ETF Edge - S&P-IHS Markit Mega Deal & Value's 2020 Comeback

Episode Date: November 30, 2020

CNBC'S Bob Pisani spoke with Dimensional Fund Advisors co-CEO and CIO Gerard O’Reilly and ETF Trends CEO, Tom Lydon. They discussed the big data deal news of the day - S&P buying IHS Markit - Plus, whether the runup in value is sustainable and the notion of rebranding and repackaging mutual funds into ETF wrappers. In the 'markets 102' segment, Bob continues his conversation with Gerard O'Reilly from Dimensional Fund Advisors. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Welcome to ETF Edge, the podcast. If you're looking to learn the latest insights on all things, exchanged traded funds, you are in the right place. Every week we're bringing you compelling interviews and market analysis, and we're breaking down what it all means for investors. I'm your host, Bob Pisani. Today on the show, we'll be delving deeper into the big data deal news of the day. S&P buying IHS market, plus whether the run-up in value is sustainable. And finally, the notion of rebranding and repackaging mutual funds into ETF rapidly. Here's my conversation with Tom Lighten, the CEO of ETF Trends, and Gerard O'Reilly, co-CEO and CEO of Dimensional Fund Advisors.

Gerard, I want to start with you. This is the first time we've had you on. Your firm is very well known to me for many years, so I'm very happy to have you on. Before we get to the ETF business, I wonder if you could just sort of describe to us for people who aren't familiar with the Dimensional Fund philosophy. Your approach to investing, I like to say it's sort of quantitative-driven. with an emphasis on keeping costs low, but maybe that's too simple. Could you give us a brief overview

of Dimensional Fund's investment philosophy? Thanks, Bob. Thanks for having me on, and nice to speak with you and Tom today. Absolutely, be happy to give you a quick overview. In a nutshell, Dimensional's philosophy combines many of the unique aspects of indexing, low cost, transparent, low turnover, and so on,

with an active implementation. And that's not too surprising, because when you look at David Booth or Macon, some of the folks that were involved with starting the firm, they actually started index funds back in the very early 70s, 1971. And over the past four decades, what we've been trying to do is improve upon indexing. And how we do that is through the research that we do,

how we design portfolios, how we manage portfolios day-to-day, and then how we trade. So that's what I call active implementation. It's taking some of the good aspects, whether it's quantitative investing, traditional active management, and combining them, then with some of the good things from indexing, you know, low-com, broad diversification, low turnover.

So a lot of the aspects of Quant, of traditional active, and of indexing all combined in what we think is a very, very good package in terms of delivering higher expected returns, robust risk management to investors. Go ahead, Tom. Your philosophy and your business model over the years has been really unique in the fact that you hand-selected advisors and institutions as clients even would bring them in

to your company to educate them on your philosophy and then approve them as far as being able to buy. I know there are a lot of advisors out there today that are really excited that you're getting into the ETF space, but that model that works so well for you over time to be able to remove the emotions of investors and keep a steady flow of new money that was coming in, are you concerned at all about opening up your investment tools to the general public. Thanks for that question, Tom. And you know, we're committed to working with financial professionals.

As you mentioned, we've worked with large institutions, we've worked with financial advisors, we work with financial professionals, and we do a lot of educational-type conferences and other types of support in that effort of working with financial professionals. We think that it's important before anybody invests with the mention that they understand what we're all about, how we approach investing, and what to expect from our investment portfolios. We think that if you're well-informed up front, there's fewer surprises when it comes to investing. We think that's very, very important, and we're fully committed to continue to work with financial professionals going forward. When it comes to ETFs, this is kind of the intersection of two what I would call very exciting developments in the industry,

or one in the industry and one with our clients. In the industry, we had the ETF rule passed last September, and that allows us to bring our kind of unique approach to investing active transparent ETFs to the take. The second one, Tom, more directly to your question, is we've had a great relationship with the financial professionals that we work with. And they tell us what they want, and they tell us what they're interested in consuming from us. And they want that unique investment philosophy, but they want it in an ETF wrapper. And we've been hearing that now from the financial professionals that we work with for a couple of years. So this is kind of those two meeting where we can do something that we've been doing for a long time in mutual funds in an ETF space, and our clients are very, very excited about kind of having that come to the table.

So you're planning to launch six new actively managed ETFs and also planning to convert six tax-managed mutual funds into these new ETFs. Is that right? Two of them launched a couple of weeks ago on the New York Stock Exchange. Did I get that right? So Bob, last June, we filed the preliminary registration statements for three actively managed ETFs that we were hoping to launch this year. So two have launched.

They launched in November and we expect the next one to list. targeting this coming Wednesday. So the two that launched was a US all-cap core equity, a non-U.S. Developed all-cap core equity, and then the emerging market is the one to come. So that's what we're hoping to do this year. They're all capped. They buy large and small, and then they overweight, small-cap, value, high-profitability firms, all what we do in our mutual fund lineup done with an active implementation, so we're doing a little bit of rebalancing every single day. The conversion then, Bob, is we're taking... You're converting. I think the key point here. The news I want to get to is you're converting from a mutual fund to an

ETF space. And this is sort of big news. You're one of the first ones, if not the first one, to be doing that. And that's sort of the, I think, the important news here, right? Yeah, that's important news. I would say that we're among the first to launch exclusively under the new ETF rule, Rule 6C-11. So that's news. And then this conversion of converting mutual funds to ETFs has not been done before in the industry. Now, these are tax-managed mutual funds, which means in their investment objective, we talk about maximizing after-tax returns and the impact of federal income taxes on returns. So these are six tax-managed funds, about 25 to 30 billion AUM, that then a couple of weeks ago

we kind of announced our plans that we hope to convert those from mutual funds to ETFs over the course of 2021. So that's big news, big news indeed. Right. And can you just, for people who get confused about this all the time, I know this may be elementary, but can you explain how moving from a mutual fund wrapper here where you're actively managed to an ETF wrapper that is also actively managed is more tax efficient? How is it more tax efficient? I know it's an elementary question, but we have to do this basic education for people to make sure they fully understand what's going on here. Absolutely, Bob. And there's two main types of distributions that funds make. And an ETF, by the way,

is a mutual fund. just a mutual fund under a slightly different wrapper. And one type of distribution is capital gains, and the other type of distribution is dividend income. So there are the two main types of distributions that funds make. When you look at our tax-managed funds, as an example, the dividend income distribution can have two parts to it,

one that's taxed at a higher level and one at a lower level, qualified versus non-qualified. So we've done a lot of work to make sure that 100% of the dividend income from those funds has been qualified dividend income. And that's unique to the funds. You don't see that as often in the ETF landscape. The other part is the capital gains distributions.

And when it comes to ETFs, there's a particular mechanism that means that you generally realize the capital gain when you sell the ETF. The ETFs don't make that money in the way of capital gains distributions over the time that you hold the ETF. So we think that this tax-managed conversion brings another tool, done this job of making sure that we're getting 100%

qualified dividend income from the fund, that's taxed at a lower rate. And now this additional tool helps us manage the capital gains distributions so that you, as the investor, are more in control of when you realize those capital gain distributions. Great. Thank you for that. Let me just go back to the U.S. core equity fund, because if you could explain a little bit of what goes into it, because when you look at the top holdings, frankly, it looks like a, you know, a large-cap quality fund here. Your top holdings are Apple, Microsoft, Amazon, Alphabet, and Facebook. It doesn't get more, I'm using the word quality than that.

And yet you sort of have a broader definition of what you're using. What are you going for here? And am I wrong in noting that this looks like big cap quality to me? So it's a all-cap strategy. So if you look at the holdings and we publish the holdings now with the one-day lag, about 2,200, give or take, stocks in that portfolio. So very, very broadly diversified. That strategy is going to overweight the value stocks, lower relative price stocks.

You were talking about that in your previous segment. Value had a pretty good month in November. And those stocks that are firms with higher profitability. So it's overweighing those stocks. If you look at the holdings of the strategy, as you mentioned, Bob, it's not deviating too far from the market. So we expect this to have low deviation from the overall market, but we expect to add value through slight overweights,

to value profitability, how we trade, how we rebalance on a daily basis. So I think your observations are spot on. The big names that you'll be familiar with in the marketplace are held inside this strategy, along with many thousands of other names, some small cap, with an overweight to small value and high profitability. Yeah, so when you talk about value and the timing right now, being able to bring your unique strategies to market in the form of ETFs, and we've got this relative value, between growth and value that we haven't seen this dispergence since 1999.

And from 1999 to 2009, the performance that your funds had were really incredible. But the last 10 years have been a bit of a challenge. What's the outlook, would you say, for the next five years, based on the markets today? Money's cheap, low interest rates. A lot of people are concerned about the 60-40 allocation. and growth has really done real well, even though we've had to pay up for that. And especially coming out of the coronavirus

and the optimism in cyclicals, might we still be challenged in the area of value? Or as Eugene Farmer always said, things revert back to the mean. Where do you folks stand in that? So Tom, that goes back to our overall investment philosophy, and we think that prices contain a lot of information. Prices are our best.

forecast of the future. And we think that people demand differences in expected returns to hold different securities. So if I give you a microcap stock versus Apple, who are you going to demand a higher interest rate to loan money too? Probably the micro cap stock. So we think those differences in expected returns are always there. Now what happens in realization is sometimes something better than expected happens and you get a real positive value premium, sometimes something worse than expected happens. But what we see from the historical data is that value is on average outperform growth and in time people, when it outperforms, it outperforms by a lot.

So when we look at next year and the year after in five years, we always expect a positive value premium. Because it's basically, price is set to a level, such as the return that investors demand equals the expected return. It's as straightforward as that. So we look for those stocks that have low prices relative to fundamentals, high expected future cash flows, that's with the profitability,

overweight those stocks. So we think that it's always a good time for value. On your other comment about growth, you know, you look Facebook, Amazon, Netflix, some of the companies that Bob mentioned, you look at those returns over the past 10 years. It's been 30% a year or so, a bit higher than 30% a year.

That means that on average, the prices have doubled every two and a half years. If you think that's going to happen for the next 10 years, it may, but it's unlikely. Usually when stocks become the biggest stocks in the marketplace, they outperform the market by a lot to get there, but on average they tend to underperform the market after they get there. And so that's this whole kind of notion of those larger stocks

having lower expected returns, And that's what has generally played out in the historical data. The problem is the patience issue, Gerard. Of course, mean reversion is real, and it exists. And we all are in the same school as you are. I think Tom and I certainly are. The problem is it's been 10 years, for example, large-cap outperformance on small-cap, growth over-value.

That's a long time to wait. And the problem, of course, is that patient. issue. And I know you believe it's always a good time for value. Let me just phrase this a little bit differently. Is there any fundamental reason why you think 2021 is going to be a good year for value? If nothing else because of the vaccine coming, would that help value? Or am I asking too much here to give a more fundamental analysis of value in 2021 other than it's always a good time? You can look at some of the stocks, Bob, that are in a value portfolio now. And a value portfolio will tend to be overweight energy right now, financials right now, maybe some of the airline stocks and so on.

And so when you look at the news that we had over the past month about three different possible vaccines coming to the marketplace and the returns of those stocks in response to some of the news that we had over the course of November, I think that if you kind of have news like that, that on average will be good for those industries, the cyclical sectors that you mentioned earlier on and in your show previously, that can turn out to be pretty good for value stocks. I always think, though, that prices do a good job of forecasting the future, the best job that we can do. And so to your other point, we expect value premiums every day.

To Tom's point earlier on, he is correct in that the spread, if you look at price-to-book ratios, a price-to-earnings ratios, or price-to-cash-flow ratios between value stocks and growth stocks is at an all-time high here in the U.S. That doesn't have too much information about it, say, what will happen to value over the course of the next year. But certainly, the valuation ratios would say, well, growth is high relative to its historical average. Value is kind of where it's been relative to its historical average. So, you know, when you look at two asset categories, and one has given you 30% or 15 to 20% a year over the past decade,

when traditionally it's given you 8 to 9, and the other one has given you what has given you over the past 80 years, which one are you more worried about? You've been kind of in a de facto way involved in the ETF business for the past five years with the relationship with John Hancock as a sub-advisor, a nice diversified group of asset classes and sectors. Will you continue in that capacity going forward? We sure hope so. We have a long-standing relationship with John Hancock going back over a decade, and we have sub-advised mutual funds and ETFs for them. So we sure hope to continue that relationship.

I think that they've helped us and we've helped them many times over the years. And so we definitely plan to continue with that relationship. Hey, Tom, on a completely separate issue that came up today, let me ask you about this big deal in the indexing slash data space here where S&P is buying IHS market. This seems to be a pretty big deal to me. I mean, we, watching the London Stock Exchange now, they're buying Refinnative, which is a big data provider as well. It seems like, you know, the old joke was software is eating the world 10 years ago.

One of our friends used to say that. And now it seems like data is eating the world, too. These data, whoever controls the data seems to control some very important information at this point. You have any thoughts on this deal, as well as the fact that they're controlling the indexes as well, these big players now? You're absolutely right, Bob. I mean, we're seeing huge consolidation. It's a big move for S&P. Now, you know, S&P has been dominant here in the U.S.,

but when you look at, for example, indexes overseas, many folks had turned to MSCI, especially with institutional mandates. Now, because Raffinitive has a lipper and a lot of FX currency indicators and indexes, They're going to be even a heavier global player combined. That will be $10 billion. And as we look at indexes really being the basis or chassis for the ETF industry, it's a big deal. So now we're going to have S&P Global being more dominant going up against MSCI. And then also, London Stock Exchange with Futsi Russell, it's getting more and more competitive in the indexing side because they are, in fact, de facto

asset managers, these indexes are bringing in a lot of money. So like the big three in the ETF space, it's going to be fun to watch. Yeah, Gerard, I don't know if you have any thoughts on this. I mean, you're a market watcher on this. This all gets into what I call the politics of index construction. As Tom mentioned, this is just a small group of people that are really controlling things. MSCI, London Stock Exchange, maybe Dax, and the S&P at this point. Does it matter to, does it matter to you at all who controls essentially not the data so much, but even the indexing situation, given how important indexing has become? I think it does matter, and we certainly pay close attention to it.

We're big data consumers, as you know, and we consume data from many, many different third parties. What we often do is combine those data into proprietary data sets. So if one person sells to another person, we continue to consume that data and blend it with all different types of data to come up with the proprietary data set that we think adds value in terms of how we go about managing the portfolios. When it comes to indexing, I think Tom is spot on in terms of some of his observations around MSCI, S&P, Futsi, Russell. They're all competing for business, and as long as there's many of them out there competing for business, and new index providers come in with some periodicity like Crisp and now has some commercial

indices as well. I think that's, you know, some healthy competition for investors to choose from. Most of the indices deliver kind of similar asset allocations when it comes to their standard indices. So it's kind of a matter of tastes and preferences which index an investor might prefer relative to another. Yeah. Well, it certainly goes to the value. I mean, given the price that they paid for this, that data and the control those indexes, that's worth a lot of money now. And it's nice to see after all these years, those of us who, like Gerard and Tom, believe in indexing, and I'm one of them myself. Now it's time to round out the conversation with some and perspective to help you better understand

ETFs with our Markets 102 portion of the podcast. Today we'll be continuing the conversation with Gerard O'Reilly from Dimensional Fund Advisors. Gerard, thanks very much for sticking around and joining us on the podcast part of ETF Edge. My pleasure, Bob. Happy to be here. You know, we have so many questions about broad investment methodologies from the viewers

that I thought you'd be the perfect one on to have on to talk about some really broad stroke investing concepts. Larry Swedro is an old friend of mine. He was on a few weeks ago. He has a new book out, the incredible shrinking alpha. And we had him on. And the bottom line for him was it's only gotten a lot worse for active managers, that it's more difficult for them to outperform over the years. And I'm wondering if you believe that as well. And why is it so difficult now to generate alpha? So Bob, it's a great question. I think it depends on your perspective of what alpha is. So let me start with what alpha is. And for me, alpha is the ability to outperform

an index-based approach. And so whether that's, you know, passive implementation index, but some type of index-based approach. And there's different ways that people have tried to accomplish that over the years. Some have tried to out-guess market prices. So try to say, when are prices too high or when are prices too low? And the data overwhelmingly supports that that's, when you look at U.S. Mutual Fund returns, the end investor hasn't really benefited from that of an approach. There's not a evidence of a systematic ability to outperform by outguessing market prices. But there's other ways to outperform an index-based approach as well. One is use the information of market prices to tell you who has high expected returns, who is low expected

returns today. Or use the information of market prices to tell you something about differences in risk or how do you manage risk more efficiently. Or use the flexibility of a daily process to drive down some of the costs associated with indexing. You were talking earlier on about, you know the index is becoming bigger and bigger and bigger. That means more assets are attached to them. When a stock goes in, there's price pressure on it to be added. And when it goes out, price pressure to be deleted. You don't have to experience that price pressure in your implementation if you're a little bit

more flexible when it comes to that implementation. So I think when it comes to that whole notion of alpha, I agree with what you say that alpha is really challenging to come by if it's about outguessing market prices. If it's about a systematic approach that uses flexibility to add value in advance of what an index can do or in excess of what an index can do, then I think there's plenty of ways that you can more reliably outperform indexes. And that's what we try to do here at Dimensional. But isn't the bottom line, I don't want to get too won't want to get too wonky or theoretical here, but I think the problem seems to be that active stock picking day in and day out seems to be based on a false notion that's something. somehow the market mispriced stocks. Isn't the whole basis of efficient market hypothesis?

That's not the case. If that's not the case, then market timing doesn't work, for example. Or picking stocks day in and day out and going in and out of them can't possibly work. Is that a fair interpretation of efficient market? I think that's a reasonable interpretation. A way to look at it is prices are forecasts of the future. And they're good forecasts of the future in the sense that it's really challenging to come up with a better forecast of what the future holds than what's built in to the price of a security.

And it gets that information by people buying and selling, so putting their own cash to work and expressing their own views about what the future is, and that's what builds that information to market prices. So the whole idea, you know, of fair market prices or efficient markets is that they're looking out to the future, and it's really challenging to outguess market prices. And I think that as technology advances, as information flows more quickly, as trading happens more quickly, that information gets its way into prices ever more quickly in markets around the world, and it makes it even more and more challenging to outguess market

prices. Is it fair to say that market timing doesn't work? I get this question all the time. For 20 years, I've been getting this question. Is it fair to say that the academic evidence that trying to get in and out of markets constantly does not work or does not outperform simple indexing when costs like taxes, and trading costs are considered. I think that's a fair to say. When you think about that getting in and getting out, you have to be right twice.

Because the market prices to such a level. Every day it sets the price level to keep expected returns positive. So you have to be better than the market to know when are you going to have something unexpected that's going to make returns negative or unexpected that's going to make the returns really positive. So you have to be right twice, not just once. So even if you had a 70% success rate of being right,

You have to get in and get out, and that gives you 49% success. 70 on the one side, 70 on the other side. You have to be right twice. And those are some of the things that make market timing so, so challenging. So the evidence overwhelmingly, I think, supports that the buy-and-hold investor, on average, does better than the investor that's coming in and going in and going out, partly because of the challenge associated with, and partly because of the costs associated with coming in and going out and all that additional trading. What about, and this is the second big frustration I get from the viewers, what about, about strategies that appear to have outperformed in the past should be, at least even by mean

reversion, and yet aren't. And of course, I'm referring to small cap versus big cap, and I'm referring to value versus growth. The value people have been holding on for 10 years, and yet, you know, maybe this is 2021 is the year that it happens. Is it fair to say it's been a long time for value, since value has outperformed? And what could make that change? I mean, Is 10 years a long time to wait for a big, big value play? When you look back over the past 10 years, Bob, I kind of spit it into the first seven and the last three. The first seven, end to end, the value premium was weakly negative,

but not too much in the tails. In the last three, we've had a very negative experience for value, in particular in the last 12 months and into the coronavirus. So that's kind of, it's been a tale of seven and three, where three, it's been very negative premium over the prior seven, not as negative. When you look at that type of a time period, you try to assess, can I find a manager that I expect to outperform?

You've got to look at the time period when value was positive during that 10-year period, because there was many months, many days, many quarters, many years even, where value stocks outperform growth stocks. In that last three, there was a bit of a kind of a headwind. So when you're thinking about, can I find a manager, and you're looking at a time period like this, basically, if you believe that,

there are differences in expected returns across stocks you believe in a value premium. It's kind of as straightforward as that. Now, what managers are able to capture that value premium when it shows up? So looking at the months or days or quarters when there were positive value premiums over the past decade, and as I said, there were many of them. That's a good way to kind of make an assessment of, is this manager able to capture that premium when it shows up? Because we fully expect that premium to show up day in, day out.

In the past, and going forward, and the data strongly supports that expectation. You've already stated many times that your belief in indexing, but you're also actively managed. So I don't know quite how to describe you, index plus maybe. Are there strategies that do work long-term? So obviously you believe in value, you believe in small cap. There's another sort of factor that's come into play in the last four or five years, this quality factor where you're looking for positive earnings momentum, for example. You combine a number of things.

Can you tell the viewers, if there is anything that really, does outperform long-term. Obviously, you guys have been looking for this index plus methodology for years. What have you discovered? So, Bob, I think about that indexing has done a lot of good things for investing in terms of bringing low-cost investments to a lot of people, you know, transparent investment approach so you understand what you're getting if you understand the index. So it's brought a lot of good things. Indexing is very rigid. And that flexibility that we bring to the table, I think, adds value in excess of that rigidity. And what do I mean by that? Well, the ability to pursue those

value stocks or high profitability stocks or small cap stocks on a day in, day out basis, so you keep yourself focused. Because just like last month, you never know when the value premium is going to show up, but you want to be there in the event that it does so you can capture those higher returns because you can't predict when it will show up. So I think that indexing has a lot of good things associated with it. And when I talk about active implementation, it means taking those good things and trying to make them better. So you make them better by the research that you do. That's all that quantitative research about size,

value, profitability, how you design portfolios to be as efficient as possible, and then how you manage them and how you trade them. Because it's all about the total cost of ownership. And that extends beyond just the fees and expenses that you see. That total cost of ownership is a very important question for investors.

So I think that it can be improved upon, and that's what we do here at Dimensional. So indexing is good. I think we're better. And it's kind of, I would call us systematic fundamental in some sense. We're systematic in that we're kind of somewhat transparent and we're process driven. Fundamental in that you have to recognize that you have to go out there into the marketplace and transact day in, day out. You have to have somewhat of a fundamental view

of the world and how the world works in order to do that effectively. Yeah. You often say you use primarily quantitative analysis. I'm wondering if you can just simply define that. I often say, you know, simply quantitative analysis studies relationships between numbers. Maybe that's a little too simplistic, but could you define quantitative analysis and how you use it? I think your definition is a good one, Bob, and how we use it is to understand what happened in the historical data by more than just chance so it can inform our expectation going forward. So you use these quantitative tools to help you analyze the data. Did this happen by random chance, or did it happen by more than just chance? So you're trying to disentangle that whole cause and

effect type of a story. I think when it comes to quantitative approaches, it's important to understand the art of the science. And that's something that we, a term that we use around here. You have all different types of models and different types of tools, understanding how to use them, when to use them, and what their limitations are are key components to having a effective quantitative approach. I'm wondering if you could distinguish, say, quantitative analysis from other approaches to buying and selling stocks like technical analysis or fundamental analysis. So we get a people love technical analysis at CNBC. The viewers like it. And on a certain level, it makes some sense. Technical analysis assumes that all of the information, it's really an efficient market

hypothesis in a sense, it assumes that all of the information is embedded in the price already and that all these concerns about PE multiples, etc. that fundamental guys are worried about is embedded in the price. And then it says, okay, what we want to do is study crowd behavior. It's a sort of behavioral economics thing. And we believe that crowd behavior is important. And we believe that you can reveal elements of crowd behavior by looking at prices and looking at volume and analyzing momentum around that. This makes some sense to me. And I can understand why the viewers love technical analysis. The problem I have with it, I wonder if you can comment on this, is anytime I look at some of the academic studies.

Burton Malkyel has been a friend of mine for many, many years, and he keeps pointing this out to me. The academic studies on technical analysis are very poor. It generally doesn't work over long periods of time. Can you comment on that? Is technical analysis a useful methodology for investing in stocks?

Generally, I would say no, because the evidence, as you point to, when you try to look at a technical analysis, the way that you would study that over a long period of time and say, OK, if I have this pattern in prices, I should do X. And then you test that in relation to other alternative types of approaches,

like buy and hold, or a value approach, or something of that nature. And when you assess them under those different types of approaches, you find that there's not much more there than can be well explained by a more traditional quantitative type approach. The same with your traditional active manager. When you analyze their returns under other types

approaches, quantitative type approaches, size, value, profitability, and say, well, what do they get paid for by inadvertently giving you exposure to these kind of quantitative approaches? You find that there's very little left in terms of excess, returns positive or negative. And so I think that the approaches don't stand up to that more rigorous analysis to say, okay, that's one approach. Let's compare to others and control for what's left over when we compare it to those other approaches. I agree with that. And whenever I bring up the academic studies, people kind of like flinch a little bit because it's such a popular method. Would you say the same thing about fundamental analysis, by the way? Does fundamental analysis stand up to rigorous academic studies? Or does that fail as well? We only have about a minute left. So if you keep the answer short, appreciate it. I'll keep it short then, Bob. When you're looking at returns of people who are trying to outguess market prices, it holds up to what we just said. Those returns are well explained. by kind of three-factor, four-factor, all these different types of models that you come up with. I will say that it's important to understand companies, how they trade, what their financials look like, and the various nuances of those financials, so that you can have a well-informed quantitative approach. So I still think there's important aspects to it, but just not to outguess market prices. Gerard O'Reilly, these are very broad-brushed 30,000-foot questions that viewers ask all the time that are very difficult to answer.

And I'm very happy we have a guy like you on who's been studying this kind of information and the right way to invest. And also studying what doesn't work for many, many decades. Gerard O'Reilly, thank you very much for joining us on ETF Edge. And we hope we can have you back again and get the benefit of your wisdom soon. Thank you, Gerard. Thanks, Bob. Appreciate being on the show. That's it for today. I'm Bob Bazani. Thank you for listening.

And make sure you tune in next week. And in the meantime, you can tweet us your questions or topic ideas at ETF Edge, CNBC.