Gaining the edge
In a race to glean fresh insights from ever larger pools of data, asset managers are deploying powerful new tools to gain an edge over their rivals.
To craft their trading decisions, quantitative fund managers are increasingly using so-called “nowcasting” techniques. This is the art of using real-time data to spot emerging economic trends well before they are picked up by regular official reports on GDP growth, inflation, employment, etc.
But all of this requires sophisticated technology to ensure big data sets can be harnessed, crunched and analysed fast using cutting edge techniques to drive real value for investors, says Angana Jacob (pictured), head of product management at SigTech, a specialist in cloud-based quant technologies for asset managers.
“Nowcasting tells you what is going on in the economy without having to wait for a public release,” she says. “There are so many different data sources: traffic, footfall, shipping, cargo boats, trade patterns... It’s a lot of data and some is exhaust data, in the sense that it is derived from other industries, or from consumers doing transactions. It’s often underutilised.”
Data management is key
Handling, storing and then drawing useful insights from vast amounts of this kind of raw data presents big challenges.
“There is of course excitement about alpha and extracting insights, but before you get to that stage, the foundational data management architecture has to be pretty robust,” says Jacob.
“It is challenging because of the size and heterogeneity of the data sets. It’s not the traditional megabytes, but terabytes and petabytes – and also how the data comes in.”
She continues: “There are so many multiple sources and the data itself is complex. So there›s a need for robust data processing and harmonisation, before you can think of deriving any kind of insight or conclusion. And then you also want the entire process of analysing multiple datasets to be replicable, otherwise it is challenging to do at scale.’
Spun off from hedge fund Brevan Howard in 2019, SigTech specialises in this kind of technology and offers its own analytics platform to hedge funds and other asset managers.
Jacob says: “It’s an end-to-end platform from data to research analytics, and then to deploying trading strategies live.”
SigTech’s technology is now being used by fund managers with up to USD454 billion in assets under management, including Alliance Bernstein and GAM.
SigTech’s unique expertise lies in its prowess at backtesting – assessing the viability of a trading strategy by discovering how effective it would be using historical data while guarding against “overfitting”.
Jacob claims the system is “nuanced, accurate and as realistic as possible”.
She says: “So what we offer to clients is that, rather than multiple disparate systems working not very harmoniously together, we provide a single cross-asset system & quant functionality and we integrate with clients’ execution systems as well as other data sources.”
The steady growth of cloud computing is allowing quant funds to access increasingly powerful systems to store and analyse the big data sets on which they depend.
“Cloud of course enables this large amount of data because you can easily deploy multiple virtual machines. You can spin up your cluster of servers, and then you can do all your deep learning models pretty easily. It’s highly scalable.”
It’s a trend that looks set to continue.
Angana Jacob, Head of Product Management, SigTech
Angana Jacob is Head of Product Management at SigTech. Prior to joining, Angana spent more than a decade in indices and quantitative strategies at Deutsche Bank, S&P Dow Jones Indices and State Street. Her roles have spanned research, development and marketing across asset classes as well as building out State Street’s ESG analytics. Angana has a degree in Computer Science from Madras University and an MBA from IIM Ahmedabad.