Nasdaq Lays Out Future as ‘True Source' of Data in WFIC Speech

Speaking to Inside Market Data after her keynote speech, Friedman called automated investing─where firms use machines, machine-learning and other automated processes to make investment decisions─the future of investment, and described Nasdaq's aspirations to be a "true source" of information, in response to the growth in this area.

Friedman describes Nasdaq as the "gold" source for the exchange's market data, meaning that the exchange is the original creator of the data. However, the exchange is also building up its range of "silver" sources, where Nasdaq takes data from other gold sources and performs analytics to create new types of information. One example is smart beta indexes, where index calculators such as Nasdaq take in data such as volatility, dividend payouts, cash flows, book values, or technical metrics to determine which assets to include in each index, as opposed to the traditional market capitalization approach.

Nasdaq is seeking to be a neutral distribution channel for these silver sources of data, and will be agnostic to any subscriber or vendor, Friedman says. "We are aiming to provide credible sources of information that have been verified, along with our own gold source of information," she adds.

In addition, Nasdaq is attempting to make both structured and unstructured gold and silver source data available in machine-readable formats, so that they can be used by automated investors. According to Friedman, $500 billion in assets under management is linked to smart beta indexes, and automated investment is growing at 20 percent year-on-year versus passive investing, which is growing at just over half that rate.

Friedman says that until now, there has been little widespread use specifically of these machine-learning-based datasets and analytics, but says she expects that once the capital markets begin using it, this data has the potential to deliver profits. Nasdaq's role in this new era of automated investment based on machine-learning-derived data will be as a source of intelligence with the mechanisms to provide that intelligence directly into firms' investment models, she adds.