The Missing Billionaires (a book about investment risk management)

[SeattleCPA]

I just finished my second read of "The Missing Billionaires." (Er, the math was a little dense for me and I needed a couple of runs through the material to understand and appreciate everything the authors said.) But gosh totally recommend book to anyone who's interested in getting more quantitative about optimizing investment risk. Especially those of you who are a bit mathematical.

Here's the TLDR summary of book:

1. Many (most?) of us take too little or too much risk. Probably because we humans don't do a great job at assessing risk. This has a big impact in our investing.

2. Nobel laureate economist Robert Merton decades ago did the math to create the formulas you or I can use to appropriately size portfolio risk. (A simplified version of the formula for people with low risk aversion: Take the equity risk premium and divide by variance. This is called the Merton share.)

3. Arguably you and I want to adjust asset allocations dynamically based on the Merton share. Over time using the Merton share probably dials up your return a little bit and dials down your risk quite a lot.

4. Though this all sounds like market-timing and an impossible route to practically take, the authors do a good job pointing out that some of the "financial thought leaders" you'd assume would wholly reject the economics here actually either implicitly or explicitly accept all or big parts of the dynamic asset allocation idea. (E.g., Warren Buffet, John Bogle, etc.)

5. This book which came out in September 2023 was on the Economists lists of best business books of the year.

[bluecollarmusician]

Thanks for the rec... I have heard this book mentioned a couple of times recently, and it sounds like something I could really use atm.

Thanks @SeattleCPA

[MustacheAndaHalf]

It's worth noting that Victor Haghani, one of this book's authors, worked at Long-Term Capital Management (LTCM) alongside Robert Merton.  They were 100% confident in their formulas before LTCM collapsed, becoming one of the all-time worst examples of risk management.  Another perspective on their investment formulas can be found in
When Genius Failed: The Rise and Fall of Long-Term Capital Management

"... Larry Hilibrand and Victor Haghani in particular would wield substantial clout and two future winners of the Nobel Memorial Prize, Myron Scholes and Robert C. Merton."

"At the beginning of 1998, the firm had equity of $4.7 billion and had borrowed over $124.5 billion with assets of around $129 billion, for a debt-to-equity ratio of over 25 to 1. It had off-balance sheet derivative positions with a notional value of approximately $1.25 trillion ..."
https://en.wikipedia.org/wiki/Long-Term_Capital_Management

[SeattleCPA]

It's worth noting that Victor Haghani, one of this book's authors, worked at Long-Term Capital Management (LTCM) alongside Robert Merton.  They were 100% confident in their formulas before LTCM collapsed, becoming one of the all-time worst examples of risk management.  Another perspective on their investment formulas can be found in
When Genius Failed: The Rise and Fall of Long-Term Capital Management

"... Larry Hilibrand and Victor Haghani in particular would wield substantial clout and two future winners of the Nobel Memorial Prize, Myron Scholes and Robert C. Merton."

"At the beginning of 1998, the firm had equity of $4.7 billion and had borrowed over $124.5 billion with assets of around $129 billion, for a debt-to-equity ratio of over 25 to 1. It had off-balance sheet derivative positions with a notional value of approximately $1.25 trillion ..."
https://en.wikipedia.org/wiki/Long-Term_Capital_Management

FWIW, the authors seem to do a pretty honest job of assessing and discussing the risk management errors LTCM made. Also the math is the math. (Part of the reason I had to read the book twice was for my first read through I duplicated every calculation not so much because I didn't trust them but because I wanted to make sure I understand the math.)

I would also say their approach is much more rigorous than the approach that some people use to say "100% equities."

[ChpBstrd]

It's worth noting that Victor Haghani, one of this book's authors, worked at Long-Term Capital Management (LTCM) alongside Robert Merton.  They were 100% confident in their formulas before LTCM collapsed, becoming one of the all-time worst examples of risk management.  Another perspective on their investment formulas can be found in
When Genius Failed: The Rise and Fall of Long-Term Capital Management

"... Larry Hilibrand and Victor Haghani in particular would wield substantial clout and two future winners of the Nobel Memorial Prize, Myron Scholes and Robert C. Merton."

"At the beginning of 1998, the firm had equity of $4.7 billion and had borrowed over $124.5 billion with assets of around $129 billion, for a debt-to-equity ratio of over 25 to 1. It had off-balance sheet derivative positions with a notional value of approximately $1.25 trillion ..."
https://en.wikipedia.org/wiki/Long-Term_Capital_Management

So the question is:

Are they less credible because they made a mistake, or are they more credible because they have experience making mistakes?

[Heliios]

2. Nobel laureate economist Robert Merton decades ago did the math to create the formulas you or I can use to appropriately size portfolio risk. (A simplified version of the formula for people with low risk aversion: Take the equity risk premium and divide by variance. This is called the Merton share.)

My problem with the various risk management/optimization strategies is that risk is also calculated based on past performance. For example, the "efficient frontier" in modern portfolio theory requires past return and past variance to calculate. Thus VTI (with high return and high volatility) and bonds (with lower return and lower volatility) would both be considered part of the efficient frontier, but international stocks (similar volatility to VTI but lower historical return) are 'inefficient'. However, the US is currently about 60% of global market cap. Will it keep growing to 70%? 80%? 90%? And how do I calculate my own level of 'risk aversion'? I might think I'm all in at 100% stocks, but next time there's a market crash, will I really stick to my allocations? If it were so easy to calculate risk, why isn't everyone wildly successful in their investments?

[ChpBstrd]

2. Nobel laureate economist Robert Merton decades ago did the math to create the formulas you or I can use to appropriately size portfolio risk. (A simplified version of the formula for people with low risk aversion: Take the equity risk premium and divide by variance. This is called the Merton share.)

My problem with the various risk management/optimization strategies is that risk is also calculated based on past performance. For example, the "efficient frontier" in modern portfolio theory requires past return and past variance to calculate. Thus VTI (with high return and high volatility) and bonds (with lower return and lower volatility) would both be considered part of the efficient frontier, but international stocks (similar volatility to VTI but lower historical return) are 'inefficient'. However, the US is currently about 60% of global market cap. Will it keep growing to 70%? 80%? 90%? And how do I calculate my own level of 'risk aversion'? I might think I'm all in at 100% stocks, but next time there's a market crash, will I really stick to my allocations? If it were so easy to calculate risk, why isn't everyone wildly successful in their investments?

I share some of these thoughts, specifically:

1) When is a market or economy so structurally, legally, technologically, culturally, and demographically different that it is no longer comparable to historical data? To what extent are 100,000 Monte Carlo simulations better evidence for a strategy than, say, a set of 50 years of actual results from the 19th century? To what extent is a Chinese stock a very different kind of asset than a UK stock or a US stock?

2) Are there cases where short-term volatility does not indicate long-term riskiness? For example, a business model with inherently variable or cyclical revenue flows, but reasonably assured long-run success? E.g. there is a store in my town that sells pool tables. They might make 3 sales in one month and 8 sales in another. If they were a stock, the stock price might be all over the place. Yet they're apparently not risky. They've been around for something like 40 years and they have a local monopoly.

3) Does the optimal point or points on the efficient frontier move around in reaction to market pricing action to an extent it is no longer useful? For example, 20-year treasuries have gone from yielding 4.5% in September 2023, to 5.25% in October, to about 4% in late December, and back to 4.5% now. These moves must have caused a significant change in the optimal asset allocation. Was it practical for a retail investor to change their AA this quickly, in reaction to the swinging market prices? And if you're changing your AA, are you no longer rebalancing? Also, the advice is to buy and hold. See what I mean?

4) Efficient frontier studies based on historical data don't seem to incorporate factors which could change the riskiness of equities, such as the introduction of liquid markets for hedging, lower corporate tax rates, or changing financial regulations. Specifically, I'm thinking about the average debt-to-equity ratio, which is now lower than it was in the 20-teens and much lower than in the booming 90s. If stocks were over 2x more leveraged in the past than they are today, then are they really the same asset?

[MustacheAndaHalf]

It's worth noting that Victor Haghani, one of this book's authors, worked at Long-Term Capital Management (LTCM) alongside Robert Merton.  They were 100% confident in their formulas before LTCM collapsed, becoming one of the all-time worst examples of risk management.  Another perspective on their investment formulas can be found in
When Genius Failed: The Rise and Fall of Long-Term Capital Management

"... Larry Hilibrand and Victor Haghani in particular would wield substantial clout and two future winners of the Nobel Memorial Prize, Myron Scholes and Robert C. Merton."

"At the beginning of 1998, the firm had equity of $4.7 billion and had borrowed over $124.5 billion with assets of around $129 billion, for a debt-to-equity ratio of over 25 to 1. It had off-balance sheet derivative positions with a notional value of approximately $1.25 trillion ..."
https://en.wikipedia.org/wiki/Long-Term_Capital_Management

So the question is:

Are they less credible because they made a mistake, or are they more credible because they have experience making mistakes?

If the goal was teaching people about the mistakes made twenty-five years ago, why wait twenty-five years to publish?

Federal Reserve recognized LTCM as a risk to the U.S. financial system, and gathered the heads of every major bank to organize a bailout (in 1998).  Over a trillion dollars in derivative contracts would have simply ceased to exist, along with LTCM.

After LTCM collapsed, most of that group formed a new hedge fund, JWM Partners LLC (including Victor Haghani, co-author of the book we're discussing).  The new hedge fund closed because of losses the 2008 financial crisis, which is admittedly an improvement over destabilizing the entire financial system.

"The fund claimed to use the same model as LTCM with more rigorous and better risk management. It also claimed a leverage ratio of 15 to 1."
"On July 7, 2009, it was announced that the fund would be closed after suffering a loss of 44% in the main fund between September 2007 and February 2009."
https://en.wikipedia.org/wiki/JWM_Partners#Mission

Personally, I'd like to finish reading "When Genius Failed" first, to have context for mistakes made by the book's co-author.  I'm not ruling out that "The Missing Billionaires" could be a valuable contribution that contains lessons learned on risk management.  But I also wouldn't want to rely on Mr Haghani to provide all of the context for his own mistakes, and I wanted to provide context for others to keep in mind.

[SeattleCPA]

It's worth noting that Victor Haghani, one of this book's authors, worked at Long-Term Capital Management (LTCM) alongside Robert Merton.  They were 100% confident in their formulas before LTCM collapsed, becoming one of the all-time worst examples of risk management.  Another perspective on their investment formulas can be found in
When Genius Failed: The Rise and Fall of Long-Term Capital Management

"... Larry Hilibrand and Victor Haghani in particular would wield substantial clout and two future winners of the Nobel Memorial Prize, Myron Scholes and Robert C. Merton."

"At the beginning of 1998, the firm had equity of $4.7 billion and had borrowed over $124.5 billion with assets of around $129 billion, for a debt-to-equity ratio of over 25 to 1. It had off-balance sheet derivative positions with a notional value of approximately $1.25 trillion ..."
https://en.wikipedia.org/wiki/Long-Term_Capital_Management

So the question is:

Are they less credible because they made a mistake, or are they more credible because they have experience making mistakes?

I think the question as to whether their professional history means they're the right person to discuss the math is fair.

But we've gotten off track here a bit. The book isn't really about what they learned from LTCM and think we should all apply now.

Rather, the book is about how to look not just at the expected mean return an investment or asset class delivers... but also at the volatility. I.e., the standard deviation or variance... Then how to use that extra insight to make smarter financial decisions about portfolio construction. (Also about spending...)

BTW you can use Merton's math to back into the expected return an investor should be expecting based on their allocation to equities.

E.g., I might use the expected mean return and expected volatility to come up with an allocation to equities.

But you might instead use an asset allocation of say 100% and then an historical average of standard deviation to come up with the expected return that would make that allocation make sense.

An interesting example of the math appears in the book: The all-in Tesla investors. Given the standard deviation (which I think is like 60% or something) the Merton share formula suggests Tesla investors to be "all-in" should be expecting an annual average return of like 70% to 80%. I think they maybe got 60% annual return in the decade preceding the book's publication date.

[Tigerpine]

How is that different than the Sharpe Ratio?

https://www.investopedia.com/articles/07/sharpe_ratio.asp#

[SeattleCPA]

How is that different than the Sharpe Ratio?

https://www.investopedia.com/articles/07/sharpe_ratio.asp#

They're kinda close right?

I.e., Sharpe ratio takes risk premium and divides it by the standard deviation.

The Merton share takes equity risk premium and divides it by (constant relative risk aversion times standard deviation squared).

BTW if the constant relataive risk aversion is 1--which should be the case for anyone arguing 100% equities--the formulas get really close.

Sort of risk premium divided by standard deviation vs risk premium divided by standard deviation squared.

FYI, I think people think the "average" constant relative risk aversion might be 2.

A 2 would make the old 60/40 allocation pretty logical. Also it appears to me that the newest strategic asset allocation from Vanguard maybe assumes a 2.

[blue_green_sparks]

My strategy since I FIRE'd is so simple, but I don't even know if it has a moniker.
Each year I allocate as much principal as required into "very safe" fixed investments of various durations (depending on the yield curve) to pay last year's expenses plus the current inflation rate. That was how I calculated my FIRE number 5 years ago. I could not care less about their fluctuating market value as it all goes to maturity. With the interest rates rising I now have a larger stock allocation than when I retired. Our interest income has grown faster than our expenses in this economy.

The rest goes into broad stock index funds. Sometimes a very small percentage goes into a relatively high-risk play for fun, but in general the infamous "sequence of returns" risk is nullified. It will never be the best performer, but I don't care. Our defined benefit income sources are just starting to kick in. We will be more and more in the market as we grow older and add-in the expected defined benefit streams. I REALLY did not want to go back to work, LOL.
 

[MustacheAndaHalf]

FYI, I think people think the "average" constant relative risk aversion might be 2.

A 2 would make the old 60/40 allocation pretty logical. Also it appears to me that the newest strategic asset allocation from Vanguard maybe assumes a 2.

As I roughly understand it, Merton share involves both volatility and expected future returns. The best predictor of future returns is CAPE (10 year P/E), with a 0.4 correlation.

How often should the typical investor recalculate Merton share?

I imagine investors might prefer yearly over weekly, especially since there can be tax consequences to selling.

https://www.multpl.com/shiller-pe
https://www.netcials.com/stock-volatility-nyse-american/SPY-S&P-500-SPDR/#firstlist

[GilesMM]

I’ve never put much stock in these complex mathematical schemes reputed to be better ways of investing. There is no secret formula, no matter what anyone says. Just whack most of it in an index or two and forget about it.

[SeattleCPA]

FYI, I think people think the "average" constant relative risk aversion might be 2.

A 2 would make the old 60/40 allocation pretty logical. Also it appears to me that the newest strategic asset allocation from Vanguard maybe assumes a 2.

As I roughly understand it, Merton share involves both volatility and expected future returns. The best predictor of future returns is CAPE (10 year P/E), with a 0.4 correlation.

How often should the typical investor recalculate Merton share?

I imagine investors might prefer yearly over weekly, especially since there can be tax consequences to selling.

https://www.multpl.com/shiller-pe
https://www.netcials.com/stock-volatility-nyse-american/SPY-S&P-500-SPDR/#firstlist

FWIW the book has a chart showing ideal allocations over last 25 years. And it's pretty stable over short term but changes over longer term. E.g., around 2000, zero allocation to equities. After the great recession, at least 100% to equities. That's slowly been decreasing but might now be 30% or 40% for typical risk aversion.

Thus, I'd say annual would work fine?

[SeattleCPA]

I’ve never put much stock in these complex mathematical schemes reputed to be better ways of investing. There is no secret formula, no matter what anyone says. Just whack most of it in an index or two and forget about it.

Four Three comments:

1. Authors say that dynamic asset allocation is better than usual rule of thumb like 60/40%. But not that much better. However many approaches worse.

2. A rule of thumb or extrapolating history (often selectively?), I'm going to argue, is not superior. Even if lots of well-known bloggers argue it is. E.g., 100% equities is not superior.

3. The formula isn't complex. The math that proves it is. But formula isn't. Also going to note that many useful simple formulas "rest" on complex math.

4. But this admission... I really like the Economist. And consider it's coverage of economics and political issues very solid. Thus, I must post a link to this week's Buttonwood article, https://www.economist.com/finance-and-economics/2024/02/19/should-you-put-all-your-savings-into-stocks, which says, "Hey maybe 100% equities is optimal." Note that article is behind paywall. You may be able to get a free 7-day subscription though. In any case, only fare to acknowledge my usual source agrees with @GilesMM 's thinking.

[SeattleCPA]

FWIW, I went and read the research paper from Aizhan Anarkulova, Scott Cederburg and Michael S. O'Doherty that is mentioned in the Buttonwood article referenced above which talks about higher allocations to equities.

A free downloadable copy of that rather excellent paper appears here, "Stocks for the long run? Evidence from a broad sample of developed markets?" but let me quote the authors' conclusions from page 28 of the 81 page research paper:

Our analysis yields three primary findings. First, the long-term outcomes from diversified equity investments are highly uncertain. Based on the historical record of stock market performance in developed markets, the 5th percentile real payoff (measured in terms of local currency) from a $1.00 buy-and-hold investment over 30 years is $0.47, whereas the 95th percentile is $23.30. This evidence stands in contrast to the conventional view that mean reversion in equity returns makes equity investing relatively safe at long horizons. Second, catastrophic investment outcomes are common even with a 30-year horizon, as the 1st percentile real payoff is $0.14 and the 10th percentile is just $0.85. An investor at age 35 saving for retirement, for example, only realizes one draw from the 30-year return distribution, and we estimate a 12.1% chance that this investor will lose relative to inflation. Third, the empirical findings based on the historical record of stock market performance across dozens of developed markets are notably different from those based on the historical U.S. experience. Estimates that rely solely on U.S. data suggest that long-term real investment losses are rare. The contrast in results highlights the importance of guarding against survivor and easy data biases in assessing the distribution of distant payoffs and also has economically significant implications for optimal portfolio choice.

[Tigerpine]

Thank you for the link!  I'll have to read it when I get a chance.

[daverobev]

FWIW, I went and read the research paper from Aizhan Anarkulova, Scott Cederburg and Michael S. O'Doherty that is mentioned in the Buttonwood article referenced above which talks about higher allocations to equities.

A free downloadable copy of that rather excellent paper appears here, "Stocks for the long run? Evidence from a broad sample of developed markets?" but let me quote the authors' conclusions from page 28 of the 81 page research paper:

Our analysis yields three primary findings. First, the long-term outcomes from diversified equity investments are highly uncertain. Based on the historical record of stock market performance in developed markets, the 5th percentile real payoff (measured in terms of local currency) from a $1.00 buy-and-hold investment over 30 years is $0.47, whereas the 95th percentile is $23.30. This evidence stands in contrast to the conventional view that mean reversion in equity returns makes equity investing relatively safe at long horizons. Second, catastrophic investment outcomes are common even with a 30-year horizon, as the 1st percentile real payoff is $0.14 and the 10th percentile is just $0.85. An investor at age 35 saving for retirement, for example, only realizes one draw from the 30-year return distribution, and we estimate a 12.1% chance that this investor will lose relative to inflation. Third, the empirical findings based on the historical record of stock market performance across dozens of developed markets are notably different from those based on the historical U.S. experience. Estimates that rely solely on U.S. data suggest that long-term real investment losses are rare. The contrast in results highlights the importance of guarding against survivor and easy data biases in assessing the distribution of distant payoffs and also has economically significant implications for optimal portfolio choice.

We've had a really good run since the GFC. Assuming we're not all getting massively more productive, there is climate change, reversion to mean happens and that US outperformance will be tempered by... let's call it the blunting of the 'evil' large companies as I see them (Facebook, Google etc taking way more of your personal info than they should - again as I see it - be allowed to)... where does a person invest for semi-stability over an early retirement?

I've shifted to, oh, about 30% non-stocks over the last year (from basically 100%). Clearly bonds are more attractive now than they were a few years ago. I've done some degree of house improvements to reduce energy expenses, though gas prices will 'wipe that out' when we come off a lucky fixed rate offer I happened to be on.

I don't need to be a millionaire. I just want to have 'enough'. Higher allocation of bonds, I suppose.

[SeattleCPA]

I've shifted to, oh, about 30% non-stocks over the last year (from basically 100%). Clearly bonds are more attractive now than they were a few years ago.

I agree bonds are way more attractive. Especially if you're not still attempting to grow your portfolio but only live off its income. The real return from US stocks is maybe 3%. Tips generate almost 2%. A good question is, why bear risk to generate an extra 1%?

Thus I found myself this morning calculating Merton shares to determine whether I should dial down my 70% allocation to equities. To do this, btw, you need to estimate the risk premium equities deliver and the volatility (or standard deviation).

I did the three sets of calculations: One using Vanguard's recent estimates of expected returns and volatility. One using CAPE 10 and VIX. One using the Gordon dividend model.

I thought the calculation results might push me to bump up my bond percentage. But maybe not surprising, the calculated stock percentages are very high if someone's relative risk aversion is 1, which is "low." So equity allocation is, like, 70%, 80% or even up above 100%.

P.S. At the "average" baseline relative risk aversion, which is 2, the equity allocation drops to level close to what @daverobev gives as his allocation. (BTW the Vanguard strategic asset allocation seems to use this same equity allocation and so must assume at some level a relative risk aversion coefficient of 2.)

[vand]

Bumping this thread because, hey, why not.

On the subject of risk and survivability..

Some may find this eye-opening.. but I think it answers a huge chunk of the Haghani's premise why there aren't more billionaires..
https://www.youtube.com/watch?v=_o_7REFkp8E

Even if you can accurately calculate your edge, if you employ optimum bet-sizing strategy as defined by Kelly, randomness will probably see to it that sooner or later you experience a losing streak so devastating that it cripples your capital base


Example given: with a 2% edge, and betting Kelly-optimized 4% each time, you'll run into a *spoiler* 92% drawdown on average if you live long enough.

[SeattleCPA]

Bumping this thread because, hey, why not.

On the subject of risk and survivability..

Some may find this eye-opening.. but I think it answers a huge chunk of the Haghani's premise why there aren't more billionaires..
https://www.youtube.com/watch?v=_o_7REFkp8E

Even if you can accurately calculate your edge, if you employ optimum bet-sizing strategy as defined by Kelly, randomness will probably see to it that sooner or later you experience a losing streak so devastating that it cripples your capital base


Example given: with a 2% edge, and betting Kelly-optimized 4% each time, you'll run into a *spoiler* 92% drawdown on average if you live long enough.

I think at the billionaire level, the same old 'safe withdrawal rate' problem occurs. I.e., if someone draws 5% or 7% or whatever even if they're really diversified, they can drain their portfolio. Also these investors often aren't diversified. Elon Musk for example. But probably also Buffett?

[vand]

Bumping this thread because, hey, why not.

On the subject of risk and survivability..

Some may find this eye-opening.. but I think it answers a huge chunk of the Haghani's premise why there aren't more billionaires..
https://www.youtube.com/watch?v=_o_7REFkp8E

Even if you can accurately calculate your edge, if you employ optimum bet-sizing strategy as defined by Kelly, randomness will probably see to it that sooner or later you experience a losing streak so devastating that it cripples your capital base


Example given: with a 2% edge, and betting Kelly-optimized 4% each time, you'll run into a *spoiler* 92% drawdown on average if you live long enough.

I think at the billionaire level, the same old 'safe withdrawal rate' problem occurs. I.e., if someone draws 5% or 7% or whatever even if they're really diversified, they can drain their portfolio. Also these investors often aren't diversified. Elon Musk for example. But probably also Buffett?

Billionares are a wild bunch and the way they tend to pop in and out of global rich-lists tells us something about getting rich vs staying rich.. no one is compounding their way to $1bn in VOO.. they are building a business and taking on the risks and rewards associated with that.

When we are talking about dynastic wealth you need to be ultra-conservative because you can't replace lost capital through income, and wealth preservation arguably becomes more important than further growth. That's not the case for your vanilla FI plan where you can just adopt a perfectly reasonable "hey, if the market crashes I'll just go back to work and top up my portfolio" plan. 

[SeattleCPA]

Bumping this thread because, hey, why not.

On the subject of risk and survivability..

Some may find this eye-opening.. but I think it answers a huge chunk of the Haghani's premise why there aren't more billionaires..
https://www.youtube.com/watch?v=_o_7REFkp8E

Even if you can accurately calculate your edge, if you employ optimum bet-sizing strategy as defined by Kelly, randomness will probably see to it that sooner or later you experience a losing streak so devastating that it cripples your capital base


Example given: with a 2% edge, and betting Kelly-optimized 4% each time, you'll run into a *spoiler* 92% drawdown on average if you live long enough.

I think at the billionaire level, the same old 'safe withdrawal rate' problem occurs. I.e., if someone draws 5% or 7% or whatever even if they're really diversified, they can drain their portfolio. Also these investors often aren't diversified. Elon Musk for example. But probably also Buffett?

Billionares are a wild bunch and the way they tend to pop in and out of global rich-lists tells us something about getting rich vs staying rich.. no one is compounding their way to $1bn in VOO.. they are building a business and taking on the risks and rewards associated with that.

When we are talking about dynastic wealth you need to be ultra-conservative because you can't replace lost capital through income, and wealth preservation arguably becomes more important than further growth. That's not the case for your vanilla FI plan where you can just adopt a perfectly reasonable "hey, if the market crashes I'll just go back to work and top up my portfolio" plan.

I have maybe told this story before but a while back, I accompanied my wife to a backyard garden party thing connected to her hobby.

When we got there and I saw the host's name, I realized she was an heir to one of the great dynastic fortunes of all time. (Okay not the Rockefeller family... but in that vein). A relatively short time after her family's economic apex, the heir was now living like a school teacher who'd retired with a good public pension. Actually for all I know, that may have been what she was.

Another tangential note: My sense and also ChatGPT's understanding is that wealth is more dynastic in Europe due to some cultural stuff (like primogeniture) and lighter estate taxation.

[vand]

I said "no one is compounding their way to $1bn in VOO" but of course I mean that within a single generation.

At long term average rates of return in global equities:

10-baggers are created after 25 years
100-baggers created after 50 years
1000-baggers created after 75 years
10,000-baggers created after 100 years

So if you can just scrape together cash for a 2nd hand Ferrari, stick it in an index fund and leave it alone until 2125 then your great-grandchildren or their children are going to have one heck of an inheritance bill.