial Crisis, this is not. And perhaps further evidence of smooth sailing on Wall Street is the sound of mergers and acquisitions floating in the air.
Over the last two-or-so weeks, the London Stock Exchange Group (LSEG) agreed to sell its entire shareholding in LSEG Italia, S.p.A, the parent company of Borsa Italiana, to Euronext for €4.325 billion (~5.1 million), though that deal is contingent on the LSEG’s deal to purchase Refinitiv going through. Speaking of Refinitiv, the vendor recently acquired the Red Flag Group, a provider of workflow, data, due diligence, and ratings solutions in the field of ESG.
Also on the exchange side, Cboe Global Markets made a bid for BIDS Trading (sorry) for an undisclosed amount. Additionally, while no official deal has been announced, Barron’s reported that private-equity firm Flexpoint Ford has put Dash Financial Technologies up for sale. (And, of course, there were non-fintech deals, as well, including Morgan Stanley’s $7 billion offer for Eaton Vance, and Citadel Securities’ buying the NYSE market-making business of IMC Financial Markets.)
On the investment front, private-equity firm LLR Partners’ growth recapitalization with YCharts was completed, and low-code platform provider Genesis Global Technology received an undisclosed strategic investment from Citi via its Markets FinTech Investments and SPRINT groups. Overall, according to a report from PitchBook and the National Venture Capital Association, through Q3 of 2020, even as the pandemic has created great uncertainty, US venture capital funds have raised $56.6 billion, which is “more than [the] $54.9 raised in all of 2019, and less than $12 billion shy of 2018’s record fundraising total of $68.1 billion.” (Editor’s note: After this story was published, it was announced that private-equity firm Thoma Bravo was buying AxiomSL for an undisclosed amount.)
So the purse strings are clearly loose, but I wanted to highlight a confirmed acquisition story and a rumored sale story because I think they show a broader trend in the industry, and I’d be interested to hear your thoughts.
First, it was announced on October 9 that TP Icap had agreed to buy Liquidnet for a total consideration of something between $575 million and $700 million. Now, from a coverage perspective, TP Icap is looking to bolster its fixed-income credentials. But I write about technology and data, and I’m more interested in some acquisitions made by Liquidnet, rather than the dark pool provider’s corporate bond trading platform, itself. There are plenty of stories that look at how this will help TP Icap compete with the likes of Bloomberg, MarketAxess, and Tradeweb…this is a different take.
In 2017, Liquidnet acquired OTAS Technologies, a buy-side market intelligence platform provider. The aim of the purchase at the time was to use OTAS’s analytics capabilities to enhance its own Virtual High Touch (VHT) trading platform. Liquidnet followed that deal with acquisitions in 2019 of Prattle, a specialist in natural language processing (NLP) tools, and institutional research provider RSRCHXchange. Prattle bolstered Liquidnet’s abilities in the realms of sentiment data and predictive analytics, and RSRCHXchange gave it a stockpile of information that the OTAS and Prattle AI tools could help enhance. Makes sense.
Later in 2019, as WatersTechnology first reported, Liquidnet’s plan was to combine those three business units into one cohesive offering. The new business line—dubbed Investment Analytics (IA)—would run alongside its equity execution and fixed-income businesses. Since then, as we reported this summer, the IA unit has begun working on experimental pilot projects with portfolio managers and traders in order to expand its data analytics offerings to institutional asset managers.
I’m going to hammer this point a few more times in the paragraphs to come, but to me, Liquidnet used its acquisitions to evolve beyond a hardcore, monolithic trading platform provider, to a data analytics company that uses those trading platforms as its foundation.
Essentially, data is God, and while that part isn’t news, cloud, APIs, and open-source are making dinosaurs of legacy trading technology providers that are slow to transition to the world of data analysis. Traders and portfolio managers want more than execution; they want insight and information pre-, post-, and during a trade because the world is becoming increasingly complex.
So did TP Icap buy itself a respected dark pool provider? Absolutely. But the sneaky, potential game-changer in the deal is the work that Liquidnet has put in by combining OTAS, Prattle, and RSRCHxchange. New product offerings that can be developed through IA will yield those much-coveted data-business revenues.
(Or, I’m WAY off base and the IA unit will be packaged off and sold to someone else…wait and see, I guess, but my money—of which there is none—is on the former.)
The second deal that I want to discuss is, right now, hypothetical. On October 6, Barron’s reported that Chicago-based futures trading platform provider Trading Technologies (TT) was up for sale. A spokesperson for the company says that “conversations with other firms about partnerships are nothing new, as we have always looked for ways to unlock additional value and share our vision for scaling the business,” so it’s important to note that any deal is speculative—BUT, with that said, I think that they fit into my narrative quite nicely.
In 2015, Trading Technologies launched a new trading platform that would go by the company’s initials, TT. For the previous two decades, the only trading platform the company had sold was X_Trader. If you think back to 2015, the idea of sunsetting a firm’s flagship product for a SaaS-delivered platform was a bit ahead of the times in the capital markets. And, as TT’s CEO Rick Lane noted previously on the Waters Wavelength Podcast, while it was a somewhat easy decision to make, it was a challenging road that required staying on course or risk losing users in droves.
In 2017, TT made a move into the surveillance and analytics space with the acquisition of Neurensic, a supplier of machine-learning tools in the compliance space. By 2018, with the company’s future foundation being laid, the vendor began plotting its move deeper into the analytics space, as well building a new order management system (OMS)—which is currently being rolled out—and the launch of an analytics product, TT Score. Then, the aforementioned Neurensic would help to serve as the basis of the 2019 debut of TT’s infrastructure-as-a-service offering.
Continuing to try new things, this past May, the company unveiled plans for a truly ambitious project: Echo Chamber, a new market data platform that would allow individual firms and groups of firms to see aggregated and anonymized order data in real time from more than 55 exchanges. At its core, Echo Chamber combines futures contracts traded on different exchanges to provide a single view of each, no matter where the contract is traded.
Lane told WatersTechnology that the reason the company is going live with Echo Chamber now is because they have a client base that represents a significant portion of lit liquidity around the world, and that is thanks, in part, to the company’s migration to the TT SaaS-based platform from the legacy X_Trader system.
“We’re just now to the point in our migration that we’re approaching where 65-70% of our volume is happening on the TT platform. That will be a much bigger number a month from now and hopefully close to 100% by the end of this year,” he said back in May. “So now we really do have the flow running through these pipes to turn something like this on and make it meaningful.”
Once again—and this is just my opinion—this shows the evolution of a hardcore trading platform provider putting in the hard work of creating a cloud ecosystem that permits it to offer unique data products that lie far beyond simple execution and screen technology…and hence why it could potentially be a valuable acquisition target in the future, because the difficult groundwork has been laid.
After an initially slow M&A environment due to the Covid-19 outbreak, the market will start heating up if not in Q4, then certainly in 2021 as uncertainty abates. Firms wanting to improve their data analytics footing can either put in the work to build unique platforms and tools, or go down the path of acquisitions—but either way, the name of the game is cloud and data.
The same way that banks and asset managers now see themselves as technology providers, rather than hoary financial “Institutions” (the capitalized “I” being important), actual financial technology providers (the old-school version of the term FinTech) are viewing themselves more as data companies and not trading platform providers. Data. Is. God.
I know that some people will say that this has always been the case, but I don’t see it that way. I’ve been covering this space for 11 years, which is long enough not to be a prisoner of the moment, but it’s also not quite long enough to be counted as a true veteran. The fact is, though, the conversations being had by executives are much different than they were just over a decade ago.
To back up my point, let’s look at a couple of other firms that are not up for sale (as far as I know), but are making moves similar to Liquidnet and TT.
As I wrote previously, HPR (formerly Hyannis Port Research) made its name as a hardware provider, but as the company moves toward the cloud, it is prepping to launch Databot, a new appliance for market data distribution, which will be delivered initially as part of its part of its Omnibot switch for latency-sensitive trading firms to manage their market data flows. HPR will first go to market with its FPGA (hardware) implementation within Omnibot, but because Databot is built into Omnibot, which also serves as a router and pre-trade risk gateway, firms will eventually be able to purchase a software-based version of the appliance.
Tony Amicangioli, the company’s CEO, wants HPR to become a “one-stop-shop” for users in the low-latency trading space, rather than just a hardware provider. A one-stop-shop, of course, must include data.
“Historically, we haven’t been that interested in the data market because it’s been a crowded vendor space,” he said. “We now believe, though, that by providing leading performance and the completeness [of a service], it will allow our clients to achieve better performance, reliability, and efficiency.”
Additionally, while writing this column, I was reminded of SmartStream Technologies, which seems to be playing into this common theme that may just be in my imagination.
In September 2019, SmartStream launched Air, the firm’s cloud-native, AI-enabled reconciliations platform. The overall goal of the platform is to allow users to manage their reconciliation needs on an ad hoc basis, while simultaneously reducing reconciliations processing and configuration times.
As Max Bowie wrote this week, SmartStream is now planning to rewrite its entire solutions suite into cloud-native software so the vendor and its clients can exploit the cost and operational benefits of serverless cloud computing.
The vendor has already released cloud-native versions of its digital processing platform Aurora, in addition to Air, but now it is targeting other applications that comprise the SmartStream’s TLM suite of solutions, including corporate actions processing, collateral management, cash and liquidity management, and confirmations management.
Reconciliations, historically, has comprised people and hardware, but more and more, it looks like software and fewer people. But automation is not just about the process of completing mundane reconciliations; rather, it’s about harnessing that data in the cloud and incorporating AI to extract valuable insights. Two birds, one stone.
I could go on and on—look at what Confluence has planned after integrating StatPro; or what stalwart data provider Morningstar is doing with RoZetta Technology as it revamps its tick data delivery architecture into a cloud-based solution; or what MarkitSERV is doing with the launch of its ambitious cloud-based TradeServ platform—but the debate is now less about how much you’ve invested in your infrastructure and more about: what can you actually do with the data we’re giving you?
Or, maybe I’m just an incoherent old fool, sitting at the bar, connecting dots that are actually droplets of beer. As always, I enjoy hearing your thoughts: [email protected].
Quantum’s Slow Development
I realize that the above rambling lasted for 2,000+ words, so I’ll speed things up here. But, I would be remiss if I didn’t talk about one of my favorite topics: quantum computing.
Last Sunday I was away on mini-vacation, but we published a very deep-dive into the quantum computing space and how banks are experimenting with the nascent technology, but the story also showed how disillusionment with it is creeping into board rooms at a few banks. Or, as one head of digital at an investment bank told Luke Clancy, “It always feels like we’re two years away from a real quantum use case. The order of magnitude of the efficacy of the processing just wasn’t where everybody thought it would be.”
Or, take what Jezri Mohideen, global chief digital officer for Nomura’s wholesale business, had to say: “Two years ago, I was a lot more bullish, and I felt the evolution would come through a lot faster. Practical quantum computers can’t be used for a lot of tasks that we typically face in 98% of financial domain applications.”
In other words, banks might have no choice but to take a back seat and wait for this revolution to further unfold.
But it’s that last piece of what Mohideen had to say that I think is so important to keep in mind when talking about quantum, because it’s also why bank executives shouldn’t lose their stomach for experimentation too quickly.
Mohideen is absolutely correct—QC is not applicable for the vast majority of problems that banks and asset managers face today. But when you listen to quantum evangelists talk, they make it sound like it will solve every problem faced by every firm known to mankind—it’s similar in many ways to blockchain, except this hammer is looking for 10 trillion nails all at once.
As with any technology, though, you have to know the problem you’re looking to solve, and quantum computers are still in their infancy—this isn’t a tomorrow thing; it’s a decade-from-now thing…give or take a couple years.
On the most recent Waters Wavelength Podcast, I asked Bill Murphy what his thoughts are when it comes to quantum computing. Bill was Blackstone’s CTO for almost a decade before stepping down earlier this year, and has been a tech exec for over two decades. I’ve always enjoyed talking to him because he takes a very cold and honest look at tech development with a critical eye toward technical debt and tech sprawl. Here’s what he had to say about quantum:
“Most of the problems that we’re solving with technology today are not what quantum is good it. [Capital markets firms are worried about] connecting workflows and processes, and making things more efficient—those types of things. So I think that quantum computing can be revolutionary in the right circumstances, [but] sometimes the marketing is like, it’s going to change everything tomorrow, and that’s not really true. It could potentially change a few things a huge amount, and we should pay attention to that and take advantage of it, but it’s not the silver bullet to solve every technology problem.”
I think the key here, though, is for banks not to simply leave QC development to non-financial firms, because then when the revolution does arrive, it will take the industry longer to capitalize on new tools and use-cases, which is similar to what happened with more complex types of machine learning. Now’s the time for experimentation and understanding, but also honest conversations—quantum tools will be massively disruptive, but we’re also not anywhere near maturation, so everyone needs to curb their enthusiasm.
Image: “Marriage à la Mode: The Contract” by William Hogarth, courtesy of the Cleveland Museum of Art’s Open Access program.
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