Victor Haghani: Lessons From the Missing Billionaires

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Our guest on the podcast today is Victor Haghani. He is the co-author of a new book called The Missing Billionaires: A Guide to Better Financial Decisions. In 2011, Victor founded Elm Wealth, an investment advisory firm for high-net-worth individuals. He 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 graduated from the London School of Economics with a bachelor’s degree in economics.

Background

Bio

Elm Wealth

The Missing Billionaires: A Guide to Better Financial Decisions, by Victor Haghani and James White

Investment Sizing and Expected Utility

“The Most Costly Investment Mistake You Can Make Is Easy to Avoid,” by Victor Haghani and James White, Bloomberg.com, Feb. 14, 2024.

“Bigger Is the Enemy of Better Investing,” by Victor Haghani and Richard Dewey, businesstimes.com, March 20, 2021.

Robert K. Merton

“Merton Model: Definition, History, Formula, What It Tells You,” by Will Kenton, Investopedia.com, Aug. 10, 2022.

“Lifetime Portfolio Selection Under Uncertainty: The Continuous-Time Case,” by Robert C. Merton, jstor.org, August 1969.

“How Much of a Good Thing Is Too Much?” by Victor Haghani, linkedin.com, Oct. 11, 2022.

“To Realize, or Not to Realize,” by Victor Haghani and James White, elmwealth.com, Oct. 22, 2020.

Lifetime and Retirement Spending

“Spending Like You’ll Live Forever,” by Victor Haghani and James White, elmwealth.com, April 6, 2021.

“Cut Your Losses Early; Let Your Profits Run,” by Victor Haghani, linkedin.com, Aug. 8, 2023.

Puzzles

“George Costanza At It Again: The Leveraged ETF Episode,” by Victor Haghani and James White, elmwealth.com, April 16, 2020.

“Who Wants Protection Like This?” by Victor Haghani, linkedin.com, Nov. 14, 2022.

Other

“Vic’s TEDx Talk: Where Are All the Billionaires and Why Should We Care?” Elmwealth.com, March 8, 2013.

Matt Levine

Michael Lewis

The St. Petersburg Paradox

Hal Hershfield

“Hal Hershfield: People Treat Their Future Self as if It’s Another Person,” The Long View podcast, Morningstar.com, Sept. 21, 2021.

Stumbling on Happiness, by Daniel Gilbert

When Genius Failed: The Rise and Fall of Long-Term Capital Management, by Robert Lowenstein

Inventing Money: The Story of Long-Term Capital Management and the Legends Behind It, by Nicholas Dunbar

Transcript

Amy Arnott: Hi, and welcome to The Long View. I’m Amy Arnott, portfolio strategist for Morningstar.

Christine Benz: And I’m Christine Benz, director of personal finance and retirement planning for Morningstar.

Arnott: Our guest on the podcast today is Victor Haghani. He is the co-author of a new book called The Missing Billionaires: A Guide to Better Financial Decisions. In 2011, Victor founded Elm Wealth, an investment advisory firm for high-net-worth individuals. He 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 graduated from the London School of Economics with a bachelor’s degree in economics.

Victor, welcome to The Long View.

Haghani: Thank you very much. Great to be here.

Arnott: We wanted to start out with some background on the book, The Missing Billionaires. I’m curious about when you first started thinking about writing a longer book like this. Was it part of the aftermath of your experience with Long-Term Capital Management?

Haghani: No, it came well, well after that. The first reaction I had to the failure of Long-Term Capital Management was to crawl under a rock and hide for a while. I spent a lot of time thinking about different things. And the idea really of this book came about when I started to think more and more about a framework that would have been useful while I was at LTCM. But it also coincided with my meeting and becoming partners with my eventual co-author James White, who were partners in business together. And he had been thinking about the same ideas and so on. And it was like, wow, here we are, both of us thinking about these same things and not that many other people were at the time. So, it came much, much later. But the idea of the book really was like, wow, this would have been a great book if I had been able to read it in my 20s, along with an admonition to really take it seriously. So, while we think that it was going to fill a gap in the literature of personal finance and household finance, it was also written with our younger selves very much in mind.

Benz: You planted some of the seeds for The Missing Billionaires book in your TED Talk in 2013. It was called “Where Are All the Billionaires and Why Should We Care?” So, the title of that speech is based on your calculation that there should be about 16,000 old-money billionaires alive today, but there are virtually none on the Forbes 2022 list of 700 US billionaires. So, what does that owe to? Does that all come down to bad financial decision-making along the way for these people who were once wealthy and now not so much?

Haghani: I think that the explanation for why there are none come down to that. If we had less but still a lot, you would say, well, there were a lot of them who just decided they wanted to consume more or that they wanted to give a lot more to philanthropy or to give most of their wealth to philanthropy. But the complete absence of anybody tracing back to there is really an indication that there is something very profound going on and that these poor financial decisions under uncertainty also have to be subtle ones. They’re not super-simple obvious ones as well, I think, for it to be so complete. But there are many factors that would stop that intergenerational maintenance of relative wealth. But yes, I think that this total lack of these families, or virtual total lack of these families, really speaks to some important lessons that we can learn about financial decision-making.

Arnott: So, it’s not just millennials spending too much on avocado toast and lattes, that kind of thing?

Haghani: Definitely not. No.

Arnott: The book deals with some pretty complex topics like how to estimate probabilities and how to maximize the utility of your decisions. But at the same time, you mentioned that you were inspired by other financial writers like Michael Lewis and Matt Levine, who both really write in a way that’s very accessible to a general audience. I’m curious, how did your writing process work and how did you try to keep the content entertaining and accessible?

Haghani: Well, it was really a challenge. And I think probably nobody more than Matt Levine inspired us that it’s possible to write about complicated topics but in a way that people can get. Two things that we tried to do was, one, we tried to get into everything relatively slowly without talking about any theory until about chapter six to really give people a chance to get their hands around all these issues without talking about anything abstract, without talking about any symbolic mathematics or anything like that until chapter six. And hopefully by then we’ve convinced people that this is important and it’s worth thinking about and it’s not going to turn out to be that complicated.

The other thing that we tried to do is to really just put in lots of stories and antidotes that really are related to the ideas in there. And we think that that kind of lightened things up. Both James and I had a lot of funny things that happened to us and that we saw over the years, and we try to pepper the conversation with practical and entertaining stories throughout. It’s really a book that you don’t need to read from cover to cover. You can dip in and dip out and get the main concepts and then decide how many examples you want to take a look at. In fact, the whole final segment of the book about puzzles that you can unlock with the ideas in the book, you can skip the whole thing without loss of understanding of the main ideas.

Arnott: There is some math in the book and some formulas that some people might be intimidated by. But I think there’s enough explanation that even if you’re not a math geek, you can still follow what you’re getting at.

Haghani: Thank you. Yeah, we hope so. Of course, our publisher told us every equation will have the number of people who buy your book. I don’t think he was right because we would have only had about 10 readers if that had been the case. So somehow that law of halving isn’t quite right.

Benz: We wanted to delve into some specific aspects of the book. One of the topics that you tackle is investment sizing, position size. Most financial advice available today to the average investor focuses almost exclusively on what to invest in rather than the equally critical question of how much investment is the right amount. So why do you think that people so often ignore that question and move straight to what?

Haghani: I think that the what question is where all of the excitement is. What should we buy? Is Nvidia going to keep going up or not? And is Apple going to rebound or whatever? Those are the stories and narratives that are so exciting and attractive to us. And it’s a full contact sport. Stock-picking is probably the most competitive sport on the planet if we count chess as a sport, too. So, I think that that’s where the attention is a lot. And the sizing question just gets left over. Also, to make the sizing decisions you need to have an idea of your own preferences, of your own level of risk aversion, of your own level of subsistence or basic income that you need. And you need to have some assessment of the expected return and riskiness of all the different things you can invest in. So, I think, for a lot of people, they just try to short-circuit the whole thing, or a lot of advisors just try to short-circuit the whole thing and say, OK, if you’re an average person, 60/40 equity fixed income is good for you. If you’re young and aggressive, 90/10 or 50/50 and somehow really jump over all of that. Whereas we think there’s a lot of low-hanging fruit, a lot of low-hanging improvement and welfare that we can get from thinking about sizing. And of course, in the extremes, it’s really important when you could potentially be using leverage or there’s a lot of decisions where this idea of how much is absolutely critical—it’s not just getting an improvement in welfare, it’s really changing your financial situation dramatically by getting it right.

Arnott: I think that’s a good point. And one of the things you write about is that as long as you’re in the right neighborhood of an appropriate allocation size, whether you’re 65% invested in stocks versus 70% is probably not going to make a huge difference, but it’s at the extremes where it can make much more of a difference.

Haghani: Absolutely. It gets really steep the further away you get, but it’s flat around reasonable or optimal places. Exactly. That’s a good thing to take away in general.

Arnott: One of the foundational concepts you discuss in the book is called the Merton Share, which is a formula for figuring out the optimal amount of wealth to invest in a risky asset or a portfolio. And it actually dates back to a paper Robert Merton wrote back in 1969. But it really never took off outside of academic circles. I’m curious, why do you think that that is?

Haghani: Well, I think there’s a couple of different reasons. One is that in its first incarnation where it came out in—actually in this pair of papers, Bob wrote The Continuous Time Version and Paul Samuelson, his mentor, wrote a discreet version of it. And both papers are pretty inaccessible. But then people worked more on it for the next 10 years or so and made it easier to understand and more realistic. But I think that one thing that happened is that that whole area of research got overtaken or overshadowed by the big breakthroughs and option pricing and derivative pricing and all these things—the whole contingent claims literature that was so exciting because it really was usable in Wall Street that it just eclipsed this earlier work on portfolio choice and lifetime consumption or lifecycle financial decisions. Interestingly, seven or eight Nobel Prizes have been given out for lifecycle investing research to Samuelson, Merton, Modigliani, and others. But it just couldn’t make that jump into the mainstream. And of course, a big part of it is, as soon as you talk about expected utility or talk about a person’s utility curve, people’s eyes can glaze over. And we hope that in our book, we’ve tried to really make all of those ideas more accessible, more practical for people to implement.

Benz: Can you discuss when you say expected utility, what does that mean just to make sure that all of our listeners are following along here, too?

Haghani: Well, what we care about is not how much money we have, but we ultimately care about what our money can do for us to make us happy to either be spending it on ourselves, or to be giving it to others as either to our family or to philanthropy. So, these are the three main things we can do with our money. Maybe they’re the only things we can do with our money, because I don’t think that counting it should count as a real use of our wealth.

So, then we have to think, well, how happy, how much satisfaction, how much welfare does spending our money on these different objectives bring to us? What we generally find is that this utility curve that’s mapping wealth or spending into happiness, that that curve is concave. In other words, it flattens out the more wealth or the more spending you do, because we have a decreasing marginal improvement in our welfare with higher spending or wealth. In the book we talk about, well, if you like gummy bears, and you have a couple of them, that’s great. The next two are going to give you less enjoyment than the first two and the 50th and 51st one are going to give you really a lot less satisfaction than the first five or 10. And that decreasing or diminishing marginal utility of consumption or wealth is what makes us risk-averse. And it’s what we have to take into account when we’re making these financial decisions under uncertainty. So that’s really all that’s meant by a utility curve is that we’re risk-averse because making more money or spending more money generally brings us less of an improvement in our welfare or happiness than the same amount of decrease would decrease our happiness by.

Arnott: Another theme that runs through the entire book is the fact that making sizing decisions with the goal of maximizing expected wealth rather than expected utility can really lead to bad results and disastrous results in some cases. Can you walk us through why that is and how the variance of the investment and your personal degree of risk aversion should also come into play?

Haghani: Absolutely. This is an observation that goes back almost 400 years to Daniel Bernoulli and the St. Petersburg Paradox, a game which was a paradox because it has an expected value. If you were allowed to play the game, the expected value is infinite, but nobody would pay all of their wealth in order to play it. It’s a coin-flipping game and I won’t go into it here, but for interested listeners, it’s fun to look it up on Wikipedia, the St. Petersburg Paradox.

We like to illustrate the idea with a more reasonable, still abstract a little bit, but more reasonable thing. Imagine that you’re allowed to flip a coin, which you know has a 60% chance of landing on heads. It’s not a physical coin, but like a computer digital coin. Every time you flip it, it has a 60% chance of landing on heads, 40 on tails. You can invest as much of your wealth as you want to on each one of these coin flips and you get to do it, say, 25 times. Well, the question is what strategy should you follow, and should you have an objective of trying to maximize your expected wealth? Well, if you work through the math of what you should do if you want to maximize your expected wealth, you’ll find that betting as much of your wealth as you can on each flip is the optimal strategy to maximize your expected wealth. But clearly, betting 100% of your wealth on every flip for 25 flips is almost definitely going to wipe out all of your wealth and nobody would want to do that because all you need to flip is one tails and now you don’t have any money left, but that gives you the highest expected wealth.

So, as soon as we realize that, we see that, oh, that’s not a good objective, that maximizing expected wealth, the expected value of our wealth, the probability of each outcome times how much wealth you’d have in that outcome, that can’t be the right thing to do. And what we find is that just by exploring this coin-flipping toy example is that there’s going to be a fraction of your wealth that you would want to bet that maximizes your comfort with the range of outcomes. And that is how you can calibrate your degree of risk aversion. If you had no risk aversion at all, you would want to bet all of your money on every flip every time. And that’s why we don’t think that really anybody should have or does have zero risk aversion, although the famous case of Sam Bankman-Fried claiming that he was risk neutral and had no risk aversion at all, well, it seems that maybe he did behave that way. But if you do behave as if as though you have no risk aversion, you will very likely go bust with a very, very high probability at a very short period of time.

So, as we think about what’s the optimal amount that we want to bet of our wealth on each one of these coin flips, which helps us to calibrate our degree of risk aversion. And what we find is that the optimal amount that we want to bet on some opportunity is proportional to how attractive it is, what the odds are in our favor, but it also is proportional to the risk that’s involved in that investment or that gamble. And what we also find is that as the attractiveness goes up, we want to bet more and more in a proportional way. But as the risk goes up, we want to bet less and less, but in a quadratic way, in a squared way. So, increases in risk bite more quickly than increases in expected return.

Benz: You have a section in the book about lifetime spending and investing, and we wanted to delve into that. Individuals now need to answer questions that they mostly didn’t need to think about in the days of employer-provided pensions, including making decisions today that incorporate planned decisions for the future. So why do you think it’s especially difficult for people to think that way?

Haghani: Well, I think that making disciplined, consistent decisions over decades is really difficult. If you could compress your whole decision-making into a few hours, you would probably be able to act quite rationally. But when it’s really spread out over a long period of time and your psychology is changing and you’re just evolving as a human being, I think it’s really hard to maintain a consistency over a long period of time that at some point you lose that discipline. It’s just hard to maintain it over a really long period of time. I think also that people are just not aware of these frameworks very much. So, people tend to take it one year at a time and don’t have a long-term plan or see how things could all come together in a long-term plan. So, I think part of it is also just awareness and education as well.

Arnott: One of the bigger challenges that people face during their lifetime is figuring out how much to spend during retirement. And you write that if you’re trying to figure this out, the optimum amount of spending each year has to be proportional to the portfolio value. So, if the portfolio goes up by 10%, you would want to increase your spending by 10% and vice versa. But at the same time, a lot of people really have a strong preference for keeping their spending as smooth as possible over time. So, are those two goals in conflict? And how do you think advisors can help harmonize them?

Haghani: I think that those two things that you just discussed are kind of the same thing. And the two things that are in conflict are that, one, people want as smooth spending as possible. They want to have smooth consumption over their lifetime more or less. So that’s one goal that they have, or that’s one thing that’s good. And the other thing that’s good is having more consumption over their lifetime. So, we want our consumption to be smooth and we want it to be big or bigger and bigger, as big as it could be. And those two things are basically in conflict with each other because the only way to get more spending over your lifetime, assuming that you’re in retirement and that you don’t have control over your labor income, that is, the only way to be able to spend more is to take more investment risk. And so that’s really where the conflict is that it’s like, if I take more investment risk, I can expect to be able to spend more, but my spending is going to be less smooth. If I want my spending to be totally smooth, I have to have a risk-free, or relatively risk-free, portfolio. And those two things are in conflict with each other. And those two things give us a trade-off that tells us that there’s going to be some optimal amount of risk to take so that the amount of spending that I get is trading off against the variability of the spending. I don’t want variability. I do want more money. And those two things take us to an optimal place.

Benz: Can you talk about time preference, the idea that people want money now versus waiting until later, and how should that affect spending in retirement?

Haghani: Well, time preference is a really fascinating topic. I didn’t realize how much research and writing there was on it. We found a whole book on time preference as we were doing our research that was fascinating with a bunch of philosophers’ contributing articles where the philosophers were talking about the arbitration between today me and me 10 years from now. Like who is this Victor 10 years in the future? I don’t know that guy. We’re linked together somehow, but it’s really some fascinating and mind-bending stuff in this whole place. But in general, the idea of time preference is that people generally value spending and enjoyment today more than they do in the future. It was the famous marshmallow test when we were kids. Maybe the famous marshmallow test is a great time preference example, where it’s like, give me that one marshmallow now; I don’t want to wait some period of time to get the two marshmallows. I’ll just take one now and enjoy it.

Benz: Right.

Haghani: It’s a little bit hard to tie down exactly what our time preference is. But if we do have a time preference of say 2% a year so that we prefer spending, or we’re indifferent between spending $100 today or $102 a year from now, adjusted for inflation that is, then what time preference does is it front-loads our spending a little bit. It makes us want to spend more in the present, in the near term, than in the very long term. But I would say the time preference doesn’t affect spending in retirement all that much. You’re 65 years old, maybe you’re going to live 25, 30, 40 years. The time preference isn’t changing that pattern all that much. We shouldn’t get too carried away with exactly what that stream looks like. We should just model it out somehow. But the time preference isn’t a huge, huge impact on our welfare for 20-, 30-, 40-year horizons. For an endowment or a foundation or a family that expects to have a very long life to their capital, then it starts to come in and has a pretty big impact on the optimal spending policy. But for, as I said, 20, 30 years, it’s not huge.

Benz: Have you seen that research from Hal Hershfield, for example, which looks at getting people to visualize their future selves and that helps them empathize with themselves and identify with themselves a little bit? Do you think there’s power in trying to help people look ahead using AI or whatever to really make it tangible what they might look like in the future?

Haghani: I’m not familiar with that particular research. That sounds very interesting and useful potentially. I’ve been also really influenced by the Dan Gilbert research and particularly his book Stumbling on Happiness that really shaped my thoughts around the same thing and how will my future self be, and so on. But that, Hal Hershfield stuff sounds, I’ll definitely take a look at it.

Arnott: When you think about retirement spending, how does an optimal spending approach differ from the 4% rule or other popular methods?

Haghani: The 4% rule is really very much at odds with the literature on lifetime consumption and portfolio choice because the 4% rule says, I retired, I have X amount of money, multiply that by 4%. Let’s say I have $2 million, multiply it by 4%. That’s $80,000. Spend $80,000 for the rest of your life, adjusted for inflation, and God willing, don’t run out of money. The 4% rule is putting a fixed spending policy against what probably is going to be a risky portfolio because it’s actually predicated not on putting all your money into TIPS or Treasury bills, but it’s predicated on having a good amount of equities in your portfolio as well. So, it’s really at odds with this idea that putting a fixed spending policy against a risky investment portfolio is a real recipe for disaster. It just happens that historically, if you invested in US equities, that 4% would have been OK over some historical simulations. But we really think that’s a very dangerous and ill-considered approach to lifetime spending.

Benz: A lot of people find the idea of living off their portfolios’ interest and dividend income appealing, and that’s a little bit more reasonable/possible today given that yields have come up so much. Why don’t you think that’s the best approach?

Haghani: Well, first of all, we feel that money is money, whether it’s the value of your portfolio, whether it’s what it’s paying you in dividends and interest, that wealth and money is just all completely fungible. And so, we think that this distinction that has to do with what are interest rates, what are dividend yields, what’s dividend payout policy, just should be irrelevant to your lifetime decisions around spending and investing as well. We don’t really believe in this whole idea of income investing, trying to invest in companies that have high dividends just because they have high dividends. We feel that that approach can lead you astray to take some amount of stock-picking risk that isn’t necessary. I think sometimes it turns out that living off your dividends and interest, it’s like, OK it’s super simple. It’s got that going for it. But also, that if depending on what your bequest desires are—if you’re trying to spend your wealth for the most part over the rest of your life, maybe you’ve given away as much as you want to to your kids or charity already, and you’re like, I just want to live off my wealth for the rest of my life. Well, if you just go off of dividends and interest, you might really wind up spending way less than you should spend. Let’s say, you’re 90-years-old and you’re living off your dividends and income, you’re spending way too little. You should be running your portfolio down at that point and living it up. I tell my mom that all the time and she’s not buying, but maybe I’m going to get her to buy a new car before she turns 90 in May. I don’t know.

Benz: I hope so.

Arnott: I think if I live to 90, I’ll have to buy myself a nice car. Yeah, definitely.

Benz: And you’re still driving better yet, right?

Arnott: Right. We can only hope. We also wanted to talk a little bit about how to implement some of the ideas in practice. And one exercise that you suggest that readers do is to write down how they’d like to dispose of their current wealth over the rest of their lives, including bequests and giving to charity, and then do the same thing, imagining that they have either less wealth or more wealth than they currently own. Is that something that you go through with your clients at Elm Wealth when you meet with them?

Haghani: We do, particularly the card of how do you want to dispose of your wealth in the central case where you know how long you’re going to live exactly? It’s really hard to get people to accept the thought experiment of, “I am going to only live this long.” It takes people a little while to be willing to engage with the thought experiment there. But no, we do do that. And we find that people find that really useful, a very useful and practical exercise. And thinking about how it changes in an up and down scenario helps to calibrate the risk aversion as well. So yeah, we do do that. We have a lot of clients who are all set, and they don’t want to talk about that stuff with us much. But we have a lot of clients that we spend a lot of time talking about that. And when we do, we really like that approach for having them really thinking clearly about their bequest priorities.

Benz: You write about why it makes sense to use the cyclically adjusted earnings yield, which is equal to one over CAPE as a forecast of the long-term real return of a broad equity market. Right now, that suggests real returns of about 3% in the US, which is much lower than what most investors are used to. What are the implications of that, of those low return expectations for the average investor?

Haghani: Well, we believe that your asset allocation should be a function of what is the expected return on all the different assets that you can own and what’s their riskiness like. And so, looking at US equities and feeling that they have something like a 3% long-term real return over a very long horizon and recognizing that, say, 30-year TIPS are right around 2% is saying that if you own US equities, you should expect to make about 1% more than a relatively safe asset with a comparable payout in terms of it being inflation adjusted. And that’s really low. And we think that as a result that people probably shouldn’t have all that much invested in US equities. Then there’s the risk component to it. We’re at a relatively low risk or low volatility state. So that might bump up how much you’re willing to own of US equities. But if we go back into a higher volatility state, you’ll really want to own very little US equities at all, I would say. Fortunately, the rest of the world looks a lot more attractive than that. And so, despite—and we’ll talk about this maybe later—but despite the incredibly disappointing returns of non-US equities relative to US equities, we think that for long-term investors, they offer a much more attractive return and should be a bigger part of one’s portfolio.

Arnott: So, are you actually overweighted in US equities with your clients?

Haghani: No, we’re still underweight. We’re very close to a neutral weight for US equities because this very low expected excess return is being offset by being in this low-risk environment. So those two things are offsetting. So, we’re just a little bit underweight US equities, and then we’re overweight non-US equities, and we’re close to client baselines for overall equity exposure relative to fixed income.

Arnott: Going back to the importance of taking volatility into account, you have a funny section of the book where you imagine a Seinfeld episode where George Costanza, he buys both a three, three X leverage long ETF and a three X leverage short ETF, and he thinks it’s a can’t-lose bet. But he actually ends up a year and a half later with one down 20% and the other fund is down almost 50%. And basically, that’s from the negative impact of leverage. Can you explain more about why leverage is so toxic and damaging?

Haghani: That’s right. I think that, well, it’s risk that eats returns. We want to have the highest compound return, all else equal. We want the highest compound return on the growth of our wealth as possible. But the more risk that we take, the more that that will eat into the compound return. And so, the more we invest in something attractive, the expected return is going up. But the more we invest, the more that risk is eating into the compound return.

So, the easiest illustration of this is, imagine something that goes up 50% one year and down 50% the next year. The average return was zero plus 50 and minus 50, but you’re left with the 25% loss over the two years. And that volatility drag, the fact that compound returns are hit by the volatility in returns is the central idea here. And leverage is allowing us to take so much risk to the S&P here that even though the S&P went up a little bit over this George Costanza trade period—which, by the way, it wasn’t even George’s idea, it was Kramer’s idea in our make-believe scenario, which makes it a little bit more understandable how it went wrong. But, the S&P was up a little bit over the period that George invested, but his three times leverage long position in the S&P lost 20% because all that volatility—let’s say the S&P has 20% annual volatility, but now you leverage it three times, so it’s like 60%. So now it’s similar to our up 50 down 50, except here is like up 60 down 60, that volatility drag is so big that it wound up generating a negative compound return even for the leverage long one. So, it’s really interesting just how much leverage or just taking too much risk really eats into our compound returns. And that’s how we get to some optimal level of exposure that we want on our investing. That’s very integral in answering the “how much” question because our expected return is going up linearly with position size, but the cost of the risk, whether it’s cost to the compound return or cost to our expected utility, is going up with the square of risk. It’s going up exponentially. And so, that’s how you wind up getting this nice, inverted parabola that has a maximum point where it’s the optimal sizing of the investment.

Benz: We did want to delve into Long-Term Capital Management, which you referenced at the beginning of the conversation. Most of our listeners are probably familiar with what happened there. I know it was a seminal event for me when I was a young analyst. It was the biggest hedge fund launch ever at the time and was initially successful in its first five years, but the fund then lost $4 billion in a very short time period in 1998. It was eventually bought out and recapitalized by a group of 14 banks and then eventually liquidated. You’ve written that your time there was a life-changing experience that led you to question and revise much of the way you thought about the economy, markets, and investing. Can you talk about when that period of questioning started? Was it immediately after things unraveled at the fund or did it take a while for things to sink in?

Haghani: It took time. Certainly, in the direct aftermath, the partners that stayed behind were working for this consortium of 14 banks and we were tasked with liquidating the portfolio, hopefully at a profit for the banks, but to liquidate it and to move on so the banks didn’t need to worry about it anymore. So, the first year after LTCM I wasn’t thinking about it all that much. I was thinking about it a little bit but was pretty busy with things. Shortly after that, I went on sabbatical—maybe another year later, I went on basically a 10-year sabbatical. I really spent a lot of those 10 years thinking about the lessons and trying to take on board what had happened.

One of the things that was really impactful on my thinking was all of a sudden waking up one day and now we had the global financial crisis. So, it was like, wait a second—if LTCM had survived in 1998 and gone on, here we would have been faced with an even bigger kind of crisis hitting all kinds of relative value types of relationships, which was our bread and butter. So, I would say that my thinking really has been reshaping and being reformed almost over the last 20-odd years or 25 years since LTCM. It’s a shame that there was so much pressure on certain people to write about LTCM within the first few months after the collapse. So probably one of the most-read books on LTCM is the Roger Lowenstein book, When Genius Failed. There was also a Nick Dunbar book called Inventing Money, and both of those were written within a year. They were racing to press to write something. That’s fine. There was demand to read about it.

But in terms of getting more lessons out of LTCM, I think that having more time to think about things and for everything to settle in would have been valuable. I think that very few lessons have been learned from LTCM as far as I can tell around the system. Over the last 25 years, we’ve continuously had highly leveraged hedge funds doing relative value trading ever since LTCM. Part of that was that right after LTCM, those investments were so profitable that they gave a huge boost to anybody that was still able to invest in them post-1998. So, it made people [say] no, this is actually a pretty attractive thing as long as you don’t follow the path of LTCM. We’ve had leveraged relative value trading for the past 25 years in bigger and bigger and bigger size. We know that liquidity in the market has been going down and down and down as a result of The Volcker Rule and Dodd-Frank and all that. And we also just see people continuing to just have massive skin in the game, which I know is a topic that we’re likely to touch on shortly.

Arnott: I think you alluded to this earlier, but you wrote that you had about 80% of your family’s personal wealth invested in the fund, although you also had sufficient assets set aside, it sounds like, so that you were able to go on a pretty long sabbatical afterward. So, in thinking back to how much you allocated to the fund, was that an issue where you were trying to maximize wealth instead of utility, or did you underestimate the potential risk of the fund’s strategies?

Haghani: First of all, I think that I was adrift, that I didn’t have a really great framework. But the best thing that I could come up with was an idea of I want to maximize my wealth subject to having enough money to not be bust if everything goes wrong. And I think that was just a really bad objective function to have. It was almost nonsensical. Because if you do that, if that really is your objective function—I’m going to try to maximize my wealth subject to keeping some money here on the side—well, what that really is, is you’re back to what we were talking about earlier, that if somebody came to me with a 60/40 coin, I should have said, OK, I’ll bet all my wealth on heads for the 80% of my money that I’m not putting off to the side. And probably I would keep doing that until they stopped letting me do that, or I lost all my money. That would have been nonsensical. I wouldn’t have done that, but I’m saying that that’s the implication of the framework that I was more or less operating with. I don’t particularly think that we underestimated the potential risk of the fund’s strategies. We had seen lots of crises happen. We knew that there was a chance that the probability of a collapse of LTCM, we would never have put that at zero or effectively at zero. We would have always had a small but still impactful probability of that happening, which I think makes my decision all the more questionable or bad.

Benz: We wanted to ask about your current firm, Elm Wealth, which you started in 2011. Your investment advisory fees there are extremely low, just 12 basis points versus a 1% industry average for people with $1 million accounts. You’re even undercutting Vanguard at that level, where their investment advisory fees for wealthier clients are like 30 basis points. So, across the industry, we haven’t yet seen that much pressure on investment advisory fees. Why do you think that is?

Haghani: Well, I think that in many cases, investment advisory fees reflect a very high-touch relationship. I think that our client base at Elm is lower touch. It’s higher net worth. We hope that that will change over time, and we’ll be able to help clients of all levels of wealth and whatever stage in life they are. But currently, we have pretty relatively high net worth. We have $1 million minimum. Our clients are generally very sophisticated. A lot of them are from the financial industry. A lot of our early adopters are very financially savvy. So, they require a lower touch. In many cases, we just feel like we’re investing the way that they would invest if they were doing it themselves. So, there’s a lot of sympathy between us and our investor base. That allows us to keep the fees low.

The genesis of Elm itself was me wanting to invest like this for my family. Then some of my friends say, “Well, Vic, if you’re going to do it in a more formal way, we’d love for you to manage some of our money.” So, to begin with, it was like managing money for my family and friends. When I thought about what the right fee should be, I thought, well, what would I be happy to pay as a fee if one of my friends were doing Elm and I were one of the clients, one of the friends and clients. That’s where the 12 basis points came from. But also, it just made sense to me that Vanguard was able to charge—back then, they were charging say 8 basis points on something like their US Equity Index Fund that was managing 4,000 individual stocks and corporate actions and all this crazy stuff—that 12 basis points really felt like that’s where the market should be. I felt that what we were doing at Elm was easier than what Vanguard was doing with some of its big index funds. If you really delve into what’s involved in running one of these big index funds with lots and lots of stocks, it’s amazing. Obviously, they do it also because they have such scale. But all of those reasons led to the 12 basis points. I think that now that it’s 12 years on from our start, things are moving there a little bit, but not quite. Betterment and Wealthfront I think are still around 25 to 30 basis points, and I think they do less. There’s less human touch than with us. But anyway, it’s interesting that advisory fees have not come down by more, but I do think part of it is in many, many cases, really an expensive thing to provide.

Arnott: In terms of the investment strategy at Elm wealth, you use a dynamic asset-allocation approach that builds on a lot of the research you discuss in the book. You start with baseline allocation and then adjust your equity allocation based on the current risk premium and the level of risk in the market, is there positive or negative momentum. So, you show some backtested results for this approach in the book. But in looking at Morningstar’s tactical asset-allocation category, for example, which is measuring mutual funds and ETFs, it seems like this approach really hasn’t worked for most portfolio managers. So, I’m curious how do you square the good backtested results with what seem to be pretty bad results in practice for funds and ETFs?

Haghani: A few different things. I think the first one is that we’re not aware of anybody out there that’s doing a purely algorithmic and very low fee approach. People have higher fees and there’s more subjectivity in the asset-allocation process that they bring to it. It might be that a simple rules-based approach is actually better than trying to do it with a more subjective human input to the whole thing. It also is probably the case that it depends a lot on also the time period. The last 12 or so years, or the last 10 years, has not been a great time to be doing any kind of dynamic asset allocation because the US market has just more or less been going up in a pretty straight line, even though on average the expected return relative to safer assets hasn’t been very high on average over that whole time. So, it depends on what horizon you’re looking at in terms of this, but also, I would say that in the case of our clients that we find that many of them are just attracted to the logic and sensibility of the idea that you should scale your asset allocation according to expected returns and risk. And they’re pretty comfortable with that as their baseline investing. Even when a more static approach would have done better, they realize that this is a sensible and logical way to invest. So, as long as they feel that it has made sense over really long periods of time, they’re at peace with living with underperformance relative to a static baseline over multiple years or even a decade.

Benz: For our last question, we wanted to ask you about a quote that you end the book with, the quote is from Milton Berle, and it’s, “Money can’t buy you happiness, but it helps you look for it in a lot more places.” Has your perspective on money and happiness changed since you first started your career?

Haghani: It really has. I think that the LTCM experience and living through that and then realizing, oh, I was pretty unhappy. But my happiness level drifted up more toward an equilibrium was one really seminal experience that I had that shaped how I feel about these things. As I mentioned earlier in our discussion, there’s been a bunch of books that explore happiness and the relationship between happiness and not only money, but lots of other situations and circumstances in your life. Many of those books have been excellent, but if there’s one in particular that really affected me a lot, it’s Dan Gilbert, the Harvard psychologist’s book called Stumbling on Happiness, which draws on a lot of research that he and others have done that really helped me to have a much more optimistic outlook on our ability to control our happiness and to make choices that are sensible and that can increase our happiness over time once we become more self-aware. Anyway, I thought definitely it’s something that as soon as you turn to questioning what drives your happiness, you’re more than halfway to an improvement because there’s lots of great research and resources out there to help you think it all through.

Arnott: Well, Victor, thank you so much for all your time today. I feel like we could probably spend another one or two hours at least talking to you. There’s so much great material in the book that’s very thought-provoking. We also really appreciate your candor in talking about some of the high points and low points of your career with us.

Haghani: Well, thank you to both of you. I love the podcast, Christine. I love a lot of the things you’ve written and it’s just a real honor for me to be on your podcast. I was so pleased when I got the email that broached the idea of appearing on it. So, I’m really excited. I’m going to continue to be a big fan of your podcast even though you put me on it.

Benz: Thanks so much, Victor.

Arnott: Thank you for joining us on The Long View. If you could, please take a moment to subscribe to and rate the podcast on Apple, Spotify, or wherever you get your podcasts.

You can follow me on social media at Amy Arnott on LinkedIn.

Benz: And @Christine_Benz on X, or Christine Benz on LinkedIn.

Arnott: George Castady is our engineer for the podcast and Kari Greczek produces the show notes each week.

Finally, we’d love to get your feedback. If you have a comment or a guest idea, please email us at TheLongView@Morningstar.com. Until next time, thanks for joining us.

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