Surviving The Quantpocalypse

A crashed Mitsubishi A6M Zero; Source: National Archives

There is a popular narrative these days that human fundamental investors are no match for quants and machine learning algorithms. They will be wiped out in the quantpocalypse. I only half believe this. My reasoning goes back to the sources of investing “edge.” We will approach the quantpocalypse through the lens of investment edge and by the end you will understand the relevance of the photo above.

First thing first. If you have no edge, and you know it, then by definition you should index your investments. That’s not meant as an insult to index investors. It’s a perfectly rational strategy. Beyond that there are three broad sources of investment edge (I do not recall exactly who came up with this but for the record it was not me):

Informational Edge: You know something others don’t about a security.

Analytical Edge: You process information in such a way as to arrive at a unique insight that indicates a security is mispriced.

Behavioral Edge: You are able to exploit other investors’ bad behavior and behavioral constraints imposed on them by others.

Qaunts are very, very good at gaining and maintaining informational and analytical edges. They are engaged in an ever-accelerating arms race to acquire and process data sets before information becomes widely disseminated and their edge is arbitraged away. This data includes things like cell phone location data and satellite photos of retail parking lots. Heard of people combing credit card data for insights? That is old news. I recently listened to an excellent podcast on this subject where credit card data was described as “table stakes.”

I will tell you right now that you as an individual have neither an informational nor analytical edge versus a decent quant shop. Most active fundamental managers don’t, for that matter. They are competing with the quants to call quarters–to identify which companies are going to beat consensus earnings estimates and which are going to miss them.

This is a fool’s errand. You will not beat a quant at the game of his choosing. That computer from Wargames said it best, “the only way to win is not to play.”

In my view, the type of edge that is still available to traditional fundamental investors is behavioral. There are two reasons for this. The first is that many quants are shorter term investors with a quarterly time horizon or less. The second is that many sophisticated investors, quant or otherwise, are constrained by their investors.

Wes Gray of Alpha Architect explains this using a poker analogy:

On one end of the table, we have our irrational investors. They drop their cards, they giggle when they get an Ace, and they ask people next to them “Is it a good thing if all of my cards have the people’s faces on them?”

On the other side of the table is an institutional poker player, hired by wealthy investors, to play poker as best as possible. This poker player is a pure genius, mathematically calculates all probabilities in her head, and knows her odds better than anyone. Now imagine that our super player, as a hired gun, has a few limits. “We need you to maintain good diversification across low numbers and high numbers. We also want to see a sector rotation between spades, aces, and clubs. Don’t take on too much risk with straights and flushes, stick to pairs like the market does…” No one would ever play poker like this. But in finance, this is how people play.

Now the cards are dealt. Super Player sees a great opportunity with a high chance of success, but it violates all the requirements of her investors. She doesn’t bet, and sure enough, she could have won big.

Thus the “easiest” edge for today’s investment professionals to exploit is behavioral. Specifically, you have a behavioral edge if you can arbitrage the time horizons and constraints imposed on other sophisticated investors.

I say “easiest” here because this doesn’t require investing millions of dollars in data sets, machine learning and top flight data scientists. It does, however, require a diligent and disciplined investment process, along with either a permanent capital base or highly aligned investors who are not going to bug out if a core position draws down 50% on a bad quarterly result.

Importantly, this is not something that can easily be arbitraged away by quants. It is a structural market inefficiency and for an investor that is a beautiful thing.

In my experience most non-practitioners have a limited understanding of the investment ecosystem, its participants and their varying motivations, constraints and time horizons. This leads to a monolithic classification of market participants. From the layperson’s perspective Bridgewater “competes” directly with Baupost in every position. This Level 0 view of the market is reinforced by media coverage that tends to compare apples to durian. Reality, as usual, is more complex (#notallhedgefunds?).

There is no “magical investment strategy” that will outperform in continuous time. Every strategy has strengths and weaknesses. The trick is to employ the right strategies in the right asset classes at the right time horizon based on your objectives.

To illustrate this another way, consider the example of American pilots flying F4F Wildcats against Japanese A6M Zeros (pictured at top) during the Second World War. The Wildcat was slower and less maneuverable than the Zero. But it was much better armored and also faster in a dive. The trick to staying alive as a Wildcat pilot was not to fight the Zero’s fight. Wildcat pilots were generally quick studies on that front (turns out staying alive is a pretty powerful incentive). If the statistics on Wikipedia are to be believed, the resulting kill ratio versus the Zero was an incredible 7 to 1.


I am generally a contrarian by nature.

To illustrate:

  • I am skeptical of home ownership as wealth creating endeavor.
  • I do not like reading “popular” books or seeing “popular” movies for the sake of being able to have conversations about them.
  • In my view at least 50% of the episodes of Game of Thrones are time-wasting filler.
  • I am generally not that into big events that draw crowds (sports victory parades, Coachella, Burning Man or Fyre Festival–but there are exceptions).

Perhaps unsurprisingly this permeates my investment philosophy. Things I like right now include a Russian natural gas company, a Brazilian aerospace company and sub-Saharan African bank holding company (I have a North African/Middle Eastern bank on my watch list, too, if the valuation ever comes down to earth). This is not a recipe for outperformance. It is not investment advice. It is just who I am as an investor.

Being a contrarian investor is great. You have good company in people like Seth Klarman and Howard Marks. On the other hand, being a contrarian in the investment business is not nearly so pleasant.

Contrarian ideas are often hard to sell and investment committees are engineered to arrive at consensus decisions. Consensus decisions are generally good for business. Consensus decisions will not deliver top quartile performance but they will not deliver bottom quartile performance, either. You can have a very nice business and never deliver top quartile performance. But woe betide you if you end up in the bottom quartile. It may well be the end of your business.

I sometimes hear about firms that designate “devil’s advocates” on committees. The devil’s advocate’s job is to argue against every single investment thesis. She is not allowed to argue in favor, or to moderate her argument. She is a dedicated short and everyone knows it in advance. This is a neat solution to the problem of encouraging a contrarian viewpoint in a high pressure group setting (contrarians can often grate on their fellow committee members). But does it make any difference?

What percent of ideas get blown up because of the devil’s advocate? Or is the whole thing just an exercise in box-checking dreamed up to please consultants? I suspect in most cases it’s the latter.

Edward Hess summarizes the issue quite nicely in an article titled “Why Is Innovation So Hard?”:

Most organizational environments won’t help us overcome our fear of failure and build our innovative thinking skills. That’s because most organizations exist to produce predictable, reliable, standardized results. In those environments, mistakes and failures are bad. That is a problem. To innovate, you must simultaneously tolerate mistakes and insist on operational excellence. Many businesses struggle with implementing that dual mentality.

Here we can learn from exemplar companies like IDEO, Pixar, Intuit INTU -1.84%, W.L. Gore & Associates, and Bridgewater Associates. In those organizations, mistakes and failures are redefined as “learning opportunities.” IDEO takes it even further, characterizing failure as good because it helps people develop the humility that is necessary for empathy—a critical skill in user-centric innovation.

But in many workplaces, people do not “feel safe enough to dare.” They don’t necessarily feel that they can speak with candor up and down the organization. Can you tell your boss the truth?  Innovation occurs best in an “idea meritocracy,” a culture where the best evidence-based ideas win. There can’t be two sets of rules—everyone’s ideas must be subject to the same rigorous scrutiny. As Ray Dalio, the founder of Bridgewater Associates, one of the largest hedge funds in the world, so bluntly said, “We all are dumb shits.” That’s why everyone at his company is engaged in a radically transparent “search for truth,” which involves candid feedback and a deliberate effort to “get above yourself,” to get past the emotional defenses that inhibit our thinking.

In other words, organizational incentives are skewed toward rewarding preservation of the status quo. If The Golden Rule is “He who hath the gold, maketh the rules,” surely immediate the corollary is “He who f***eth with The Golden Goose shall meet with a pointy reckoning.”


Why We Believe What We Believe

Most people do not reason from first principles when developing their political views. Rather, they develop a set of views based on their life experiences and retrofit facts and narratives to conform with that worldview (myself included). How else do you explain something like the backfire effect?

David McRaney of You Are Not So Smart writes:

Geoffrey Munro at the University of California and Peter Ditto at Kent State University concocted a series of fake scientific studies in 1997. One set of studies said homosexuality was probably a mental illness. The other set suggested homosexuality was normal and natural. They then separated subjects into two groups; one group said they believed homosexuality was a mental illness and one did not. Each group then read the fake studies full of pretend facts and figures suggesting their worldview was wrong. On either side of the issue, after reading studies which did not support their beliefs, most people didn’t report an epiphany, a realization they’ve been wrong all these years. Instead, they said the issue was something science couldn’t understand. When asked about other topics later on, like spanking or astrology, these same people said they no longer trusted research to determine the truth. Rather than shed their belief and face facts, they rejected science altogether.

In my view most people are “conditioned” to a set of political beliefs over time. The conditioning happens through the interaction of individual effort and experience and external stimuli. The process is path dependent.

If I am an entrepreneur, and I labor diligently for years to build my business and become wealthy and successful, I am conditioned to believe market systems work and are fair in allocating resources. I am more likely to support light regulation and promote individual accountability.

Likewise if I grow up in a community where financial institutions operate with predatory business models, I am conditioned to believe market systems are broken, and that a wealthy few (say, 1% of the population) manipulate markets to strip assets and wealth from communities like mine. I am more likely to support tight regulation and institutional accountability.

These are overly simplistic examples but I find them instructive. For someone like me who believes most individuals act based on incentive structures and not based on rational analysis, this is a powerful idea. It is consistent with the historical institutionalist approach to history, but on an individual level.

From Wikipedia:

A related crux of historical institutionalism is that temporal sequences matter: outcomes depend upon the timing of exogenous factors (such as inter-state competition or economic crisis) in relation to particular institutional configurations (such as the level of bureaucratic professionalism or degree of state autonomy from class forces).[6] For example, Theda Skocpol suggests that the democratic outcome of the English Civil War was a result of the fact that the comparatively weak English Crown lacked the military capacity to fight the landed upper-class. In contrast, the rise of rapid industrialization and fascism in Prussia when faced with international security threats was because the Prussian state was a “highly bureaucratic and centralized agrarian state” composed by “men closely ties to landed notables”.[7] Thomas Ertman, in his account of state building in medieval and early modern Europe, argues that variations in the type of regime built in Europe during this period can be traced to one macro-international factor and two historical institutional factors. At the macro-structural level, the “timing of the onset of sustained geopolitical competition” created an atmosphere of insecurity that appeared best addressed by consolidating state power. The timing of the onset of competition is critical for Ertman’s explanation. States that faced competitive pressures early had to consolidate through patrimonial structures, since the development of modern bureaucratic techniques had not yet arrived. States faced with competitive pressures later could on the other hand, could take advantage of advancements in training and knowledge to promote a more technical oriented civil service.[8][9]

The obvious takeaway from all of this is shouting at people about politics, either in person or on social media, is a complete waste of time and energy. Beyond that, however, this provides an objective framework for understanding why people believe certain things and why people behave in certain ways. This is of critical importance to investors, who must account for higher order, non-linear effects when making decisions.

Barring an “impact investing” mandate, an investor must set her political beliefs aside when making decisions. Rather the investor must focus on the beliefs of others. It is the beliefs of others that impact the economic and market environment.

Just Say No To News

If you have ever owned an individual stock–especially a large cap stock with a lot of coverage–one thing you probably learned very quickly is to tune out day-to-day newsflow. For example, the largest cap individual stock I currently own in my portfolio is Gazprom. Hundreds, if not thousands, of news stories are published daily either about the company itself, or about energy industry or geopolitical events that could impact the stock.

Here are sample headlines from a quick Google news search:

Gazprom Eyes Brazil’s Natural Gas Opportunities

Gazprom—the LNG pivot?

EU says wants Russia’s Gazprom to sweeten antitrust concessions

Russia’s Gazprom Neft ‘holds its nose’ at global oil output cut

Kiev allowed to arrest Gazprom’s property: there is nothing but gas

Russian Parliament to Consider Tax Preferences for Gazprom

You get the idea.

I could spend a lot of time tracking Gazprom news. I could probably write an entire blog just about Gazprom (I am not sure it would endear me to the Russian security services). I would never want for material. But it probably wouldn’t improve my investment results much. It might even hurt my results.

Most of this daily news is just noise. It is exacerbated by the fact that Gazprom is majority owned by the Russian government — pro-Russian and anti-Russian news outlets have every incentive to put out biased coverage. If you immerse yourself in the noise, it is easy to lose track of business fundamentals. You start wondering whether you should buy or sell based on commentary from some journalist (who may or may not be able to read a balance sheet). You will be tempted to sell on every price move, either to avoid a loss or lock in a gain.

The problem is the news cycle moves very, very fast. Business cycles move slowly. The ratio of noise (meaningless information) to useful information in the news cycle is quite high. In the business cycle that ratio is lower. As a long-term fundamental investor you want to think in terms of business cycles as they are more aligned with your investment horizon.

Furthermore, when it comes to things like currency risk and geopolitical risk there is nothing about monitoring news that will give you any more control over the situation.  Either the stock has properly priced the graft, administrative inefficiency, currency risk and geopolitical risk embedded in the business or it hasn’t. You deal with that up front, with the margin of safety you demand at purchase. There is no point getting worked up over day-to-day newsflow. It is not constructive.

So it is with almost all types of news. Especially political news.

We are in the midst of a particularly vicious political cycle in the US. In my view this is a cyclical phenomenon. (Bridgewater did a nice little piece on populism a while back–I don’t believe it’s a coincidence that the last time populism had this much momentum in Western countries was in the decade following The Great Depression) Anyway, the forces that shape the political climate of a given era are much larger than you or me. Much like the geopolitical risks facing Gazprom, the political environment is beyond our control.

A majority of the news we consume is meaningless noise. I am looking at the title of a news story on my phone as I write this: “Woody Harrelson’s Dinner With Trump Was So Bad He Had To Smoke A Joint.” Now if I hate Donald Trump I am laughing at this story. If I am a Trump supporter it is fake news or liberal propaganda and I am angry. I will go to Breitbart and read something uplifting about glib liberal cucks. Vice versa for “Mark Zuckerberg and liberals seek to weaken bail system that keeps us safe.”

Again, this is meaningless noise. But worse than that it is noise that gets people emotionally charged up. That is what most political news does. Indeed it is designed that way–all the better for the clicks and social shares (not to mention Facebook’s margins).

In general I try to keep my political news consumption to minimal levels. I will read the top political stories in the Financial Times. I will also read a brief set of bullets I receive each business day from another investment professional. The bullets are non-partisan and succinctly summarize major developments and strategic considerations for each political party.

Beyond that I am careful about my political news consumption. The reason? Much of it is written to drive an emotional response and precious little of it actually matters. In his book Fooled By Randomness, Nassim Taleb observes:

We just saw how the scientifically hideous George Will and his colleagues can twist arguments to sound right without being right. But there is a more general impact by information providers in biasing the representation of the world one gets from the delivered information. It is a fact our brain tends to go for superficial clues when it comes to risk and probability, these clues being largely determined by what emotions they elicit or the ease with which they come to mind […]

In that sense the description coming from journalism is certainly not just an unrealistic representation of the world but rather the one that can fool you the most by grabbing your attention via your emotional apparatus–the cheapest to deliver sensation.

If the major cable news networks and their legion of apoplectic commentators winked out of existence tomorrow, what would really go missing from your life? (Ditto the HuffPosts, Daily Beasts and Breitbarts) Would this impede your ability to earn a living? Would it diminish your relationships with family, friends and professional colleagues? Would it negatively impact your physical and psychological well-being?

My guess is no.

In fact, if surveys conducted prior to the 2016 election are anything to go by, I suspect most individuals and their relationships would be all the healthier minus the incessant yammering of the pundit class.

So my humble suggestion is that you give the news cycle–particularly the political news cycle–the Gazprom treatment. Ignore it. Or at least ignore it a majority of the time. I suspect you will find it makes very little difference in your life. To the extent it makes any difference at all, it will probably be a positive.

The Dumbest Friend Test

Conceptually, cycles might be the most important thing in finance and economics. There are lots of cycles in finance. Probably the most important of these is the credit cycle. If you would like a fun and easy-to-follow primer on the credit cycle you should watch this video from Ray Dalio:

Anyway cycles are pervasive in financial markets and in my view it is as important to watch qualitative indicators as quantitative indicators to mark a cycle’s progress. As an example, I was recently in a meeting with a successful investment manager who said “it was not time” to short stocks again (the last time he shorted stocks heavily was in the early 2000s as the technology bubble collapsed). I asked him what would indicate “it was time” to short again. “When clients are calling me with stock tips,” he said.

I am fascinated by the cryptocurrency phenomenon partly because I have not seen a market run really, really hot since I have been investing (though I sure have seen some faddish silliness). People talk about the S&P 500 being overvalued these days but the S&P 500 has got nothing on crypto when it comes to sheer investor euphoria.

So I propose a simple qualitative test to help determine whether a market is running really, really hot. Ask yourself: what is my dumbest friend doing? If your dumbest friend is “easily” making money hand over fist it is probably safe to say that market is running hot. To illustrate here is Simon Black via Zero Hedge:

I vividly remember having a conversation several years ago with a woman about her real estate investments in the United States.

It must have been around 2005 or 2006… the peak of the property bubble.

She was a psychologist from somewhere in the midwest, telling me about how she was flipping off-plan condominiums in Florida.

Basically she would put money down to secure a condo unit in a building before it broke ground, then sell her contract to someone else at a higher price when the building was closer to completion.

I remember as she told me this story she was practically cackling at how quickly and easily she was doubling and tripling her money, and at one point said, “It is just soooo easy for me.”

Those words stuck.

I remember thinking, “Investing isn’t supposed to be easy. There’s supposed to be risk and hard work involved.”

But she wasn’t alone. Legions of amateur investors were piling into the market doing exactly the same thing.

Everyone seemed to be flipping condos. And everyone seemed to be making money.

It didn’t add up.

I remember one investor explaining to me how he would flip his condo contract to someone else when the building was 30% complete. Then that buyer would flip the contract to another investor when the building was 60% complete. Then another sale when the building was 80% complete, etc.

“But who is the person at the end of the line?” I asked. “Someone has to eventually live in all of these condos and be willing to pay the highest price.”

“Oh there will ALWAYS be plenty of people who will live here,” he told me.

Valuing A Bitcoin – Part III

Building off yesterday’s post today I will unveil a Bitcoin valuation.

Before we go any further I must emphasize that I am sharing this information as an intellectual exercise and for entertainment purposes only. This is not an investment recommendation and the output of this model should not be used to make investment decisions. You should consult with a financial advisor before making any investment decision. In the interest of full disclosure you should also know that I currently own neither cryptoassets nor exchange traded cryptoasset products (ETPs and ETNs).

The theoretical underpinning from this model is taken from Burniske and Tatar’s book, Cryptoassets. The authors propose adapting the Equation of Exchange (MV = PY) for valuing cryptocurrencies.

What the equation of exchange tells us is that the money supply times the velocity with which money circulates (left side) must equal the price level times real output (right side, a.k.a nominal output). So:

M = Money Supply

V = Velocity of Money

P = Price Level

Y = Real Output

I will apply the model to Bitcoin using data from Many of my inputs will be rounded but I have always believed that perfect is the enemy of good when it comes to investing and valuation in particular. I am not sweating the small stuff. You are welcome to redo the work to two decimal points if spurious precision is your thing.

Anyway, we start with the supply of Bitcoin. This is easy. There will only ever be 21 million Bitcoins (unless of course the code is changed and that is a governance issue for the time being not a valuation issue). To be conservative I will assume all 21 million Bitcoin are in circulation for the valuation calculation.

The velocity of Bitcoin is a bit fuzzier but I can try to approximate the number using Bitcoin transaction data. According to the data Bitcoin transaction volumes are fairly stable oscillating around 200,000. We can annualize this by multiplying by 365 which equals about 73,000,000. We divide 73,000,000,000 by the current Bitcoin supply of about 16 million to get a velocity of about 4.56.

Price in USD is the variable we solve for. So we will pass over it for now.

With output we make a small adjustment and use output in USD terms as it will be easier to place our assumptions in context that way. This is about $1bn per day currently which we can annualize to about $365bn. That is estimated output today. What we need for our model is to also estimate the output at some point in the future. For the sake of this exercise let’s say in five years we think the USD equivalent transaction output for the Bitcoin network will be $1tn. This is a critical variable and some readers may think I am being overly conservative. Maybe so but do consider that this represents a compound annual growth rate of 112% a year.

We set up the model as follows:

21,000,000 x 4.56 = P ($1,000,000,000,000)

Solve for P using basic algebra and you get about .000096 BTC/USD. To make this number intelligible we take the reciprocal 1/.000096 to get USD/BTC which (using a spreadsheet for spurious precision) is about $10,443. That is a the estimated value of one Bitcoin five years from now.

For the final step we simply discount this price 5 years at our required rate of return. Since discount rate estimation is a pain and something of a guessing game in the best of times I like to simply choose a desired hurdle rate. For an asset like BTC I think 30% is reasonable given the risks and the immaturity of the asset class.

So discounting $10,443 for 5 years at 30% I estimate the value of one BTC today at $2,813. A summary of these calculations is included below.

Sources: Burniske & Tatar (model); Myself (calculations & tweaks)

Contrary to what some may think modeling is not about predicting the future. Rather it is about being explicit with your assumptions. This helps you test your assumptions for reasonableness. It also helps you identify the key variables you need to get right. Finally, it helps you build and maintain conviction in the face of market price volatility.

With Bitcoin here are the key variables:

  • How big can it get? -> How much “share” of global transaction volume will it take?
  • How long will it take to get there?
  • To what extent will it be used to transact versus as a store of value? The lower the velocity the more it is being used as a store of value and vice versa.
  • How much reward do you require given the risks?

You might disagree with my results and that is fine. However, I would ask you to consider where our views differ in the context of this model. Is it because you believe Bitcoin will get “bigger” and/or that it will get there “faster”? Is it because you think Bitcoin is less risky than I do?

I hope to update this valuation from time to time as Bitcoin evolves as an asset.

In closing, I would like to once again emphasize:

I am sharing this information as an intellectual exercise and for entertainment purposes only. This is not an investment recommendation and the output of this model should not be used to make investment decisions. You should consult with a financial advisor before making any investment decision. In the interest of full disclosure you should also know that I currently own neither cryptoassets nor exchange traded cryptoasset products (ETPs and ETNs).

Book Review: Cryptoassets: The Innovative Investor’s Guide to Bitcoin and Beyond

Cryptoassets_CoverI pre-ordered this book on Amazon after seeing it mentioned on Josh Brown’s blog, The Reformed Broker. I was intrigued because it purported to be a rigorous treatment of cryptocurrency and cryptoassets written from the perspective of a relatively sophisticated investor.

Burniske and Tatar state their goal was to produce a book that is the equivalent of Benjamin Graham’s Intelligent Investor for cryptoassets. That is kind of like Dennis Rodman saying he wanted to do for rebounds what Michael Jordan did for dunks. To the authors’ credit I think they have done an admirable job of approaching a fast-evolving space in a balanced and rigorous way.


The book is well-organized. It is segmented into three parts: What, Why and How.

What: Discusses the theoretical underpinnings of cryptoassets and provides background information on the history and evolution of several major cryptocurrencies: Bitcoin, Ethereum, Ripple, Monero, Zcash and Dash (I may have omitted a couple). Burniske and Tatar take pains to distinguish between cryptocurrencies, cryptocommodities and cryptotokens.

Why: This section provides an overview of Modern Portfolio Theory (MPT) and the use of mean-variance optimization in constructing an investment portfolio. The authors argue for the inclusion of cryptoassets in an investor portfolio based on their potential to improve overall portfolio efficiency, similar to more “traditional” alternative investments such as hedge funds, private real estate and commodities. I skipped most of this section as I am very familiar with MPT.

How: This section was really what attracted me to the book as it lays out a framework for performing due diligence on a prospective cryptocurrency investment. The authors address issues of custody, valuation and trading, as well as some of the nuances of trading in fragmented markets with the potential for wide fluctuations in trading volumes. The valuation model they float for cryptoassets is more or less the Equation of Exchange (MV = PY or in this case P = MV/Y). One issue I don’t think they adequately address is the issue of reflexivity in the “velocity” of crypto transactions (speculative trading activity drives up network activity which in my view creates a kind of feedback loop).

Who Should Read This Book

Anyone looking for a comprehensive introduction to cryptoassets would benefit from reading this book. It would be particularly useful financial advisors looking to educate themselves in order to address client questions or advisors considering cryptoassets for inclusion in client portfolios. The book is very much written in the language of the financial professional.

Who Should Not Read This Book

This book does not contain any secret sauce for getting rich quick. People who are looking for “hot tips” or “hacks” will be disappointed. While the authors are clearly bullish on the long-terms prospects for cryptoassets, they emphasize the need for investors to educate themselves, conduct thorough due diligence and develop an investment discipline. The due diligence concepts outlined in the book are applicable to any asset class or investment opportunity.

My comments on this book should in no way be taken as a recommendation to buy or sell any cryptoasset. If you are wondering whether you should own cryptoassets as part of your investment portfolio you should consult with a financial advisor who can advise you based on your unique financial circumstances.

The Home Ownership Scam

We are all curmudgeons about something. Some people don’t like cats or dogs. Others don’t like children. Me? I don’t like residential real estate. In fact, I think for the average American household home ownership is something of a scam. The scam is perpetrated by a massive housing value chain, which accounts for something like 4% of US GDP.

Think for a moment about the people lined up to rip your guts out when you buy a home: the seller; the seller’s real estate agent; your real estate agent; the home inspection guy/gal; the mortgage broker; the bank/wholesale finance operation funding the mortgage; the insurance company. All of these individuals have an explicit financial incentive to promote home ownership as your path to wealth and happiness, no matter the sticker price.

To make my point another way, here are some charts from JPMorgan:


See the con?

Despite the mid-2000s housing crash, the estimated multiple of average family income needed to purchase a home has increased nearly a full turn since 2000. This despite increases in median household income:


Massive housing price inflation has been driven primarily by one thing: cheap debt. Mortgage rates have come down steadily since the 1980s. This looks a hell of a lot like a super cycle to me. In fact it’s two inter-related super cycles: one in rates and another in debt (incidentally, you see the same thing with corporate debt — companies have spent the last 30 years swapping debt for equity in their capital structures by borrowing at low rates and using the proceeds to buy back shares).

One thing I try to remain conscious of as an investment professional is when people lose sight of cycles. Cycles can take a long time to play out and cyclical inflection points are difficult to forecast in advance. Hence, people tend to extrapolate naively from the present when thinking about the future. But I will tell you right here and now, households cannot continue to pay ever-increasing multiples of income for homes without access to cheap financing. Some day there will be a pointy reckoning.

One of the most pathetic things I have ever read about is people writing personalized letters to home sellers. If you are doing this intentionally as a Machiavellian value play knowing you are the low bid I have no problem with that. That’s on the seller for being a sucker. But the fact this tactic works at all demonstrates perfectly how emotionally warped our collective view of home ownership has become.

That, friends, is the home ownership scam. A cultish view of home ownership takes a straightforward asset purchase and transforms it into some bizarre emotional and cultural touchstone. So actually you end up feeling good about getting your faced ripped off in the course of the transaction.

Because when you think about it emotionally, any price seems justified. What is the American Dream worth? What is the boost to your image and self-esteem? How about a great school district for your kids and a nice, roomy yard for Flopsy? Are those things worth 4x household income? 5x? 10x?

For most people, it all depends on whether they can make the monthly payment work.

Flopsy (at left) & friends


Valuing Bitcoin – Part II

In my previous post on valuing Bitcoin I settled on supply/demand balance as the “least-bad” valuation model. I have been thinking more on how one might actual implement this in practice. The supply side is fairly straightforward. There are lots of free calculators that allow you to play with cost assumptions for Bitcoin miners. Now, there are probably going to be places in the world where an astute Bitcoin miner can arbitrage differences in electricity costs. But for now that’s splitting hairs.

The far trickier part is the demand side.

The reason is that while there are lots of use cases for Bitcoin, far and away the most prevalent is speculative trading. Therefore, if you take network activity at face value you are probably missing the fact that there is some reflexivity in those statistics. It’s basically a circular error problem. Speculative trading activity drives up network activity which drives up miner’s costs which causes the equilibrium price to rise. BUT, if speculative trading activity slackens (e.g. Bitcoin is in an asset bubble that deflates in the future) then the reverse will occur on the way down.

So in my view what you need to do is account for potential increases or decreases in speculative trading activity (and other kinds of activity) in your model. To do this you would need data that segments different transaction types.

The trick is finding that data.

As always this is not an investment recommendation. It is written for entertainment purposes only. As my thorough disclosure states very clearly, you should never make any investment decision based on something some random dude writes on the internet. Everything I am saying here could be wrong. In fact it is likely wrong. If you are looking for a recommendation on whether to own Bitcoin or any other cryptocurrency you should consult with a trusted financial advisor.