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Data Science Platforms Help the Buy Side Integrate Alternative Data

Traders Magazine Online News, October 10, 2018

Ivy Schmerken

Asset managers are looking for ways to mine alternative data sets for investment ideas, recognizing that stock pickers cannot rely on traditional research.

An explosion in alternative data, ranging from satellite images to mobile geolocation data and unstructured text, has created an arms race among hedge funds and quantitative funds. Many firms have hired data scientists to dive into pools of data and to use machine learning algorithms to extract insights or predictive signals. Traditional buy-side firms are also eyeing big data sets while wrestling with how to incorporate them into the investment process.

“Alt data is starting to become a little more mainstream in that asset managers realize they need to find new sources of alpha to gain an edge,” said Bill Stephenson, managing director of AIR Summit, a conference that was held Sept. 5-6 in New York City.

The two-day event, which stands for Alpha Innovation Required, focused on facilitating discussions on challenging and innovative trends impacting the institutional investment management industry, especially active managers. AIR Summit 4.0 enabled buy-side firms to connect with startups in the “alpha technology” or alpha tech space.

This year, 20 startups presented at AIR Summit 4.0 out of 400 candidates. On average, companies presenting were in business for four years with 14 hailing from New York, five from London, and one from Vancouver.

For example, Predata, a predictive analytics company, identifies online shifts in human behavior and anticipates global events through machine learning and alternative data. “It turns metadata into insights,” said Hazem Dawani, CEO, adding that “metadata is language agnostic across the world whether it’s in English, Swahili or German.”  Predata collects meta data daily from tens of thousands of web sources, and then organizes the data into categories within countries and on topics related to security, social and political unrest, and economics.

When the Trump Administration in April of 2018 imposed unexpectedly harsh sanctions on Russia, the ruble dropped more than 8% over four days. Predata had signals predicting the possibility of new US sanctions and these signals peaked six days ahead of the currency’s move.  Customers receive early warnings on average 14 days in advance of events.

Recent signals included perceived risks that the NAFTA negotiation will fail.  On Sept. 18, it produced a US midterm signal observer about online activity on issues related to the November elections.

“Geopolitical risk moves financial markets and most of the time this is not priced into the currencies or the assets,” said Dawani, whose customers include government agencies, global macro risk managers, hedge funds and prop traders.

Increasing pressure from low-cost index funds has been cited as a factor in the buy-side’s search for an edge in alt data.

“It seems to me there is going to be this massive disruption in the coming years, significant consolidation, clear winners and losers in our business,” said Stephenson.  “I think there’s an opportunity to reinvent our business,” asserts Stephenson.

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