Nasdaq has begun to search for sources of alternative data found in Asia to add to its global business of developing products for investors.
Tomas Franczyk, the exchange’s regional managing director and head of global information services, says fintechs, quant funds, hedge funds and traditional buy sides all want to find alpha (outperform the market) using data.
Nasdaq has a big business already in using the core asset-class data it produces, which it sells to trading desks, media and redistributors such as Bloomberg and Refinitiv.
For the past few years, Nasdaq’s data strategy for this region has been to provide its information on U.S. equities and indexes to Hong Kong or mainland China-based fintechs, brokers, Big Tech companies, media, and other users.
But now the strategy is changing, as Nasdaq seeks to allow analytics on alternative data. “We find sources in the market to help firms make more data-driven investments,” Franczyk said.
Last year Nasdaq acquired Canadian alt-data firm Quandl, and part of Franczyk’s work is to identify data sets for Quandl as well as for Nasdaq itself.
“They [Quandl] seek the same thing in Asia as what they look for in North America,” he said. “They want data from local firms to build investment models.” This could come from e-commerce sites, insurance companies, or telecom companies.
For example, in the U.S., Quandle partners with big insurance companies to access policies on new car purchases, to accurately report on car sales before auto manufacturers do.
“Hedge funds want effective tools that generate alpha,” Franczyk said, “be it the raw data or, for those that may not know how best to use it, a more tailored product idea.”
Although the biggest demand remains in the U.S., particularly among funds trading China A-shares, Franczyk says Japan and Singapore also boast investors and fintechs keen to use alt data.
Franczyk says the alternative-data industry is becoming huge. He says it will become a $5 billion industry in the next few years. That means there is also scale for niche players like Quandl as well as for purveyors of core data such as Nasdaq.
But finding data that can be packaged and sold is difficult. “Some firms don’t now how to monetize the data they have,” Franczyk said. And the firm stays away from personal, private information. Some countries’ data-localization laws can also be a barrier to commercialization.
So far, as he goes market by market, he hasn’t yet built an Asia-specific data product. He is open to partnering with local fintechs or others that have core data that could migrate to the Quandl platform, such as earnings estimates or analyst ratings.
The biggest challenge is simply finding sets of data that are unique and can help investors make money. Often it lacks enough volume, or the quality is poor, or the information isn’t unique.
“Maybe one source out of ten works out,” Franczyk said.
