Cutting through the noise
This article first appeared in the April 2023 Technology Insights Report
Hedge funds’ use of and need for alternative data continues to increase. Today, the problem is less about how to get enough, and more about how to manage what you have – and extract value.
The spread of data into hedge fund managers’ investment process – driven by an accumulation of investment opportunities, reporting requirements, and technological advancements – continues to accelerate.
In the run up to next year’s switch from T+2 to T+1 for US equities, a recent study by Gresham Technologies found that 90% of global hedge funds, asset managers, and fund administrators had increased their number of external data feeds in the past 12 months.
Hedgeweek’s own research suggests hedge funds’ use of big data as a driver of performance alpha is currently more visible than the use of artificial intelligence (AI). While quant managers are inevitably the biggest users, close to 40% of traditional discretionary managers now employ data in their investment process, with that number rising to 57% among tech-savvy discretionary firms.
Data’s ability to deliver tangible performance alpha was brought into sharp focus last year when Citadel weaved complex weather pattern information into a series of successful trades in commodities markets, helping to push profits at Ken Griffin’s long-running hedge fund giant towards $16 billion.
Yet, having access to data is not enough. In 2023, the bigger challenge is homing in on what you need. More than half the portfolio managers and investment analysts surveyed by fintech firm Exabel recently said ‘too much’ alternative data and difficulties prioritising it was the biggest hurdle to extracting value.
For tier one hedge fund firms – where the problems are idiosyncratic, and the resources are plenty – this has usually meant creating new capabilities inhouse.
The likes of Citadel, Millennium Management, Point72, and Man Group have built large teams of engineers, data scientists, and analysts, and combined them with sophisticated tech infrastructure to turn sizable volumes of raw data into investment outperformance.
Speaking at Hedgeweek’s Technology Summit in 2021, Mark Brubaker, Point72’s CTO, said: “Very rarely is there something that’s out-of-the-box and adds value. In many cases, where that does exist, then the alpha is already gone.”
Framing the problem
Man Group was required to look in-house to create the technology needed to cope with “the ever-increasing amount of data and complexity of front-office research,” says Man Alpha Technology CTO Gary Collier of the firm’s new database management tool, ArcticDB.
“Ten years ago, when we first started work on ArcticDB, the data problem space was more focused on time series data. In practical terms, this meant that data frames – the primary method for organising data and a very natural way for data scientists to think – were very long and very narrow,” Collier explains. “Within AHL, we had a growing need for something that could scale horizontally in a way that was a challenge for the third-party vendor solutions we were using at the time.”
Today, the data frames being used at many investment management firms are vast in both width and length. For reference, Collier says quantitative analysis of a contemporary corporate bond universe might require a data frame 500,000 columns wide and millions – even billions – rows deep.
Ultimately, Collier believes investment professionals can benefit from having access to as much data as possible – the challenge they face is managing that data, determining what’s valuable and extracting that value. “There’s a finite set of truths about financial assets and the more relevant data you have and can process effectively, you can get incrementally closer to understanding what those fundamental truths are, which in turn helps you understand how a particular asset might behave in future”
In 2023, consumer spending data is one such ‘asset’ being explored by fund managers, with 76% saying it will provide an ‘outsized’ information edge in the near future, according to Exabel research.
“If you are a hedge fund who has consumer or retail names in your portfolio, for example, it is verging on irresponsible not to have access to the kind of transaction data that can give you early insights,” says Exabel CEO Neil Chapman. “If you don’t have it, then you’re taking on a significant risk on behalf of your investors.”
Digitising credit markets
Among traditional bottom-up strategies, Hedgeweek’s manager survey suggests clear fault lines over tech take-up remain. While 38% of discretionary managers now use big data in their investment strategy – the top score for the three technologies covered here – a greater proportion said they had no plans to).
Industry participants note that certain fundamental strategies, particularly equity-focused funds and the more illiquid credit portfolios comprising stressed and distressed space, are less readily applicable to data-heavy trading.
In the credit markets – where swathes of the information flow remain in the analogue age – vendors are looking to provide hedge fund clients with a timely edge as new opportunities emerge in both public and private spheres.
“Many hedge fund managers seeking bigger returns are looking beyond equities at other interesting asset classes, such as loans and private debt,” says Aani Nerlekar, Senior Director, Solutions Management and Consulting at SS&C Advent. “The collapse of Silicon Valley Bank – and the ripples of related events throughout the bond markets – could further fuel this trend.”
As Nerlekar notes, the credit market has historically been underserved by automation and technology, with the flow of loans and credit agreements in PDFs, emails and even faxes. “The next step for our industry – and where we are focused – is automating and digitising agent notices into actionable data delivered to an investor or a manager’s downstream systems.”
Hedgeweek expects few hedge fund firms to resist the advantages of – and developments around – big data for long. In part, because of the edge it is providing an increasing number of their competitors. But also, because addressing it today, will help minimise issues in the future.
As Man Alpha’s Collier says, data is constantly evolving, so the problems facing managers are always evolving, too. “If you’re in the business of dealing with problems, you’re in the business of dealing with data – and you need technology that can help your process that data and extract value as efficiently as possible.”