Predictive Analytics Times
Predictive Analytics Times

1 year ago
Wise Practitioner – Predictive Analytics Interview Series: Stephen Morse, Advisor at Neudata


In anticipation of his upcoming conference presentation, Leveraging Alternative Data Sources to Gain a Critical Competitive Advantage at Predictive Analytics World for Financial in New York, Oct 29-Nov 2, 2017, we asked Stephen Morse, Adviser at Neudata, a few questions about his work in predictive analytics.

Q: Can you briefly introduce yourself and your organization.

A:  I’m a consultant and advisor in the areas of FinTech, AI and Big Data. I work with disruptive businesses in these three domains, where of course there’s a ton of exciting things going on. One such firm is Neudata, a firm specializing in Alternative Data discovery and intelligence. We work with investment managers in finding new, novel data sources that are most promising for alpha generation.

Q:  So what’s happening in Alternative Data and why is this such a hot topic now?

A: I think there are two driving forces. Firstly, traditional financial market participants are under pressure from many sides, not least active managers face pressure with deteriorating returns among most hedge funds and long only funds, who are also facing the astounding wave of passive money management.  Simultaneously, we have massive amounts of new and non-traditional data that’s becoming available in a new digital era – that we now term “alternative data”. In this new world order, early movers are looking to these data sets, consuming and analyzing this data, and finding new sources of alpha.

Q: What types of data and use cases are you seeing and what will you be talking about at the conference?

A: We’re seeing many hundreds of new data sources, with new ones emerging almost daily.  Sourcing, quantifying, cleansing, backtesting and onboarding these datasets is no simple task. At Neudata we classify 19 types, such as satellite and drone, IoT, weather, location, transactional data, web scraped data and social data among others.  At the event, I’ll be digging into social data analytics in more depth, including with sources like Twitter and others, where we see use cases from consumer insights that are predictive of stock price moves, to sentiment, to breaking events.  

Q: Can you describe quantitative results, such as the predictive nature of models or the ROI of analytics initiatives?

A: There are many examples of predictive signals ahead of security price moves and also an increasingly large amount of academic research that we’ll discuss in the presentation.

Q: What surprising discovery or insight have you seen with predictive signals from social data?

A: It’s well publicized now that President Trump’s Tweets have often moved markets –  so I guess that’s no surprise anymore. But, that’s just one high-profile example of very many. You’ll have to come to the presentation to hear more…

Q: Sneak preview: Please tell us a take-away that you will provide during your talk at Predictive Analytics World.

A:  New, novel, alternative data sources are an exciting and very real source for incremental investing insights, risk and trading signals.  Among the many different sources, I’ll dig into social data analytics – where early movers have been capturing alpha and gaining competitive advantage.


Don’t miss Stephen’s conference presentation, Leveraging Alternative Data Sources to Gain a Critical Competitive Advantage on Monday,  October 30, 2017 at 4:15 to 4:45 pm at Predictive Analytics World for Financial in New York. Click here to register to attend. Use Code PATIMES for 15% off current prices (excludes workshops).

By: Eric Siegel, Founder, Predictive Analytics World

Eric Siegel is the founder of Predictive Analytics World ( — the leading cross-vendor conference series consisting of 10 annual events in New York, Chicago, San Francisco, Washington DC, London, and Berlin — and the author of the award-winning book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die – Revised and Updated Edition, (Wiley, 2016).

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