An Evidence-Based Look at the Struggles of Value Investing | Larry Swedroe

[00:00:00] When it comes to investing, it must be true that even 10 years is noise or likely to be noise. And the reason is if it wasn't true, there'd be no risk premiums. You cannot make the argument that the value investing has become a priority. That's obviously wrong. Active management is even more of a loser game than it ever was.

[00:00:26] If you ask the average investor which industries have had over the 100 years the highest returns, they would all say either healthcare or technology. And it's the sin stocks, which are all value stocks of gambling, tobacco, alcohol.

[00:00:43] Welcome to Excess Returns, where we focus on what works over the long term in the markets. Join us as we talk about the strategies and tactics that can help you become a better long-term investor.

[00:00:52] Jack Forehand is a principal at Validia Capital Management. The opinions expressed in this podcast do not necessarily reflect the opinions of Validia Capital. No information on this podcast should be construed as investment advice. Securities discussed in the podcast may be holdings of clients of Validia Capital.

[00:01:05] Hey guys, this is Justin. In this episode of Excess Returns, Jack and I sit down with Larry Swedrow, a renowned author and respected financial and investing expert. We ask Larry some big-ticket questions that come up a lot in our discussions, including whether systematic value investing is dead, how passive investing and flows are impacting the markets, the effectiveness of fundamental-based strategies, international diversification, the impact of AI on investing, and much more.

[00:01:27] Larry provides thoughtful and insightful answers, offering investors practical advice and a deeper understanding of today's most pressing investing challenges.

[00:01:35] As always, thank you for listening. Please enjoy this discussion with Larry Swedrow.

[00:01:38] Larry, how are you? Thank you very much for joining us again on Excess Returns.

[00:01:42] It's my pleasure to be back. Dylan Finham on the right side of the grass. It's a good day.

[00:01:47] You spent your career educating investors on a whole host of topics, factors, evidence-based investing, long-term investing, how to be better investors, and how to think about markets.

[00:01:58] And we've talked to you about a lot of different things on the podcast over the years.

[00:02:01] But what we thought we would do today is kind of take a little bit of a different approach with you and sort of talk through some of what we believe are some of the things that are on investors' minds, some of the things that might be maybe a little controversial with different sets of investors, types of investors, and sort of just get your opinion and your thoughts and your feelings on where some of this is headed.

[00:02:25] And I think hopefully what investors can learn from this and these topics.

[00:02:29] And so there's a bunch of different issues, the effectiveness of value investing, and also factors, the rise of passive investing and influence of markets, and then get your thoughts on market concentration.

[00:02:39] But I guess to start, let's start with value investing and this idea that maybe systematic value investing is dead, or maybe its effectiveness won't be as much as it's been in the past due to maybe a whole host of arguments or issues that we want to work through.

[00:02:59] And there's a lot of them.

[00:03:01] So we don't want this to be like a list type format.

[00:03:03] But I guess the first one is to hear your thoughts on what influence the Fed has had on value investing with the rates and value relative to growth stocks.

[00:03:17] To answer that one, what I do always is look to the literature.

[00:03:24] And the literature says there is no real good answer to that one because the movement of interest rates has various effects.

[00:03:35] And rising and falling rates don't seem to have too much of a shift in the yield curve a bit seems to have a very modest impact.

[00:03:45] And the reason that there isn't a lot of relationship, or at least not strong ones, between value and interest rates is think about it this way.

[00:03:55] Let's say you have interest rates are, just to pick a number, 5% because we think growth will be 2% and inflation is 3%.

[00:04:05] Now, what happens if inflation drops to 2%?

[00:04:10] Well, then the interest rates have dropped from 5% to 4%.

[00:04:14] But that should have no impact on corporations whatsoever because corporate earnings are real and they move up and down with inflation.

[00:04:25] If you have 2% less inflation, corporate earnings in a real sense will be unchanged.

[00:04:31] But in a nominal sense, they'll be down, which means this whole idea of this, you know, the Fed model and interest rates is nonsense.

[00:04:40] Think of it also this way.

[00:04:42] Let's say interest rates go up from 5% to 6% because you're going to get 3% growth and 3% inflation instead of 2% growth and 3%.

[00:04:54] Well, what is that?

[00:04:55] Why is value going to be impacted by stronger economy?

[00:05:02] It should mean there's less risk in the economy.

[00:05:05] Corporate earnings will be stronger.

[00:05:07] So that should offset any change in interest rate.

[00:05:11] Should have no impact.

[00:05:13] And stocks shouldn't be higher or lower valued because they shouldn't be impacted.

[00:05:20] There should be this offset here.

[00:05:22] So the evidence is very unclear.

[00:05:24] What we do know in terms of economic growth is this.

[00:05:28] Value stocks, particularly small value stocks, tend to do poorly when at the onset or people are anticipating recession.

[00:05:38] And that makes perfect sense because value companies tend to be riskier.

[00:05:45] That's why they're trading cheaper, right?

[00:05:47] They, for example, tend to have more irreversible capital.

[00:05:51] They can't cut their spending as quickly.

[00:05:54] Okay.

[00:05:55] But then they tend to recover much faster because the market begins to anticipate the recovery.

[00:06:03] They know the Fed will act.

[00:06:05] They know the government will act and cut spending.

[00:06:08] I mean, increased spending, fiscal stimulus.

[00:06:11] And that should help by making them less risky again.

[00:06:15] And their earnings tend to grow much faster coming out of recessions.

[00:06:19] So that's about all you can say.

[00:06:22] And the problem is there are no good forecasters who can predict these things well enough that you could take advantage of it.

[00:06:31] In fact, we often don't know until nine months later when a recession actually started, right?

[00:06:37] The government, the NBER, which is the official declarer, doesn't even announce it often until six or nine months later.

[00:06:44] So my view is that we don't know what the Fed impact may have happened.

[00:06:51] My only other comment would be this.

[00:06:53] In my opinion, the Fed made a horrible mistake in monetary policy.

[00:06:58] I actually had a debate with the Federal Reserve, the head of St. Louis' Federal Reserve, at a conference, by keeping rates suppressed for very long.

[00:07:10] And what that meant is that interest rates were zero, meaning the price to take risks, you know, went way down because you didn't have, you know, the alternative of a risk-free rate.

[00:07:23] And that drove people into very risky assets.

[00:07:26] And that helped a lot of growth in lottery-like spots and those kinds of things, spurring investment in speculative assets.

[00:07:35] So that sense, yes.

[00:07:38] Now, the reverse, you would think, would eventually be true.

[00:07:43] Do you think there's anything to be said for too many people being value investors?

[00:07:50] And I'm not talking about traditional, like, concentrated stock picker value investors.

[00:07:55] But in terms of these quant strategies and index-based strategies that are trying to tilt towards value, do you think just the pure amount of assets in those strategies has sort of affected or reduced the value premium over time?

[00:08:07] It's a very logical question because we know, and it's very logical, that when academic research is published, they uncover a risk premium, right?

[00:08:22] First of all, you might ask, didn't the market know this already?

[00:08:26] Well, before Farmer and French and even before others in the 80s, quote, discovered this value premium, people like Benjamin Graham and Mauren Buffett had been value investors for decades.

[00:08:39] So it wasn't like it was a brand new idea.

[00:08:42] But once this stuff gets published, a lot of people might say, hey, this is a good thing.

[00:08:48] I'm going to add assets.

[00:08:51] So one of two things can happen.

[00:08:53] If you're a risk-based premium, then that premium should shrink, right?

[00:08:59] Because more people are buying it.

[00:09:02] But it should never disappear, at least if markets are logical.

[00:09:07] Because if it's risk-based, there should be a premium.

[00:09:09] But premiums are time-varying depending upon the economic regime, right?

[00:09:15] And if the economy is doing well, then the value stocks are less risky.

[00:09:20] If the economy is doing poorly, then they become more risky.

[00:09:23] So the premiums should jump up and down.

[00:09:27] Unfortunately, as we just said, there aren't good predictors.

[00:09:31] Now, the question is, what happens when that premium moves, right?

[00:09:38] Well, if lots of money flows in, the premium shrinks.

[00:09:42] Let's just say we're at a starting point when PEs for growth stocks are 20 and value is 12.

[00:09:50] Well, if money is flowing in and coming out of growth, the PEs relatively shrinker will be maybe 18 for growth and 14 for value.

[00:10:01] So that means the value premium has gotten smaller, but it's still there.

[00:10:06] Okay.

[00:10:06] So that's what should happen if it's risk-based.

[00:10:10] If it's behavioral-based, it should virtually disappear.

[00:10:14] But there are, we know, limits to arbitrage like the risks of shorting.

[00:10:19] And we should talk about that because I think that's changed a lot in the last few years.

[00:10:24] Not only the risks, but the costs of shorting.

[00:10:26] Okay.

[00:10:27] So now to answer your question specifically.

[00:10:29] While it's a logical argument, if more people are investing, the premium can shrink.

[00:10:36] But the exact opposite has happened because we're in what I would call a story or narrative environment.

[00:10:44] No different than we were in the Nifty 50 era, in the era of the late 90s and the dot-com.

[00:10:51] And now we have this narrative about large growth stocks, you know, technology, whatever.

[00:10:58] Okay.

[00:10:58] And the spread has widened.

[00:11:01] So you cannot make the argument that too much money is chasing value because the spread should have come in.

[00:11:09] And Cliff Asnes and the team at AQR has written a bunch about this and wrote some papers you can find on their website on their monitor that show that the spreads, last time I remember their last analysis on this, they had reached like the late 90s level of the 99th percentile of cheapness.

[00:11:31] And then they've come back.

[00:11:33] And then they've come back since maybe they're in the 90s or 90s still.

[00:11:37] So you cannot make the argument that the value investing has become a craven.

[00:11:44] That's obviously wrong.

[00:11:47] You mentioned the narrative-based market.

[00:11:49] And that's something you hear a lot now is that people care a lot more about narrative than they do about fundamentals.

[00:11:54] And that that's a long-term thing now, that we expect that to persist and that's a problem for value.

[00:11:58] What do you think about that?

[00:11:59] I think, again, that's nonsense.

[00:12:03] You know, the problem is this.

[00:12:07] One of my most used expressions is that when it comes to judging investment performance, whether it's a strategy or a mutual fund, whatever, the typical investor, and this includes, unfortunately, even most institutional investors.

[00:12:26] And in my experience, even many professional advisors, okay, they think three years is a long time.

[00:12:34] Five years is a very long time.

[00:12:37] And 10 years, virtually infinity.

[00:12:40] And we know this is true based upon the CARES flows, based on Morningstar's ratings.

[00:12:45] We know it's true because even consultants who should know better, they look at three-year periods, maybe five, and then recommend to these endowments and state pension plans to keep shifting strategies around and firing managers.

[00:13:04] Well, the research makes very clear that the managers that they recommend hiring go on to underperform the very managers they just fired.

[00:13:16] That tells you that this idea is bad.

[00:13:20] If you're any good financial economist who are telling you when it comes to investing, it must be true that even 10 years is noise or likely to be noise.

[00:13:33] And the reason is, if it wasn't true, there'd be no risk premiums.

[00:13:37] Because all you have to do is wait three, four, five, or six years, and you're going to get your return.

[00:13:43] And if that was true, then the risk premiums would shrink dramatically, and we wouldn't see the kind of volatility we see in the market.

[00:13:52] So let me give you one good example.

[00:13:54] I wrote about this 20 years ago or so.

[00:14:00] In 1999, at the end of the year, of course, this was the dot-com bubble, and growth stocks were going through the roof, and value was dead.

[00:14:10] And Warren Buffett was declared, like an idiot.

[00:14:14] He doesn't know better.

[00:14:15] Time has passed them by.

[00:14:17] He had his worst relative performance during that period.

[00:14:22] At that point in time, whether you look back one, three, five, 10, or 15 years, value stocks had underperformed.

[00:14:31] There was a negative value premium.

[00:14:36] Most investors, I think we can agree, would say, that's a really long time.

[00:14:42] If you wait one year, every one of those numbers reverses, and there's a value premium in every single period.

[00:14:49] And we know that next decade, value went on to outperform dramatically.

[00:14:54] In fact, from 2000 to 2007, it had the biggest value premium ever.

[00:15:00] And we reached those kind of spreads, you know, not too long ago.

[00:15:05] And I think that's a good example that investors should keep in mind.

[00:15:11] We've seen the same thing before in bubbles, we wrote stocks in the late 20s, in the 60s, in the 90s.

[00:15:19] And it's certainly possible that we're seeing that.

[00:15:23] You have to have a very long horizon.

[00:15:26] And here's my last point on this subject, which is, I think, the most important takeaway for investors, besides having a very long horizon.

[00:15:37] You should never judge a strategy by the outcome, which is what most investors do.

[00:15:45] You should judge it by the quality of the investment decision-making process.

[00:15:50] And if your process was good, which you can question, and you get a bad outcome, all that means is the risk shoulder.

[00:15:59] And as we just discussed, 15 years is noise.

[00:16:03] And anyone who doubts that, just look at the period from 1969 through 2008.

[00:16:09] And large cap and small cap growth stocks, 40 years underperformed the 20-year treasury, which is the riskless instrument for a pension plan with nominal obligations.

[00:16:26] 40 years, do you give up on investing in growth stocks because of 40 years of data?

[00:16:34] I would hope not.

[00:16:35] But that's the perfect example of why you have to understand that all risk assets are going to experience long periods of underperformance.

[00:16:47] And that doesn't mean you should avoid investing in them.

[00:16:53] What it means is you should hyper-diversify so you don't get stuck wholly owning the thing that is done for worse,

[00:17:02] which always happens after periods of high valuations when everyone thinks there's no risk like investing in technology, et cetera.

[00:17:13] This next one comes from our interview with Oswalt Demodaran.

[00:17:16] And he had made the point that, you know, back in the 1970s, if you wanted to run a Ben Graham screen, you had to go to a physical location.

[00:17:22] You had to find a book.

[00:17:23] You had to make the calculations by hand.

[00:17:25] His point was we should expect the strategy to be less effective now than it was back then because it's much easier to do.

[00:17:31] I mean, I can go to any website and run a Ben Graham screen in about two seconds now.

[00:17:35] Do you think there's anything to that?

[00:17:36] Absolutely.

[00:17:36] We said that earlier.

[00:17:39] Once you have academic research published, you should expect the premium to shrink because more people will take advantage of it.

[00:17:49] And also, you have to be aware that premiums are time-veraring.

[00:17:52] And in fact, I think the risks are much greater to investors because of AI and high-speed computers.

[00:18:01] When I was going to college, my first year, which I'm really going to date myself now, when you wanted to test a hypothesis, like does price-to-book work, you would program it on punch cards, take it into my computer class, and hand it in.

[00:18:22] And you'd be lucky if two or three days later, you got the answer, and you couldn't run multiple tests because it was very expensive to do.

[00:18:32] So the key was how to have a hypothesis before you ran the data.

[00:18:39] Today, that is no longer required because of the access to great databases and the ability of high-speed computers.

[00:18:50] Now, you could run for almost no cost an infinite number of strategies, and then you get a data mining outcome because there may not be any causation.

[00:19:01] So you have to make sure in my book on factor investing, and also pointed this out in my book, You're a Complete Guide to Successful and Secure Retirement, and my Black Swan book.

[00:19:17] Here's the key.

[00:19:19] To minimize, you can't completely eliminate the risk of data mining outcomes, but you can minimize it by requiring six things from an investment strategy.

[00:19:30] First, there has to be a premium for you to even think about investment.

[00:19:34] Then the premium has to be persistent across long periods of time and economic regimes.

[00:19:42] So you know it wasn't just a lucky outcome.

[00:19:45] That's number one.

[00:19:46] Number two, it should be pervasive across sectors, industries, countries, regions, even asset classes.

[00:19:55] So we know value, buying what cheap works across every country in the world virtually.

[00:20:02] It has worked across industries.

[00:20:05] Okay?

[00:20:06] So you get a higher premium by buying cheap technology or healthcare stocks than you buy the higher growth stocks over the long term.

[00:20:17] So it works there.

[00:20:18] It works whether you use price-to-buck, price-to-earnings, cash flow, EBITDA, enterprise value.

[00:20:24] It has to be robust to various definitions, as we just said.

[00:20:30] And it has to survive transactions costs.

[00:20:34] It doesn't matter if you get a 4% premium on microcaps and it costs you 5% to execute.

[00:20:43] And last, there better be a good risk-based, my preference, because you can't totally arbitrage it away,

[00:20:52] or a behavioral explanation, which I'm willing to accept.

[00:20:56] I just wouldn't put as heavy an emphasis in my asset allocation for factors or strategies that are behavioral-based

[00:21:05] because they could, in theory, be eliminated.

[00:21:08] I think human behavior and limit don't change or tend not to, and limits to arbitrage make it very difficult to go short.

[00:21:19] And the recent incidences, say, with Melvin Capital and GameStop, where these, you know,

[00:21:25] Reddit investors ganged up legally to go and attack them shows how expensive that can be, right?

[00:21:33] So those criteria have to be met, all of them.

[00:21:39] Otherwise, you should not invest.

[00:21:41] So I think that, and that is directionally absolutely right.

[00:21:45] And that's why you can't just blind reinvest.

[00:21:49] You always should consider valuation and be willing to, you know, stick with the strategy

[00:21:56] if maybe the valuation are now showing, hey, the premium has now gotten smaller.

[00:22:01] And if you're not, then you should abandon that strategy because you say,

[00:22:06] I'm not willing to take a risk in owning stocks if there's a negative risk for me.

[00:22:12] And I can give you a good example.

[00:22:14] In 2000, in my opinion, there was clearly a bubble.

[00:22:19] So I think Fama is wrong in saying you don't know when a bubble exists.

[00:22:23] To me, a bubble is when the yield on PIPs, which is a totally worth for the investment

[00:22:28] if you hold to maturity, was higher than the Cape 10 inverted.

[00:22:35] So the earnings yield was like 2% or 2.5, and TIPS yields were well above that.

[00:22:41] That, to me, said there's clearly a bubble, which had to be resolved by either PEs falling

[00:22:48] with TIPS yields falling.

[00:22:50] And if TIPS yields solved, you'd be very happy with a gain on some longer-term TIPS.

[00:22:57] So hopefully that answers your question on Damodaran.

[00:23:00] It does.

[00:23:01] And I can't tell you how many times I've used that framework of your criteria in my career

[00:23:04] to explain, you know, to look at factors and to explain factors to other people.

[00:23:07] So that's been a great service to the community that you guys put that out there.

[00:23:09] I only ask that you quote myself and Andy Birkin when you get there.

[00:23:13] We always do.

[00:23:14] Well, that's great.

[00:23:14] We always do.

[00:23:15] I've seen it, Carter, all the time or reference, and I almost never see, you know, us giving

[00:23:22] credit for it.

[00:23:23] But I do take pride in the fact I believe we were the first people to put that in writing.

[00:23:30] Another point Damodaran made was this idea of the rise of winner-take-all businesses.

[00:23:34] So he gave the example of Airbnb with hotels.

[00:23:36] And he said, you know, if that's becoming a winner-take-all business, an Airbnb is eventually

[00:23:41] going to dominate, and we can obviously argue that.

[00:23:43] But are the other hotels, which might be sitting in the value stock range, are those worth less

[00:23:49] than they were before?

[00:23:50] And so maybe they look cheap, but they're not actually cheap as technology takes over

[00:23:53] and we get more of these winner-take-all businesses.

[00:23:55] That's assumes, that statement assumes that the market is ignorant and doesn't, can't foresee

[00:24:01] it and hasn't already priced that.

[00:24:03] And is the market right or wrong?

[00:24:06] And you're betting, let's say in that case, one, that Airbnb will be the winner.

[00:24:12] And number two, that it will in fact knock out the others, right?

[00:24:17] And the market is stupid and doesn't recognize it.

[00:24:20] And you're smarter than everyone else.

[00:24:22] If that is really true, then what we should be seeing is more evidence that active managers

[00:24:30] are outperforming and the exact opposite, as we wrote with Andy Birkin in The Incredible

[00:24:38] Shrinking Alpha, the percentage of active managers who are outperforming has been declining

[00:24:44] rapidly.

[00:24:45] And when I wrote my first book in 1998, it came out virtually the same month as Ellis' book

[00:24:53] Winning the Loser's Game.

[00:24:55] And when he wrote his book, about 20% of active managers were showing statistically significant

[00:25:02] alpha, okay?

[00:25:04] By 2010, just 12 years later, Fondland French published the paper showing that number pre-tax,

[00:25:12] of course, here, was down to about 2%.

[00:25:15] Other papers since have confirmed that.

[00:25:18] And so after taxes, since most of us tend to pay taxes, certainly higher net worth individuals

[00:25:25] have most of their money taxable counts.

[00:25:28] With taxes being the greatest expense, you're probably at 1%.

[00:25:32] I don't know about you, Jack, but I don't like odds of 99 to 1 against me.

[00:25:38] I don't buy that argument, even if he's right in terms of that is going to happen.

[00:25:45] But I would argue that that argument has always been made, that someone's going to be a winner.

[00:25:51] And the market drives those prices to often crazy levels.

[00:25:58] And digital equipment and Data General and Polaroid and Kodak were dominant in their industries.

[00:26:05] And every one of them is gone then.

[00:26:08] They were the Airbnbs of their day, right?

[00:26:13] Yeah, absolutely.

[00:26:15] And the next one kind of is a parallel to that, which is this idea that value is underweight technology.

[00:26:20] Because if you run an unconstrained value strategy today, and you look at the weighting of technology in the S&P 500,

[00:26:26] you're going to be way below that.

[00:26:27] And the idea is if technology continues to be more and more and more of the market because it does so well,

[00:26:33] we're hamstringing ourselves as value investors by having this under-exposure to technology.

[00:26:37] So what do you think about that?

[00:26:38] Yeah, so I would make two arguments.

[00:26:40] First, the evidence is, I think most people would get this wrong.

[00:26:45] If you ask the average investor which industries have had over the 100 years the highest returns,

[00:26:52] they would all say either healthcare or technology.

[00:26:56] And it's the sin stocks, which are all value stocks of gambling, tobacco, alcohol.

[00:27:02] And that's true in other countries like the UK.

[00:27:05] So that's falsehood number one.

[00:27:09] But the other way to address this problem, which I think is logical,

[00:27:14] is you can address that in the way AQR does and to say we're going to be industry neutral.

[00:27:21] So what you do is you say technology, say, is 20% of the market cap.

[00:27:29] We're going to hold a portfolio of value stocks that's 20% and we'll buy the cheap stocks in the value sector

[00:27:40] or the value industry.

[00:27:42] The problem has also become another one, though, which we should mention, is 50 years ago, value companies and companies in general looked very different.

[00:27:54] They tended to be mostly physical assets.

[00:27:58] So book value was a good measure.

[00:28:01] And it was good because it was also very stable.

[00:28:04] So when you go to implement, you don't have a lot of turnover.

[00:28:07] P.E.s are much more volatile and people forget, even if P.E. was a little better predictor of returns than price to book,

[00:28:16] it would be a lot more volatile.

[00:28:18] You have a lot more turnover, a lot more trading costs, and you may end up with low return,

[00:28:23] which is why Fama and French originally chose price to book.

[00:28:27] They've adjusted to include things like profitability.

[00:28:31] Others, and the evidence shows you're much better off in almost everything using an ensemble method.

[00:28:37] They're using multiple metrics because they all work.

[00:28:41] They're robust for various definitions.

[00:28:44] And in different eras, different metrics work better.

[00:28:48] So you get a diversification benefit and smooth it out.

[00:28:52] But here we're talking about now you have intellectual capital, which is often the greatest asset of companies.

[00:28:59] And that doesn't show up because it's not accounted for.

[00:29:03] So it doesn't show up in the price to book.

[00:29:06] So what some people have done, and it's very tricky, is to put that back on the balance sheet and then depreciate it,

[00:29:13] just like you would with physical capital.

[00:29:17] And that would have helped somewhat to address the value premium.

[00:29:22] It would not have solved the problem because most of the outperformance in growth stocks was not earnings growth being much faster.

[00:29:32] It was multiple expansion, which can't be repeated unless you think trees go to the sky.

[00:29:38] But that is a way to try to address it.

[00:29:42] The hard part is to measure how much of that intellectual capital will be realized and how much will be wasted on bad investments.

[00:29:53] You really don't know until often 10 years later.

[00:29:56] So it's very tricky.

[00:29:58] DFA or dimensional, for example, has decided not to be wrapped as well.

[00:30:03] So other metrics can help address that, looking at cash flows, for example.

[00:30:10] Just as an aside on your point about running value sector neutral, what are your thoughts on that?

[00:30:13] Like when we had Wes Bray on, his idea was if you're running it long short, you probably should run it sector neutral.

[00:30:18] If you're running it long only, you should probably run it more unconstrained.

[00:30:21] Would you agree with that?

[00:30:23] Here's the problem, and I won't argue it all with Wes.

[00:30:27] I would hate to be on the other side of an argument with Wes or Cliff Asness.

[00:30:32] So both of them are smart people, and they disagree.

[00:30:37] Certainly we know that over time, different industries dominate value.

[00:30:42] Some years it's oil stocks.

[00:30:44] Some years it's automobile stocks.

[00:30:46] And you want to own them because they're really cheap and distressed.

[00:30:51] Right?

[00:30:52] And that's how value premium has gotten so big.

[00:30:55] And it's also why the value strategy has worked.

[00:30:59] Because most investors, what are you, crazy?

[00:31:02] I'm not going to own these lousy auto companies.

[00:31:05] And they can't take it.

[00:31:06] And after three years of bad performance, they bail out.

[00:31:10] And we know that reversion to the mean of abnormal earnings is the most powerful force in the river.

[00:31:18] So remind me, because I want to come back to that point.

[00:31:21] This is really important for investors to hear.

[00:31:25] Okay.

[00:31:25] So human behavior is critical.

[00:31:28] In fact, if you're an investment advisor, I tell people you're not really managing money.

[00:31:33] You're managing people and their behaviors.

[00:31:36] Because most people make these mistakes, not only of recency bias, but relativity, comparing their portfolio to something else which should be irrelevant, or you would own that only.

[00:31:49] Okay.

[00:31:49] So if you are set to neutral, you reduce the risk of tracking variance, which is a big behavioral problem for investors.

[00:32:02] You won't eliminate it, of course.

[00:32:05] Right?

[00:32:05] Right.

[00:32:06] Because, but you will reduce it because you will own more of, in this case, technology.

[00:32:13] I don't think it would have prevented lots of investors from bailing, but it might have prevented some.

[00:32:18] So if you believe in human behavior being the problem, you know, I think that's a good way to go.

[00:32:27] And I think because of changes in regulation and stuff, that would be my preference.

[00:32:33] But, you know, I won't argue against the other strategy because there is logic to it.

[00:32:41] I was excited to have you on because I wanted to ask you about a recent research paper that came out that we actually had the authors of the paper on.

[00:32:47] And it sort of called into question, I think, the last part of your evaluation criteria for factors, which is the intuitive part of it.

[00:32:54] And it was Andrew Chen and Alejandro Lopez Lira.

[00:32:57] And what they did is they looked at, they put factors into buckets.

[00:33:00] They looked at factors with a risk-based explanation, a behavioral explanation, and then factors effectively with no explanation.

[00:33:06] And they looked at them, you know, they tested them, and then they looked at them out of sample.

[00:33:10] And what the conclusion was, and you can probably explain the paper better than I can, but the conclusion was there really wasn't much of a difference there in terms of the risk-based factors, the behavioral-based factors, and the ones with no explanation.

[00:33:21] So it calls into the question the idea of do we need an explanation of why these factors work for them to continue to work out of sample?

[00:33:28] So I just want to get your thoughts on that.

[00:33:29] I believe that's absolutely, Adil, and I think they drew the wrong conclusion.

[00:33:34] I'm not arguing with the findings of the paper at all.

[00:33:37] Well, the findings are what they are, right?

[00:33:40] And you don't throw them out if they don't happen to agree with your views.

[00:33:44] So the first thing is we know that there are limits to arbitrage and the risks of shorting and the cost.

[00:33:51] So behavioral explanations can persist.

[00:33:54] I mean, Fama, who is the father of efficient markets, he fought against momentum and including it in strategies for decades because there is clearly no good risk-based argument.

[00:34:07] It's purely behavioral, right?

[00:34:10] And even he eventually, maybe with Ken French pushing him, DFA decided, yeah, the mensal, we're going to incorporate momentum signals, at least eliminating buying stocks that are crashing from our portfolio until the negative momentum ceases.

[00:34:31] So a growth stock that became value, they would buy it.

[00:34:36] But now they would say, no, we will not buy it.

[00:34:40] We'll delay.

[00:34:41] It'll be in our eligible list for we won't buy it until that negative momentum stops.

[00:34:47] And stocks that are growing rapidly and they leave value, we would have sold them early.

[00:34:53] Now we may delay the trade a little bit until that positive momentum.

[00:34:59] So they prioritize things in that way.

[00:35:03] So because something's behavioral doesn't mean it can't persist.

[00:35:09] That's number one.

[00:35:11] On the value side being risk stories, okay?

[00:35:15] Well, we've just discussed that when something's published, you should expect the premiums to come down because money is going to flow in, right?

[00:35:25] It doesn't mean that the premium doesn't exist.

[00:35:30] It means it's likely to have shrunk because more people are aware, more money is going to come in.

[00:35:36] If there's a risk-based premium, the logic is you cannot arbitrage it away.

[00:35:44] So the only question is, is it really a risk-based premium?

[00:35:48] Is there logic behind it?

[00:35:50] And you want to look for the academic papers that would support that and would value, just to add this, there are really good papers showing a risk-based premium.

[00:36:02] And there are really good papers showing a behavioral one, which is mostly that growth stocks are persistently overvalued.

[00:36:13] And now I'll come back to the point I mentioned earlier, which is on the reversion to mean of abnormal earnings growth.

[00:36:20] The reason, by far, that growth stocks tend to underperform in the long term is that investors persistently, including analysts,

[00:36:33] overestimate the ability for abnormal earnings growth to persist.

[00:36:39] That's this Airbnb argument, if you will, that Damodaran has made.

[00:36:45] So let's say that typically earnings are growing at 6% a year.

[00:36:51] Okay, so 3% real, 3% inflation.

[00:36:55] And you're growing at 26%.

[00:36:58] So you're growing 20% faster.

[00:37:01] Falmer and French wrote a paper long ago, I think about 20 years ago or so, maybe even 98, so 26 years ago now,

[00:37:10] which found that abnormal earnings growth, both positive and negative, tend to revert to the mean at a rate of about 40% per annum.

[00:37:24] And that's very logical because you have the abnormal earnings growth.

[00:37:29] What does that do?

[00:37:30] It attracts competition.

[00:37:31] If you have negative abnormal earnings growth, what happens?

[00:37:35] Companies exit the industry, capacity gets struck down.

[00:37:39] And the negative earnings, the negative side tends to revert even faster than the positive reverts down.

[00:37:48] So they look at the estimates from analysts, the IDES kind of data,

[00:37:56] and they find that the analysts persistently overestimate this growth rate.

[00:38:04] In fact, they're underestimating the reversion to the mean.

[00:38:07] And that is ultimately what causes P-E ratios to come down.

[00:38:13] And that's why growth underperforms.

[00:38:16] Investors are overconfident about the ability of companies to either grow persistently or to forget that the economy, you know,

[00:38:27] causes, you know, contraction in industry.

[00:38:30] So supply shrinks.

[00:38:31] Just think about any mining stuff.

[00:38:34] What happens if, you know, some mineral is in short supply?

[00:38:40] Well, it takes a long time to open a mine, get regulatory approval.

[00:38:45] You know, it may take five or 10 years before you get the ore out of the ground.

[00:38:49] But then all of a sudden, prices go up and up.

[00:38:51] And then all of a sudden, the supply comes on board.

[00:38:54] And the prices go crashing down because you got new supply.

[00:38:59] So the earnings revert to the meat.

[00:39:02] And the same thing happened when prices are too low.

[00:39:06] Capacity gets shut down.

[00:39:07] May take five years to, you know, to restart a mine or whatever.

[00:39:12] And so you get these cycles.

[00:39:14] And so every industry has these issues.

[00:39:17] And I think this gets overlooked and investors chase whatever is done well when.

[00:39:25] What do you think of, what do you make of these factors that we can't come up with a good explanation for?

[00:39:30] Like in their testing, they held up in the data.

[00:39:32] They held up out a sample.

[00:39:33] You know, they were doing things like dividing cost of goods sold by accounts receivable or something.

[00:39:36] You know, they were just combining everything together.

[00:39:38] But I mean, is there an argument, especially in a world of machine learning,

[00:39:41] that we're going to see more and more of that stuff being used?

[00:39:43] Or I mean, should that stuff be used?

[00:39:44] No, that's the real danger of artificial intelligence.

[00:39:48] The outcomes are very likely to be data mined.

[00:39:53] You're torturing the data until it confesses is the expression.

[00:39:57] And that's why I would be extremely careful to never invest in any strategy that doesn't need all six of the criteria.

[00:40:07] Not even if it meets three or four of them.

[00:40:09] It's got to need all six because that risk is there.

[00:40:13] It's very easy to create a good backtest, but it's meaningless.

[00:40:18] The best example, and this is back in the 90s, I think.

[00:40:22] Somebody, an economist ran the UN's database on economic statistics.

[00:40:29] And he found the best predictor of the S&P 500 was butter production and Bengals gas.

[00:40:37] Now, I think any rational person would not believe that that has any predictive value and bet money on it.

[00:40:45] But that's exactly what can happen.

[00:40:47] So you should ignore it.

[00:40:49] Don't, you know.

[00:40:50] But it's a huge risk out there with these products because of artificial intelligence.

[00:40:57] I just have one more topic here I wanted to cover before I hand it back to Justin.

[00:41:00] I want to ask you about the rise of passive investing.

[00:41:02] It's something we've talked about a lot in the podcast.

[00:41:03] It's something I've been thinking about a lot.

[00:41:05] And particularly the question, does this impact the market in some way?

[00:41:09] I mean, many people argue it does not.

[00:41:10] But as I think about it more and I think about the idea that, you know,

[00:41:13] if the liquidity of these big companies is not scaling with their size,

[00:41:17] is it possible that more and more people putting money into their 401ks

[00:41:21] is increasing the value of these bigger companies relative to the rest of the market?

[00:41:25] I mean, do you think there's anything to that?

[00:41:26] No, I don't.

[00:41:30] But here's what I think has happened.

[00:41:32] First of all, we have a lot of good data on this

[00:41:36] because the trend to passive investing began in the late 70s with John Bogle.

[00:41:42] I think 77, they create the first index one, right?

[00:41:45] For the public.

[00:41:47] There was a private one run by Wells Fargo for some Illinois pension plan, if I remember.

[00:41:53] By the late 90s, it had finally begun to pick up steam, but it was in single digits.

[00:42:00] But today it's, I've seen various estimates.

[00:42:03] Let's say passive investing is 50%.

[00:42:06] So you heard these arguments early on that the market would become less efficient.

[00:42:13] And by that, I mean that it would be easier for active managers to win

[00:42:19] because you have so many people ignoring valuation fundamentals.

[00:42:25] They're just blindly following.

[00:42:27] Well, if that were true, then how do you explain the fact that over this last 26 years,

[00:42:35] we've seen the percentage of active managers outperforming collapsing?

[00:42:42] So here's another point.

[00:42:45] Jack, I'll just ask you because you're a highly knowledgeable investor.

[00:42:49] How many mutual funds were there in the 1950s?

[00:42:54] A lot less, but I don't even know the answer to that.

[00:42:57] It's a rough number.

[00:42:57] Today, let's say it's roughly 10,000 and maybe there's 10,000 hedge funds,

[00:43:02] just rounding big picture.

[00:43:04] So like 20,000 investment vehicles.

[00:43:07] There's probably more, but let's just use that.

[00:43:09] How many mutual funds were there in the 1950s?

[00:43:14] Something in the hundreds, maybe?

[00:43:15] About a hundred.

[00:43:17] There was almost no hedge funds, like maybe a couple were around.

[00:43:21] And even then, the markets were relatively efficient.

[00:43:27] Not more than we would randomly expect outperforming persistently.

[00:43:33] Now you've got tens of thousands competing.

[00:43:37] And would you argue that today's investors are much smarter,

[00:43:42] have more knowledge of capital market theory,

[00:43:46] have faster or slower computers, more access to databases?

[00:43:52] Right?

[00:43:53] They all clearly, they have PhDs in finance or nuclear physics.

[00:43:58] They're rocket scientists.

[00:43:59] They have the best databases.

[00:44:02] And yet the markets were efficient with a hundred investors,

[00:44:06] made it tough.

[00:44:07] We've got tens of thousands.

[00:44:09] The prices are today, I would argue, still the most rational,

[00:44:16] the best estimates of the right price.

[00:44:18] Now, so that means active management is even more of a loser game

[00:44:23] than it ever was.

[00:44:24] So that's one argument about efficiency.

[00:44:28] But the other argument is this.

[00:44:32] Clearly have less people who are actively trading.

[00:44:37] Right?

[00:44:38] Okay.

[00:44:39] Oh, and by the way, 50 years ago,

[00:44:42] what percentage of stocks were held by individuals

[00:44:45] in their own accounts that they were managing?

[00:44:48] What was in the first?

[00:44:50] I'm probably like, oh, individuals, a very small percentage.

[00:44:55] No.

[00:44:55] Maybe like...

[00:44:55] 50 years ago, Justin, it was 90%.

[00:44:59] 90%, okay.

[00:45:00] Or maybe I need to go back a little further,

[00:45:02] make it so the 1950 or so.

[00:45:05] So coming out of World War II,

[00:45:07] only 10% of money held in stocks was held in investment vehicles.

[00:45:13] It was on an individual brokerage.

[00:45:15] Oh, interesting.

[00:45:15] Okay.

[00:45:16] Yeah.

[00:45:16] Today, that number, of course, has probably flipped.

[00:45:20] And clearly, the institutional investors managing the money

[00:45:23] are more sophisticated than the individual investors,

[00:45:26] who we know dramatically underperformed the market.

[00:45:29] So the market, clearly, it's harder to outperform

[00:45:32] because you're competing.

[00:45:35] The competition is much tougher.

[00:45:37] In 1950s, Buffett was competing against me, and he'd kill me.

[00:45:42] Today, Buffett is competing against Renaissance technology,

[00:45:46] J.P. Morgan.

[00:45:47] I mean, all these highly sophisticated investors,

[00:45:51] world-class mathematicians, all the best data and tools.

[00:45:54] It's much harder to outperform.

[00:45:57] Now, here's the problem.

[00:46:00] Markets have also gotten more efficient in trading costs

[00:46:04] if you're trading small amounts.

[00:46:07] Commissions are way down.

[00:46:09] Bid-offer spreads are way down,

[00:46:12] especially when we went from trading in quarter or half points

[00:46:15] to deciles and pennies today.

[00:46:19] So the spreads are narrower.

[00:46:21] But because of the narrowing in spreads,

[00:46:24] and this is what I think the market hasn't focused on enough,

[00:46:29] because of those narrowing in spreads,

[00:46:31] there are no more market makers

[00:46:33] because they have no incentive to take positions

[00:46:36] where before they did because there was a good spread

[00:46:39] that they could take advantage of

[00:46:42] and be willing to take a big position.

[00:46:44] So if you're trading 100 shares,

[00:46:46] you're getting very cheap execution.

[00:46:49] You're an active manager,

[00:46:50] and you got a 10 million share position in some company.

[00:46:54] Good luck trying to sell that stock.

[00:46:56] You can sell a few hundred shares or a few thousand

[00:46:59] at the bid price,

[00:47:01] and the price will start dropping very quickly

[00:47:04] as people figure out you're trying to do it.

[00:47:07] So market impact costs have gone way up.

[00:47:10] So here's my argument.

[00:47:14] While information may be less available

[00:47:17] because there aren't so many investigating

[00:47:20] these smaller companies, et cetera,

[00:47:23] the cost of implementing that

[00:47:26] and exploiting that information

[00:47:28] has gone way up,

[00:47:30] offsetting any benefit in informational efficiency.

[00:47:35] And I think the costs and risks of shorting have gone up,

[00:47:38] so you're going to see a lot less people betting on shorting,

[00:47:43] and those people who short are the most sophisticated investors

[00:47:47] who keep prices more rational.

[00:47:50] So I think you're going to see now

[00:47:52] more persistent overpricing,

[00:47:55] which to me is all the lottery stocks,

[00:47:58] the high-growth stocks,

[00:47:59] is more risk of bubbles

[00:48:00] because you can't correct those mispricings.

[00:48:04] Underpricings are easy to correct.

[00:48:06] You just buy, and all you can lose is 100% of your money.

[00:48:10] You go short, you can lose thousands of percent,

[00:48:13] and you can go bankrupt

[00:48:14] even if you're right in the long term,

[00:48:16] but you're dead because of the margin calls.

[00:48:20] So that's the problem here.

[00:48:23] I think in one sense,

[00:48:25] the markets are more efficient

[00:48:26] because it's harder to win,

[00:48:28] and therefore the right strategy

[00:48:30] is only to be a systematic investor.

[00:48:33] Don't try to pick stocks or time the market.

[00:48:37] Your odds are succeeding or minuscule,

[00:48:40] but at the same time,

[00:48:42] you're going to see more mispricing,

[00:48:45] particularly in the smaller stocks.

[00:48:47] You can easily go short Microsoft.

[00:48:49] You can't get squeezed there.

[00:48:51] Go short some stock with a few hundred million market cap,

[00:48:55] and it's easy for them to gang up.

[00:48:58] They discover they don't even have to buy the stock.

[00:49:00] They buy some out-of-the-money calls,

[00:49:03] and gamma traders who are riding that other side

[00:49:06] have to go in and start to hedge their position,

[00:49:09] and that pushes the stock up,

[00:49:11] and that more people jump in,

[00:49:13] and boom,

[00:49:14] and Melvin Capital loses $5 billion

[00:49:16] on a company that clearly was way overvalued,

[00:49:19] but they couldn't hold their position.

[00:49:22] It's a really interesting...

[00:49:24] So now what you would have

[00:49:26] is a paper by a University of Chicago professor.

[00:49:30] I forgot his name.

[00:49:31] I'm stating for the moment.

[00:49:36] Anyway, it's the inelastic markets hypothesis.

[00:49:40] So the markets are becoming more inelastic

[00:49:43] because of this less liquidity,

[00:49:47] and the cost and risks of shorting,

[00:49:50] which allows more mispricing,

[00:49:53] particularly of these lottery-like stocks,

[00:49:56] the ones in bankruptcy,

[00:49:57] penny stocks,

[00:49:58] hyper-growth stocks without profitability

[00:50:01] that people are just betting on.

[00:50:05] It seems like about a year ago,

[00:50:08] if I had my timing right,

[00:50:09] that more investors were talking about

[00:50:11] the risk of the concentration in the market.

[00:50:14] So a handful of companies making off,

[00:50:15] you know,

[00:50:16] whatever it was,

[00:50:17] 30% of the overall market,

[00:50:20] something like the S&P.

[00:50:20] But I just did the math,

[00:50:22] and right now,

[00:50:23] there's seven basically tech companies

[00:50:25] that make up about 32%

[00:50:27] of the S&P as of today,

[00:50:29] even though your average stock

[00:50:30] has kind of caught up,

[00:50:31] maybe a little bit here,

[00:50:32] over the past month or so.

[00:50:34] But how do you think investors

[00:50:36] should think about this

[00:50:38] concept of concentration

[00:50:39] and market cap-weighted indices?

[00:50:40] Yeah.

[00:50:41] So I wrote about this in my book,

[00:50:43] Reducing the Risk of Black Swans,

[00:50:45] because concentration creates risk

[00:50:50] of big crashes.

[00:50:53] Every time in history,

[00:50:55] which doesn't mean it necessarily

[00:50:56] will happen now,

[00:50:57] or it might happen in 10 years,

[00:50:59] but every time we've had

[00:51:01] this concentration,

[00:51:02] it's been then succeeded

[00:51:05] by a long period of underperformance

[00:51:08] of those kinds of companies,

[00:51:12] 60s, 90s.

[00:51:13] And my guess is,

[00:51:14] that's what we're likely,

[00:51:16] but not certain,

[00:51:17] to see now.

[00:51:19] If you,

[00:51:20] the problem for investors,

[00:51:21] which I wrote about in my book,

[00:51:23] and I really urge your listeners

[00:51:24] to get a copy and read that,

[00:51:27] is this.

[00:51:28] If you ask Justin,

[00:51:30] the average,

[00:51:31] not only investor,

[00:51:32] but I've done this,

[00:51:34] the average investment advisor,

[00:51:35] and said you have a client

[00:51:37] with $100,000,

[00:51:39] sorry,

[00:51:39] $1,000,000,

[00:51:40] say,

[00:51:41] in a portfolio,

[00:51:42] that was 60-40

[00:51:44] stocks and bonds,

[00:51:46] how much of your risk,

[00:51:48] what percentage of the risk

[00:51:49] in the portfolio

[00:51:50] is in stocks,

[00:51:52] the vast majority,

[00:51:53] say,

[00:51:54] 60%,

[00:51:55] right?

[00:51:56] Because you've got

[00:51:57] $600,000 in stocks,

[00:51:59] so your risk,

[00:52:00] that's really wrong.

[00:52:03] The actual number

[00:52:04] is much closer to 90%,

[00:52:06] because the stocks

[00:52:08] are so much more riskier

[00:52:10] than, say,

[00:52:11] bonds.

[00:52:12] If you own a typical

[00:52:13] midterm,

[00:52:14] say,

[00:52:15] five-year treasury,

[00:52:16] the vol is about

[00:52:18] four,

[00:52:18] roughly.

[00:52:20] And so,

[00:52:20] 40% times four

[00:52:23] is 160

[00:52:24] risk points,

[00:52:26] and volatility

[00:52:28] of a stock portfolio

[00:52:29] is roughly 20,

[00:52:30] so 60 times 20

[00:52:33] is 1,200 risk points.

[00:52:36] So now I add

[00:52:37] those two numbers up,

[00:52:38] and you can see

[00:52:39] almost 90%

[00:52:40] of the risk is there.

[00:52:42] And that's how

[00:52:43] you can get killed

[00:52:44] in years like

[00:52:45] 73-4,

[00:52:47] 2000-02,

[00:52:49] and especially

[00:52:49] in periods

[00:52:50] when it's inflation

[00:52:51] causing the bear market,

[00:52:53] because now your stocks

[00:52:54] and your bonds

[00:52:55] get destroyed.

[00:52:56] So I'm a big believer

[00:52:58] that you should own

[00:52:59] lots of other assets

[00:53:01] that have very different

[00:53:03] risk profiles.

[00:53:04] So adding things

[00:53:06] like value,

[00:53:08] momentum,

[00:53:09] other strategies

[00:53:10] like reinsurance,

[00:53:12] private credit,

[00:53:13] private real estate,

[00:53:14] where you're getting

[00:53:15] big illiquidity

[00:53:16] premiums even,

[00:53:18] clearly earthquakes

[00:53:20] and hurricanes

[00:53:21] don't cause bear markets,

[00:53:23] and bear markets

[00:53:24] stone-caused earthquakes

[00:53:25] and hurricanes.

[00:53:26] So there's a logical

[00:53:27] reason to own it.

[00:53:29] It's a logical

[00:53:30] risk premium

[00:53:31] that's hundreds of years

[00:53:33] of dating there.

[00:53:34] I would own

[00:53:35] long-short strategies

[00:53:36] like eight QRs,

[00:53:38] because they're

[00:53:38] uncorrelated

[00:53:39] to the market,

[00:53:40] and they're uncorrelated

[00:53:41] to bonds as well.

[00:53:43] And they have

[00:53:43] inflation hedges in them,

[00:53:45] because as interest rates

[00:53:46] go up,

[00:53:47] they're sitting on

[00:53:47] that collateral.

[00:53:48] Same thing

[00:53:49] for reinsurance.

[00:53:50] Private credit

[00:53:51] is all floating rate debt,

[00:53:53] so you get rid of

[00:53:55] the duration risk,

[00:53:56] you're taking

[00:53:57] some credit risk,

[00:53:58] but you're getting

[00:54:00] a massive

[00:54:00] illiquidity premium.

[00:54:02] And if you stick

[00:54:03] to the high

[00:54:03] credit quality,

[00:54:05] like in Clifford's fund,

[00:54:07] it's all

[00:54:07] seen,

[00:54:08] cured,

[00:54:09] and backed

[00:54:10] by private equity.

[00:54:11] Average LTV

[00:54:12] is about 40%.

[00:54:14] Historical defaults

[00:54:16] are less than 1%.

[00:54:18] Recoveries

[00:54:19] are like 70%.

[00:54:21] So you don't have

[00:54:22] significant risk there,

[00:54:23] but you're getting

[00:54:24] a massive premium

[00:54:25] that is unrelated

[00:54:26] to the economic

[00:54:28] cycle risk

[00:54:29] of either stocks

[00:54:30] or bonds.

[00:54:31] So my own

[00:54:32] portfolio

[00:54:33] looks much more

[00:54:34] like that of the

[00:54:35] L's and Harvard's

[00:54:36] of the world,

[00:54:36] as I've moved

[00:54:37] from having

[00:54:39] very low allocations

[00:54:40] to alternatives

[00:54:41] like 10%

[00:54:42] 10 years ago

[00:54:43] to about

[00:54:44] 50%

[00:54:45] today,

[00:54:46] because I believe

[00:54:48] you should be

[00:54:49] a hyper-diversifier,

[00:54:50] and innovation

[00:54:52] has driven

[00:54:53] the costs

[00:54:53] way down.

[00:54:54] Let me just

[00:54:55] give one

[00:54:55] simple example.

[00:54:57] Say you're

[00:54:58] an investor

[00:54:59] in a BDC,

[00:55:00] a business

[00:55:01] development company

[00:55:02] doing private credit,

[00:55:03] let's assume

[00:55:04] for argument's sake,

[00:55:05] it's a well-run

[00:55:06] business

[00:55:07] with focus

[00:55:08] on high quality

[00:55:10] like an Aries,

[00:55:12] something like that.

[00:55:12] Well,

[00:55:13] these funds

[00:55:14] were typically

[00:55:14] charging 2 and 20.

[00:55:16] Let's just say

[00:55:17] you could get 15%.

[00:55:19] Well,

[00:55:20] 20% of 15 is 3,

[00:55:22] 2% fees,

[00:55:23] you're at 5,

[00:55:24] now you're getting 10,

[00:55:26] you're giving up

[00:55:27] most of,

[00:55:27] if not all,

[00:55:28] of the premium

[00:55:30] to the sponsor.

[00:55:32] So I didn't invent.

[00:55:33] Today,

[00:55:34] the Clifford

[00:55:34] Fund

[00:55:35] effectively

[00:55:36] has an expense

[00:55:37] ratio

[00:55:38] of about

[00:55:39] 1 and a quarter

[00:55:39] once you adjust

[00:55:40] for the leverage,

[00:55:41] which they don't charge on,

[00:55:43] they only charge

[00:55:43] on net assets,

[00:55:45] not gross,

[00:55:46] and there's no count.

[00:55:47] Today,

[00:55:48] that fund is yielding

[00:55:49] 11.5%,

[00:55:50] so you're getting

[00:55:54] a massive risk premium

[00:55:55] and a Vanguard

[00:55:56] high-yield fund

[00:55:57] which has worse

[00:55:58] credit risk

[00:55:59] is yielding less,

[00:56:00] I love,

[00:56:00] something like 7,

[00:56:02] maybe 7.5%.

[00:56:03] So,

[00:56:04] you got the ratio risk,

[00:56:06] you got more

[00:56:06] credit risk,

[00:56:08] and then you're

[00:56:09] giving up this

[00:56:10] premium just because

[00:56:11] you think you need

[00:56:12] liquidity.

[00:56:13] I've yet to meet

[00:56:14] a high net worth

[00:56:15] investor

[00:56:15] taking more

[00:56:16] than their R&D

[00:56:18] that are in

[00:56:19] retirement,

[00:56:20] and you can get

[00:56:21] 20% a year

[00:56:22] at a minimum,

[00:56:23] right,

[00:56:24] because you get

[00:56:24] 5% every quarter.

[00:56:26] Yeah.

[00:56:26] They don't own it

[00:56:27] because they need

[00:56:28] liquidity.

[00:56:29] The Yales and the

[00:56:30] Harvids long ago

[00:56:31] figured out

[00:56:32] that they could

[00:56:33] exploit

[00:56:33] illiquidity

[00:56:34] premiums

[00:56:35] because they only

[00:56:36] spend by their

[00:56:37] charters,

[00:56:38] say 5% a year.

[00:56:40] So you want to

[00:56:41] look for assets

[00:56:42] where you

[00:56:42] could take

[00:56:43] risks that

[00:56:44] aren't really

[00:56:45] risk to you,

[00:56:46] at least for

[00:56:47] some significant

[00:56:49] portion of the

[00:56:49] portfolio.

[00:56:50] So I think

[00:56:51] most investors

[00:56:52] should be

[00:56:52] owning,

[00:56:52] say,

[00:56:53] at least 30%

[00:56:54] of theirs

[00:56:56] if they have

[00:56:57] access to the

[00:56:58] kind of vehicles

[00:56:59] that are in this.

[00:57:01] Within the

[00:57:02] equity portion,

[00:57:03] how do you think

[00:57:04] about international

[00:57:05] diversification?

[00:57:06] It's been a long

[00:57:08] period of U.S.

[00:57:09] over international.

[00:57:10] We've had a lot

[00:57:11] of people on the

[00:57:11] podcast that you

[00:57:12] say,

[00:57:12] you know what,

[00:57:13] U.S.

[00:57:15] especially large

[00:57:15] caps,

[00:57:16] have a lot of

[00:57:16] their revenue

[00:57:17] coming from

[00:57:17] overseas.

[00:57:18] You're getting

[00:57:18] the international

[00:57:19] exposure through

[00:57:20] the profits.

[00:57:21] Or should

[00:57:22] investors be

[00:57:23] more targeted

[00:57:24] or country

[00:57:25] specific with

[00:57:26] their international

[00:57:26] investing?

[00:57:27] What do you

[00:57:27] think on that?

[00:57:27] Well,

[00:57:28] yeah.

[00:57:28] So the

[00:57:28] argument about

[00:57:29] U.S.

[00:57:31] multinationals

[00:57:31] owned a lot

[00:57:32] of international

[00:57:33] assets,

[00:57:34] let's for

[00:57:34] argument's sake,

[00:57:35] say Ford

[00:57:37] Motor has

[00:57:38] 50% of

[00:57:39] their

[00:57:39] sales overseas.

[00:57:42] Well,

[00:57:42] so does

[00:57:43] Daimler-Benz

[00:57:43] and maybe

[00:57:45] more.

[00:57:45] Right.

[00:57:46] And the

[00:57:47] evidence shows

[00:57:48] that U.S.

[00:57:49] stocks that

[00:57:50] are multinationals

[00:57:51] tend to trade

[00:57:52] more like U.S.

[00:57:53] stocks in

[00:57:54] German and

[00:57:54] Japanese

[00:57:56] multinationals

[00:57:56] tend to trade

[00:57:57] like their

[00:57:58] stocks.

[00:57:58] So I don't

[00:57:59] buy that

[00:57:59] argument.

[00:58:00] The other

[00:58:01] argument is

[00:58:02] again this

[00:58:02] recency bias.

[00:58:04] International

[00:58:05] emerging markets

[00:58:06] far outperformed

[00:58:07] U.S.

[00:58:07] in the 70s

[00:58:08] and 80s.

[00:58:09] 90s,

[00:58:10] it went the

[00:58:10] other way.

[00:58:11] The aughts

[00:58:12] went the

[00:58:12] other way.

[00:58:13] And now for

[00:58:14] the last 15

[00:58:15] years,

[00:58:15] it's been

[00:58:15] reversed.

[00:58:16] There's no

[00:58:17] argument that

[00:58:18] anyone can

[00:58:19] make that

[00:58:20] says the U.S.

[00:58:21] can't be the

[00:58:21] next Japan.

[00:58:22] In 1990,

[00:58:23] everyone

[00:58:24] thought Japan

[00:58:25] was the

[00:58:25] only place

[00:58:26] you should

[00:58:26] invest.

[00:58:27] They had

[00:58:27] far outperformed.

[00:58:28] They were

[00:58:29] buying up

[00:58:30] Pebble Beach

[00:58:30] and Rockefeller

[00:58:31] Center.

[00:58:32] There was

[00:58:33] almost no

[00:58:34] semiconductor

[00:58:34] plants even

[00:58:35] left in

[00:58:36] the U.S.

[00:58:37] The head of

[00:58:38] Sony was

[00:58:38] on the

[00:58:39] cover, I

[00:58:40] think, of

[00:58:40] Fortune.

[00:58:41] They're going

[00:58:42] to take

[00:58:42] over the

[00:58:42] world.

[00:58:43] And their

[00:58:44] returns to

[00:58:44] Japanese

[00:58:45] stocks have

[00:58:46] been zero

[00:58:46] virtually for

[00:58:48] 34 years.

[00:58:49] And the

[00:58:51] same thing

[00:58:51] could happen

[00:58:52] to the U.S.

[00:58:53] It's possible.

[00:58:54] So the only

[00:58:55] right strategy

[00:58:56] unless you

[00:58:56] have a

[00:58:57] clear crystal

[00:58:57] wall is

[00:58:58] to diversify.

[00:59:00] Having

[00:59:00] said that,

[00:59:01] I believe

[00:59:02] that you

[00:59:03] should diversify

[00:59:04] because we

[00:59:05] don't have

[00:59:05] clear crystal

[00:59:06] wall.

[00:59:07] But you

[00:59:08] must recognize

[00:59:09] that the

[00:59:10] world is

[00:59:11] getting smaller

[00:59:12] or flatter,

[00:59:13] to use

[00:59:13] Thomas Friedman's

[00:59:15] words.

[00:59:16] So the

[00:59:16] correlations of

[00:59:18] U.S.

[00:59:19] and international

[00:59:19] emerging market

[00:59:21] have risen.

[00:59:23] So instead

[00:59:24] of, say,

[00:59:24] the correlation

[00:59:25] between emerging

[00:59:26] U.S.

[00:59:27] might have

[00:59:27] been 0.6

[00:59:28] 40 years

[00:59:29] ago, now

[00:59:30] maybe it's

[00:59:30] 0.8.

[00:59:31] And the

[00:59:32] correlation

[00:59:33] of international

[00:59:33] might have

[00:59:34] been 0.7,

[00:59:35] and now

[00:59:36] it's 0.9

[00:59:37] or something.

[00:59:38] So you

[00:59:38] still want

[00:59:39] to diversify

[00:59:40] because it's

[00:59:40] just logical,

[00:59:42] but you

[00:59:44] now need

[00:59:45] other sources

[00:59:46] of risk

[00:59:46] that add

[00:59:48] to the

[00:59:48] portfolio

[00:59:48] because

[00:59:49] international

[00:59:50] is not

[00:59:51] as effective

[00:59:52] to diversify.

[00:59:53] It's still

[00:59:53] effective,

[00:59:54] it still

[00:59:54] adds value,

[00:59:56] just not

[00:59:56] as much

[00:59:57] as it

[00:59:57] used to.

[01:00:00] What are

[01:00:01] your thoughts

[01:00:02] on artificial

[01:00:03] intelligence?

[01:00:04] Let me just

[01:00:04] ask you,

[01:00:04] have you

[01:00:05] used any

[01:00:05] of these

[01:00:06] like

[01:00:06] ChatGPT

[01:00:06] or

[01:00:07] Claude

[01:00:07] or any

[01:00:08] of these

[01:00:09] AI systems

[01:00:10] for anything

[01:00:11] that you're

[01:00:12] working on,

[01:00:12] like content

[01:00:13] or anything?

[01:00:13] Yeah,

[01:00:14] I do use

[01:00:14] it.

[01:00:15] One,

[01:00:15] when I have

[01:00:16] a question,

[01:00:17] I want

[01:00:17] to summarize

[01:00:18] something

[01:00:19] like a

[01:00:20] key

[01:00:20] technical

[01:00:21] term.

[01:00:22] you know,

[01:00:24] so I'll

[01:00:24] go in

[01:00:25] and I'll

[01:00:26] put a

[01:00:27] highlight

[01:00:27] in or

[01:00:28] a link

[01:00:29] and

[01:00:30] to

[01:00:31] put a

[01:00:32] definition

[01:00:32] say from

[01:00:33] Wikipedia.

[01:00:34] So that's

[01:00:34] what I

[01:00:34] used to

[01:00:35] do.

[01:00:35] Now I

[01:00:36] go ask

[01:00:36] Gemini

[01:00:37] and say,

[01:00:38] can you

[01:00:39] provide a

[01:00:39] short

[01:00:40] summary

[01:00:40] and I'll

[01:00:41] take it

[01:00:41] and maybe

[01:00:42] write it

[01:00:43] myself.

[01:00:43] I'll also

[01:00:44] write up a

[01:00:46] paper,

[01:00:46] I always

[01:00:46] write them

[01:00:47] first,

[01:00:48] but then

[01:00:48] I'll ask

[01:00:49] Gemini

[01:00:50] to critique

[01:00:51] it and

[01:00:52] I look

[01:00:52] at their

[01:00:53] critiques

[01:00:53] and they

[01:00:53] make some

[01:00:54] good

[01:00:54] suggestions

[01:00:55] and I

[01:00:56] incorporate

[01:00:56] it into

[01:00:57] what I

[01:00:57] write.

[01:00:58] But I

[01:00:58] never

[01:00:58] ask them

[01:00:59] to write

[01:00:59] a paper

[01:00:59] first.

[01:01:00] I think

[01:01:01] that's the

[01:01:01] wrong way

[01:01:02] to go

[01:01:02] about

[01:01:02] things.

[01:01:03] So I

[01:01:03] think

[01:01:04] it does

[01:01:05] provide

[01:01:05] value.

[01:01:06] I often

[01:01:07] find

[01:01:07] some good

[01:01:09] small

[01:01:09] suggestions

[01:01:11] from their

[01:01:13] statements,

[01:01:13] so I use

[01:01:14] it regularly.

[01:01:15] And I

[01:01:16] need to

[01:01:16] regularly

[01:01:16] to do

[01:01:17] research

[01:01:17] as well.

[01:01:20] Yeah,

[01:01:21] and I

[01:01:21] think,

[01:01:21] you know,

[01:01:21] we'll see

[01:01:22] how these

[01:01:23] types of

[01:01:24] strategies

[01:01:24] pan out,

[01:01:25] but there

[01:01:26] are some

[01:01:27] firms now

[01:01:28] that are

[01:01:29] utilizing

[01:01:30] sort of a

[01:01:31] composite

[01:01:31] approach of

[01:01:32] these large

[01:01:33] language models

[01:01:34] to actually

[01:01:34] they're kind

[01:01:35] of feeding

[01:01:36] it like the

[01:01:36] inputs of

[01:01:37] what they're

[01:01:37] looking for

[01:01:38] and types

[01:01:38] of the

[01:01:38] stocks

[01:01:39] they're

[01:01:39] looking for

[01:01:39] and then

[01:01:40] building

[01:01:40] portfolios

[01:01:42] that hold

[01:01:43] those types

[01:01:43] of securities.

[01:01:44] So it'll

[01:01:45] be interesting

[01:01:45] to see how

[01:01:46] that's

[01:01:46] right.

[01:01:46] If you

[01:01:47] have your

[01:01:48] hypothesis

[01:01:48] first,

[01:01:50] then you

[01:01:50] could test

[01:01:51] the data

[01:01:52] and test

[01:01:53] it in

[01:01:53] infinite ways

[01:01:55] and do it

[01:01:55] fast that we

[01:01:56] couldn't have

[01:01:57] done.

[01:01:57] So that's

[01:01:58] why I think

[01:01:58] we're likely

[01:01:59] to see

[01:01:59] some minor

[01:02:01] improvements

[01:02:02] in implementation

[01:02:04] because of

[01:02:05] AI.

[01:02:06] But the

[01:02:06] big

[01:02:08] impacts

[01:02:08] have already

[01:02:09] been discovered

[01:02:10] because the

[01:02:12] factors that

[01:02:12] we have

[01:02:13] that in

[01:02:14] my book

[01:02:14] on factor

[01:02:15] investing,

[01:02:16] the five

[01:02:17] for equities

[01:02:18] and two

[01:02:19] for bonds

[01:02:20] explain like

[01:02:21] 97, 98%

[01:02:23] of the

[01:02:23] variance.

[01:02:24] So how

[01:02:25] much more

[01:02:25] can you do?

[01:02:26] But you

[01:02:27] might be able

[01:02:27] to get

[01:02:28] better

[01:02:28] implementation.

[01:02:29] I know,

[01:02:30] for example,

[01:02:31] every good

[01:02:32] money manager

[01:02:33] today is

[01:02:34] using AI

[01:02:35] to do their

[01:02:36] trading.

[01:02:37] And to

[01:02:37] address my

[01:02:38] point,

[01:02:38] just to

[01:02:39] demonstrate

[01:02:39] this issue

[01:02:41] of liquidity.

[01:02:42] You're a

[01:02:43] liquidity

[01:02:43] demand that

[01:02:44] you're going

[01:02:44] to get

[01:02:44] hurt.

[01:02:45] Dimensional,

[01:02:46] for example,

[01:02:47] had told me

[01:02:47] recently,

[01:02:48] virtually all

[01:02:48] their trades

[01:02:49] today are

[01:02:50] 100 shares

[01:02:50] because they

[01:02:51] don't want

[01:02:52] anyone to

[01:02:52] see what

[01:02:53] they're doing

[01:02:54] and they

[01:02:54] want to keep

[01:02:55] their costs

[01:02:56] down.

[01:02:56] And so they

[01:02:57] just trade

[01:02:57] very patiently

[01:02:58] being a

[01:02:59] provider of

[01:03:00] liquidity

[01:03:01] rather than

[01:03:02] a taker.

[01:03:03] And that's

[01:03:03] why, for

[01:03:04] example,

[01:03:05] AQR ran

[01:03:06] a test

[01:03:06] looking at

[01:03:08] trading costs

[01:03:08] versus what

[01:03:09] the literature

[01:03:10] said,

[01:03:10] and they

[01:03:11] found that

[01:03:12] their live

[01:03:13] trading costs,

[01:03:14] which is

[01:03:15] their sample,

[01:03:16] so they know

[01:03:17] what the

[01:03:17] costs are,

[01:03:18] were like

[01:03:19] one-tenth

[01:03:19] of what

[01:03:20] the trading

[01:03:21] costs that

[01:03:21] were estimated

[01:03:22] in the

[01:03:23] literature.

[01:03:23] So that

[01:03:24] might tell

[01:03:25] you that

[01:03:25] premiums

[01:03:26] are maybe

[01:03:27] bigger than

[01:03:27] some people

[01:03:28] think,

[01:03:28] as long

[01:03:29] as you

[01:03:30] could patiently

[01:03:31] trade.

[01:03:33] So we have

[01:03:34] a new

[01:03:34] standard

[01:03:34] closing

[01:03:35] question.

[01:03:35] I'm going

[01:03:36] to throw

[01:03:36] it out

[01:03:37] here so

[01:03:37] what you

[01:03:38] have to

[01:03:38] say to

[01:03:39] this,

[01:03:39] but what

[01:03:40] do you

[01:03:40] think is

[01:03:41] the one

[01:03:41] thing that

[01:03:42] you believe

[01:03:42] about

[01:03:42] investing

[01:03:43] that the

[01:03:44] majority

[01:03:44] of your

[01:03:44] peers would

[01:03:45] disagree with

[01:03:45] you about?

[01:03:46] This was a

[01:03:46] tough one

[01:03:47] for me to

[01:03:47] come up

[01:03:48] with one.

[01:03:49] But in

[01:03:50] my book

[01:03:50] on factor

[01:03:51] investing,

[01:03:52] we limited

[01:03:52] the equities

[01:03:54] to five

[01:03:54] factors that

[01:03:56] we thought

[01:03:56] people should

[01:03:57] consider.

[01:04:00] Beta,

[01:04:00] of course,

[01:04:02] value,

[01:04:02] size,

[01:04:03] investment,

[01:04:04] and

[01:04:04] profitability

[01:04:05] or

[01:04:06] quality.

[01:04:07] Profitability

[01:04:08] is just

[01:04:08] a subcategory.

[01:04:10] Now,

[01:04:10] actually,

[01:04:11] I put

[01:04:12] more money

[01:04:13] on the

[01:04:14] size and

[01:04:14] value and

[01:04:15] beta

[01:04:15] premiums because

[01:04:17] they are

[01:04:19] risk-based,

[01:04:20] at least to

[01:04:21] some degree.

[01:04:22] There is

[01:04:22] at least a

[01:04:23] risk.

[01:04:23] There is

[01:04:24] no logical

[01:04:24] risk-based

[01:04:25] story,

[01:04:26] I think,

[01:04:27] for quality

[01:04:28] and or

[01:04:29] momentum.

[01:04:30] Momentum,

[01:04:30] we know,

[01:04:31] is under

[01:04:31] or over

[01:04:32] reaction.

[01:04:33] Quality,

[01:04:34] to me,

[01:04:35] the argument

[01:04:35] is simple.

[01:04:36] If a

[01:04:37] company is

[01:04:38] lower

[01:04:38] volatility of

[01:04:40] earnings,

[01:04:40] lower debt

[01:04:41] ratios,

[01:04:42] is a

[01:04:42] safer

[01:04:43] company,

[01:04:44] how can

[01:04:44] you argue

[01:04:45] that you

[01:04:46] should get

[01:04:47] a risk

[01:04:47] premium for

[01:04:48] it?

[01:04:48] But the

[01:04:48] data is

[01:04:49] so powerful

[01:04:50] that I

[01:04:51] don't ignore

[01:04:52] it.

[01:04:54] An

[01:04:54] investment

[01:04:55] is the

[01:04:56] same

[01:04:56] logic.

[01:04:58] So,

[01:05:00] the one

[01:05:00] I didn't

[01:05:01] put in

[01:05:03] there,

[01:05:03] but came

[01:05:04] close to,

[01:05:05] was on

[01:05:05] low

[01:05:05] volatility.

[01:05:06] A lot

[01:05:07] of

[01:05:07] advisors

[01:05:09] emphasize

[01:05:09] this low

[01:05:10] volatility

[01:05:11] strategy.

[01:05:12] And it

[01:05:12] fails the

[01:05:13] test for

[01:05:14] me,

[01:05:15] for one

[01:05:15] reason.

[01:05:16] First of

[01:05:17] all,

[01:05:17] it purely

[01:05:18] has to

[01:05:19] be a

[01:05:20] behavioral

[01:05:20] story,

[01:05:21] right?

[01:05:21] Because if

[01:05:22] something

[01:05:22] is less

[01:05:23] volatile,

[01:05:23] that's

[01:05:24] certainly

[01:05:24] one

[01:05:24] measure,

[01:05:25] but not

[01:05:25] the only

[01:05:26] measure of

[01:05:26] risk.

[01:05:27] Okay?

[01:05:28] It's less

[01:05:28] volatile,

[01:05:29] it's less

[01:05:29] risky,

[01:05:30] and therefore

[01:05:31] should have

[01:05:31] a negative

[01:05:32] risk premium.

[01:05:34] So,

[01:05:34] why do we

[01:05:35] have a

[01:05:35] premium?

[01:05:36] It's a

[01:05:36] behavioral

[01:05:37] story.

[01:05:37] Investors

[01:05:38] like to

[01:05:38] bet on

[01:05:39] these

[01:05:39] lottery

[01:05:39] stocks.

[01:05:40] They're

[01:05:41] higher

[01:05:41] beta

[01:05:42] stocks

[01:05:42] as well.

[01:05:43] They're

[01:05:43] beta.

[01:05:44] High beta

[01:05:44] stocks

[01:05:45] have

[01:05:45] god-awful

[01:05:46] returns.

[01:05:47] Okay.

[01:05:48] So,

[01:05:50] but the

[01:05:50] data is

[01:05:51] strong.

[01:05:51] So,

[01:05:51] why don't

[01:05:52] I

[01:05:53] recommend

[01:05:53] it?

[01:05:55] It's

[01:05:55] because

[01:05:56] volatility

[01:05:57] as low

[01:05:58] vol has

[01:05:58] only had

[01:05:59] a premium

[01:06:00] when it's

[01:06:01] been in

[01:06:01] the value

[01:06:02] regime.

[01:06:03] So,

[01:06:03] I think

[01:06:04] you're

[01:06:04] better off

[01:06:05] owning

[01:06:06] value

[01:06:06] stocks

[01:06:07] that screen

[01:06:07] out the

[01:06:09] junk.

[01:06:12] Low

[01:06:12] profit,

[01:06:13] focus on

[01:06:14] value that's

[01:06:15] more

[01:06:15] profitable,

[01:06:16] non-high

[01:06:17] investment,

[01:06:18] and stuff,

[01:06:18] so you

[01:06:19] don't get

[01:06:20] the other

[01:06:20] side of

[01:06:21] that

[01:06:22] behavioral

[01:06:22] trade.

[01:06:23] I think

[01:06:24] all you're

[01:06:24] doing is

[01:06:25] lowering

[01:06:25] your

[01:06:25] beta,

[01:06:26] and you

[01:06:26] shouldn't

[01:06:27] expect

[01:06:27] a

[01:06:27] premium.

[01:06:29] Low vol

[01:06:29] is good

[01:06:30] when it's

[01:06:30] cheap.

[01:06:31] Low vol

[01:06:32] is not

[01:06:32] good

[01:06:33] when it's

[01:06:34] expensive.

[01:06:35] This is

[01:06:36] a case,

[01:06:36] in my

[01:06:36] opinion,

[01:06:37] when I

[01:06:37] last looked

[01:06:38] at it,

[01:06:38] I haven't

[01:06:38] looked at

[01:06:39] it in

[01:06:39] quite a

[01:06:40] while,

[01:06:40] but when

[01:06:41] I last

[01:06:41] looked at

[01:06:42] it,

[01:06:42] all the

[01:06:43] money

[01:06:43] flowing

[01:06:44] into

[01:06:44] low

[01:06:44] vol

[01:06:45] had put

[01:06:45] it

[01:06:46] into

[01:06:46] the

[01:06:46] growth

[01:06:46] category,

[01:06:47] and guess

[01:06:48] what?

[01:06:48] Low vol

[01:06:49] has done

[01:06:49] poorly.

[01:06:51] That would

[01:06:52] be the

[01:06:52] one where

[01:06:53] maybe

[01:06:53] there's

[01:06:54] disagreement.

[01:06:57] Thank you

[01:06:57] very much,

[01:06:58] Larry.

[01:06:58] It's always

[01:06:59] a great

[01:06:59] conversation

[01:07:00] with you,

[01:07:01] and we

[01:07:02] really

[01:07:02] appreciate

[01:07:02] it.

[01:07:02] Thank you.

[01:07:03] Thank you.

[01:07:03] My pleasure.

[01:07:04] Happy to

[01:07:04] come back

[01:07:05] anytime.

[01:07:05] These are

[01:07:06] important

[01:07:06] questions,

[01:07:08] and I

[01:07:09] wish I

[01:07:09] had all

[01:07:09] the answers.

[01:07:10] I'm only

[01:07:11] somewhat

[01:07:12] confident

[01:07:12] in them.

[01:07:14] Always

[01:07:14] have to be

[01:07:15] a little

[01:07:15] humble

[01:07:15] about what

[01:07:16] our

[01:07:16] beliefs

[01:07:17] are,

[01:07:17] which is

[01:07:18] why I

[01:07:18] hyper

[01:07:18] diversify,

[01:07:19] by the

[01:07:20] way,

[01:07:20] because I

[01:07:20] know I

[01:07:21] don't

[01:07:21] have a

[01:07:21] clear

[01:07:22] crystal

[01:07:22] ball.

[01:07:24] Thank

[01:07:24] you,

[01:07:24] Larry.

[01:07:25] This is

[01:07:25] Justin

[01:07:25] again.

[01:07:26] Thanks so

[01:07:26] much for

[01:07:27] tuning in

[01:07:27] to this

[01:07:27] episode of

[01:07:28] Excess

[01:07:28] Returns.

[01:07:29] You can

[01:07:29] follow Jack

[01:07:30] on Twitter

[01:07:31] at

[01:07:31] Practical

[01:07:32] Quant,

[01:07:32] and follow

[01:07:33] me on

[01:07:33] Twitter

[01:07:33] at

[01:07:34] JJ

[01:07:34] Carbono.

[01:07:35] If you

[01:07:36] found this

[01:07:36] discussion

[01:07:37] interesting

[01:07:37] and valuable,

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