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‘Information overload’: Making sense of the crowded data landscape

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The use of data within the hedge fund industry has grown exponentially over the past decade, with fund managers from across the spectrum increasingly turning to ever-more complex datasets in a bid to stay ahead of the competition.

The use of data within the hedge fund industry has grown exponentially over the past decade, with fund managers from across the spectrum increasingly turning to ever-more complex datasets in a bid to stay ahead of the competition.

Speakers at this year’s hedgeweekLIVE European Emerging Managers Summit, which took place at the Reform Club in London, discussed how fledgling funds can most effectively use, store and interrogate data in an increasingly crowded information landscape.

Moderating the discussion, Evan Lubin, director of EMEA at Sentieo, said a major challenge for managers right now is trying to pin down what is “value additive” about certain datasets.

“The challenge is that it is overwhelming – there is so much data available, there are so many large datasets and different inputs,” said Phillip Chapple, COO at Monterone Partners, who explained that his firm looks to zero in on what data may ultimately strengthen its position-building process.

“It is so easy to head down so many rabbit holes and spend lots of time and money on data that may not be additive,” Chapple explained, adding that as a fundamental equity-focused manager, his firm tends to use data as part of an investment thesis on a particular position, rather than looking to identify trends.
“We always look at very specific data related to specific investments,” he explained.

For Tillman Sachs, CIO and Head of Research, CEO and founder of managed futures fund J8 Capital Management, data inputs are key for its trading models, which typically lean on long-dated futures data to seek out trends in markets.

Reflecting on his strategy’s use of data providers, Sachs commented: “Data is of course super-important, because that is the basis on which we build everything. You have to invest, but it’s easy to spend money on enormous amounts of data you don’t need. When you are an emerging manager, you want to keep costs as low and as economical as possible.”

The discussion weighed up best practices in terms of data use and storage, as well as the pitfalls of selecting data vendors, and heard how the two contrasting strategies typically approach the use of data in their respective investment models, and effectively sift through the sheer volume of information available. 

Both Sachs and Chapple acknowledged that the recent data explosion continues to prove challenging, and cautioned that incomplete datasets can ultimately prove misleading – and expensive – for managers.

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