Moontower Money Wiki

I started compiling notes on finance stuff about 4 years ago. I lurked on Twitter to learn. Weighing arguments, curating reliable sources. All in service of building a coherent tree trunk of knowledge that I could branch from. On one hand, it was chasing adjacent knowledge from my native option trading background. But it was also practical. How I can learn to manage our own money better?

About 2 years ago on a trip to Vancouver with college friends, I wrote a short essay on the flight. I showed it to my friends and they affirmed it reflected how they felt about money. They encouraged me to write and share. The essay is called Does This Sound Like You?

Since then it has been my intention to consolidate and create some flow around my learning so I could share it publically. The newsletter and blog show bits and pieces but I’ve wanted to create a more coherent wiki. A more polished version of my personal wiki.

With some encouragement and guidance from my friend Khe, I’m building a public version in Notion (Khe is a Jedi btw, if you are trying to level up your productivity you need to hit him up). It will be a reference filtered by what I think matters. It will have relevance for households as well as institutions. I have no clue how long it will take to port it all in a consumable way (there’s a lot of content) but I’ll prioritize expediency. As a wiki, it’s a living document anyway.

I have 2 overarching beliefs that are neatly reflected in how my private wiki is organized.

1. Human capital is your most important capital.

This is most obvious when you are young. We don’t worry when a 23-year-old dentist has $150k in debt because it’s backed by human capital. This wiki will include all my explorations for improving how I think. It will include the self-help stuff that has worked for me. I expect this section of the wiki will be published second. It’s more fun but also more speculative.
2. Financial capital should be governed by process

  • Get a basic understanding of levers. Basic does not have to mean naive. That’s why I wanted to do this project.
  • Implement a framework.
  • Meta-tweaks: decide the conditions under which you will make tweaks. Because the ultimate goal is to get on with your life. Not keep tinkering with your investments (unless that’s what you like doing).

Your money is in service of you. Not the other way around.


A Brief Intro to The Moontower Money Wiki
The wiki is initialized and you can see the headings that will be populated at least to start. There will be branches of topics and subtopics. (Link)

Continuing from last week, the first entry is Defining the Problem which includes the retirement model. I think that’s a good starting point because that exercise is like a diagnostic on not just your situation, but your understanding of the problem.

Putting this together has been a long-overdue project. I hope you find it useful and I’m gracious I have many smart readers that can give feedback which in turn helps out the other readers. 95% of all the content and work belongs to others, I’m just acting like a GC on a construction project. I hope it’s worthy of the efforts that inspired it.

The Moontower Retirement Model

With all the market chaos, a bunch of friends, most of them outside the field of finance, have dove into a Whatsapp chat devoted to money strategies. The chat is aptly named “Early Retirement Inc”. This is a smart group of people with good careers. The nature of public money discourse seems to revolve around what stocks are going to do or even worse what single stocks are going to do. This means everyone, even smart people, are breathing polluted air.

I’m gonna take a stab over the next couple weeks at a healthier approach. A lot of financial advisors read this so I’m sure I’ll be corrected. But if you want to get the right answer to something, you publically say something obviously wrong. Let’s see what happens.

The Retirement Problem

You work for 40-50 years but you live for 20 to 30 years more. The problem you must solve: don’t run out of money. Retirement finance is a vast field filled with overly precise mathematical treatments of “safe withdrawal rates” and investment allocation “glide paths” (think a target-date fund that is aggressive when you are young and conservative as you age). William Sharpe who won the Nobel Prize for the CAPM model called it the hardest problem in finance.

I’m not going to bore you with all that. I’m also not going to bore you with my soapbox rant about how destructive I think the whole vision of retirement is as portrayed by Charles Schwab commercials. The fact that it takes a moment to figure out if it’s a financial commercial or a Viagra ad is enough of hint that drugs are being sold in both cases.

Instead, I will encourage you to walk through an exercise that identifies the most important levers of the problem. I’ve put together a Moontower Retirement Model that you can make a copy of and play with your own numbers. I built it years ago and because of back and forth in my Whatsapp chat had a chance to dust it off and improve it. The model’s value is not in its output. “Hardest problem in finance”, remember?. It’s laden with assumptions and simplifications. It also spits out a path without confidence intervals. You can’t get away from the shortcomings. But if you have never worked through something like this, you are going to think about money in a much more enlightened way afterward.

Here’s the Moontower Retirement Model

(Please don’t hesitate to ask questions, point out errors and so forth. I’d like to enhance it over time.)

Here’s a screenshot of the input screen:

You will have fun trying to estimate numbers for your household income and expenses and if not it may alert you to get a grasp on these things.

Once you have some reasonable assumptions start tinkering with:
1) Inflation and investment return rates

Inflation is applied to pay and expenses evenly. Investment returns are applied to your entire net worth. Since net worth includes cash, homes, and stocks try to estimate a decent weighted-average return.

2) Retirement Age

Every year you delay retirement has a double impact. You increase savings that can grow AND you don’t withdraw return-generating assets.

3) Savings

A dollar saved is another source of big swings. You not only reduce the expense but you reduce the compounding of that expense. Or you can say that a dollar saved is also extra dollars in the future due to compounding. This is the most interesting lever because it’s high impact and insofar as you can control your expenses, it’s the lever you can steer the best. In contrast to, say, inflation. Good luck understanding inflation nevermind controlling it.

Don’t focus on the specific numbers as if you saw your future. You didn’t. This exercise has immense value despite that.

Pulling Earnings From The Distant Future

The rally in the markets for the past 2 weeks has many scratching their heads. It must be especially dissonant for business owners and landlords who see the market and their own P/Ls as 2 trains headed in opposite directions.

For the visually inclined:

Sure estimating forward earnings right now is like using binoculars to study the moon, but the point remains. The market despite being lower than it was in early February may actually be equally or even more expensive as a discount of future cash flows.

Let’s remember that stocks were up 30% in 2019 despite earnings being flat. Pure multiple expansion. Mocha Joe plays the buy-stocks-then-fall-into-a-coma-game:

So I’ll add 3 comments to this in descending levels of conviction.

1) The market is actually more expensive than the Credit Suisse chart suggests

Why? The implied volatility is much higher than it was last summer. If you are willing to pay the same multiple for an asset whose volatility has doubled you are willing to accept a lower geometric return. I know many people want to shut down when they hear “geometric return”. The more you are exposed to it, the more intuitive it becomes. Internalize these bits:

  • When talking about compounding quantities like investment returns, geometric returns are what you care about.
  • An expected geometric return allows you to compare assets of different volatilities (without resorting to Sharpe ratios). By pulling in the notion of volatility it is more obvious that this market is more expensive than the June 2019 market.
  • For the formula people, geometric returns = arithmetic returns – σ² / 2. Returns are dragged down in proportion to volatility squared.
  • The easiest way to remember why compounding is so heavily impaired by volatility is to recall that you need to return 50% to make up for a 33% loss. So to make up a loss you need to return Loss / (1 – Loss). This reality means your wealth-growing process hates volatility.

I’ve explained this in more depth and with different types of examples in The Volatility Drain. (Link)

2) The market appears willing to pull earnings from ever further into the future 

Perhaps this is a form of inflation. Perhaps the “Fed Put” looms larger in investor discount rates as every market crisis is deemed inseparable from a human crisis. To use a computer science analogy it’s like the Fed response has become the “greedy algorithm” which chooses immediate gratification at every node in the search tree.

Either way, I’ve said this before: I wish I could buy call options struck on the P/E ratio not the SP500. (Link)

For savers who hang out in cash looking for bargains, this is what financial repression looks like. A city without a single dive bar. You can pay up for bottle service, velvet ropes, and bad music. Or stay home.

3) Gun to my head: the next 10% in the market is higher.

First, nobody is putting a gun to my head, so this is a no-skin-in-the-game guess. Not investment advice. But sentiment seems to think that this rally is stupid and makes no sense a la Mocha Joe reasoning. This means the “stupid price” is making a lot of people look stupid. And since markets like to maximize the area of stupidity under the curve, the integral is largest if we rip even higher. I’m only using second-order reasoning but since the market can go either up or down it might be just as effective as 4th, 6th, 8th or any even number order reasoning.

Is Volatility A Risk?

A finance version of “categories are made for man”.

What is the definition of “risk”? If you ask a quant, they will say volatility. If you ask Warren Buffet he will tell you that’s stupid and that risk is the chance of permanent loss as opposed to price variation. I don’t want to get into a taxonomy of risk definitions. And I definitely don’t want to get into semantics. Or near-semantics like “risk” versus “uncertainty”.

Just like the border drawn on a map. It has nothing to do with some objective sense of right or wrong. The criteria for evaluating the definition of a border is simply how useful it is. The concept of risk is useful insofar as it helps you judge the merit of an investment. No single measure of risk is sufficient. Think of risk as a multi-faceted prism. The same investment projects different qualities depending on which angle you view it.

Check out this Twitter poll by @Econompic:

This poll targets differing views of risk. It’s trying to find a weakness in the “risk is volatility” definition. It does this by showing that asset B which has very low volatility is an inferior investment. It is, therefore, riskier according to any non-volatility based definition. It is riskier in a common-sense definition of risk. It’s possible however to find a context where the volatility-based definition matters. Let’s say you are a bank and mandated to hold all excess reserves in one of these investments overnight (I know it’s a stretch). Well, the volatility-based definition is useful if losing 2% in one day is an unacceptable outcome.

This exercise a reminder that any definition of risk should be evaluated by its usefulness. Any single definition is incomplete and insufficient for making an investment decision.

Picking on the quants’ definition of “volatility as risk” as popularized by Buffett is not new. Cliff Asness defends the quants in the first item of his cranky list My Top 10 Pet Peeves. (Link)

I also like #10 on poor justifications for individual bonds to bond funds.


I published my notes this week for an old interview between Ted Seides and Basil Qunibi of Novus. Novus is a fund consultant that is best described as “Moneyball for allocators”. Novus does performance attribution. Which means they figure out if a manager’s edge is what they say it is. If a manager’s performance has been due to good timing but they say their edge is security selection you should care. Especially if you attribute timing to luck as opposed to a persistent skill. You will also learn about the 4 Cs that they track and how they predict performance. (Link)

The Seppuku Portfolio

Markets have been chaotic

Extremely high realized volatility.

  • Weekly moves look more like annual moves. In other words, the market has been sqrt(52) or about 7x more volatile than in past years.

Whipsaw correlations

  • There have been days when bonds and stocks have simultaneously sold off significantly. Gold correlation is a random number generator.

Dislocations galore.

  • Some of these are ETFs and closed-end funds deviating from NAVs. This screener can show you closed-end dislocations. Be careful with this stuff.
  • Treasury basis trades
  • This week gold futures surged higher relative to spot prices amidst talk of delivery bottlenecks across the pond. Then Friday front month-second month gold futures spread collapsed $30.
  • Oil contango exploded wider this week with the front month now trading at a 15% discount to the second month. Annualize that. It’s not surprising that tanker pure plays surged higher (if you are interested in a deeper look, check out this Adventures in Capitalism post.). The contango widened similarly during the GFC as the arb was limited by supply of credit. This time it’s about the limited supply of storage/tankers.

The chaos reflects the uncertainty in the real economy

Unemployment claims this week was a 30 sigma event which says as much about using normal distributions on financial variables as it does about how acute this shock is to the economy.

Options trader turned restauranteur and entrepreneur extraordinaire Nick Kokonas linked to Vanity Fair’s:

“You Can’t Speak in Strong Enough Dystopian Words to Describe It”: Why the Coronavirus Pandemic Could Change Dining as We Know It, Forever

The combination of perishable inventory and high labor costs as a percentage of sales makes the restaurant biz especially vulnerable. Restaurants are one of the better examples of the types of businesses facing an existential threat. Businesses that are exposed for their outsize degree of operating leverage.

I recommend Howard Lindzon’s Panic with Friends YouTube interview with Rob Koyfin as they dive into that idea. Rob’s the founder of Koyfin which is what Yahoo Finance would be if Bloomberg owned it. That’s a joke by the way. I use Koyfin myself but really liked watching Rob navigate the platform on the call to demonstrate just how the market was reacting to high operating leverage businesses. It was a markets lesson and tech tutorial in under 30 minutes. (H/t to Brian for the rec)

Personal portfolios

I like reading how markets people invest personally. We have a professional subscription to Jared Dillian’s Daily Dirtnap and he posts his portfolio and what he’s doing. His letter is paid so I will not share his allocations.

2 of my favorite fintwitters are public about their own investments:

Corey Hoffstein (Link)
Meb Faber (Link)

Moontower Portfolio

If you are curious about the Moontower portfolio it’s roughly:

1/3 real estate
1/2 short term notes and cash
15% public investments
<5% private investments

A look at the public portion:

8% RE
39% international equity
14% domestic equity
20% metals
18% US energy

Recently doubled down on energy/metals tilt, rotating out of treasury notes.

I refer to the public portion as the Seppuku Portfolio since it would be suicidal for a US investment manager to hold.

Cash

A note on carrying so much cash compared to most recommended allocations. It is a risky long-term proposition. Just consider the price of stamps in the past 30 years. But in the near-term, it provides a lot of optionality.

It’s reasonable to argue we overpay for this. While we don’t own our own businesses, there is a lot of volatility in our professions. A lot of lumpiness in our cash flows. But just like financial options I believe there are additional multi-order greeks on this optionality. They don’t come from differential equations. They are psychological. A behavioral edge even though I sort of hate this term.

Let me rationalize, I mean, explain.

We put a lot of value on the ability to not work for an extended period if we chose to. Not because of laziness but for the feeling that choosing to work where you are is an active choice. When Yinh took 2018 off this felt like a stress-free harvesting of the optionality. She was able to search for the best possible match for a new job. I feel like the payoff from being able to find a match without pressure is a payoff that does not show up in your Mint view as a line-item. But it will one day show up disguised as a different balance sheet asset.

Our parents are immigrants. They came to the US in 70s with little. We learned everything about grinding from watching them. They still have little. They passed scarcity mindsets to us. And Kiyosaki likely thinks we are fools who learned our lessons from “Poor Dads”. But we did manage to learn about leverage and its many forms.

Our lack of financial leverage enables us to maximize our human capital leverage. With implied prospective returns uninviting for the past few years, this seemed like a reasonable trade. Our total allocation reflects that tilt. With that lens, I guess you can file this under market-timing. Call me a sinner.

If you can’t watch a bull market rage without you this is just as risky as being YOLO long. No easy answers when you think of multi-order effects of an allocation. You need to do what’s best for you. It starts with asking the right questions. And they mostly have nothing to do with finance.

Should You Invest In Stocks Now?

Should you invest in stocks now?

With the market down 30% from the peak, I’ve seen many variations of this question in recent weeks. Mostly people who dollar-cost average by adding money from every paycheck wondering if they should increase the amounts they put in since the market is “on sale”. It’s an understandable question — I load up on Lucky Charms when they go on sale.

Ok, number one, nobody is qualified to answer this question for you, so let’s get that out of the way. While I hope the following will help you come to your own answer, the learning opportunity here is to get a better understanding of how markets work.

We need to address the mistaken presumption in the question. There’s a bit of a myth that the market is cheaper today. Well, this is true if you compare current prices to past earnings. But markets look forward. Lower nominal prices do not mean bargain. If fundamental deterioration was steeper than the price decline the market is actually more expensive. What a buyer is really interested in is whether the prices are a better value. If Trader Joes sells bruised bananas for half price, the cheapness is for a reason. Right now corporate America’s prospects are brown and soft. Is 30% the right discount? It’s a coin toss.

The market from a bystander perspective is nothing more than the fair point spread. In other words, whenever you put money in you are basically investing at the fair price. I’ll preempt some pushback to that by saying this perspective is a bit scope dependent. There are people who make money in narrow niches of the market that can be mispriced. Dislocations and liquidity frictions can mean opportunities for those experts. Just like if you were an expert in your local real estate market (have great contractor and banker relationships, got the look from the broker you grew up with, some other form of private info), market turmoil could lead to some easy layups. But zoom the scope out until you are a tourist and you are back to tossing fair coins.

This is always the case when you put money in the market. The price balances the buyers’ and sellers’ consensus of the future. Right now all buyers and sellers are meeting at prices that assume earnings in the future will be worse than they expected back in January. If you bet on Bucs to win the Super Bowl this year and Tom Brady gets hurt, the price to bet on the Bucs will get cheaper. The lower price to buy them is probably an equivalent value to the higher non-injured Brady price. It just reflects bleaker fundamentals.

Let’s belabor the point from another angle. The silliness of statements like “I’m a buyer of the market if it goes down to 200” when it’s currently trading for 3000. The unsaid assumption baked into that statement is “all else equal”. Well duh, all else equal, when the market is trading for 3000 there’s a stack of bids from 2000 to 3000. The only way your 2000 bid becomes in play is if the world is different. A bid is an inherently conditional statement. I wish I could have bought my house for $200k. But if my neighbor’s house ever goes on sale for $200k, it’s more likely we’re about pestilence deep into Egypt’s 10 plagues than I’m getting the deal of a lifetime.

Evergreen advice

It’s widely understood that the average stock picker is no better than chance at figuring out what a value is. A full-time endeavor whose output is no better than chance. The conclusion is obvious. Trying to time or beat the market is a low-yielding object of attention. You cannot do this reliably or repeatedly. Not worth the brain damage to trying to decipher if the market is a value. You aren’t counting cards to overbet a stacked blackjack deck here.

Focus your energy on understanding your liquidity needs. Give that exercise its full due. Only you have visibility into your family’s income in a slowing economy. Make sure you have the cash you need to live. Nothing has changed about the fact that the market tempts you with a reward in exchange for volatility. If the risk is suitable, stick to your regular plan.

(Mandatory disclaimer…I’m not giving investment advice. I’m not qualified and have zero credentials.)

A word on market consensus right now

The debate rages on whether the market is oversold or has a lot further to fall. The market price collapses the expected value into a single number. There’s plenty of smart-sounding people with models and forecasts and opinions and degrees on both sides of that price. All of these ideas are swamped by the other market-based consensus: the volatility. The options market is pricing the 1-year standard deviation of the SP500 at 40%. This is about 2x the market’s typical confidence interval. Volatility is a more actionable input into your investment process because it directly feeds into the thing you should be thinking most about — your cash requirements for upcoming expenses. If that kind of volatility is intolerable given your upcoming liabilities (retirement, college, buying a house, and so on), then you are overexposed. Stock returns have always been an award with strings attached. Volatility is not just small print. It’s a double-edged feature. If it didn’t exist markets would not offer a reward.

A Recipe For Overpaying

On the Gestalt University podcast, Chris Schindler has an intuitive explanation for the CAPM-defying empirical result that says higher volatility assets actually exhibit lower forward returns. Very simply explained — a large dispersion of opinion leads to overpaying. He points to private markets where you cannot short a company. The most optimistic opinion of a company’s prospects will set the price.

Options markets don’t care about CAPM. They model geometric returns. Higher volatility explicitly maps to lower expected geometric returns. I’ve referred to this idea as a “volatility drain” before. But here’s another way to see this. If you hold the price of an asset constant and raise the volatility the median expected outcome is necessarily more negative. Why? Because a stock is bounded by zero, so increasing the volatility should seemingly make the expected value of the asset higher. But if the market thinks the stock price is worth the same despite the higher volatility, that implies the probability of the asset declining must be higher.

(In reality, markets are constantly voting on the price, the volatility, and the left and right skew which allows an inclined observer to impute a continuous distribution.)

Back to Schindler’s point, if you want to fetch a high price for an asset, you want its value to be highly uncertain. Then sell it in an un-shortable auction with many bidders.

Dinosaur Markets

This past Wednesday, a NYT oped wrote:

..But after watching the stock market plummet on Monday and governments struggling to get hold of the contagion, I’ve begun to smell doom.

A response to this quote on Twitter:

“Hilarious. He only needs reactions of others to react, not basic facts.”

What do you think of that Twitter response? Is the oped author guilty of herd thought?

Let’s take a detour first, I promise it will re-connect in the end.


What Are Markets

There are various ways humans self-organize. Home life is an autocracy. Parents wield absolute power. If the kids get to vote on what’s for dinner it’s because the elders signed off on a temporary puppet democracy. In broader civilization, there are networks and governments. Plutocracy, theocracy, monarchy, parliament, communism, fiefdoms, tribes, democracy. No matter which backdrop they must operate in, one of humanity’s most clever constructs was the marketplace.

Through trade and barter, markets focus a multiplicity of needs, desires, and trade-offs into prices. Prices allocate resources. High prices attract supply and ration demand. A consistent ability to shrewdly respond to prices either as a company, investor, or consumer leads to profit. The potential and motive to profit certify prices as honest signals.

The Dinosaur Question

Democracies are controlled by votes. All votes are equal. But, markets are not democracies. To understand the difference I’ll recount a lesson I was taught as a trader trainee 20 years ago.

It was explained:

If you poll the population, “Did humans walk the earth at the same time as dinosaurs?”, the responses come back split about 50/50. That’s democracy.

Now imagine there is a contract that trades openly on an exchange that is worth $100 if it is true that dinosaurs and humans co-existed and $0 if that is false. Even though the population is split, this contract is not going to trade for $50. It’s going to zero. Why? Because the small percentage of people and scientists who know the truth are going to see a profit from selling this contract even down to $1 since they know this proposition is false. And if the scientists don’t have enough money, they will be able to convince or get hired by people with more money to back this venture of selling this contract to zero.

That is the value of markets. You get correct answers. While a democratic poll may tell you what people believe or desire, it does not assign the proper truth value to the proposition. Now consider the implications of being correct. You make more money which gives you more resources to continue being more correct. The marginal price in markets is set by the market participants with the most money and as a group, they have the best-calibrated assessment of what fair value is. And these groups are in the minority of the total betting population. Markets are not a democracy. To dismiss prices is an impressive act of arrogance.

An Aside For Finance Folks

You may recognize traces of strong-form efficient market hypothesis in this view. It is fashionable to point to market failures and bias which can distort the truth value of prices in our economy. Markets are nested within laws that are nested within our democracy. There are many joints in the structure subject to friction or even corruption which dilute the purity of markets. But for a market to be efficient doesn’t mean its truth value is decreed by the all-knowing. The standard to be efficient is simply to what extent you can earn an excess risk-adjusted profit betting against it. Well, by that standard market prices have a sterling track record revealing most players to be nothing but tourists. It could be wrong, but that doesn’t mean you can do better.

When Prices Seem Irrational

The correct reaction to strange prices is not to say “that’s stupid”. It’s “why is somebody paying that?” Prices are amazing discovery tools to explore “why”. When Vancouver condos are trading at egregious multiples over local wages, rather than presume the buyers were suckers, you may have discovered that Chinese nationals were restricted in how much Yuan they could expatriate. Real estate is a convenient store of value, not just shelter. While it’s not as stable as a savings account, the price of real estate as a safe haven for cash is not being set at the margin by someone like you. It’s set by a family across the world who finds its local savings account a bit too close to its government’s paws. The extra volatility is seen as nothing more than a convenience fee.


Ok, back to the tweet:

“Hilarious. He only needs reactions of others to react, not basic facts.”
Record scratch. Stop right there, freethinker.

When AAPL releases earnings, you don’t read the 10Q unless that’s your job. You look at the price after-hours to see how the market understood it. When a star player is placed on an injury report you look at the game line to see if the odds changed. These are correct reflexes for good reasons.

When you hear people lament that market prices in response to COVID-19 are being set by traders who know nothing about virology instead of doctors, pause for a moment. Are the sharps who set betting lines doctors capable of handicapping recovery times of turf toe or patellar tendons? Of course not. Their expertise is in looking at past data, pattern-matching, and propagating newly calibrated parameters through proven models to generate bets. A sharp’s long-term track record is a self-evident testimonial.

The best investors are information-synthesizing odds setters. This is being done across decentralized domains. The option guys are betting on volatility surfaces, the macro gals are thinking about growth rates and international money flows, while the fundamental folks are thinking about how many people are going to be watching Netflix, buying Purell, and working remote. VCs are Slacking their biotech founders while reporting back to their investors on calls. Those same investors close the loop back to the hedge fund managers who look up from their own war room analysis. The emergent consensus from all this hive activity is in fact what finance is. A networked machine optimized for pricing future states of the world. This optimization likely includes being networked to medical intelligence through its fastest pathways. The fact that it’s not all medical professional pathways should not offend. Instead, it speaks to how efficient this architecture is.

They say when you write to imagine who you are writing to. I feel like I just wrote to that person who has a market take based on what his rheumatologist uncle told him about viral infections. I’ll take my chances that the smartest people setting prices have access to the smartest minds in epidemiology.

The topic of market efficiency, the validity of prediction markets, and the wisdom of crowds would take several scholarly lifetimes to sift through. Who has time for that? I’ll just give you the tl;dr based on my professional experience.

  • Markets are very smart. If you cannot make sense of what they are doing most of the time you are missing something. I could fill a blooper reel of me getting served this lesson.
  • In the cases when you seemed to outsmart the market you are not actually on solid ground. You have probably just found seen an oasis in an epistemological desert.
  • Give prices their due. Understand your basis for mistrusting them when you do and see if you can test the supports for that basis with data as it emerges.
  • Finally, do not feel bad when you defer to liquid prices for an opinion. You will likely be in the smartest company.

 


If you are interested in the study of when to diverge from consensus, then muster some courage to read Inadequate Equilibria: Where and How Civilizations Get Stuck by Eliezer Yudkowsky. I plan to write a summary blog post of it one day but in the meantime read it for free online (Link).

I don’t follow the news much but keeping up on COVID-19 is one of those times. I subscribed to Taylor Pearson’s Twitter list which includes many smart voices ranging from scientists to investors. (Link)

For a single great follow on COVID-19, check out Balaji Srinivasan. He has been very on point in synthesizing the intelligence he’s gathered from various nodes in the system. He’s trying to steer a multi-disciplinary response to the virus (Link).

COVID-19 and Markets

I’ve explained in a past letter how the expensive put skew embedded in SPX option prices reflects 2 realities. First, the average stock in the index will see its volatility increase but more critically the cross-correlation of the basket will increase. Since index option variance is average stock variance times correlation, there is a multiplicative effect of increasing either parameter. The extra rocket fuel comes from the parameters themselves being positively correlated to each other.

In other words, correlation increasing leads to volatility increasing. Since volatility is a practical restraint on position sizing you can think of investment exposures as secretly levered to low correlations. Any battle-tested risk manager will pay close attention to not just net exposures of a hedged book but the gross exposures. The absolute size of the longs and shorts regardless of how offsetting they appear to be. Those gross exposures jump out of the closet to scare you at the worst times. When correlations rip higher.

Check out this bit from Byrne Hobart’s letter this week. First on correlation:

It’s a commonplace observation in finance that when markets go down, all correlations go to one. This makes perfect sense from a Minskian perspective: investors feel safe levering up when they expect economic fundamentals to stay healthy, but the more they lever up, the more any one fundamental change can break the entire system. But it’s also a broader truth: “Black Swans”—extreme events that blow up the assumption of a normal distribution—really only happen if a lot of seemingly-unrelated things are serially correlated. The reason models of the 2016 election underrated Trump was that they underrated the chance that the polling error could go in the same direction in every swing state. The reason credit default swaps on real estate-backed structured products were cheap in 2006 was that most investors didn’t realize that cheap credit had raised the correlation between housing markets, and that asset selection raised the correlation further within each structured product.

Correlation. A cute number between -1 and 1 upon which numbers with many more zeros rest. This can feel abstract if Excel is not your first professional language. When trying to adjust the current virus crisis to compare with historical ones, it’s useful to search for hidden forms of leverage including non-financial types.

Hobart continues:

The outcome of this is that every technology entrepreneur and investor needs to care about the global economy. The trends you’re counting on—free flow of capital, goods, information, and people—are dependent on a set of conditions that might not hold. And they’re correlated. Most useful macro discussions revolve around China, since it’s the axis around which the world economy revolves. But it’s also the lynchpin of the global electronics supply chain. Any plan that presupposes continuous improvements in smartphones and continually cheaper components assumes that China keeps on growing at the same pace, and remains tightly-coupled to the US, Europe, and emerging markets.

Manufacturers are realizing, and consumers are about to realize, that supply chains offer their own sort of leverage, with their own potential for a “Minksy Moment” in which a disruption in one place causes cascading chaos everywhere else. Coronavirus might be a minor speedbump, but it, or something like it, will eventually force a wholesale change in the pace and nature of globalization.

This week concerns of economic slowdown and supply chains as single points of failure are gripping markets. Wall Street is getting way in front of this one, calling for zero economic growth in 2020. Do we just jump to visions of empty planes and restaurants? Morgan Housel likes to remind investors of Napoleon’s definition of military genius: “The man who can do the average thing when everyone else around him is losing his mind.”

From Headlines To Numbers

Slow down to break it down. Consider what variables are being pushed around. Have a model. If your model maps variables to outputs then start turning the knobs to see how sensitive the outcomes are to different scenarios. The point here is not to do numeric Mad-Libs then believe the silly story you wrote. It’s an exercise in thinking. A model turns emotional headlines into dispassionate inputs so you can actually reason about them probabilistically.

My favorite analysis in this vein comes from the philosopher-king of valuation Professor Aswath Damodaran. He starts with his general model then shows at which nodes COVID-19 developments have an impact.

Again the actual numbers aren’t the point. It’s the calming process of seeing how abstract arguments which threaten to shut our minds down into fight-or-flight mode can be safely downshifted into cold digits. Type into cells, hit F9, generate an opinion that can just change with the facts. The full article including Damodaran’s spreadsheet. (Link)

I don’t have a strong corporate finance background. Damodaran’s website is one of the best resources on the web for learning. You can take his NYU course online or just go through his prolific writing. Tying together how growth rates, discount factors, reinvestment, and payout ratios all interconnect before arriving at valuation is actually fun to understand. I found it demystifying to work through this spreadsheet and I recommend it to anyone trying to understand the basics of how to think about share values. (Link)

If you want to see how he adjusts to new facts step through this post from Q42018 (Link)

Do Professional Investors Understand Fees?

Fees Are In Focus


Retail

Giant fund manager/brokerages like Vanguard and Fidelity have made fees front and center. Like Walmart, if you are the lowest cost provider and wield blue whale scale, you are going to compete on price. Competition has spurred a race to the bottom on fees. With many investment choices commoditized, the focus on fees has served customers well. 

If I wanted to nit-pick, I might say investors don’t fully account for more opaque fees when choosing funds. These can swamp the management fees. Turnover, slippage costs, borrowing costs and abysmal sweep account rates all have significant impacts on net performance. These hidden costs are not easily reduced to a number that can be compared to a management fee. Hint: it’s a good place to search for how managers are able to drive fees to zero. But that’s a digression. I’m not especially interested in retail. Their financial advisors are doing a good job using steak and wine to box out the fund managers. There’s only so much fee to go around.

Professionals

Allocators have a more difficult job. They devote teams to parsing alternative investments. A sea of private investments and complex hedge fund strategies. Within that context the allocators must construct portfolios that trade-off between tolerable risks and the probability of meeting their mandates. 

The allocators rummage through a diverse mix of strategies each with their own mandates. Growth, wealth preservation, defensive, hedged alpha. A fund can be thought of as a payoff profile with an associated risk profile. A thoughtful allocator is crafting a portfolio like a builder. They want to know how the pieces interlock so the final product is useful and can withstand the eventual earthquake. 

A builder cannot think of materials without considering cost. Wood might make for a better floor than vinyl but at what price would you accept the inferior material? When builders estimate their costs they must consider not only the materials, but transportation costs and how the cost of labor may vary with the time required to install the material. 

So let’s go back to the allocators. If the menu they were choosing from wasn’t complicated enough, they must also evaluate the costs. This is a daunting topic. They face all the opaque costs the retail investors face. But since they are often investing in niche or custom strategies that are not necessarily under a public spotlight they have additional concerns. A basic due diligence process would review:

  • Which costs are allocated to the GPs vs the LPs
  • Liquidity schedules
  • Fund bylaws
  • Specific clauses like “most-favored-nations”
  • Netting risks1

Unlike their retail counterparts, the professional investor’s day job is devoted to more than just investments but terms. Like our builder, this cannot be done faithfully without understanding the costs. Mutual funds sport fixed fees but complex investments often have incentive fees (a fee that is charged as a percentage of performance, sometimes with a hurdle) making them harder to evaluate. Regretfully, I suspect a meaningful segment of pros do not have a strong grasp on how fees affect their investments. 

Understanding Fees

While it is challenging to price many of the features embedded in funds’ offering documents, there is little excuse for not understanding fees whether they are fixed or performance-based.  After all, if you are an investor this is one of the most basic levers that affect your net performance and does not rely on having skills. It’s a classic high impact, easy to achieve objective. It’s the best box in that prioritization matrix that floats around consulting circles. 

Let’s take a quick test. 

You have a choice to invest in 2 funds that have identical strategies.

They have the same Sharpe ratio of .5

There are 2 differences between the funds. The fee structure and volatility.

  Fund A Fund B
Expected Return 5% 15%
Annual Volatility 10% 30%
Annual Fee 1% 2%

Let’s assume the excess volatility is simply a result of leverage and that the leverage is free.

Which fund do you choose?

Normalizing Fees By Volatility

The correct way to think about this is to adjust the fee for volatility.

  • Fund A’s fee is 10% of its volatility (1% / 10%).
  • Fund B’s fee is 6.7% of it volatility (2% / 30%)

If you doubt that Fund B is cheaper from this reasoning you could simply sell Fund A and buy 1/3 as much of Fund B.

Let’s use real numbers. Suppose to had a $300,000 investment in Fund A. You would be paying 1% or $3,000 in fees. 

Instead, invest $100,000 in fund B. Your expected annual return and volatility would remain the same, but you would only pay 2% of $100k in fees or $2,000. Same risk/reward for 2/3rd the price. Compound that.

I am not alone in this observation. From his book Leveraged Returns, Rob Carver echoes that a fund’s fees can only be discussed in context with its volatility:

I calculate all costs in risk-adjusted terms: as an annual proportion of target risk. For target risk of 15%/year and costs of 1.5%/year, your risk-adjusted costs are 1.5%/15% = 0.10. “This is how much of your gross Sharpe ratio will get eaten up by costs.

 

A Clue That Some Allocators Get This Wrong

Allocators will often target lower vol products for the same fee when a higher vol fund would do. To be fee-efficient they should prefer that managers ran their strategies at a prudent maximum volatility. Optimally some point before they were overlevered or introduced possible path problems. There are many funds and CTAs that would just as easily target higher volatility for the same fee. Investors would be better off for 2 reasons:

  • Allocators could reduce their allocations

As we saw in the Fund B example, it is more fee-efficient for vol targeting to be done at the allocation level not the fund level.

  • Limit cash drag.

They would stop paying excess fees for a fund that had been forced to maintain large cash reserves since it was targeting a sub-optimal volatility. Why would an allocator be ok with paying fees for funds that are holding excessive t-bills?

If you are not convinced that investors’ preference for lower vol versions of strategies demonstrates a lack of fee numeracy then check out this podcast with allocator Chris Schindler.  As an investor at the highly sophisticated Ontario Teachers Pension he witnessed firsthand the folly of his contemporaries’ thinking around fees. While mingling at conferences he would hear other investors bragging that they never pay fees above a certain threshold.

As we saw from our example, these brags are self-skewers, revealing how poorly these managers understood the relationships between fees and volatility. Not surprisingly, these very same managers would be invested in bond funds and paying optically low nominal fees. Sadly, once normalized for volatility, these fees proved to be punitively high. 

This brings us to our next section. How would you like to pay for low volatility or defensive investments?

Tests to Compare Fixed Fee Funds with Incentive Fee Funds

A Low Volatility Example

Let’s choose between 2 identical funds which only vary by the fee structure.

Both funds expect to return 5% and have a 5% volatility. Yes, a Sharpe ratio of 1.

  • Fund A charges a fixed .75%
  • Fund B charges 10% of performance from when you invest. Fund B has a high watermark that crystallizes 2 annually.

Which fund do you choose?

A Large Cap Equity Example

This time let’s choose between funds that have SPX-like features

Both funds expect to return 7% and have a 16% volatility.

  • Fund A again charges a fixed .75%
  • Fund B again charges 10% of performance from when you invest. Fund B has a high watermark that crystallizes < annually.

Which fund do you choose?

Studying The Impact Of Fee Structure

I wrote simulations to study the impact of fees on the test examples.

The universal setup:

  • Each fund holds the exact same reference portfolio
  • 10 years simulation using monthly returns
  • Random monthly returns drawn from normal distribution 
  • 1000 trials
  • Fixed Fee Fund charges .75% per year deducted quarterly
  • Incentive Fee Fund charges 10% of profits crystallized annually

Case 1: Low-volatility 

Simulation parameters:

  • Monthly mean return of .42% (5% annual)
  • Monthly standard deviation of 1.44% (5% annually)3

This chart plots the outperformance of the fixed fee return vs incentive fee return fund annually vs the return of the portfolio which they both own. The relative performance of the 2 funds is due to fees alone. 

Observations

  • It takes a return of about 7% or higher for the fixed fee fund to outperform.
  • This makes sense. A 75 bp fee is difficult to overcome for a 5% vol asset.
  • If the asset returns 5% the performance fee would only be 50bps and we can see how the difference in fees approximates the underperformance of the fixed fee fund for 5% level of returns.

Case 2: Large Cap Equity Example

The universal setup remains the same. 

We modify the simulation parameters:

  • Monthly mean return of .58% (7% annual)
  • Monthly standard deviation of 4.62% (16% annually)

Observations

  • Most of the time the fixed fee fund outperforms. So long as the return is north of about 4% this is true.
  • The most the fixed fee fund can underperform is by the amount of the fixed fee. Consider the case in which both portfolios lose value every year. The incentive fee fund will never charge a fee, while you will get hit by the 75bps charge in the fixed fee fund. You can see these cases in the negative points on the left of the chart where the portfolio realizes an annual CAGR of -5%.
  • Conversely, the incentive fee can be very expensive since it captures a percentage of the upside. In cases where the underlying portfolio enjoys +20% CAGRs, the simple fixed fee fund is outperforming by about 150 bps per year. 

Bonus Case: The High Volatility Fund

Finally I will show the output for a low Sharpe, high volatility fund.

The universal setup remains the same. 

We modify the simulation parameters:

  • Monthly mean return of .42% (5% annual)
  • Monthly standard deviation of 10.10% (35% annually)

Observations

  • This case demonstrates how complicated the interactions of fees and volatility are. The fixed fee fund will massively outperform by even as much as 200bps per year when the portfolio compounds at 20% annually.
  • The fixed fee fund even outperforms at low to mid single-digit returns albeit modestly. 
  • The high volatility nature of the strategy means lots of negative simulations, thanks to geometric compounding (for further explanation I discuss it here). When a fund performs poorly you pay less incentive fees so it’s not surprising that in many of these case the fixed fee fund underperforms by nearly the entire amount of the management fee. 

Takeaways

Fixed Fees

  • Best when the volatility of the strategy is high and the returns are strong (again you are warned: most high volatility strategies don’t have strong returns because of geometric compounding).
  • The most a fixed fee investor can underperform an incentive fee investor is by the amount of the fixed fee.

Incentive Fees

  • Best when the strategy is low volatility or returns are negative. Or the asset is defensive in nature. For hedges or insurance like funds, you may prefer to pay a performance fee to minimize bleed.
  • The amount an incentive fee investor can underperform is technically unbounded since it’s a straight percent of profits.

General

  • Fee structures must be considered relative to the volatility and goals of the strategy. There are no absolutes. 
  • By dividing fixed fees by the fund’s volatility you can normalize and therefore compare fund fees on an apples-to-apples basis. Even seemingly low fixed fees can be very expensive when charged on low volatility funds. 
  • Incentive fees look like long options to the manager (which implies the investor is short this option). The investor has unbounded potential to underperform a fixed fee solution and can only outperform by the amount of the fixed fee (the left hand side of those charts). To further study the embedded optionality of incentive fees see Citigroup’s presentation.
  • Incentive fees are meant to align investors and management. Who can argue with “eat what you kill”? But they can also create bad incentives. If trapped below the high watermark, the manager has nothing to lose and may swing for the fences irresponsibly. In addition, a staff working at a fund that is underwater might be dusting off their resumes instead of focusing on getting back on track knowing that they need to work through uncompensated p/l before they see another bonus. 
  • Fixed fees can encourage management to diversify or hold more cash to lower the fund volatility. These maneuvers can be combined with heavy marketing in a strategy more colloquially known as “asset-gathering”.

Conclusion

Fees need to be considered in light of the strategy. This requires being thoughtful to understand the levers. Unless you are comparing 2 SP500 index funds, it’s rarely as simple as comparing the headline fees. If we all agree that fees are not only critical components of long-term performance, while being one of the few things an allocator can control, then misunderstanding them is just negligent. A one size fee doesn’t fit all  alternative investments so a one size rule for judging fees cannot also make sense. Compared to the difficulty of sourcing investments and crafting portfolios getting smart about fees is low-hanging fruit.