Sprott: New ETF Captures Investor ‘Buzz’

April 19, 2016

[The following "ETF Industry Perspective" is sponsored by Sprott Asset Management]

The recently launched Sprott BUZZ Social Media Insights ETF (BUZ) is a first-of-its-kind fund that leverages insights from social media as an investment strategy. Edward Coyne of Sprott Asset Management USA and Jamie Wise of BUZZ Indexes discuss the thesis underlying the creation of the fund.

Who is Sprott Asset Management and what is the Sprott BUZZ Social Media Insights ETF?
Edward Coyne: Sprott is an alternative money manager with a growing suite of smart-beta ETFs. Our strategy is to leverage our experience as active managers to design innovative and unique ETFs that address unmet investor needs.

The ETF harnesses big data to identify actionable investment insights from the social media collective, which we believe provides investors with an innovative and valuable investment strategy. The ETF is designed to be a sentiment-driven momentum strategy with the potential to add alpha to a portfolio.

Why is now the right time to launch this ETF?
Coyne: Over the past few years, the investment world—which has always been on the lookout for new ways to gain an informational advantage—recognized the value of big data.

Quantitative- and fundamental-based investment managers are integrating social media's big data into their investment processes. Data providers such as Bloomberg and Thomson Reuters are providing social analytics on individual stocks to their clients. The Sprott BUZZ Social Media Insights ETF provides investors with access to this institutional strategy—packaged in a convenient ETF.

Can you give me an overview of how you came to create the BUZZ index and what it's intended to capture?
Jamie Wise: The process for us started a little over three years ago, when I realized what was happening in the space with consumer product companies gleaning insights from big data from social media to understand their customers' behavior and their customers' perception of their individual brands.

They're using that data to help them drive product development decisions and marketing and advertising decisions. That led to me thinking about how that would ultimately develop within the world of finance.

Back then, there was some early academic research about investment insights to be gleaned from the social media landscape, and we started doing our analysis. We found it was still in the early stages. There were the beginnings of some interesting data, but there wasn't enough depth to the conversation for us to have confidence that what was being said online could ultimately translate into observable results within asset prices and stock prices specifically.

And it all really changed within the last couple of years, where a few key things happened. The first was the adoption by Twitter of the cash tagging methodology—that's where you put the dollar sign before the stock symbol. That created a forum where people could find common ground to talk about their stocks and it really widened the breadth of the discussion.

All of a sudden, the growth of online discussion with respect to investments just started to skyrocket. It was really creating baseline levels of conversation—the bigger the stock, and the more widely held the stock, the more people there were talking about it online.

Once we saw that happening, we could start to model and look for changes in sentiment as it relates to those stocks. We discovered that the overall level of buzz or sentiment around stocks was in fact predictive, and could lead to a process where you could select stocks ranked based on that level of sentiment and ultimately come up with a portfolio of securities that could outperform the market.


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