Clients often ask me why we named our company SigTech.
I explain the first part of our name has two origins: “Sig” is short for signals. We are in the business of providing technology so investors can find signals in the market.
It is also a nod to our history: “SIG” was the acronym for Systematic Investment Group, the team I led when I worked at the hedge fund Brevan Howard.
When “Sig” is combined with “Tech” it explains our mission: to provide leading technology to help investors distinguish “signals” from the “noise”.
The idea of the business was first conceived while I was hiking Inca trails to reach Machu Picchu in late 2017.
In 2019, we officially started out offering services to buy-side portfolio managers at hedge funds, pension funds, and sovereign wealth funds. We are now expanding that effort by leveraging generative AI to make those advanced decision-making tools available to anyone in capital markets.
I’m passionate about democratizing access to data and information in part because I came to the world of finance unexpectedly.
After completing my undergraduate degree in electrical and electronics engineering at China’s Shanghai Jiaotong University in 2003, I began doctoral studies in computer science at the University of Cambridge.
That gave me the opportunity to help research and develop Xen, the virtual machine monitor that ushered in the era of cloud computing when it enabled Amazon to build AWS.
In 2007, after my PhD studies, I went to work at Barclays Capital in quantitative investment strategy trading, and in 2015, Brevan Howard where I later became the chief investment officer running the Systematic Investment Group.
Brevan Howard puts an emphasis on intellectual honesty. The culture encourages employees to analyze trades to determine how much of our success was due to luck versus skill. In the past two decades, the firm has generated over $30 billion in returns for investors.
In February 2019, Brevan Howard spun off SigTech as a fintech business supporting other firms making data-driven investments.
This process of distilling data into signals is challenging. You must overcome a high degree of background noise in the data. But this distillation is core to the investment process.
Once you find a signal, you need to determine if it will accurately predict an outcome significantly better than the market. You also have to decide if you can structure trades to monetize your prediction so that your upside is greater than the downside.
Solving those problems is where generative AI comes in, and it’s a game-changer.
At SigTech we expect the technology we are building to change how decisions are made in capital markets.