Goldman’s Quant Fund Clients Will See “Massive Speed Improvement” After $100M Trading System Upgrade
In an interview with CNBC, Goldman Sachs’ CTO of electronic trading revealed that the investment bank has committed to investing $100 million to overhaul its stock trading platform to make it more appealing to the biggest quant funds like Renaissance Technologies and Two Sigma, who are among the bank’s “most demanding clients from a technology perspective.”
While Mike Blum, the Goldman quant CTO, didn’t offer any specifics about what he bank’s “Project Atlas” will entail, at a time when banks’ trading revenue is shrinking, eliciting layoffs for hundreds of human traders, the biggest banks will be battling one another for a bigger piece of a shrinking pie, as more equity trading – and even some credit trading – shifts to high-frequency players who rely on algorithms to place orders at speeds that human traders couldn’t possibly detect.
The big quant funds are among Goldman’s “most demanding” clients, Blum said. And the bank is revising its equity trading platform with their needs at the forefront. The bank is competing with JPM and Morgan Stanley.
“With this investment we’re trying to tackle the quantitative hedge fund space and do so front-to-back to create a seamless experience for our clients, and just try to get as efficient as they are at doing their jobs,” said Blum, a 25-year electronic trading veteran who joined Goldman in 2017.
As CNBC points out, the three banks mentioned above have made $11.4 billion in stock trading revenue so far this year, which is 14% lower than in 2018.
With “Atlas”, Goldman is targeting a group of more than a dozen of the most sophisticated quant funds by focusing on a range of different trading styles. The bank believes that, if it can satisfy this group of clients, it can satisfy any type of hedge fund or asset manager. The upgrades will allow these funds to trade at speeds measured in microseconds in more than 32 markets around the world, while also extending this speed to other functions like clearing and settling trades, allocating stock, lending shares, and trade reporting.
“As we learned the quantitative client base and what their demands and needs were, we decided to take the technology and basically turned it into a framework that can be used to solve lots of different problems,” Blum said.
One of the project’s goals was to improve the firm’s performance on trade orders that can last for a microsecond – a millionth of a second – to about 30 seconds. Trades that once took hundreds of milliseconds (thousands of a second) will soon be executed in less than 100 microseconds. The platform will also improve the time it takes for the bank to digest floods of orders that sometimes emanate from certain quant firms.
The bank has also brought in more quants to rewrite its algorithms and improve “quality of execution.”
“As we roll it out globally, they should absolutely see a massive speed improvement,” Blum said. “They should see quality of execution go up, not just because of speed, but we’re completely rewriting our algorithms, we’ve brought in more researchers, more quants to improve our algos.”
In other words, Goldman will soon be able to offer these quant clients an edge over the competition: Faster execution means clients will effectively be able to more easily front run their rivals orders (in a way that’s totally legal) – and it’s difficult to put a price on that.
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