ETF Edge - ETFs for the Space Race & Betting on Bitcoin

Episode Date: April 5, 2021

CNBC’s Bob Pisani discusses tracking social sentiment in ETFs, Bitcoin ETFs and the space trade with Art Amador, Co-founder and COO of EquBot, Jamie Wise, Founder of Buzz Indexes, and Todd Rosenbluth, Senior Director of ETF and Mutual Fund Research at CFRA. In the 'markets 102' portion of the podcast, Bob continues the conversation with Jamie Wise from Buzz Indexes. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

The ETF Edge podcast is sponsored by InvescoQQQ, Supporting the Innovators Changing the World, Investco Distributors, Inc. Welcome to ETF Edge, the podcast. If you're looking to learn the latest insights on all things, exchange traded funds, you're in the right place, my friend. Every week, we do the interviews, we do the analysis, we break down what it all means for investors. I'm your host, Bob Pisani. Today, we're looking at the many ways to stay ahead of the game by using artificial intelligence, pick stocks, and tracking social sentiment. What's all the buzz about these days? Plus, we'll get another update on the latest push to get a Bitcoin ETF approved by the SEC. Yes, it likely is coming. Will 2021 actually be the

year? We get it. Well, here's my conversation with Art Amador, the co-founder and C.O. of Equibot. Jamie Wise is the founder of Buzz Indexes and Todd Rosenbluth, senior director of ETF and mutual fund research at CFRA. Jamie, we had you on a month ago. I said we'd have you back. You had a big launch there with Dave Portnoy as your partner. You've got, I think, nearly 500 million bringing me up to date on that in assets under management. But you're still very heavily invested towards a lot of the old school tech stocks. I see AMD in there, Apple and Amazon. I see some new stuff there. I see Square. I see Tesla, Virgin Galactic thrown in. What are you hearing these days? What do you learn running this thing for a month using social

media as a method of buying stocks? Tell us what you've learned. You bet. Nice to be back. And while it's been a month since the ETF has been live, of course, the index behind the fund has been around for almost five years now. So we've really learned a lot throughout that time. And while we, as you mentioned, experienced a very successful, you know, launch of the index in the last month, what we've really learned over the last five years is that there's so much more to the insights that we can observe from, you know, the millions of people talking about stocks and the kinds of stocks they're talking about. And it's not all high-flying growth stocks or tech stocks.

You know, there's a lot of different lenses that people can look at security valuation. Of course, that can be growth is one of those lenses, but naturally values another lens and a lot of reasons why people are talking about stocks, especially of late. Maybe what we've learned more recently is we've seen that rotation continue a little bit within the buzz index, where we've, you know, welcomed as of the last monthly rebound, stocks like Costco and Target, but Norwegian cruise lines, Marathon Oil, so some more value-oriented or traditional old economy stocks.

I think the collective conviction and where people are positive, they're seeing some of these trends reemerge. They're seeing the end of COVID potentially in sight, and they're starting to position their portfolios accordingly. And certainly some of those old stocks drove performance last this year to date, right? We look at the best performing names in the Buzz Index,

and you'll see a name like Ford or American Airlines really contributing to the continued outperformance of buzz over, you know, traditional long-only strategies. Yeah. And Art, it's interesting what Jamie has to say about that, you know, value tilt that we've been seeing. He reflects that. He can rebalance on a monthly basis.

AIQ, AIEQ has also been around a pretty long time. You still have some pretty heavy bets on tech, though. Apple, applied materials, alphabet, intel. I see amongst your biggest holdings here. Can you tell us how AIEQ works? How do you pick stocks and explain why you've still got a fairly heavy tech tilt towards that? And what's the model telling you at this point? Yeah, so AIEQ is powered by IBM Watson and ECBOT AI.

And the idea is to identify U.S. companies with the highest potential for price appreciation. And Bob, we do this every day by combining millions of news articles, social media posts, and industry reports, macro and market data, financial statements on more than 6,000 U.S. companies. And then we select about 150 companies that, in aggregate, have the highest opportunity for price appreciation. And one of the things that we're currently seeing within the models is we're observing positive signals for technology hardware demand. And this is being reflected in demand for chips. So semiconductors is actually the largest overweight that we're seeing. In the top 10, you'll find names like applied materials, Intel, A&B. And then kind of interesting, you know, although we are overweight technology names,

we've actually been seeing kind of a scaling back of some of the technology software names, names like CrowdStrike, Zoom, DocuSign, Z-Scaler, where these used to be, you know, top holdings. They've been scaled back quite a bit. We still own them. They're still important stocks. But we're seeing kind of a reallocation to some of the reopening benefactors, companies like Uber, Bank of America, Simrich's Energy, and Six Flags, as well as some reeds. Yeah. Now, Art, demystify this a little.

You say we see positive signals for technology. What are the positive signals? This all sounds, you know, a little mysterious here. The Robo advisor is telling you I see positive signals. Well, what is the positive signals? Can you tell us? Just explain it a little more. Yeah, so I think the best way to break it down is that each company has four deep learning models running on it.

And so the first model is looking at things like financials, I think fundamentals, GPS, revenue, ebada. The second is news and information, looking at things like sentiment, pricing, and volume data. Third is, you know, management models looking at things like ESG, innovation spend. And the fourth is macro models, think GDP unemployment and housing starts. And one of the important things is it's never just one signal, Bob. And so it's hard to say, hey, it's this one piece of data, right? AI is all about recognizing patterns. And so it's patterns right across the structured data and the unstructured data.

You know, it's combining things like sentiment with financials, with macro, that really makes AIQ's, you know, predictability so powerful. Yeah. Todd, you've been watching this for a long time, attempts to pick stocks using not just fundamentals, but all sorts of other metrics and then combining them. We now have the AI to do this. The ability to crunch these numbers is why they're remarkable to me. We've never had this ability up until fairly recently.

What do you make of all these attempts to use ETFs to capture whatever, trader sentiment or broad ranges of data points. What's your take on all of this? So we've had, as you mentioned, Bob, we've had multifactor strategies that are combining momentum and value and profitability characteristics. But what we haven't had up until these two products is something that is rebalancing either on a monthly basis in the case of buzz or the potential to make changes on a daily basis in the case of AIEQ. For example, MTF, which is the I-Share's momentum ETF, rebalances every six months. So it still is heavily laden towards technology and consumer discretionary

and has less exposure to industrial, has almost no financials, has zero energy exposure. Those latter sectors have been leading the market to start 2021, and they're just not catching up within the ETF. it will get there in the coming months, but it's something that's happening and rebalancing faster or the potential to do so is going to respond to market sentiment shifts in a more rapid manner. Yeah, you know, that's a good point. Jamie, you know, last time you were on, I believe we had the fellow who was launching the FOMO ETF, the fear of missing out ETF. Not with us yet, but it's been in a filing. That would rebalances once a week. You rebalances once a month. It seems like this rush toward rebalancing is accelerating toward it almost daily rebalancing. What are the pros and cons of rebalancing on a more or less regular basis? Yeah, and, you know, the approach of Buzz is very different than FOMO.

It's not about identifying the current meme stock and quickly getting exposure to it. What we're doing with Buzz and why we think it's important to rebalance monthly is we're capturing these sentiment trends. And Todd had a great point around the factor exposures. that exist in the market, our view it buzz over the last five years has always been that, you know, sentiment has been a factor that's existed for hundreds of years in price discovery. The difficulty, as you mentioned, Bob, was that it couldn't be measured until we had the tools to measure it and the platforms of millions of people talking about individual stocks where we could now measure the difference between the sentiment on Boeing and Disney and GE and Netflix

and Microsoft and all the other stocks we're familiar with. And to the extent that we can do that, essentially the return stream of buzz is the sentiment factor, the sentiment factor that people have been after for a long time that we can now measure and support with data. So it's not about proxies to try and measure sentiment or an expert's opinion. We can support it with data. We can support it with a five-year live track record. And we can now introduce that sentiment factor into other factor-based approaches. So to the extent that sentiment is this dynamic factor that can have exposure to energy and financials as market environments shift, you can achieve that exposure by rebalancing.

monthly to that sentiment factor. Yeah. Art, I'm wondering where all this is going down the road. You know, I grew up with science fiction, and I grew up with, you know, robots and artificial intelligence in the 50s and 60s, and we're finally here to a certain extent. But the way I see this, eventually my AI trading program, which will be a subset of my personal digital assistant, will eventually launch, and it'll be trading against your AI. and it will be pretty darn good because it'll have access to very, very wide swaths of information very, very quickly.

So maybe, you know, maybe I'm not Renaissance technologies yet, but I'm pretty darn close. And I don't think that's actually very far off. Can you give us, you're an AI guy? What I'm saying, making any sense? Is it quite likely in the future? We already have viewers messaging me saying, you know, Bob, I really want to figure out. tell me more about these ETFs that buy stuff that's really moving fast. I don't know what's going on, but I want to be on this Reddit story, even though I don't

know where they are. Figure out how to do that and how to capture it. So can you envision a day when my AI trading program interacts with your AI trading program, and they're all pretty darn good, and the ability to outperform one against the other gets smaller and smaller eventually? That's so far in the future, Bob, and here's why, right? So Todd kind of touched on this briefly. So when I think about the current algers in the market, right,

a lot of these are these legacy factor models, right? And I want you to think about models and data, right? And these legacy factor models, right, they're all very similar, right? They're all kind of based on that Chicago School of Thought. And the data that they're looking at, right, is very limited, right? This is kind of the structure, historical data. And I say it's limited, right?

Because think about what our partner at IBM says, right? 90% of the data in existence today, right, has been created in the past, past two years, right? We're going to be saying that every two years, right, going forward. So AI's ability, right, to capture this growing amount of data, right, only right now, only scratching the surface, right? And the other thing is, you know, when I think about AI models, right, the diversity within the AI models, right, is incredible. So what happens is you get crowded trades with legacy factor models, and with AI models, diverse debt, growing data, there's going to be alpha for these funds for the foreseeable future.

There's going to be many different models. So this is just the, this is just the first inning club. It sounds to me, Todd, like, you know, what happened a number of years ago when, do you remember the late 90s when all of a sudden we had very efficient matching engines that suddenly started coming up that were trading programs? and I'm thinking of programs like Island that existed, programs that like the NYSE bought, the really fast programs they bought. And these programs, many of them initially just employed, were employed by people

who were matching the S&P futures in the trading pits against the S&P futures that were trading electronically. And Todd, remember there was a period where you would think it's the same it's the same instrument. They're fungible. And yet there was a very noticeable gap between that, between the electronic trade and the pit trade. And it made a number of firms very, very wealthy for a long time. And that kind of, I guess we call it statistical arbitrage or whatever, eventually became much more difficult to do. You can still do that, Todd, but it's a lot harder. And that's my point here, I guess I'm trying to make with everybody, that, yes, you can still do it. I don't know how much longer it is in the future where there's enormous amounts of money to be made, essentially scalping different people's opinions on a day-to-day basis.

Well, I think what we also need to bring into this is that most ETFs are tracking more traditional indices that don't rebalance that regularly. The S&P 500, that's a market cap-weighted, price momentum-driven approach to it. And then we've got this smaller subset, but growing actively managed. ETF universe that's using qualitative factors. So the ARC funds that Kathy Wood runs would be a perfect example of it, whereas what AIEQ is doing is actively managed, but using a much smarter computer models than I would be, if I was picking stocks or a portfolio manager, might be picking stocks,

but there's less qualitative factors that you're less likely to stick with a winner longer, with a longer time horizon the way that, you know, that Kathy Wood and team are doing. Yeah. I want to move on and get everybody's opinion on the Bitcoin ETF because I'm wondering where this might fit in with Jamie or maybe even AIEQ. Todd, bring us up to date on the Bitcoin ETF. Two weeks ago, as I recall, the SEC sort of set the clock ticking. They acknowledge Van Ex-Bek's Bitcoin ETF. That acknowledgement is really setting in motion,

a legal review, essentially they'll have 45 days from that date, it's about two weeks ago, in which they can accept, reject, or extend the timeline for consideration for the Vanek Bitcoin ETF. What, in your opinion, do you think they're going to do in the next, say, 30 days or so? So I think the greater likelihood is that they extend the time frame for this. I just think their information is flowing rather rapidly. We've got a number of firms that have either attempted, gone through the filing process or have previously filed but are waiting for more clarity. The SEC is less likely, we think, to try to pick a winner as to who comes first. And I think we're more likely to see them if they do approve an ETF to approve multiple Bitcoin-related ETFs.

We've got a number of firms that have entered. We think we're likely to see one in the coming year or two. but we don't have a firm timeframe as to when the answer would be yes. Yeah, I think you mentioned before, Todd, and I agree with you, that if they approve someone, they're going to approve all of them. They did this with semi-transparent ETFs. I believe you and I have talked about that before. They approved a whole bunch of them all at the same time.

Hey, Jamie and Art, is there a place for Bitcoin in Buzz or AIEQ? What about you, you two guys are thought leaders? Give us your ideas, sir. Well, I can tell you from the algorithms we use to listen to, you know, social content, essentially, discussions around stocks. Naturally, there's an awful lot of discussion around Bitcoin and other crypto, crypto assets and tokens. For Buzz, no, you shouldn't expect to see any crypto into Buzz.

Buzz is very clearly defined as large-cap U.S. equity exposure by sentiment and would not hold Bitcoin or other crypto assets. But that's not to say that our models aren't listening and judging sentiment on those various tokens. And we'll see what happens in the future. Maybe not in Buzz. maybe in something else. Yeah, so for AIQ, similar, we can't invest into Bitcoin, right? But we do think it's really important to get exposure to the ecosystem.

And so AIQ is doing that by investing in some smaller cap names. One is Silvergate Capital. It provides cash management services to digital currency businesses. And the other is Marathon Digital Holdings, which mines cryptocurrencies. These are newer positions. We entered into them last quarter. But they've been up over the last 12 months, you know, 1,500 percent. Silvergate over 9,000 percent for, you know, Marathon Holdings. So we do see a lot of positive

signals around cryptocurrencies, and so we want investors to have exposure. Now, that said, we're also seeing a lot of regulatory headwinds, not just here in the U.S., but also globally. So, you know, right now it's got, you know, a couple percentage points in the portfolio, and as those regulatory headwinds kind of subside, I would expect, I would expect, you know, increases into the ecosystem. them. Okay. We hit Bitcoin. I want to get your thoughts on space because Kathy Woods has finally launched the ARC space ETF, ARKX symbol there. You know, Todd, what interests me at looking at the top holdings, other than Trimble, which is a pretty big bet, 9%, rather big tech company,

really. What's amazing is how many essentially aerospace companies are here. This is part of the problem with investing in space. You're largely got Lockheed. here, Boeing, Komatsu, L3 Harris here. These are pretty old-school companies. I mean, you've got iridium, too, but this is the problem with investing in something like space, right? I mean, it's just not enough pure place to really make a huge difference, or am I wrong in thinking about this? No, we agree with you. I mean, so it's a narrow universe right now of publicly traded companies that have a clear indication, a clear beneficiary for space. exploration. Thematic

ETF investing is often open to interpretation, and so the way that ARC describes its space ETF includes companies that will benefit from aerospace activities or technologies used to support aerospace, and so you've got companies,

like you mentioned Boeing, and L3, but it owns companies like deer and Netflix, which would likely be beneficiaries of this, but it's not owning companies that you find within UFO, for example, like Laurel Space and Communications. Again, it's different, and the $450 million is a sign that investors had interest

in something Kathy Wood and team were going to manage, but I'm not sure they fully appreciated what they were getting. Yeah, this is a pretty, and I'm a big Kathy Woodbacker. I think she's got a tremendous vision, and she's not afraid to take big outside bets. You know, 31% in five companies, 50% in 10 companies, those are. they're outside bets, but it's really a stretch to argue, you know, L3 Harris and Komatsu and Lockheed and Boeing. You know, I mean, I know they're in aerospace, but, you know, we're thinking space. We're thinking, you know, satellites and we're thinking the moon race and we're thinking

a lot bigger than that. It seems like a little bit of a stretch here. Jamie, and Art, any thoughts on space and where it belongs in your portfolios? Yeah, we see it, actually, in the buzz holdings. you know, Virgin Galactic was a holding that came into the index, I think late last year, and again, within the top 10 contributors to this year's performance, one thing I think we know about space, it's certainly a long-term theme, and I give Kathy all the credit in the world for, you know, staying true to her approach at Arc, but we know that sentiment will likely shift toward the prospects for, you know, viable space travel over the next five to ten years. And I think that's, you know, again, what we,

really believe in the approach of buzz is that being dynamic around sentiment with respect to space versus boxed into a long, forever space position might give you a little bit more flexibility, especially around defining which are the names that are going to lead us into space and our investor is positive toward that contribution, or is perhaps now not the right market environment for that kind of investment. Art, want to close that out on space? Any thoughts? Yeah, so, Bob, I mean, I totally agree with your point. So, you know, AIQ, we leverage a knowledge graph, which basically connects a bunch of different concepts, you know, space being one of them. So it's something that we're continuing to kind of build upon and learn on a daily basis.

But it's still very difficult to kind of get exposure to that. And it's also, you know, kind of more further out in the future. And because AIQ's got the dynamic nature to trade daily, right, you're not going to find a whole lot of exposure to space at the moment. But as things change, right, and we learn more, we're going to be able to identify, you know, who the women are. are. And so you'll see exposure right when the time is right. I agree with you. Again, I grew up with science fiction in space. I find this current environment really exciting. But the excitement is coming from people like Elon Musk and Jeff Bezos and Richard Branson. And they're the ones that are generating real excitement, I think, because they're

making a real difference. So my hat goes out off to those guys. And let's just hope we get more space, not less space in the near future. Going to have to leave it there, everybody. Fascinating discussion, as always. Now it's time to round out the conversation with some analysis and perspective to help you better understand ETFs. This is the market's 102 portion of the podcast.

Today we'll be continuing the conversation with Jamie Wise from Buzz Indexes. Jamie, thanks for sticking around. One of the things that people have asked me about the Buzz Index is, gee, I thought GameStop was the biggest buzz out there, and GameStop's not really there. Can you, again, review what the criteria

is for what goes in and what goes out and why something like GameStop was not in there initially. Yeah, thanks for having me again, Bob. And I think it's important to understand how the index is constructed and why GameStop, you know, wasn't featured in the Buzz Index back in January and even up until today, the end of March. There's a few criteria. The Buzz Index is not meant to be reflective of, you know, very short-term meme-like stocks, stocks that are suddenly in the news for either, you know, a corporate event or just a sort of, social media event that's happening around them. What Buzz is really trying to reflect and present

to investors is the view of large cap U.S. equities through a longer-term sentiment lens, something that we think about in terms of a monthly basis, which is why the index rebolences each month. There's a couple of criteria for a stock to be eligible in the Buzz Index. The first, it has to be a large-cap U.S. equity. We define that as, you know, a stock that has a $5 billion market cap or higher. The second criteria is the nature of the conversation behind those large cap U.S. equity. So every quarter we assess the large cap U.S. equity universe. There's about 1,000 or 1,500 stocks that meet the $5 billion and up market cap threshold. But then we look back at those stocks and we say, how have the community talked about them for the past 12 months?

And is there breadth and diversity and consistency to the conversation? That's very important when measuring sentiment because we want to ensure that we're capturing the sentiments of the widest amount of people possible through that widest lens possible. And so what that typically results in is an eligible universe of somewhere between 250 and 350 stocks that meet both the large-cap 5 billion market cap threshold, but also the breadth, diversity, and consistency of conversation threshold. So I like the word that you use the nature of the conversation, how it's talked about breadth. So basically, you're picking up on the nuances of how people are discussing the stock.

And it has to meet a certain criteria of positive mentions, is it the right word? It's more nuanced than that. I understand that. But that's what we're getting at here. Exactly. Before a stock could be featured in the buzz index, it has to be eligible to be featured. And the kind of conversation is, you know, are there a lot of people talking about this stock consistently day and day out, regardless of sentiment, right? So sentiment will be measured each month at rebalance, and the top 75 sentiment names are featured in the index.

the universe from which we look to measure sentiment are these stocks that are being talked about day and day out. GameStop, you know, we talked about that. It certainly would meet the mentions threshold. Where it failed to meet the eligibility was in the market cap threshold back in January when we set the quarterly eligible universe. And that excluded GameStop for the next three monthly rebalances. So it was not eligible January, February, or March because it didn't make that market cap threshold. And the reason we saw that. set the quarterly universe for eligibility is it's part of the safeguards of the approach so that stocks that, you know, like GameStop did in January, it had a big rally and then a big,

you know, coming back to Earth as it was really a short squeeze. It wasn't a fundamentally driven story. You know, those types of names aren't really sentiment. There's something else happening there. It's supercharged conversation, not the type of sentiment the buzz is looking to portray or capture in the methodology. Of course, if a stock can maintain a market cap threshold for a period of months. And when we come back to the next quarterly rebalance, which we just did yesterday on April 1st, you know, we look at where's GameStop and it's over $5 billion. And we also look at the conversation around GameStop.

And it's very different today than it was back in January. It's fundamentally driven. There's significant management changes. You know, you're looking at a large organization, 6 to 7 billion of annual sales, nowhere near the top of the list of large cap U.S. equities in terms of a price to sales ratio that the stock is trading at. And so it's very much a different kind of conversation today. That won't mean the GameStop will be in the April rebalance. We'll have to measure its sentiment on the selection date, which comes up in a couple of weeks. But we'll see

it will be eligible now. It's a different kind of conversation. It's a seasoned market cap story. Those are the kinds of names that we're interested in. I think that $5 billion market cap is very important. I have to say, in the last year, I've gotten an extraordinary amount of people who I think are probably obviously younger investors. I don't ask their age, but they ask me about investing in pink sheets, in microcaps. Just an extraordinary amount. I mean, this has always existed, as you know, somebody's always talking about a three-cent stock or a ten-cent stock that's going to, you know, go to a two-dollar stock or something like that. But it really has gotten a lot higher, the interest level. Would it all be ever feasible to do a buzz index?

on microcaps? Or would there be some kind of limitation or technical difficulty or something else doing it on a small cap, on a microcaps? Certainly the algorithms and the models can read the text of these people talking about the microcaps or even small cap securities. The challenge from an investment perspective

is making that investable. These stocks are so thinly traded. That's partially why they're talked about, right? You have extreme moves. It doesn't take a lot of capital. to move these stocks. And to the extent that you have, you know, meaningful capital invested in an ETF product

that is trying to deploy into these very small securities and thereby even exasperating and furthering some of these price moves, my view is that it's really not appropriate or practical to try and target this approach to the microcap space. Yeah, I agree with you. You know, I've been doing 31 years at CNBC, and our general approach is we do not cover microcap stocks

and pink sheet stocks. for the simple reason that the sheer act of talking about them, the sheer act that you would mean talking about a microcap stock would move a good, bad, or indifferent. And you don't generally want that to happen. And so that's been our general rule. It's not an absolute rule, but that is the general rule we have used. And I think it's a very good one.

Have you ever thought about the opposite of buzz? How about a negative sentiment index buzz index? With something like that work? It would work. And we do track it, of course, because to the extent that we're measuring sentiment and across large-cap US equities, it's not all positive. Each month in our update newsletter, we actually feature the five most negatively trending stocks

that aren't a part of the buzz index, just as that tease or that insight for people to understand that certainly some stocks are trending the other way. You know, last month, Visa and IBM were at the top of that list, interestingly enough. And so certainly there's opportunities for long-short strategies around the insights from, you know, the sentiment readings that we can observe

or even a short version of Buzz. But for now, we're sticking to sort of the benchmark approach for large-cap U.S. equities, which is Buzz. Yeah. And we had some, I don't know if it was you or Art mentioning the Chicago School. I guess we're referring to efficient market hypothesis, the idea that the current prices of stocks reflect all available information. And that consumer sentiment, I'm not trying to put words you about, but the idea here is that consumer sentiment is actually a reflection of what people feel that these stocks are worth right now. I'm trying to ask you to tie in, I guess,

efficient market hypothesis that stocks reflect all available information, current prices at that time, with where social sentiment helps with that understanding. Yeah, you know, when we launched the index five years ago, the theory or the thesis behind it was really that this thing called sentiment, which as investors you and I have known have existed in markets forever, you know, now that we can measure at the individual stock level, is it predictive or not, right?

That was the whole rationale for creating the buzz index. And of course, what we found over the last five years is that it turns out stocks, just like other aspects in consumer products, positive sentiment is a tailwind to their performance, right? And that's what we've shown in the buzz index. I think from an efficient market hypothesis perspective, you know, we look at explaining return streams through a host of factors, right? We can look at it, you know, is momentum, value, size, volatility, all of these factors that we're familiar with these days. What are,

what are the attributes of the return stream for those factors and the unknown part of the factor that's alpha? And what we're saying with Buzz and what we've seen over time with Buzz is that Buzz doesn't correlate to those other factors. Sentiment is its own factor. It always has been. It's just that now you can measure it. So I think a portion of the historic alpha, which was the unexplainable factor return, is actually sentiment. And I think you can deconstruct that now out of a factor, you know, that factor out of the return stream. And to the extent you have one more variable that can be explained through Buzz, that leaves

less alpha to be explained, which narrows or, you know, helps with the efficient market hypothesis. Right. Well, that's an interesting thought. You think sentiment is a factor that should be considered. along with, well, the ones that mattered, I'm going to want to get too far into Chicago school and, you know, Eugene Fama, but momentum, size, value, quality. I mean, those are like the three or four that academics believe have shown some modest alpha over and that most of the other ones don't seem to matter. You actually think sentiment, you can make an argument for sentiment as another

factor that should be considered? Absolutely. And there's been a lot of academic research trying to understand that for decades now, right? How does sentiment play into price discovery? How does sentiment play into performance of different stocks? It could never really be measured. That was the challenge with sentiment, right? We only had these macro-based proxies, whether we're talking about the VIX or, you know, different surveys that are out in the market, or, you know, even other market-related proxies like put call ratios or an expert telling us something about sentiment with no data to back it up. I think that there is vast agreement in academia and in traditional asset management that sentiment drives prices. It is a factor of that return stream. We've been saying it for a long time.

And now we have a way of presenting that factor, investing in that factor and benefiting from it, simply because we have these millions of data points that we can analyze, accurately measure for sentiment, and create a return stream that is driven not by another factor, not by sector exposure. It's completely dynamic with respect to all of those things. The common factor that's involved with all these stocks and the Buzz Index is they are positive sentiment stocks. That is the return stream. Yeah. That's a very interesting point.

Jamie, always enlightening chatting with you. I really appreciate you spending a little more time with me. We've been speaking with Jamie Wise, the founder of Buzz Indexes, and of course this is the ETF Edge podcast. That does it for this week's podcast, everybody. Thank you for joining us, Jamie. Thank you for joining us. Again, healthy, happy, and safe trading week to every. InvestcoQQQ believes new innovations create new opportunities.

Here's the greater possibilities together. Learn more at investco.com slash QQ, Invesco Distributors, Inc.