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How AI and Algorithms Can Help You Find Winning Stocks

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(0:40) - Investing With AI & Big Data

  • (3:45) - Natural Language Processing
  • (5:20) - What Is The Source Of The Big Data Used?
  • (10:00) - BUZZ U.S Sentiment Leaders ETF Overview: BUZ
  • (12:45) - Market Value and Sector Weighting Breakdown
  • (15:35) - Investing Themes Using BUZ Strategy: The Rise Of Big Data
  • (20:40) - What's Next For AI, Big Data and Social Media?
  • (22:25) - Episode Roundup:

As more and more content appears online, it is creating a tsunami of data that is on a totally unprecedented scale from a historical perspective. Tweets, Facebook posts, blog entries, and a variety of other content fills up the internet with millions of messages and fresh data points on a minute-by-minute basis, and it is only increasing by the day.

Some might think there is too much noise out there and that any sort of useful signal is too difficult to find in this sea of data, but that may not be true. That is because recent advances on the technological front—specifically in the fields of Big Data and natural language processing—make sifting through loads of data a whole lot easier than what we saw even a few years ago.

This could be great news for stock investors too, as we can now utilize new Artificial Intelligence applications to shift through the data and find key trends in terms of online sentiment. For more on this approach, I spoke with Jamie Wise, the CEO and founder of Buzz Indexes in this week’s Dutram Report to learn how investors are tapping into technological advances, and how ETF investors can play this information revolution too. 

Buzz Approach

First off, Jamie and I discuss what is actually meant by ‘natural language processing’ and what kind of technological advances we have seen in the data world over the past few years. These key changes make analysis of online sentiment trends possible for stock investors, allowing algorithms to read online posts and determine if they are focused on the stock, or on a given customer’s experience with a company instead.

Once we’ve gone over the basics, we move on to what kind of sources are used for the information, and this includes everything from Twitter (TWTR - Free Report) and Facebook (FB - Free Report) , to posts on various other sites as well. Some do receive higher weights than others in the models, but it is clear that a number of sources are used for the data.

Index & BUZ ETF

Beyond that, we also talk about how this is put into practice with the BUZZ NextGen AI US Sentiment Leaders Index, the basis for the BUZ ETF. Jamie lets us in on how this index was developed, and some of the key factors that go into this benchmark’s construction. We also talk about what is meant by ‘sentiment’ and why focusing on this metric could be a good idea for investors.

One area that was especially interesting to me, was the idea that investors generally focus in on a few companies in a select number of industries. How does one expand the reach to a broader company list, and is there enough info for some of the smaller stocks out there? Jamie walks us through the answers to these questions in the podcast, but it definitely seems like the group of possible stocks is growing by the day as more information is hitting the web all the time.

We also discuss a few ways in which this approach has been helpful as of late, focusing in on the tech sector. In particular, we zero in on the chip space, which has definitely been in the spotlight lately.

Two companies that we highlighted were Advanced Micro Devices (AMD - Free Report) and Nvidia (NVDA - Free Report) . Check out the podcast for more on how the Buzz model spotted these stocks ahead of some strong performances for both, and what this means for stocks in the future too. But definitely check out the podcast for additional information on the index’s construction, and the key things to note about this AI-focused approach!

What’s Next?

Jamie and I also talk about what is coming down the pike for Buzz Indexes, and the additional ways this approach could be utilized in the ETF world. I also make the parallel between this technique and the idea of the ‘wisdom of the crowd’ and we discuss how this index—in many ways—is a more advanced application of that popular concept.

Finally, we also discuss what is ahead for the world of social media and the big data landscape too. Check out the podcast for more information on these topics, and more, in this edition of the Dutram Report!

Bottom Line

But what do you think about this approach to finding winning stocks? Can the wisdom of the crowd be a leading indicator for investing? Make sure to write us in at podcast @ or find me on Twitter @EricDutram to give us your thoughts on this, or anything else in the fund market.

But for more news and discussion regarding the world of investing, make sure to be on the lookout for the next edition of the Dutram Report (each and every Thursday!) and check out the many other great Zacks podcasts as well!

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