Prop Shop Culture: Tyler Capital's Chris Donnan

Tyler Capital's CTO Chris Donnan explains the importance of culture and its focus on machine learning.

chris-donnan-tyler
Chris Donnan, Tyler Capital

Two years after leaving Barclays for London proprietary trading firm Tyler Capital, CTO Chris Donnan talks to John Brazier about the firm’s attitudes toward, and advances in, machine learning, the importance of getting the right culture in place to achieve its objectives in a changing marketplace, and why he is “more here” than ever. Photos by Jonathan Goldberg

At first, there doesn’t seem to be anything out of the ordinary at Tyler Capital’s offices: meeting rooms, banks of desks piled high with various screens, multiple televisions mounted on the walls, each streaming a different news channel. It’s everything you would expect to find at a proprietary trading firm on a Monday afternoon.

Then you notice the little things, barely noteworthy on their own, but which, when taken together, provide a different perspective on the way things are done here. The size of the open-plan kitchen shows that this isn’t just somewhere to make tea, but an informal meeting place, complete with foosball table and a stack of Xbox games in the corner. The roof terrace is dotted with benches and plants, and then you realize there’s also a miniature putting course neatly laid out. Once the complete picture comes into view, it’s clear that at Tyler Capital, culture is just as important as its technology focus. 

CTO Chris Donnan, who joined the firm in September 2014 after a four-year stint at Barclays, jokes that the firm has an almost extreme “no jerks” rule that ensures the various teams are able to work as a streamlined collective. For a small prop shop like Tyler Capital, that collective culture can make all the difference, not just to its financial success, but to attracting the kinds of people that are able to facilitate the firm’s momentum.

Tyler Capital has a headcount of 75, spread between its London headquarters and its Singapore office, which opened in 2014 and provides a gateway to the Australian market, allowing the firm to best use its resources to compete against its larger counterparts. “The feeling of community is not like any place that I have ever been, but that is also hard to preserve—it takes a challenging moment to actually test competence and character,” Donnan explains. “We really are orienting the company as a system in and of itself, to help us achieve that focus, from the leadership team straight through to all the people doing that work. At a company our size, it is possible to do that.”

Tech Beginnings

“Agile often winds up being something that happens in a software team or two—we are a different thing, and all of the people here are part of that thing. We want to make the organization a system to achieve our objectives, and I don’t mean just technology, I mean everybody. Agile has parts of that and lean is also a part of that, but these tend to be much more technology-focused.”

Established in 2003 by James Tyler, Tyler Capital has always had its roots in technology-based operations in large-dollar trades and short-term interest-rate products. Previously, the technology investments at the firm were more trader-centric, providing the necessary front-office platform and features, but current iterations of the organization have become more systematic in nature, partly because of the wider range of equipment and technology expertise required.

Donnan was tapped from his previous position at Barclays as head of the bank’s equities electronic trading technologies to help further the firm’s strategy and build out its technology team. Alongside new CEO Michael Bushore, Donnan was recruited to take the firm’s technology infrastructure to the next level.

“What the firm needed was a way to sort out its data story; we needed to bring technology to the leadership table, essentially, as opposed to it being a cost center,” he says. “It is important to have that senior input into how that is really going to make a difference. So getting somebody on board who knew how to do the systematic trading technology thing was actually critical for them.”

The first part of that work began as what Donnan describes as a “clean-up” phase to get both the organization and its technology tools oriented, followed by a period of “setting up” in two key areas: “One was on data and getting a significant data platform in place, and the second was on getting a high-performance single trading platform, to execute all of our activities in a more homogeneous way on top,” Donnan says.

Now, Tyler Capital has moved into its “build-up” phase, according to Donnan. While there is still much focus given to the firm’s underlying technology stack, especially with respect to its machine-learning capabilities, equal prominence is given to ensuring that the organization as a whole is working toward the same, clearly-defined objective—moving fast enough to establish Tyler Capital as a dominant player in automated trading systems predominately driven by machine learning.

It’s all a far cry from Donnan’s time at Barclays, building out the electronic equities business at a multi-national bank, and there is the genuine conviction that it’s a much better fit for both Donnan and Tyler Capital. “It’s a rare moment when you get a team of people who actually are at that right place for them and at the right place for the company—it is very liberating,” Donnan says. “The many people on the technology team who were already here are also in the right place, they just needed amplification, in essence, by bringing in a few other guys here who had experience working on big systematic trading strategies and engines.”

Culture into Process

Placing such an emphasis on the working culture is commendable, yet to reap any tangible benefits there also needs to be a defined pathway for the results to feed into the working process. Having a staff the size of Tyler Capital’s means it’s easier to direct its collective efforts, according to Donnan, who says trust and camaraderie can be lacking in larger, sell-side organizations where both personal and enterprise-wide politics can slow the process down. Many firms of a similar size to Tyler Capital utilize agile methodologies in their development projects; however, Donnan highlights a critical difference between this deployment strategy and the way Tyler Capital approaches its process.

“Agile often winds up being something that happens in a software team or two—we are a different thing, and all of the people here are part of that thing,” he explains. “We want to make the organization a system to achieve our objectives, and I don’t mean just technology, I mean everybody. Agile has parts of that and lean is also a part of that, but these tend to be much more technology-focused.”

The aim of all this goes back to Tyler Capital’s primary objective: to become a dominant force in machine-learning-driven automated trading systems, which is no mean feat.

Donnan takes inspiration from some of the multinational technology giants across the world—Facebook, Google and Alibaba—and the way these firms center on an open-minded technology base, fully utilizing different bodies of talent. It’s similar to the process at Tyler Capital where the objective is to orchestrate the firm’s activities in a horizontal fashion, as opposed to the more vertically oriented businesses that operate in the same space, such as larger hedge funds that have the resources to bring in a number of machine-learning specialists.

“It is about how we conceive the entire thing as a system, and that goes back to how prop-trading firms are going to be challenged going forward for all kinds of reasons. They have all kinds of petty disincentives where there are independent silos in and among themselves,” Donnan says.

Regulation is, unsurprisingly, one of those challenges. The same goes for the firm’s data process; asset managers across the buy side are having varying degrees of success with data management projects and the resulting intelligence gleaned off the back of such initiatives. 

“If I have large quantities of data all over the place and I can’t make sense of it, it’s just giving me a hard time,” explains Donnan. “So the opportunity is about us being able to monetize an ever-increasing body of data in the financial markets where we are regulated to participate.”

Artificial Intelligence

The changing nature of proprietary trading that Donnan highlights has brought with it opportunity for firms like Tyler Capital—not, say, breaking into new product areas such as equities, but harnessing its talents in managing data processes and filtering through into its machine-learning capacities. This is where the horizontal orientation Donnan speaks of comes into play. The firm considers people, processes and products—the automated trading strategies, or the “fruit of our labor”—to be equally important, according to Donnan.

While he says the process is kind of a boring word, he underlines just how important it is to ensuring that everyone at the firm is moving toward the same point. “In a jazz band, the drummer is the process guy, he keeps everything focused, but it provides all this space for people to work within, the cadence and a framework,” Donnan says.

This cadence and framework has allowed Tyler Capital to explore and expand its capacity for machine learning as the primary driver of its trading strategy. Almost all of the firm’s technology stack is proprietary in nature, supporting its entirely machine-learning-driven trading strategy that has been in operation for over a year. According to Donnan, taking an off-the-shelf machine-learning model and plugging it into generic data sources simply doesn’t work because it’s too readily available, although by the same token, he recognizes the challenge involved when it comes to understanding how the markets are moving and getting the data right first.

“The industry will be all the more dominated by technological players using machine learning as a device to continue to compete,” says Donnan. “We compete on intelligence in these markets, and automating the acquisition of intelligence and automating systems that embody this intelligence.”

The machine-learning fundamentals at Tyler Capital will be expanded further over time, as the “gentrification” of the firm’s more traditional quantitative and systematic trading strategies means new pieces of tech will be plugged into the system, making it both more powerful and more responsive to market developments.

It’s an area of technological development that Donnan has been following for some time. While large swaths of the capital markets are now starting to get serious about its application though hefty investments and development initiatives, Donnan was working on machine-learning projects over a decade ago with Jeffrey Katz, an American scientist, artificial intelligence specialist and author of The Encyclopaedia of Trading Strategies.

Partly due to the fact that this was back in 2003 and 2004, some of what Donnan and Katz were working on resulted in the realization that computers would have to become substantially more powerful in order to achieve the possibilities presented by artificial intelligence. That might sound overly simplified, but while machine learning has become one of the standout areas of focus for the buy side this year, few firms have been able to move with enough speed and conviction in the technology to pull ahead of the competition.

Donnan acknowledges the hyperbole surrounding machine learning and states that this is a cyclical occurrence, one that is again happening now with technologies including machine learning and distributed ledgers. While Tyler Capital has made a sizeable investment of time and resources into machine learning, it comes as part of the over-arching organizational strategy. “The business model is something that you can be disruptive on,” says Donnan. “It’s very hard to cherry pick the next super-disruptive technology.”

Transatlantic

Prior to his time at Barclays, Donnan served a stint at London-based hedge fund Polygon Investment Partners, crossing the Atlantic permanently shortly after the financial crisis as part of the firm’s event-driven trading desk, which saw him involved in a number of different tech-based projects. 

Following a period of restructuring at Polygon where Donnan found himself sitting on his hands much of the time, the opportunity to join Barclays in January 2010 was too good to pass up. He became an integral part of the bank’s equities business, which was in the process of getting off the ground, developing its trading technology strategy, first in Europe, and then on a global basis.

“The idea of actually orienting everybody to point in the same direction and allowing the teams to have focus on really making the material things happen has been an important lesson learned,” Donnan says of his time at Barclays. “I have been in plenty of other organizations where there is too much short-termism and you can’t complete what you are already on. You really need that senior leadership to keep everybody focused. The same was required in Barclays building out the equities business—you can’t be dragged around by your nose when you are trying to take an equities business from non-existent to existing.”

While Donnan was handed what he calls a great remit and great team to work with, there was also a lot of volatility due to the fallout following the acquisition of Lehman Brothers, which culminated in September 2014 with a fine of $15 million from the Securities and Exchange Commission (SEC) over the bank’s failure to maintain an adequate internal compliance system. It was around that time that Donnan first acquainted himself with the Tyler Capital leadership team, and after a number of meetings, was persuaded to move across to the buy side.

Donnan describes his move to London with his family as an adventure and an educational opportunity for his young sons. It also seems fitting for him to be in a smaller, more focused buy-side organization, as opposed to a sprawling institutional bank, where he can be a little closer to both the team and the technology. 

A keen music fan, Donnan compares it to programming as a form of abstract creation and the emphasis on culture that pervades Tyler Capital facilitates what Donnan describes as a feeling of being “more here” than he could be anywhere else. “It’s been two years here for me now, and if I thought I was making a good choice at the time, it has been off-the-charts better than what I expected,” he says. 

Chris Donnan Fundamental Data

Name: Chris Donnan

Title: CTO, Tyler Capital

Education: Audio Engineering

Hobbies/Interests: Programming, reading anything and everything, music, hiking/nature, travel, spending time with family

Biggest Career Achievement: Putting together the current team at Tyler Capital and building its latest trading platform, Omega

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