Problem solvers: How Brevan Howard spin-out quant platform SIGTech is building a “data refinery” for hedge funds and asset managers
Spun out from Brevan Howard Asset Management in 2019, SIGTech is a London-based fintech company providing what founder and CEO Bin Ren (pictured) describes as a “next generation quant platform”.
In the two years since launch, the firm has steadily built an information evaluation, curation and analysis platform supporting data-driven, rule-based systematic investment processes for asset managers and hedge funds globally.
“We want to solve the technology and engineering problems for asset managers, hedge funds and asset owners who are repeatedly solving the same problems all by themselves, over and over again,” Ren says.
“We want to give them one solution so that they can get on with their job and focus on their secret sauce which is to manage money and generate good returns for their investors.”
As chief investment officer of the Systematic Investment Group at Alan Howard’s high-profile global macro hedge fund, Ren had originally developed the platform as Brevan Howard’s in-house system over the course of eight years before spinning out in 2019.
“In 2018, we realised there was a strong demand in the market for the technology that we had built. We decided to pivot the business from a quant fund management business to a fintech,” adds Ren, who was also CEO of crypto-focused Elwood Asset Management and, before his time at Brevan, was a partner and portfolio manager at Decura Group, focused on quantitative research and investment. He began his career at Barclays Capital as an equity exotics trader managing quantitative investment strategies.
“I have crossed over from being a trader and an investment manager to being a service and platform provider to buyside firms, and a lot of the people we have hired have similar experiences,” Ren observes of his career background. “And being a fintech, we look for people who have that rare combination of expertise in both finance and technology.”
The firm has gradually grown to more than 50 full-time employees over the past two years, and recently launched a US office, as well as securing a strategic partnership with IHS Markit.
“In the last nine months, we have been seeing double-digit growth in terms of sales pipeline, on a month-over-month basis, which is quite extraordinary, with major client wins in the US, Europe and Asia,” he says, pointing to a USD200 billion asset manager in the US, and a USD120 billion asset manager in Europe. “That demonstrates the size of our total addressable market.”
As technology continues to evolve at a breakneck speed, Ren believes digitisation is a broader, multi-decade, industry-wide trend that is fuelling the firm’s growth, as data has grown exponentially.
“What that means for investment managers is that they are being overwhelmed by the amount of data they have to analyse to help them make better decisions,” he adds.
“Raw data itself is a bit like crude oil. Without being processed in a refinery, it’s practically useless. Investment managers now are under tremendous pressure from things like fee compression; they need to justify their fees by showing they are doing a good job and generating alpha and beating the market consistently. So there is a strong demand for a “data refinery” among investment managers. That’s the role SIGTech is playing.”
He continues: “We take the raw data and provide state-of-the-art analytics tools, and then we allow the users – portfolio managers, traders – to be able to analyse data in one platform and extract actionable insights and turn those into their best investment decisions.”
Quantitative hedge funds have traditionally deep-mined historical data to fuel their investment systems. But the past 18 months have also demonstrated the critical importance of adapting and responding to new situations and new information. Ren says the Covid-19 pandemic has sharpened hedge funds’ and asset managers’ focus on the crucial need to upgrade their technology stack in order to do their job better.
“Quant funds, or any fund that conducts a data-driven, rule-based investment process, almost by definition is using historical data to look for patterns, which, in financial markets, do tend to repeat themselves. But Covid was unprecedented – it caught a lot of people off-guard,” he remarks.
“One exciting development that has emerged from that is the concept of ‘nowcasting’. Before, everybody was doing forecasting. Nowcasting is not about forecasting things, but using data to measure certain metrics at a much higher frequency.
“It’s not a new concept, but up until recently it’s only used as an essential tool for a select few elite fund managers.”
He points to the example of GDP figures, which are typically subject to several months delay. Nowcasting, by contrast, allows users to analyse certain alternative datasets on a weekly or even daily basis to better estimate GDP growth.
“It gives that trader or that firm a much more timely view, an almost real-time view of what’s going on in the world and, therefore, an edge,” he explains.
Social media is another major example of how alternative data can shape investment performance, Ren says. The co-ordinated short squeezes on stocks such as GameStop and AMC that played out on Reddit’s r/WallStreetBets discussion board showed just how costly a lack of analysis of certain alternative data sets can be for managers.
“Many long/short strategies had a tough time because they were not monitoring the information on social media, and were essentially missing a huge piece of the puzzle when they were making those investment decisions,” he says. “Social media over the years has become a higher frequency source of news. This ties in with the concept of nowcasting – social media is an essential source of information.”
Looking ahead, the firm is looking to strengthen its US presence over the next 12-18 months, and Ren says a major aim is to further broaden its curated dataset offering. The firm also works closely with its affiliate, Coremont LLP, to provide a high-tech operating infrastructure for investment managers in the face of increased electrification of markets.
Building on this point, he says there are four basic problems that SIGTech aims to solve for its clients.
The first challenge centres around time to market. “If you build this kind of technology stack in-house, and then launch a new investment strategy and try to attract new investors, that’s an expensive two- to three-year process,” he notes. “Our users can do truly cross-asset strategies within a few weeks.”
The second point relates to curated data. “Data does not equate to information - there is a lot of noise,” he says. “So we do a lot of processing of data – cleaning, evaluating and curation – so that the clients can have a reasonable degree of confidence that it will be helpful, and not be just pure noise.”
The third part is developing trustworthy and efficient backtests.
“There’s a running joke in this industry that there is no such thing as a bad backtest. Every single one is amazing and makes money,” he observes. “But there are many mistakes that occur that make many backtests over-optimised, and therefore do not represent any realistic expectation. We aim to provide assurance that our users’ backtests are likely to be correct.”
The last step is the production stage. Ren says SIGTech strives to help clients successfully deploy their strategies from the research environment stage to a real-life product environment where their trades can be executed on exchanges using investor capital, while still ensuring the two environments are consistent.
“It’s not a trivial job, and we try to make that experience seamless,” he continues. “Our users can deploy trading strategies with one click into production and start trading. That has proven a huge time-saver for our clients.”