Guest User

October 1, 2026

Who Causes Stock Market Anomalies? (w/ Victor Haghani) | #429

Guest User

October 1, 2026

Victor Haghani has 40 years’ experience working and innovating in the financial markets, and has been a prolific contributor to academic and practitioner finance literature. He founded Elm Wealth in 2011 to help clients, including his own family, manage and preserve their wealth with a thoughtful, research-based, and cost-effective approach that covers not just investment management but also broader decisions about wealth and finances.

Victor started his career at Salomon Brothers in 1984, where he became a Managing Director in the bond-arbitrage group, and in 1993 he was a co-founding partner of Long-Term Capital Management. He lives in London and Jackson Hole, Wyoming.

In this episode, we’re joined by Victor Haghani, founder of Elm Wealth and co-author of The Missing Billionaires, for a wide-ranging conversation about how different types of investors shape financial markets. Victor explains the framework behind his forthcoming paper, Who Killed the Random Walk?, and how fundamental investors, static investors, and extrapolators interact to produce momentum, excess volatility, and other market anomalies.

We explore why return chasing is different from momentum investing, how investor flows and inelastic demand can move markets, and how the Merton share connects expected returns and risk to portfolio allocation. Victor also discusses long-short direct indexing and tax-loss harvesting, his experiment giving investors tomorrow’s Wall Street Journal today, how AI performed in the same trading game, the role of leverage in financial markets, and when borrowing to invest might make sense. We finish with Victor’s advice to his younger self: be intentional about financial planning, build financial literacy, and make a plan.

Key Points From This Episode:

(0:01:20) Lessons from The Missing Billionaires—practical insights on sizing and the Kelly criterion.

(0:03:13) Who Killed the Random Walk?—persistent puzzles in stock returns: excess volatility, momentum, fat tails, booms, and busts.

(0:05:06) Victor’s three investor types: fundamental value investors, static investors, and extrapolators.

(0:07:54) How static investors amplify market movements through inelastic demand.

(0:11:11) How investor types interact to shape volatility, momentum, and equilibrium.

(0:14:02) Wealth flows between investor types and how they create instability in simulations.

(0:18:15) Distinguishing extrapolative return chasing from systematic momentum strategies.

(0:20:34) How extrapolators create price trends that momentum investors exploit.

(0:23:46) The Merton share—risk premiums, volatility, and risk aversion in determining equity exposure.

(0:26:39) Combining value and momentum for higher Sharpe ratios.

(0:32:34) Long‑short direct indexing and how leverage increases tax‑loss harvesting.

(0:34:00) Why fees, complexity, and risk of direct indexing may not be worthwhile without alpha.

(0:43:21) The “crystal ball” experiment—advance information, poor sizing, and excessive leverage.

(0:49:28) The role of leverage in markets—ETFs, options, embedded leverage, and nonlinear instability.

(0:52:50) Why leverage can create nonlinear interactions and amplify market instability.

(0:52:55) When borrowing to invest can make sense, particularly for younger investors with substantial human capital and limited financial capital.

(0:55:00) Why borrowing costs, expected equity returns, risk, and the possibility of losing a large portion of savings make leverage a difficult decision.

(0:57:29) Why the risk-adjusted return from additional equity exposure matters more than the headline expected return.

(0:58:42) The relationship between human capital and leverage—and why human capital is not necessarily bond-like.

(1:00:01) Victor’s advice to his younger self: be proactive, become financially literate, and make a lifetime financial plan.

(1:02:18) Why dedicating time to financial education can meaningfully change how people approach financial decisions.

Read The Transcript:

Ben Felix: Welcome to episode 429 of the Rational Reminder Podcast. I'm Ben Felix, Chief Investment Officer at PWL Capital.

Cameron Passmore: And I'm Cameron Passmore, Chief Executive Officer of PWL Capital. Today, Ben, we're joined by Victor Haghani, who previously appeared in episode 270. Victor is the founder of Elm Wealth, which is a wealth advisory firm in the US. He has over 40 years experience studying financial markets.

Ben Felix: Studying and working in them. He's got real practical experience too. In the episode, we discuss how different types of investors impact the market, when leverage does or does not make sense, and what financial advice Victor would give his younger self.

Cameron Passmore: Of course, we'll talk about our thoughts of the conversation at the end, but for now, let's get to the episode with Victor.

Ben Felix: Victor Haghani, welcome back to the Rational Reminder Podcast.

Victor Haghani: Thank you. Great to be here for a second time. I'm honored.

Ben Felix: We're excited to have you back and we have a lot to talk about. You've been busy writing about stuff since the last time.

Victor Haghani: Yes, just a little bit.

Ben Felix: Victor, since the last time you were on, when we talked about your, at the time, new book, Missing Billionaires, what have you learned since then?

Victor Haghani: In some ways, the thing that we learned is that there was a gap in the literature for this kind of book with this kind of treatment. Our publisher, God bless them, were like, you guys have way too many equations in there. You're not going to sell any books.

And we're like, well, they're not hard equations. People will get them. And we've really been so pleasantly surprised by the fact that a lot of people have been interested in the book.

When you write about something where people have a little bit of a blank area in their minds, talking about sizing and Kelly and the Merton share and all this, it's much easier to convince people because you're not changing anybody's mind. You're just sharing with them things that they might not have known. And to be clear, we didn't come up with anything original in the Missing Billionaires.

We were just channeling a lot of great research of other people. So yeah, it's been satisfying for us. Another thing that we learned is that a lot of people said to us, we love this kind of treatment and this kind of discussion at this level.

And I wish that you would write something for my kids or for my nieces or nephews or my young friends or whatever that's shorter, that doesn't go into as much depth on sizing and is a more broader thing. So, you know, as we talked about before, we wrote a book over the summer that's coming out in early 2027 called Get Rich Once and Other Financial Wisdom for Our Younger Selves. It's going to be available on Amazon for pre-order. So we could talk about that later, but just a quick plug there.

Ben Felix: Yeah, no, that's exciting. We will bring that back up later. You mentioned you didn't come up with the ideas in the book, but it's pretty rare.

I don't know if I can say that you're the first, but certainly one of the first to communicate those ideas, which can be pretty mathy and pretty technical in a way that's pretty practically accessible to a broad audience. That's what you guys really brought to the table with that book.

Victor Haghani: Thank you. Yeah. That's really great to hear that.

Ben Felix: I said, you've been busy. You've got a paper coming out shortly in the Journal of Investment Management, Who Killed the Random Walk? So I want to ask a little bit about that. Can you talk about what some of the most persistent puzzles in stock returns are?

Victor Haghani: Every class in asset pricing theory really starts off with all the things that asset pricing theory really has a tough time explaining. And I think the biggest of all of the strange things about the stock market is this idea that there's excess volatility, that stocks bounce around by much more than fundamentals would seem to dictate. And this goes back to Campbell and Shiller in the 80s.

And as one of the big contributions of Shiller that probably led to his Nobel prize is this idea that stocks are so much more volatile than changes in expected earnings. But there are all these other things too out there. There's persistent price level momentum in stocks.

There's very stochastic volatility, but that it also persists. There's fat tails, there's booms and busts. All of these anomalies really, each one of them, you could kind of come up with some explanation, maybe a rational expectations type of explanation or that there's some dark matter that's doing something.

It's not that these haven't been explained, but we got attracted to trying to put together an explanation that would be comprehensive and touch on all of these. As with the Missing Billionaires, it's not like we came up with anything original, but I think that maybe we took the existing research, took it one step further and also maybe posit it in a way that's much easier for a broader audience to understand versus some of the more technical academic treatments that we've had.

Cameron Passmore: And how do the types of investors that participate in the market interact with the observed anomalies?

Victor Haghani: Historically, the idea has been that we have this rational investor that's always looking at the long-term expected return or some expected return of what they're investing in based on cash flows, some kind of a value investor representative agent. And if that's what we had, if that's actually how investors were, then we just wouldn't see any of these anomalies. In fact, instead of seeing stock market volatility higher than fundamentals, we would actually see these fundamental value investors dampening volatility.

Because when the market would go down and expected returns would be higher, they would want to own a little bit more than what they owned, because now what they owned was worth less because prices had gone down. So they would be dampening volatility a little bit. But instead, we actually see volatility exacerbated by different investor types.

So in the simplest form of our model, we have three investor types. We start off with this valuation, value-based fundamental investor, which we know are out there, Warren Buffett having been one of them. But then we add two other types that are very prevalent in the marketplace.

One of them, there can be no doubt of whatsoever, it's a static investor. We know that so many investors out there have a static strategic asset allocation, maybe 60% equities, 40% fixed income, or 70-30, or endowments have these pretty strategic asset allocations. Over time, they're just rebalancing back to those more or less.

They will move somewhat over time, but not much. So we can think of them as static. And their behavior exacerbates any exogenous changes in supply and demand that take place.

But then really the critical key investor type that we believe is generating so much of the perceived market anomalies is the extrapolative investor, the return chaser, the investor who comes up with their expected return for the market based on what the market has done recently. We call them extrapolators. And we say they make their asset allocation decisions based on recent returns, not just using recent returns exactly as they've been with some squeezing, with some rational use of that historical return.

But when historical returns are higher, they want to own more equities. And when historical returns are lower, they want to own less equities. And those guys combined with the static guys just overwhelm this fundamental investor and give us so many of the behavioral things that we see in the marketplace.

Ben Felix: Can you go into a little bit more detail about why static investors are exacerbating the demand shocks?

Victor Haghani: Just take a simple example that we can follow with words without a blackboard or anything. Imagine that the marketplace is only made up of static investors that want to be 50% in stocks and 50% in fixed income. So that's where they are.

And then some companies turn up and they're like, we need to buy back our stock because that's what we want to do with our excess cash flow. We're going to buy back our stock. They decide, just let's keep the numbers as simple as possible, even though they're a little bit unrealistic.

Let's say that companies want to buy back 10% of all outstanding equities. We know that the only place they can buy them from is the static investors because that's our only investor class. So they have $50.

The static investors have $50 of stocks. They have to sell $5 of stocks to the companies buying back their stock that are buying back 10% of the whole marketplace. So now they're left with what?

They're left with, if market prices don't move, they have $45 of stock and $55 of cash or fixed income. What has to happen is that their $45 of stock has to become worth $55 because they want to be 50-50. So the only way that can happen, they can't trade with each other.

That doesn't help anything. The only way that that could happen is the price of the stock market has to go up, not by 10%, but by 20% because we have to go from $45 to $55, which is $10 on $45, call it 20%. If companies are buying back 1% of their stock, stock prices are going to have to go up 2% if the only investors are these static weight strategic investors and if they're a 50-50 weight.

If their asset allocation were 60-40 or 40-60 or whatever, it would be a little bit different, but that shows you how the numbers work and it's really simple like that.

Ben Felix: We've heard a lot about that, the inelastic demand from investors over the last couple of years as we've explored the effect of index funds on financial markets and I guess they'd be a good example of that static investor.

Victor Haghani: Yes, yes. We talk about the Gabaix and Koijen paper in our article. They came at it a different way.

Many different practitioners and observers think about what this elasticity is. Our number is lower than the Gabaix-Koijen one. It's like half of that or so.

So we think that 1% might cause a 1% move in the market exogenous change in demand. They're two or three times bigger. But one of the most interesting things from their research was when they sent out a survey question to, I don't know, like 50 or 100 economists, and they said, imagine that there's some investor that needs to buy 10 basis points worth of stocks.

How much will that move stock prices? The vast majority of financial economists said zero, that the marketplace is like perfectly elastic. I just thought that was so telling and interesting in terms of where we've been and how things are changing in terms of our understanding of stock market behavior.

Ben Felix: Yeah, that's really interesting. In the basic form of the model, you mentioned that there are three investor types. We have a value investor, the static investor, and the performance chasing investor. Can you talk about the effect that each investor type has on the market?

Victor Haghani: As we said already, the value investor is stabilizing things a little bit, but the extrapolator is pushing the other way. The market goes up, they want to own more equities, and this is making it more difficult to reach an equilibrium. The extrapolators are creating momentum in the price series.

They're also creating this excess volatility. When you have a fundamental positive shock, like earnings are going to be higher, everybody wants to buy more stocks. The fundamental guys do, the static guys do because they want to get back to their 50-50 weight, and the extrapolators do because the market's gone up, and so they have a higher expected return.

They're the primary cause of these behaviors that we're seeing. It's really these exogenous shocks that eventually can cause things to turn around, but it's a pretty fine balance. When we look at U.S. stock market performance, a number of observers have pointed out that this tremendous U.S. stock market performance over the last three decades has primarily been driven by a compression in valuation, a lower earnings yield, a higher PE, rather than the earnings growth. Earnings growth of U.S. stocks versus non-U.S. stocks has been faster, but also you have to take away the effect of buybacks in making that earnings growth look faster than it really is. Earnings growth has been good, but really it's this compression in the risk premium that's given us a very large part of this tremendous performance we've had over the last 30 years in U.S. stocks.

Ben Felix: Of the three investor types, which one performs the best?

Victor Haghani: None of them do great. The static investor just kind of gets the return of the market over the long term and it's kind of okay. The extrapolator kind of does poorly because ultimately it all catches up with them.

They're not following a super rational strategy, but the value investor does a little bit better than the static investor, but not hugely because they just have to suffer through these really long periods where the expected risk premium is low, but the market's going up, up, up. None of those investor types do great, but there are some investment strategies that do better, which we can get to, but it's surprising in one way that the value investors don't do great, but we kind of know that also from history too. We know that getting really underweight equities when the risk premium is low is a difficult position to take and doesn't create a much higher Sharp ratio and much better returns.

It's better in the long run, but it's not like as much better as you might imagine, as I might imagine.

Cameron Passmore: What's the impact of wealth moving between the investor types over time?

Victor Haghani: We've modeled these kind of exogenous shocks where each investor type is getting some extra cash or needs to spend some cash generating this noise trading, this idea that, oh, somebody needs to buy a house or somebody needs to pay for college or somebody got a big bonus and was investing it in the market. We've tried to model pretty heavy flows and not the same flows between the different types of investor to get some of that noise. It does, I think, what you'd expect. When the extrapolators are getting more capital, either because of some exogenous cashflow shocks or because they're just doing so well because they're riding a good trend, then the market behavior that we see from them gets more exaggerated.

One of the challenges in building our model was that in early versions of it, things would just blow up. All of a sudden, the price would just go to infinity because the extrapolators got all the money and there was nobody that they could trade with, so there was no price. But as we made it more realistic, we found that the simulations that we were running behaved much better as well, but it is a fine balance.

Ben Felix: Really, really interesting. Can you talk a little bit about momentum and extrapolation and how those two things are not the same?

Victor Haghani: I love this topic. Twelve years ago, I was at a conference where Rob Arnott was speaking to an audience and he said, the number one thing that people do to shoot themselves in the foot is to be return chasers. This is the number one behavioral foible of investors.

Right around that time, I had been reading the research on time series momentum and I was thinking to myself, how amazing that at the same time as Rob is saying this, which I agree with, other researchers were saying the most salient anomaly, the single best thing you could have done as an investor historically is to be a momentum investor. Momentum has been everywhere and at all times. Time series momentum in particular is what I'm talking about here as opposed to cross-sectional.

Right around that time, there were all these papers coming out or a number of papers looking at long-term time series momentum and how prevalent it was everywhere and everything, every commodity, every equity, etc. I was like, why do these sound exactly the same? How could it be that one of them is the worst thing and the other one is the best thing?

What I realized is that first of all, momentum has a fully agreed upon definition. When we talk about momentum, more or less, we're all talking about the same thing. If you measure momentum slightly differently as a one-year moving average or as a one-year look back or as a six-month look back or whatever, you get the same kind of results.

But return chasing is a little bit more like when we see it, we know it. There is not a definition of return chasing. What is this return chasing behavior?

A number of observers have put forward ideas about why return chasing hurts and momentum helps. Cliff Asness has one of the more repeated ideas of what return chasing is. He says return chasing is momentum investing, but with a five-year look back.

I don't know how that stacks up in cross-sectional momentum, and maybe that's where Cliff is referring to it as being an explanation, so I can't speak there. But in time series momentum, that's not really a good explanation. We don't really see somebody following a five-year look back with a binary momentum strategy as really being the worst thing that they could do.

It's not a good thing. It's not helping them, but it's not crushing them. So there's something else, I think, that's at work here.

The way that we define return chasing or what we see as return chasing is the way we've modeled it in the paper and the way we've talked about it in previous papers, because we've been writing about this for maybe almost eight or 10 years, is that it's this more gradual thing. Momentum is a binary. It's either you're overweight or you're underweight.

It's binary. As soon as momentum flips one way or the other, you do that. With return chasing, it's this more gradual thing.

So when we model it in this research that we've done, you're looking at historical returns, and the better historical returns are, the more you want to own of equities. So as the market's going up, historical returns are getting better. You're getting more and more and more overweight equities.

And then now the market starts to go down and returns start to look not as good and worse and worse and worse. And now you're unloading. It's that behavior, which is different from the momentum trading that basically results in the return chasers doing poorly and the momentum guys doing well.

But I have to caveat this really importantly, that it really depends on the relative size of these guys. Because if the return chasers are just a few guys doing that, and everybody else has their money in these momentum strategies, well then we don't get that anymore because everybody's having impact. In this framework and in the real world, we think there's a lot of impact from people trading large size.

It's this behavior that I've described, and also it's the fact, or what we think is the fact, that the return chasing behavior is operating on a lot more capital than the momentum strategy, than time series momentum is in general. The beautiful thing about time series momentum, in terms of why I think it generally doesn't get too big, is because it just seems ridiculous. I thought the thing was we're supposed to buy low and sell high, and this strategy is sell low and buy high, that when time series momentum is working, people are like, oh this is great, I love it.

But as soon as it stops working, as soon as you go through one or two years where time series momentum doesn't work, people are saying, I knew this was the stupidest thing ever, of course it would never work, and they pull their money out. Now I think people's attitudes are changing over that. Probably there's been so much research and talk, I think people are sticking with it maybe longer than before.

But I think it just has a bit of trouble in attracting large amounts of capital for the long term, because it's just something that people like as long as it works, and when it doesn't work they flee, and that has that impact. But I don't know, at some point this time series momentum could just be the dominant force, and then everything would be different.

Ben Felix: The performance chasers, the extrapolators, are they creating the momentum factor?

Victor Haghani: Yes, they'd be creating. It's their impact that's creating that evolution of prices that allows the momentum guys to make money.

Ben Felix: They're cumulatively buying more and more of the asset class, pushing its price up and up, and the momentum folks are seeing that signal with their more defined look back period, and they're buying the thing that's going up.

Victor Haghani: They're getting ahead of it. You could think of them as front running that trend on average. It relies on the momentum guys not having too much impact.

Ben Felix: That works until it doesn't, which sucks. People get whipsawed, and they lose a bunch of money and momentum, and then they bail on momentum, and the fact that that happens, it's almost like a bit of a risk premium story. Not different, but people get blown out of momentum, and that's why that it has continued to work. Is that the right mechanism?

Victor Haghani: I think that's one explanation. There's another explanation too, which is worth discussing, which is that when we talk about risk assets, when we talk about equities and things that are like equities, risk assets, the other thing that we know is that volatility tends to be skewed, that we have high vol when the market goes down and low vol when the market is going up and when it's grinding higher. Momentum also happens to be correlated with the strategy of vol targeting.

If you're doing vol targeting where you reduce exposure when the market becomes more volatile, and you increase exposure when the market is calmer, then you're also following a bit of a momentum strategy. Not a bit, you're highly correlated with somebody who's following a momentum strategy. That vol targeting, in our opinion, is a very rational, logical thing to do.

It goes back to the Merton share, it goes back to normal scaling logic of the higher my Sharpe ratio, the more exposure I want, which means the higher the expected risk premium I want more, and the higher the risk I want less. And so vol targeting, to the extent that momentum is rhyming with vol targeting, it kind of makes sense that it also is working and that it's helping to generate better risk-adjusted returns for investors if you're following momentum with risk assets like equities, like oil, like REITs. So there's that also, which I think is really, really important as well.

We wrote an article a while ago where some investment bank was saying, what you really should do is when VIX goes above 30%, when volatility is above 30, you should really load up on equities, which is the opposite of vol targeting. And we kind of showed just through the simple backtest of how the strategy would have done, that doesn't generate a higher Sharpe ratio. And we also talked about that logic as well.

So maybe for somebody who's thinking, oh, when the market goes down and vol goes up, I want to buy. Well, when the market goes down and vol goes up, you want to sell. When the market goes down and expected returns are higher, you want to buy.

And so you have these two competing factors, and it kind of depends on how much of one versus the other has happened. So it's better to separate those things than to simply say, when vol goes up, I want to buy. It's more like vol goes up, you should reduce, and expected returns go up, you should want to increase.

Ben Felix: Maybe just for the benefit of listeners who didn't listen to your last episode or have not heard us talk about the Merton share, can you talk about the Merton share logic behind the statement that you just said?

Victor Haghani: So Bob Merton and Paul Samuelson attacked the lifetime consumption and portfolio choice problem in the late 60s. They came up with this solution where under a very stringent and unrealistic set of assumptions in terms of how risk assets behave and all that, but it gives us a good rule of thumb. The amount of exposure you should want to have to risky assets in your portfolio is proportional to the expected risk premium that those risky assets are giving you.

You have to have an expected return and know what the safe asset is offering, divided by the risk of those risky assets where you're measuring risk as variance. Also, you would scale that based upon your own personal degree of risk aversion. So there's a constant in there that's like your personal constant that you would divide by your degree of risk aversion.

And that Merton share, as we call it, that also is actually the same as is a more inclusive version of the Kelly criterion where the Kelly criterion is the Merton share where that coefficient of risk aversion is equal to one. And that gives you the Kelly criterion, which comes at the problem from a different place, but winds up in the same place. Another way to think about the Merton share that might be easier is that the amount of risk that you want is proportional to the Sharpe ratio of the risky asset portfolio that you want to invest in.

And then that's the amount of risk you want. And then to figure out how much exposure you want, how much of those assets you want, then you would divide by their risk. And that's why we wind up with risk squared with standard deviation of return squared in the denominator.

Again, it's a rule of thumb, but it ties expected utility theory to the investment process. You can get more general and more realistic, but that's the simple rule of thumb from Bob Merton and well, Paul Samuelson's paper too. But I think Bob, we call it the Merton share because I think Bob kind of came up with it.

And then Professor Samuelson was his mentor. They published joint papers at the same time, but I think that Bob came up with it in continuous time first is what I understand, but I'm not sure.

Ben Felix: Yeah, I don't know. I've seen it called the Merton Samuelson share too. I don't know how much it matters.

I've never heard Bob complain about it being called either way. A really good explanation. And it's really interesting how that ties into momentum and the persistence of momentum because people are changing their asset allocations as risk and expected return evolve.

And that is driving momentum and momentum should then persist unless it becomes the dominant where most of the capital sits, I guess.

Victor Haghani: Yes.

Ben Felix: Super interesting.

Victor Haghani: When we were talking about other investors that could do better, one simple strategy that actually does really well is a value and momentum combination. So combining fundamental long-term cashflow investing signals with momentum. So value and momentum gets a much higher Sharpe ratio when you combine those two.

And this really goes to kind of explain in some ways very satisfyingly the results from the Asness et al paper. I forget when it's from, but value and momentum everywhere that I think has had an impact everywhere on people's thinking. I mean, I think that was a really seminal paper, certainly shaped our thoughts a lot at Elm.

Cameron Passmore: What do you think your model adds to our understanding of markets?

Victor Haghani: There's a vast, vast literature of these heterogeneous agent model approaches to the markets and from the Santa Fe Institute to Northeastern universities, and there's all kinds of contributions here. And I think that the two things that we really add to our understanding about this is that number one is that we're presenting this in a way that's much easier for people to understand that there's not heavy math here. All of the most recent papers use a lot of heavy math and they're really hard for most people to comprehend.

And then the early papers were more like stick models. Larry Summers and DeLong, Summers, et cetera, Shleifer kind of had a stick model early on because they were just kind of showing the general contours of what things look like in a multi-agent setting. So one is that we've made it more accessible.

Then the other one is that we've made it more general. So nobody, as far as we know, has built a model that has six or seven different kinds of investors in there. We have the three that we talked about.

We have a value and momentum investor. We have a buy the dip short-term reversal investor. We've modeled a more anticipatory investor in there as well.

So this kind of generality of the broadness of it going and allowing you to put in any kind of investors you want and was going to help people who want to take the research further and put in more realistic investor types and make the simulation more and more realistic.

Ben Felix: You mentioned the value and momentum insight. How else did thinking through and writing down this model affect your views on asset allocation?

Victor Haghani: That's perhaps the main one, but I think when you come to appreciate how important extrapolators are to what's happening in the world, maybe it's a little bit of, to a man with a hammer, every problem is a nail, but it just feels like understanding these extrapolators and how much they can affect behavior creates a lot more humility in terms of what the markets can and might do. Also kind of gives you this focus in terms of trying to understand what's putting more focus on them than on any other investor type and behavior in terms of trying to understand what's going on. So many people, long-term market observers, they look and they say, gosh, I don't understand what's going on.

We have higher interest rates. We have this bad government deficit. We have tariffs.

We have global political instability, all these different things we have going on. And they're like, I don't understand why the market is 20% higher after all these things have happened. What is going on?

To us, thinking with this lens on, it's like, well, one simple explanation is that until recently, US companies were buying back over a trillion dollars of their stock per year. There were no IPOs, flows into 401ks and so on were also running at like a trillion dollars.

So here was a couple of percent of the total or more than a couple of percent of the total US market disappearing or being bought by exogenous demand each year. Combine that with people's just seeing these returns. And I mean, I don't know how many people I've heard just say, just keep all your money in equities because you're going to get 10% a year.

It's been 10% a year for a hundred years, and it's going to be 10% a year forever. That's self-reinforcing for a long time.

Ben Felix: For some indeterminate amount of time.

Victor Haghani: Another thing that we kind of tried to play around with in the model is there is some time when there's probably some time when you can get a lot of supply of equities. When it looks like the long term expected return of equities is below government bonds, we would anticipate that companies will issue a lot of equity. When it really becomes clear, when equity becomes cheaper than debt, company treasurers, company CFOs, company CEOs and boards pay attention and they're like, okay, we should raise equity.

There's a lot we can do when equity costs less than debt. And we still, the market would need to go up quite a bit more to get there. But there is some boundary condition, I think that's out there.

Japan hit that boundary condition in the late eighties. Boy, did they issue a lot of equity in the late eighties in Japan, right? They issued a lot of equity in that run-up.

Ben Felix: We got a ways to go still is what you're saying.

Victor Haghani: We have a ways, maybe it's another 50% up all else equal or a percent or two higher in interest rates. If we got 10-year tips at three and a half, 10-year treasuries at six, we'd see more equity issuance if the market stayed here, that is.

Cameron Passmore: If they didn't go down.

Ben Felix: Very interesting to think about. I haven't thought about US stock market valuations in a while because whenever we talk about it, the market just keeps going up.

It's like, all right, maybe we're contributing to the extrapolation by no longer talking about it.

Cameron Passmore: Exactly.

Ben Felix: You did a great article on long-short direct indexing. Can you talk a little bit for listeners just about what that is before we start asking you questions about it?

Victor Haghani: There's been so much over the last couple of years in the US on different kinds of strategies to help people defer their taxes, or in some cases, pay less taxes. What we've had for quite a long time are direct index tax loss harvesting programs where you give your money to a company like Parametric, which I guess is now owned by somebody else and a lot of companies are offering it. They put you into a portfolio of individual stocks like the S&P 500.

Then when individual stocks go down, they sell them. Then they try to buy them back later on to realize losses as much as they can and to try to track the S&P 500 over time while realizing losses. Well, more recently, it's this strategy that people have thought about in the past is taking that to another level of let's go leverage long stocks and run a short position against them.

Instead of just taking $100 and buying $100 of stocks, I could take $100 and control $300 or $400 of stocks. I can get a lot more tax losses in that way to offset gains that I might have elsewhere. This is called leverage long-short tax loss harvesting because it's using leverage and it's using shorting, but it's still tax loss harvesting with individual stocks.

It's grown quite a bit. There's been a bunch of articles about it. We've been writing about this for a while.

We started off writing about direct index tax loss harvesting and we made the argument that most investors shouldn't really have a lot of capital gains. If they're long-term equity investors, they shouldn't have a lot of capital gains to worry about other than the fact that they are selling some stocks over time to consume. The point of the wealth is to spend it so you have to sell over time stuff that you have in a taxable account and realize some gains.

But overall, if you are invested in stocks, you don't have a lot of capital gains. You're getting a lot of deferral just naturally. But if for any reason you do other kinds of investing, maybe in hedge funds or other things, and you get realizations, you have a lot of capital gains, you might want to try to reduce your payment of them over time and defer those gains into the future.

We've written about this. And with respect to direct index tax loss harvesting, we've said, well, after you figure out the fees, because this carries fees, and after you figure out the extra risk that you're bearing, you might be just as well off owning ETFs and doing tax loss harvesting on your ETFs. Own Vanguard Broad, Total Market, and if that goes down, replace it with the S&P 500 index fund and do something like that.

Or maybe own the different sectors of the S&P 500 and do something like that. And that takes you to about the same place. You have less risk.

Probably it's slightly better, but you just have less complexity. You don't wake up one day with a 400 stock portfolio that you don't know what to do with, where you have corporate actions and all this stuff that you have flexibility by having a simple portfolio and you're getting about the same result. When there started to be more interest from people in leverage long-short direct indexing, we analyzed that and we came to a similar conclusion.

Well, the conclusion that we came to in our research was that if you don't believe that the long-shorts are going to generate alpha, we don't really think it's worth doing. The fees are much higher than in the unleveraged version because here you have higher fees from the manager and you also have a long-short friction that Fidelity or Schwab or whoever the custodian is, is charging to run the longs and shorts. That if you don't believe that there's alpha in this long-short strategy, then probably it's not worth doing.

I mean, we're not saying it's terrible, but it's just probably not worth doing. And again, you get all this complexity and you're kind of locked into this portfolio and it's messy for however long you're doing it. That was our conclusion.

We think there are special cases where this stuff can make sense for people. For instance, if you have a lot of short-term capital gains, that some of these strategies could make sense to try to reduce those and create long-term capital gains out of them and get a conversion for US investors. Or if you're living in California and you're going to move to Alaska and you know that you're going to do that and it's I just want to defer my gains for a few years because I'm going to a low tax state, maybe that could make sense too.

But in general, for most people and for young people in particular, we don't think it's really worth the squeeze. It's interesting because we've written about this stuff and journalists have talked to us about it. The last time a journalist was talking to us about it, she was saying, well, can I quote you in this article?

And I was like, that people that get quoted in your articles really get some nasty stuff said about them in the public domain. So please, if you wouldn't mind, please don't mention my name. I've had enough bad things said about me over my life.

She said, well, but you have this research. And I was like, yeah, I know, but still like, if you don't mind. So then she said, well, who else could I talk to that's done this research and feels the same way that you do?

And I was like, oh my goodness, there's nobody really that I can think of. There should be somebody. And then I started to think, well, maybe we're just all wrong about this stuff.

I don't know, but that's what we think. We're not crazy about all this stuff. There's no holier than thou stuff going on here.

You know, we're just saying that if you don't think there's alpha there, then you don't really want to do it. If you think there's alpha great, but then you kind of have to ask yourself a little bit the question of if you thought there was alpha there, why weren't you doing it to begin with? And you might say, well, I thought there was a little bit of alpha, but not enough to overcome the fees.

Okay. You know, that's fine. But I think there has to be this question of, do you think that somebody can run long-shorts in a systematic way and generate alpha? Maybe. It's tough. We know that Renntech does it.

We know that there's a bunch of people out there who do it. And generally, whoever you can be sure of that does it doesn't take outside investors. So we know that it's possible, but in general, it seems as though when somebody really cracks that nut, they very quickly send everybody's money back.

So if somebody is still taking money to do it, maybe they found a way to do it in scale. It's possible, but everybody's entitled to their opinion about the alpha. We're kind of more alpha skeptical.

You know, I mean, that's why we're invested in broad index funds for our clients so much. So we're like alpha skeptics in general anyway.

Cameron Passmore: So why the hype around the products?

Victor Haghani: People love to pay less taxes. I mean, I think some people would like rather pay somebody a fee and pay less taxes and be in the same place than not paying the fee and paying more taxes. And, you know, I think that some of the purveyors analyze the tax benefits in a fairly optimistic way, you know, like maybe, oh, you're going to roll this until forever.

And then you're going to get step up in basis or we're going to do a 351 into an ETF. I don't know how people are marketing it, but if you're an RIA and you're like, hey, I've got this great thing for you client, you know, I'm charging you some money to be your RIA. Here's this shiny new thing.

You know, people like shiny new things. This is not even close to the weirdest things going on in our marketplace today. Like we should be saying, why are people buying these buffer funds?

It's like the things of why are people doing X? This is like...

Ben Felix: I've got one for buffer funds.

Victor Haghani: This is like almost defensible. This is in the zone of defensible. Like we're saying, ah, it's not quite worth it on a risk adjusted basis. Like we're not saying it's terrible. There's other stuff that's terrible.

Ben Felix: On your perspective on this, you guys do run an ETF, but you've got clients like effectively wealth management type clients. And so you come to something like this from the perspective of let's do the research and see if we should be using it. Is that the right way to characterize it?

Victor Haghani: Well, we actually built a direct index tax loss harvesting product and we ran it on some of our own money for a couple of years. And we were just thinking about, because people were asking us to do it and we built it and we thought it was a good version of it. And we're like, oh, we don't want to offer this to clients.

We would rather clients get about the same amount of expected tax losses or tax efficiency, but keep it simple and not get into this whole thing. I mean, one of the big problems with direct index tax loss harvesting is that always in the back of your mind, you're going to be wondering, everybody knows kind of what these direct index tax loss harvesters trades are going to be. IBM is down.

Somebody is going to harvest that. Everybody's going to harvest that. And there's a trillion dollars in these programs.

When we're wondering about how is Jane Street and Citadel and Renntech and all these guys, how are they making money every single day of the year without ever losing money in general? You know, not quite these days, but close. That might well be part of it.

When Goldman Sachs and JP Morgan are making billions of dollars on their trading desk, you got to wonder and throw in their Millennium and Balyasny and all these guys, like you got to wonder if you start to underperform in your direct index tax loss harvesting thing. If you're underperforming, you're going to be like, oh, this is terrible. This is what's happening.

And you're going to be really bothered by it. And if you're outperforming, you're going to be like, oh, I got lucky. You know that the direct index tax loss harvesting guys are not doing any analysis.

They're just trying to do the tax loss harvesting and manage the tracking error. So when it goes well, it's like, oh, this is great. I got lucky. When it goes badly, it's like, oh, I got picked off by Citadel.

Ben Felix: That's interesting.

Victor Haghani: And that's uncomfortable. And that's like a big reason that we just thought, oh, this is so uncomfortable. If you're really reporting your returns properly to investors, it's just going to be super uncomfortable to be saying, oh, you underperformed by 75 basis points.

And we don't know why it was just bad luck. And then it's like, oh gosh, I don't want to do that.

Ben Felix: Yeah. The tracking error, the comment about maybe the tax loss harvesting trades are priced in. And so you're giving up whatever tax benefit there might be to asset pricing when you trade.

Victor Haghani: Yeah. A little bit of frictions. I mean, we know trading has frictions and when a lot of people are doing the same thing, it has impact, but I don't know.

We've never done any research on that. It's just a hypothesis, a speculative hypothesis.

Ben Felix: We like simplicity too. When your research and analysis supports the simple answer, we're always excited to see that.

Victor Haghani: Yeah, definitely.

Ben Felix: Why isn't a crystal ball enough to beat the market?

Victor Haghani: This is one of our favorite bits of research that we did. It kind of sat with us for a long time. We did this research where we wanted to test out something that Nassim Taleb had tweeted about long ago.

He said, give a man the front page of the Wall Street Journal a day ahead of time, every day of the year. And within a year, he'll be broke. It's like, wow, that would be so interesting to try to test this out.

So we created a game where we give people the front page of the Wall Street Journal a day ahead, historically, and let them trade on that in stocks and bonds and see how they do. A lot of those days are employment days and Fed announcement days. So there's real news.

We ran the experiment with real money, mostly with MBA and finance graduate students to begin with and some practitioners. And then we just opened it up. We've had 100,000 people or more play it since then for fun.

And it's really hard to generate a good return. It turns out that on average, people didn't do very well despite having this newspaper a full day ahead of time. Part of it, I think there are two things mostly going on, or three things, maybe.

One of them is people really had a hard time sizing their bets in a sensible way. People oversized their bets. They were sure that stocks were going to go up because they could use leverage in our experiment.

And so they would be like 40 times leveraged and the market would go down 2%. And that was it. They lost 80% on that day.

And they couldn't come back from that. So one is that the sizing just didn't correspond to sensible sizing or proportional to how clear the signals were. Sometimes the signals were pretty clear and other times not.

And people didn't size like that so much. That was one thing. Second thing was that many of the people who played the game really wanted to trade stocks.

But the news is much more economic. And Wall Street Journal news is much less ambiguous when it comes to bonds. When you get something that's like the economy is stronger than we thought.

Well, that could be good for stocks or that could be bad for stocks because interest rates might be going up. But it's bad for bonds generally. So we also found that people had a predilection to speculate in stocks more than bonds.

And they would have done better in the bonds in general. People did better in their guesses on bonds. And then people just had some difficulty parsing the news.

When we brought in some senior macro type traders to play, we got six or seven of those guys to play it. And they did well. But they only had a hit ratio of like 60%.

But still, they did well. They had a good Sharpe ratio in the end after 15 things. And they doubled their money on average over 15 sets of bets.

So it was possible to do well. Quite a lot of experience was needed. I think if you gave the front page a day ahead of time to a bunch of macro traders, they would make good money over time.

They wouldn't be making their money grow tenfold. They doubled their money after 15 of these. Those were some of the interesting findings.

And then, of course, I think you'll probably ask, we had this idea like a year later to let the AIs loose on it and to let the AIs play. And that was as much fun as anything.

Ben Felix: Since you brought it up, I was going to ask about it.

Cameron Passmore: Yeah, you have to.

Ben Felix: How did the AIs perform relative to the humans?

Victor Haghani: We got the AIs to play. And we'd spent a lot of time trying to make sure that they weren't like cheating, like figuring out, oh, that front page was from this date and figuring out what happened exactly on that date. We're pretty sure that they didn't do that.

And we're also pretty sure they didn't do that because the first time that we let them loose on it, they didn't do very well. They had a good hit ratio, but they took too much risk. They didn't size things correctly.

Now, we were using the free versions. And this is what, six months ago or so. So we were using free versions as of six months ago.

We weren't using Fable. When we then went for the paid versions of three of them, because we couldn't get a paid version of Grok going, the paid versions of Claude, ChatGPT, and Gemini did better than the more free versions. And then when we told the AIs to read our book, The Missing Billionaires, and to think more about sizing, then they did even better.

They probably became a little bit overly conservative. But they did a really good job on figuring out whether the markets would go up or down and how strong. I mean, they were smart.

It was impressive. But they got the sizing wrong to begin with, which was interesting. If we probably did it today, they'd probably do better because the non-premium versions are probably much better than the best versions were back then.

But it was really interesting to see that generation of AIs play the game and do well, except also struggle with sizing a bit.

Cameron Passmore: How much attention do you think normal investors should pay to the news?

Victor Haghani: In terms of investing, very little. In terms of human experience, in terms of our life as humans, I think it's important to know what's going on in the world, to be good citizens and all of that. But I think as an investor, kind of close to zero.

I think as an investor, you just don't need to be following the news very much at all. I think that a sensible, long-term investing strategy, even if it's a dynamic asset allocation variety, just doesn't really need to follow the news very much at all. Very little. I think that as people, though, we have a responsibility to follow it somewhat.

Ben Felix: Got to be informed to some extent.

Victor Haghani: Isn't it just amazing? Even when we're following the news, just how little we are really seeing of what's going on in the world. I don't even know the last time that I heard about what's happening in Thailand.

No idea. Every once in a while, it's like, oh, this happened in South Africa, or this happened in India. We get such a narrow version of news.

I don't know what we could do about it because there's just so much news. How much of it could we consume anyway?

Ben Felix: That's an interesting question. Not all of it, probably.

Victor Haghani: Yeah.

Ben Felix: How do you choose? How concerning do you think the amount of leverage in the US stock market is currently?

Victor Haghani: Leverage is something that we built into our model for our Who Killed the Random Walk paper, and then we didn't wind up using it at all. We left it out even though we built that in. Leverage certainly exacerbates all of the instabilities that we have.

I think that the leverage is concerning, particularly the leverage that we have embedded in leveraged ETFs, which we know have to do systematic trades at the end of every day, when the market or stock or whatever the thing is based on goes down, they have to sell, and when it goes up, they have to buy. Margin interest is pretty big, but I don't think margin interest is terribly concerning. It probably helps that Fidelity and Schwab are still charging 9% for margin.

I think that makes it clear to many people that you don't want to be running leverage longs for long. Then we have this absolute explosion in options trading, and that is effectively potentially a lot of leverage. When you go back and think about October of 1987, that Black Monday, and how the Brady Commission or whatever was like, yeah, this got caused by portfolio insurance and the trades that needed to be done, and the portfolio insurers need to sell 60 billion of stocks, and that set the whole thing off.

I think that the market can absorb things sometimes, and other times it doesn't. I think that leverage is concerning, not massively concerning, but concerning. There's more than meets the eye from just looking at the margin figures.

All of a sudden, you hear about something like the Situational Awareness situation. I never knew about that leverage. I had no idea.

Who else is out there with leverage and leveraged long-shorts? Fidelity and Schwab are kind of saying, hey, going back to the leverage long-short direct index thing, they're saying, we're a little bit concerned about this. We don't want too much more of this on our custodial balance sheet or in our custodial system, because they're a little bit worried about it.

Sometimes the markets can really deal with a certain amount of leverage, but that same amount of leverage sometimes can be problematic.

Ben Felix: Situational Awareness, just for any listeners who don't follow the financial news as closely as we do, was a fund that was highly levered, invested in AI-related stocks, and had a fabulously large downfall or decline in the value of its holdings.

Victor Haghani: I guess not downfall, but decline, yeah. It's like a lot of leverage that we didn't know about.

Ben Felix: I know listeners will have caught on to the comment about the daily resets on leveraged ETFs, because we've had some discussion within our podcast community about how, from the investor's perspective, daily resets are actually not a terrible thing, even for a long-term investor, but you're talking about the effect, I think, on volatility and asset prices in the market. There is a recent paper looking at the effect of leveraged ETFs on the Korean stock market recently, and they do show that in that case, it's a smaller market, obviously, different environment than the US, but they did significantly increase volatility, which is pretty interesting.

Victor Haghani: Boy, that Korean market, that's incredible, yeah. Things spill over. There's all kinds of interrelationships, which is all pretty highly nonlinear, all this stuff.

We have the butterfly effects, where a small thing can really get things going with these interrelationships.

Cameron Passmore: When does it make sense to borrow to invest in stocks or any other risky assets?

Victor Haghani: First of all, the iconic sensible case for leverage involves young people where they have a lot of human capital, where hopefully a lot of that human capital is not highly related to the stock market. They have human capital, and it doesn't have a super high beta, so to speak, and they don't have much financial capital. They're like, okay, well, how much stock should I own?

They're like, well, I should own 50% of my total wealth, my financial capital, my human capital in the stock market. It's like, well, I just have a little bit of financial capital, so I should be leveraged. This makes rational sense.

The problem though with it is that leverage is expensive in general. It's also the leverage is pretty variable in terms of cost, but we talked a moment ago about Fidelity and Schwab, E-Trade. I don't know.

Every brokerage has their own cost of leverage, which tends to be on average really high for offering leverage through brokerage accounts. There are a few places that have lower costs of leverage, and also sometimes futures are implicitly giving you leverage at a lower cost than those high costs of 9% or whatever at Fidelity and Schwab, but it's hard to be an individual investor and to be borrowing at less than 1% over treasury bills or 1.5% over treasury bills. That's the very best that you can do on relatively small size, which is kind of the case of the person who doesn't have much financial capital.

That person doesn't have $50 million to have at interactive brokers and get the overnight rate plus 50 basis points. That person is going to be at 1.5% over the overnight rate. So now it becomes a question of, well, if the expected return of stocks is just 2% or 3% higher than the risk-free rate, does it really make sense to borrow paying 1.5% because that 1.5% is a sure cost. The 3% is a risky expected return, and we need to kind of haircut that to make it risk-adjusted. There just tends to not be a lot of juice there. It depends a little bit on the environment.

Right now we're in a low expected return environment. Levering up probably doesn't make sense for most people. It could make some sense for some people, but in general, we'd say it probably isn't worth the complexity, the risk of losing most of your savings.

It kind of hurts. You're 27 years old and you saved up a couple hundred thousand dollars and all of a sudden you have $30,000 left because you were leveraged doing something sensible, but still that pain is tough. You need to be monitoring it and keeping the exposure constant and all of that.

In some places, the deleveraging happens automatically. You don't get a chance to make a margin to top up or to do it yourself. Net, net, net, we would say that for older people that have a lot of financial capital relative to their human capital, probably it doesn't make sense to leverage.

For younger people, it's more of a borderline call and maybe just keeping things simpler and not doing it makes sense and just focusing on getting the savings into the market is going to be more comfortable.

Ben Felix: Spent a lot of time recently reading about leveraged ETFs, like just long leveraged index ETFs. The spreads above the risk-free rate are around 50 basis points, which is not crazy, but of course you're paying the 1% or whatever it is, 80 basis point fee to get access to that. It's not really that cheap, but it's maybe better than margin rates at brokerages.

Victor Haghani: It's certainly better than Fidelity or Schwab, but it starts to look like going long futures.

Ben Felix: In the product, it's closer to that. The thing that I realized looking at these over the last couple of months is that the live history of the US equity leveraged ETFs has been through a period of time where interest rates were super low and equity returns have been super high. People look at these products and they're like, wow, I want to lever up because look how good the returns are. But if you go back just a little further in time, rates were higher, realized returns were lower.

Some of the products that did exist back then in the mutual fund wrapper, they do have slightly higher fees, but still they've underperformed or they've just now broken even with just a regular US equity ETF. Going back to the 1990s, there's a pretty severe recency bias where the products that people can easily see and access look really, really good, but it's because of a very specific set of factors over that period of time and it's not always going to work out that well.

Victor Haghani: If you're going to do that, you don't want to have any cash sitting around. You don't want to have 30% of your account in cash and then have 70% in a leveraged ETF, which a lot of people can do that. I think leveraged ETF futures, some of the low margin cost brokerages, all can get you to probably 1% over risk-free rates.

But even if expected returns of equities is 2% over risk-free rates, that doesn't mean you should do it because you have to think about what's the risk-adjusted return at the margin of owning the equities. In general, that's always going to be lower than the expected return. The risk-adjusted return is always lower.

It can never go the other way because risk is always a cost. It just starts to get really marginal, I think, very quickly. In a different world, a different environment, if CAPE were 15, earnings yield was high and interest rates were low and risk premium was high, it could look a bit different, but there's plenty of risk.

If you're close to 100% in equities, that's a lot of risk. That's another thing I would say is that's just a lot of risk. It doesn't feel like a lot of risk today, but one day you'll wake up and it's going to be a lot of risk.

It's a lot of return. If markets keep going up and you had 100% in equities, you'll do really well.

Ben Felix: The human capital argument for young people is also really interesting because it makes sense. The Merton share argument for leverage makes sense for a young person, but then you start thinking about what does the human capital of a young person actually look like? Is it really bond-like for someone entering the workforce? I don't know that it is.

Victor Haghani: I don't think anything is totally bond-like. There's always going to be some beta in there. A lot of times, the person that's thinking about leverage is the person who has high beta human capital too.

It's the person working in tech, the person that's got a trading job in Wall Street or something. So many of the people are people with high beta human capital. You also have all the people that are just doing it for living, influencers and so on that are out there.

It's not totally clear what their human capital is deriving from other than things that are pretty economy sensitive.

Ben Felix: There's the beta for sure, but then there's also the tails. You look at software developers right now, there's just a lot of folks who I think are realizing their human capital was a lot riskier than they maybe thought it was just because of what AI is doing to that profession. You've got a new book that you mentioned early on in this conversation, Get Rich Once and Other Financial Wisdom for Our Younger Selves.

To finish off our conversation here, what financial wisdom would you give to your younger self?

Victor Haghani: I'm embarrassed to say this, but I would say read a book like this. Do something proactive to make a plan and to really think about your finances. I say that it sounds so obvious in a way, but I can tell you that when I started in Wall Street in 1984, I went for a really long time without thinking about my personal financial situation.

I was busy, I was doing well, I was dating, and I just didn't do it. I had learned this stuff in university. I studied finance in university, but there was some kind of disconnect between leaving university, working in Wall Street, where I just didn't think about this stuff.

I would say, whether you read our book, there's so many ways today to make yourself really financially literate and to give yourself enough financial sophistication so that you can make a plan, you can make a lifetime plan, you can get your financial affairs in order, and you can do all of that in the time it takes to watch one season of your favorite Netflix series. In 10 hours, you can just really have your whole situation sorted out. This is how much I really need to save.

I'm doing the best with my 401k match or whatever we have in Canada. All of these things, they are simple, but it just takes some time. We should all be doing that.

Besides our book, our forthcoming book, there's so much other resources out there for people to use to get there. There's parents, there's other elders, there's other colleagues, there's other friends. It's just a question of being intentional and devoting that time to it, because it's amazing how many of us didn't do it and how many people are not doing it today.

Ben Felix: You said you were embarrassed to reference your own book as the resource. I don't know, man. I was doing an interview for a newspaper recently, and they asked me the same question, and I thought about it. I was like, you know what? They should listen to this podcast.

Victor Haghani: Absolutely.

Ben Felix: If you're producing good information, you should tell people to consume it. It's not an embarrassing thing.

Victor Haghani: So many of my friends are huge fans of your podcast. Absolutely. It's a great way for people to get educated, and there's great stuff out there. It's just being intentional about going after it and doing the right thing.

Ben Felix: It matters. We hear, and it's not just our podcast. Like you said, there's lots of good stuff out there, but we hear from people who they'll email Cameron and I, and they'll say, you changed my life.

You completely changed the course of my life just by having good information. They're making financial decisions more confidently now, and it matters, but the resources are out there. You just have to dedicate the time to consuming them.

Victor Haghani: Super rewarding for all of us, for sure.

Ben Felix: 100%. Well, that's a good place to finish, Victor. We really appreciate you coming back on the podcast. This was a great conversation.

Victor Haghani: Thank you both very much. Hope to see you guys in person before long too.

Ben Felix: Definitely.

Cameron Passmore: That'd be nice. Thanks, Victor.

Victor Haghani: Thanks, guys.

Cameron Passmore: That was something.

Ben Felix: Yeah.

Cameron Passmore: Trying to think like how do you encapsulate the conversation?

I wrote down a line, and he basically off mic said the exact same thing, which is there's so much to talk about in a market portfolio environment, and it's true.

Ben Felix: Yeah, it is true. We covered so much ground. I love talking about super nerdy stuff.

You were messaging me as we were going about how the nerds are getting their fill, and they were, but the whole conversation about direct indexing, super interesting. His paper on Who Killed the Random Walk, also fascinating. Just thinking about where the different market anomalies come from, and where the different return premiums come from that we see in the market and kind of thinking about who is responsible for that, what's going on at the investor level that's causing the anomalies that we see.

Their little study that they did on whether you can predict returns from tomorrow's news, super interesting. That's such a cool experiment to run.

Cameron Passmore: I mean, tomorrow's news today, I had no idea they've been done that many times, but that's pretty amazing. Even AI couldn't really take advantage of it.

Ben Felix: I love the discussion on leverage. That's something I've been looking at quite a bit recently, and I think Victor's thoughts are so good. He applies just the Merton share thinking so well to so many of these topics.

I'm glad that we talked a little bit about what the Merton share is, and what it means, and why investors should care about it during the conversation. Victor, we mentioned in the introduction, he is the founder of Elm Wealth.

They've also got an ETF out through their firm that's doing position sizing based on Merton share thinking. They're using expected returns and volatilities over time to change the allocation between equities and fixed income. It's kind of neat, but they've also got a wealth practice as I understand it.

Victor was one of the founding partners of Long-Term Capital Management, which is a very academic hedge fund. A bunch of academics were involved. That collapsed in 1998 quite spectacularly.

Cameron Passmore: To say the least.

Ben Felix: To say the least, yeah. We talked in our last episode, episode 270 with Victor about that experience and how it shaped his thinking in the rest of his career after that event.

I remember the first time Victor reached out to us, I knew him as a character in that story about Long-Term Capital Management.

Cameron Passmore: He was in the book.

Ben Felix: I was blown away when he reached out, but he's very thoughtful. It's neat to see him doing research that's getting into some journals. Great thoughts from him on all those topics.

Cameron Passmore: Good guy and a great communicator. It's really nice to have him on.

Ben Felix: Anything else?

Cameron Passmore: No, I think that's good. Thanks everybody for listening, of course.

Ben Felix: Yeah. I hope everybody enjoyed the episode.

Disclaimer:

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This communication is distributed for informational purposes only; the information contained herein has been derived from sources believed to be “truthy,” but not necessarily accurate. We really do try, but we can’t make any guarantees. Even if nothing we say is fundamentally wrong, it might not be the whole story.

Furthermore, nothing herein should be construed as investment, tax or legal advice. Even though we call the podcast “your weekly reality check on sensible investing and financial decision making,” you should not rely on us when making actual decisions, only hypothetical ones.

Different types of investments and investment strategies have varying degrees of risk and are not suitable for all investors. You should consult with a professional adviser to see how the information contained herein may apply to your individual circumstances. It might not apply at all. Honestly, you can probably ignore most of it.

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Participate in our Community Discussion about this Episode:

https://community.rationalreminder.ca/t/who-causes-stock-market-anomalies-w-victor-haghani-429/43446

Sources From Today’s Episode:

https://zbib.org/62e42e55fae14cb0a1aa62941d6996a2

Papers From Today’s Episode:

Who Killed the Random Walk? How Extrapolators Create Booms, Busts, Trends, and Opportunity — https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6062494