I have often written about the need to be discriminating in the information you consume. Particularly as an investor. The overwhelming majority of information you will encounter on a daily basis is random noise: breaking news; talking heads shouting at each other over the latest cultural or political outrage; mindless entertainment.
Of all the noise you encounter, mindless entertainment is probably the least damaging. I would take an episode of Hell’s Kitchen over an hour of CNN, Fox News or CNBC any day.
Regular readers will know we treasure our useless degrees around here. Happily, we are not the only ones willing to evangelize for the value of studying worthless, outmoded subjects such as English literature, philosophy, religion and language.
Recently the financier Bill Miller donated $75m to the study of philosophy at Johns Hopkins University. The size of the gift made headlines, but few stopped to remark on the other surprise in the story: that someone who studied philosophy went on to create a fortune estimated at about $1bn — and thought this study valuable enough to encourage others to do the same.
Mr Miller is anomalous, obviously. If you really want to understand how to create an enormous fortune from nothing, you should look to someone like George Soros, who studied . . . philosophy. Or consider billionaire investor Carl Icahn, who resigned last year as an adviser to Donald Trump over potential conflicts of interest. He graduated from Princeton with a thesis on “The Problem of Formulating an Adequate Explication of the Empiricist Criterion of Meaning”: another philosopher. Clearly not all philosophers are moral philosophers. But they know how to think.
The brain is like any other muscle: working it makes it stronger, faster, more flexible. Being able to hypothesise, think conditionally and reason inductively as well as deductively are all features of the theoretical training that goes on in good humanities departments — and not only there. The most advanced work in mathematics moves away from real numbers toward imaginary and irrational numbers. That’s where the difficult thinking occurs: in the realm of the imaginary, which is by no means antithetical to the logical.
Let me be clear: useless degrees do absolutely NOTHING to prepare you for schlepping around in an entry level position in any industry.* In reality, most entry level jobs in most industries can be learned through apprenticeship. However, employers like to use education as an easy screen to narrow down pools of job applicants. This is no different than an investor screening stocks trading on EV/EBITDA multiples over 5x out of her investment universe. Yes, she will miss some good companies. That’s not the point. She’s using the screen to narrow the field to a manageable number. She doesn’t have the time, energy and resources to model every company in the Russell 3000.
As with good companies trading on “bad” multiples, screening processes can make it difficult for people holding useless degrees to get their feet in the door initially. For rich people it’s not so bad, because they’ve got lots of wastafrom knowing other rich people. The rest of us have got to build networks and demonstrate our ability to add value. This can be a circuitous path. I started my career in finance as a Customer Service Associate in retail banking. Paying dues like this is no fun and can cause us useless degree holders to despair at times.
However, I contend that a useless degree holder with sufficient motivation is exposed to significant positive convexity in his career / earnings progression over time.
As your career progresses, your job is less and less about executing straightforward tasks that can be taught through regimented training and checklists. It becomes more about thinking strategically and (dare I say it?) creatively to solve business problems. The potential rewards for thinking strategically and creatively are much, much greater than those for being really good at executing straightforward tasks. Roles that require strategic thinking tend to be roles involving risk taking and risk management, with variable compensation schemes that scale up massively in line with business results. Owner, Partner, CEO, COO, Portfolio Manager, Line Manager, etc.
Hence, the returns to a useless degree are very small relative to other, narrowly focused degrees for several years. If there is a return at all. Until one day you work your way into a role that demands “being able to hypothesize, think conditionally and reason inductively as well as deductively” (such as running a hedge fund). Then those returns grow exponentially.
That, friends, is the power of convexity.
Chris Cole, who I mentioned above, put out a great white paper about convexity as relates to George Lucas’s profits from the Star Wars franchise. Prior to Star Wars, everyone “knew” film merchandising rights were worthless. Lucas cleverly made a deal where he took a much lower directing fee (the “best” way to get paid at the time) in exchange for merchandising rights. We all know how that played out…
Now, when people asked me where I studied finance, I delight in telling them I was a dual major in English and German. “Your CFA charter is what gets you hired,” I tell them. “The English degree is what gets you promoted.”
* Pro Tip: Adding value as an entry level employee is super simple and revolves entirely around making your boss’s life easier by proactively solving problems, while simultaneously being someone your co-workers enjoying working with. That’s literally all there is to it.
(Standard disclaimer applies here. This is not investment advice and it’s not a research report. Don’t blindly follow or believe anything you read on this blog. I could be making all of this up. This is written for informational and entertainment purposes only.)
This is a follow up to my technical analysis post. In it I will discuss how technical indicators informed my decision to trade shares of Embraer (ERJ). As of 01/17/18, I had earned a 66% IRR on my ERJ trade versus what would have been a 35% cash return from buying and holding the shares. I don’t say this to claim I am the world’s greatest investor or trader. I promise you I am not. I am merely writing to illustrate my thought process and why I believe there are real dollar benefits to looking at the world through both fundamental and technical lenses.
I am an investor first and a trader second (if at all). I seek out long-term investments and will only trade them actively if the following conditions are met:
High confidence in my estimate of the business’s intrinsic value. For ERJ, by playing around with the numbers in a discounted cash flow model I estimated the stock was worth $25-$30/share at time of purchase and could be held for the long term based on a competitive moat and full-cycle returns on capital. For me, intrinsic value serves as the anchor for any trading activity. The less confident I am in my valuation, the less likely I am to trade.
The stock is liquid enough to trade actively. I invest in small caps and even micro caps at times. Even my very small orders can move the market for those securities. If my market impact will be significant I would rather not trade as transaction costs (namely the bid-ask spread) will weigh heavily on returns.
High confidence the stock price is misaligned with intrinsic value,and that the misalignment will correct or over-correct in time. Usually this means there is some element of cyclicality in play, but it can also be the product of non-fundamental buying and selling.
ERJ met all of these criteria.
It is worth mentioning I have a clear idea of what I am trying to achieve when I actively trade a stock: I am looking to improve the IRR on the position versus what I would earn as a buy-and-hold, cash return. I don’t typically trade fully in and out of positions. Rather, I dynamically overweight and underweight positions over time. This is my preferred strategy for investing in well-run, cyclical businesses (poorly run cyclical businesses go bankrupt so are dangerous to own without solid stressed/distressed investing chops).
Embraer’s (Abridged) Fundamental Story
ERJ is a Brazilian aerospace manufacturer. Despite being domiciled in Brazil, most of its revenue is earned abroad, specifically from its North American commercial aviation business, which competes with Bombardier. ERJ also manufactures executive jets and military aircraft. The bulk of today’s revenue and operating profit lie in the commercial aviation business.
ERJ is nearing the end of an investment cycle for the next generation of its successful E-Series jets. Major capex programs create business uncertainty, as well as a near-term drag on financial results, and this is what created the opportunity in ERJ shares. I believe my initial estimate of ERJ’s intrinsic value was higher than the market’s because the market had underestimated the probability of success for the E-2 Series program, and was undervaluing the optionality of the defense and executive jet businesses.
As ERJ’s price approached $24 it was also approaching the lower end of my valuation range ($25-$30). However, the fundamentals of the business hadn’t really changed. Nor had the uncertainty inherent in the E-2 Series program been resolved in a significant way. And with 2018 set to be a “transition” year for the business as the first E-190 jets rolled out to customers, it was very possible a temporary setback such as a weak quarter or E-2 development delay could easily send the shares much, much lower. Given the deteriorating risk/reward ratio, this seemed like a great opportunity to trim the position and lock in some gains. $24 coincided with a resistance level for the stock (though honestly I didn’t draw the lines when I placed the trade). Around this time the money flow index was also indicating the stock was overbought.
Again, I was lucky in my timing. I waited patiently for ERJ to fall to its established support level of ~$19.50 and rebuilt the position. The stock traded sideways until late December, when ERJ and Boeing confirmed they were engaged in merger talks. I will not bore you with the details but I felt there was a high probability the talks would end with no deal or at best some kind of joint venture agreement due to a veto right held by the Brazilian government related to ERJ’s defense business. During this time, the prior resistance level of $24 turned into the new support level.
That makes intuitive sense. No chart pattern voodoo is required. Previously, $24/share had been on the high end of fundamental investors’ estimates of the stock’s value. Now that ERJ’s fundamentals had inflected positively, it would make sense for that price to become the low end of a new range.
A couple of weeks after the original announcement a news story broke that Boeing had offered $28/share for a full takeover. $28 happened to lie smack in the middle of my $25-$30 valuation range. This was a critical piece of information because it implied the risk/reward tradeoff had deteriorated significantly. There was probably 1:1 upside to downside in the position at best. I trimmed heavily at a little over $26 and still hold a small position. If a deal gets done I will make a little more money on the takeout. If a deal doesn’t get done I will have an opportunity to rebuild the position at a lower level having gained additional conviction in my fundamental investment thesis.
This case study illustrates my view of active trading: it is a tool for managing the risk/reward tradeoffs embedded in a portfolio. Personally, I want to overweight positions when the risk/reward tradeoff is good and underweight them when it deteriorates. What I do not want to do is make binary decisions (e.g. choosing between “fully invested” and “100% cash”). In my opinion, there is too much randomness and uncertainty in the world and in markets to make blanket, binary calls about position sizing. See the chart below for a stylized example.
A good business will steadily compound its intrinsic value over time (red line). However, there are times when market price overshoots or undershoots intrinsic value (black line). In this way, having the ability to trade at the market price is kind of like owning an option struck at the intrinsic value per share. When a stock is overvalued the ability to trade functions like a put option (you can sell the stock for more than it is really worth). When a stock is undervalued the ability to trade is like a call option (you can buy the stock for less than it is really worth). The cost of the option is your transaction costs (commissions, bid-ask spread, taxes).
Put more simply: active trading allows you to overweight risk when you are getting paid well for taking it and to underweight risk when markets get stingy. However, using this approach, it is absolutely critical to have a high confidence estimate of intrinsic value. Otherwise you risk burning up capital as you chase the price around, getting whipsawed by reversals as you go.
Given how many smart people end up working in investment management, I am always surprised how siloed we can be. You tend to be a fundamental guy, OR a quant gal, OR a technician. Never all three. In my view there ought to be more interdisciplinary investment strategies. One reason there aren’t more of them is that capital allocators have a hard time underwriting strategies that don’t fit neatly into pre-established boxes (a subject for another post).
Personally, I don’t believe our world breaks down into neat little boxes, so I am interested in opportunities to integrate analytical techniques from different disciplines. To that end I have been studying up on how you might marry fundamental and technical analysis in a disciplined way. Typically a vast chasm of prejudice separates the two camps.
Fundamental Analyst:“Intrinsic value is what matters. Market price fluctuations are just noise to be ignored. Analyzing charts is like tossing chicken bones and reading the entrails of livestock to see the future. It is like trading based on ancient superstition.”
Technician:“Market prices are what matter. Market prices reflect supply and demand dynamics, as well as investor psychology. Prices are real and tangible, unlike some academic’s estimate of intrinsic value, which depends on “squishy” estimates of growth rates and discount rates.”
What we have here are two people talking across each other. It is like two people arguing over whether hammers or screwdrivers are “better” tools. In reality hammers and screwdrivers are different tools with different use cases.
I don’t believe technical analysis is particularly useful over long time horizons. There is plenty of evidence that in the long run, stock prices track earnings and dividend growth. I also don’t believe fundamental analysis is particularly useful over short time periods. If you are placing a trade, it is supply and demand that impact your execution, not market price relative to intrinsic value.
Fundamental analysis is going to give you a better idea of whether a business will be a good investment for the next decade. Technical analysis is going to give you a better idea of why today’s price is moving up or down.
Now, I should be up front about the fact that I am not at all interested in chart patterns. I have no interest in scouring candlestick charts for head-and-shoulders or cups-and-handles or van-gogh’s-remaining-ear. As far as I’m concerned that really is like tossing chicken bones or reading animal entrails. I prefer to use simple technical indicators to get a sense of price momentum and investor psychology.
For the time being at least I have focused on three indicators:
Support/Resistance Lines: You can draw a support line across the lows on a chart and a resistance line across the highs. In my view (I certainly don’t claim to be an authority on technical analysis), these lines are rough indications of where valuation sensitive investors have acted to counter a stock’s momentum. The support line forms where valuation sensitive investors step in to buy the stock. The resistance line forms where they sell the stock.
Moving Averages: Moving averages quantify short-term price trends versus long-term price trends and are useful for visualizing momentum. It is generally a bullish sign when a shorter-term moving average crosses above a longer-term moving average and a bearish sign when a shorter-term moving average crosses below a longer-term moving average.
Money Flow Index: The money flow index is an indicator tracking volume-weighted price momentum. It is an oscillator that moves between a range of values. It is useful for understanding whether price momentum is overextended in either direction, and whether it might soon reverse. More on the calculation and interpretation of money flow index here.
I think of the support/resistance lines as marking out the upper and lower bounds for the market’s estimate of a stock’s intrinsic value. Fundamental investors enforce these boundaries by trading contra-momentum (they sell when they believe a stock is overvalued and buy when they believe a stock is undervalued). Inside those boundaries, a stock will tend to ping-pong back and forth until the fundamentals change unexpectedly or fundamental investors significantly alter their expectations. A variation on the latter is when the type of investor dominating a stock’s investor base transitions from value to growth investors or vice versa.
Thus, I would argue, if you are an investor with a high degree of confidence in your estimate of a stock’s intrinsic value, and that estimate differs significantly from market expectations, you may be able to profitably trade around momentum-driven price swings–the goal being to generate higher position-level IRRs than you would earn by simply buying and holding.
In a follow on post I will walk through a live case study from my own portfolio to make this more concrete.
Throughout the book, and in a recent conversation we had, Dalio insists the key to his turnaround was revisiting failure and learning from it. He is enamored of the framework described in Joseph Campbell’s “The Hero with a Thousand Faces.” Campbell’s book examined the evolution of mythological figures, whose failure leads to discovering new wisdom that they use to achieve their goals. Dalio wanted his failures to have the same results, so he created a broad set of rules to do so:
View mistakes as opportunities to improve. He calls this “mistake-based learning.”
Own your errors. Never hide them, but bring them forward to create a learning opportunity. His advice is to “fail well.”
Pain + reflection = progress. The “pain of failure” should lead to reflection, from which your wisdom derives.
Track what you do; keep systemizing what you learn from your mistakes.
There are many more principles, but this gives you an idea of some of the basics.
Dalio does things that most ordinary people don’t do. Set aside for a minute his remarkable track record as an investor and note the following unusual business behavior: He writes down and reflects on everything he does. Then he systemizes it, eventually turning these into algorithms that his firm’s computer systems help backtest against earlier eras. The end result of this is a hybrid of human creativity and machine learning that produces results better than either could separately.
Imagine you are a chicken. Each day a farmer comes and feeds you. After a few months of this you conclude that whenever the farmer visits, he will bring you food. All the empirical evidence supports this conclusion. Then, on an otherwise unremarkable day, instead of feeding you the farmer chops your head off.
That is a gruesome introduction to the problem of induction. (Though I have heard the chicken example many times I believe it originated with Bertrand Russell)
I have been noodling around with scientific reasoning and logic as relates to investment due diligence. What grates on me is that I have come to believe much of what people are looking to get out of a due diligence process cannot actually be achieved. For example, when we due diligence an investment manager the emphasis is on proving the manager is skilled. In reality we cannot prove this. At best we can conclude it is highly probable a manager is skilled. Alternatively, we can prove a manager is not skilled, provided we define a measure of “skill” in advance.
The average due diligence process is grounded in inductive reasoning. We make observations about the investment manager, her strategy and her firm. If the observations are favorable, we generalize that the manager is likely to be skilled and will perform well in the future. Logically this process is flawed.
The Problem of Induction
I first became aware of the problem of induction several years ago via Taleb’s Fooled By Randomness. The issue is we can only use inductive reasoning to conclude something is “likely” or “unlikely.” We cannot use inductive reasoning to prove something is true or false.
The classic example is the black swan. For a long time people believed all swans were white. They did not know all swans were white (they would have to have observed all the swans in existence to prove this). Rather, people inferred an extremely high probability for all swans being white because all the swans observed to date had been white. Then, in 1697, Willem de Vlamingh discovered cygnus atratus in Australia.
In the context of investing we struggle with the naïve extrapolation of past performance into the future. On the basis of past performance I can say, “I believe it is probable this investment manager is highly skilled.” However, I cannot use that data to prove, with certainty, that the manager will continue to outperform in the future. This WSJ article hit piece discussing Morningstar ratings is a practical exploration of the issue (although for the record I believe the WSJ badly misrepresented what Morningstar is trying to achieve with its ratings).
The problem of induction is central to the validity of the scientific method. Science does not prove the truth of hypotheses, theories and laws. It merely verifies they are consistent with empirical results. However, as with inferences about the colors of swans, it only takes one false case to disprove a scientific theory. The philosopher Karl Popper therefore concluded falsifiability is the essential criteria determining whether a theory can be considered scientific.
Among his contributions to philosophy is his claim to have solved the philosophical problem of induction. He states that while there is no way to prove that the sun will rise, it is possible to formulate the theory that every day the sun will rise; if it does not rise on some particular day, the theory will be falsified and will have to be replaced by a different one. Until that day, there is no need to reject the assumption that the theory is true. Nor is it rational according to Popper to make instead the more complex assumption that the sun will rise until a given day, but will stop doing so the day after, or similar statements with additional conditions.
Such a theory would be true with higher probability, because it cannot be attacked so easily: to falsify the first one, it is sufficient to find that the sun has stopped rising; to falsify the second one, one additionally needs the assumption that the given day has not yet been reached. Popper held that it is the least likely, or most easily falsifiable, or simplest theory (attributes which he identified as all the same thing) that explains known facts that one should rationally prefer. His opposition to positivism, which held that it is the theory most likely to be true that one should prefer, here becomes very apparent. It is impossible, Popper argues, to ensure a theory to be true; it is more important that its falsity can be detected as easily as possible.
Applications To Due Diligence & Investment Analysis
This means you cannot “prove” an investment thesis is correct. At best you can gather evidence to build conviction that your investment thesis is “probably” correct. In my experience much due diligence is conducted with an inductive mindset. This leaves due diligence processes vulnerable to confirmation bias.
Should we invert the process?
In other words, you would organize due diligence with the goal of falsifying an investment thesis. If the thesis cannot be falsified, you invest. As a risk management discipline, you then establish a series of easily falsifiable statements constituting “thesis breaks” (e.g. “Company A will average double-digit revenue growth over the next 3 years”). When a thesis break is triggered, the investment is re-evaluated or removed from the portfolio.
At a high level, evaluating an investment opportunity can almost always be boiled down to the following:
People: Management has integrity and is aligned with investors.
Process: Processes are disciplined, repeatable and based on sound economic principles.
Performance: Past performance supports management’s ability to execute.
The due diligence process should not be structured to verify these statements as accurate. It should be structured to prove they are false. In practice to guide your work you would need to establish a whole series of falsifiable statements underneath these broad headings. For example, under People:
Management has never committed or been associated with securities-related offenses.
Management has no prior record of personal or business bankruptcy.
Management has never been convicted of a felony or misdemeanor offense.
Management owns >10% of shares outstanding / maintains significant personal investment.
In my view this is a more straightforward, disciplined and logically sound method of organizing a due diligence process. To a non-practitioner the distinction may seem silly. However, the structure is designed to minimize confirmation bias—a common and dangerous cognitive bias in investment research and portfolio management.
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?
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.
I 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.
Investing is a humbling activity. Mistakes are inevitable. Every Warren Buffett has his Dexter Shoe Company. On top of that, there is the old saying that the market can stay irrational longer than you can remain solvent. It is often difficult (many would argue it is impossible) to distinguish between results generated through skill versus luck.
Because of this it is absolutely essential to focus on process versus outcomes. There are times you will make “mistakes” because of bad luck, despite a solid process. Other times mistakes will result from process gaps or failures. In this way you can distinguish versus “good mistakes” and “bad mistakes.”
Good mistakes happen when you identify the correct investment thesis and you do the analysis but the investment position does not “work” (maybe because of timing). An example of this is the legion of short sellers who had The Big Short trade on in housing and mortgage bonds but ran out of time before the payoff, either because their investors ran out of patience or due to other portfolio issues.
Bad mistakes result from analytical blind spots or insufficient higher order thinking. Bad mistakes are things you should be getting right more often than not. If you dip-buy a bunch of oil companies following an oil price crash, for example, and you are not hedged to the commodity, and oil prices collapse further, and you lose even more money, then that is a bad mistake. You have fallen into a classical value trap.
The very worst mistakes are unforced errors stemming from laziness and/or hubris. Bill Ackman’s Valeant investment was the absolute worst kind of bad mistake. Not only did Ackman get Valeant spectacularly wrong, but he repeatedly deferred to Valeant management and rejected evidence contrary to his investment thesis. The result was a $4bn loss to his investors.
Extrapolating beyond investing, this becomes a pretty robust framework for thinking about daily life.
Bad shit happens in life. A lot of the worst of it is completely out of our control. However, there are plenty of things you can control on a daily basis. The most foundational of these is awareness of your thought patterns and behavior.
A surprising number of people do not choose to live a particular way so much as default to the behaviors that come most naturally to them. To these individuals, every misfortune is bad luck or the cosmos conspiring against them. I guarantee you have met someone who fits this profile. You are likely related to at least one of these people: someone who is perpetually ill, or short on cash, or falling victim to some “random” calamity, pinballing from one misfortune to the next.
If your process for daily living involves no conscious effort at maintaining your health, mental acuity and financial stability, you will always be vulnerable to the random shocks the cosmos throws at you. These shocks are also more likely to have a catastrophic impact.
Process, process, process! Mistakes are inevitable. What is not a foregone conclusion is what, if anything, you will learn from them.