Alternative data providers see huge potential in providing their data to discretionary asset managers who are losing assets to quantitative and systematic funds.
As active managers trail the performance of passive index funds and ETFs, discretionary fund managers are scrambling to consume big data analytics in their decision-making processes.
While early movers in the big data analytics industry have mainly been quant hedge funds and systematic fund managers, the next wave is going to be discretionary fund managers, according to panelists at an event sponsored by Wall Street Horizon, Estimize, OTAS Technologies and FlexTrade Systems.
While big data is a nebulous term, perceptions are also shifting around what constitutes alternative data. “There have been a bunch of data sets sitting out there but no one thought of them as data,” said Jha. News analytics and social media analytics companies are turning text from 10Qs and 10K filings and earning call transcriptions into data that computers understand. That means turning this data into sentiment. “Fundamental investors have been using this data for years, but this is alternative data for quants,” said Jha.
Even some of the older data, such as earnings estimates, has been optimized and is now perceived as alt data. “Our data is the quintessential example of an old data set, an earnings calendar,” said Barry Star, Wall Street Horizon’s founder and CEO. “We reinvented it,” said Starr. “Individually the events that we track could be considered old alpha, but people are constantly coming up with new ways to utilize the data,” he said. Take the case of date breaks— if the earnings date for a company moves from Monday to Thursday there’s all kinds of information involved in how many days the date moved. Does it move forward? Does it move backward? There is alpha all over that information,” Starr said.
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