A Mental Model For Politics

Politics is the process by which tribal groups negotiate the distribution of power and resources in a society. A tribal group may identify strongly with a particular philosophy. However, conflating politics with philosophy (“values”) is a muddy way of viewing the underlying drivers of political conflict. It took me a long time (about 15 years) to realize this.

I now realize there are two dimensions to tribal politics:

  • The competitive dimension (the political process itself). This is essentially a strategy game. Because it is a strategy game, effective political operatives (Lee Atwater) needn’t actually concern themselves with “correct” policy or philosophy. Their role is simply to “win”–that is, secure power and resources for the tribal group they serve.
  • The philosophical dimension (the inner lives of tribal group members). This is the process by which tribal group members construct their identities, bond with one another and develop a shared vision of how power and resources should be allocated across society. Tribal group members may or may not develop their identities through a rigorous process of reasoning from first principles. That depends largely on the mental complexity of each individual.

Thus, mental complexity is a key input to this model:

  • Socialized minds simply adopt an identity consistent with their surroundings.
  • Self-authoring minds go a step further and build their own identity.
  • Self-transforming minds go a step even further and work to develop a meta-understanding of tribal group dynamics, in order to integrate that into a more “complete” mental model of how the world works.

To make that more concrete:

  • The socialized mind says: “Everyone in my town and my workplace supports Political Party A. Political Party A is the place to be. I am A.”
  • The self-authoring mind says: “I identify with aspects of Political Party A, but also Political Party B. Furthermore, I believe in X, Y and Z based on my education, life experience and vision for what I want to achieve in life. I combine these inputs to formulate my own identity, views and goals. I am a C.”
  • The self-transforming mind says: “I am a C, but it is possible (in fact likely) that my views as a C are incomplete, inaccurate, or oversimplified. I must leave room to modify these views over time. Over the years I will likely transform from a C to a D, to an E, and so on as I constantly integrate new learnings into my mental model of the world.”

Morgan Housel provides a good example of how a self-transforming mind views tribal politics:

Everyone belongs to a tribe and underestimates how influential that tribe is on their thinking. There is little correlation between climate change denial and scientific literacy. But there is a strong correlation between climate change denial and political affiliation. That’s an extreme example, but everyone has views persuaded by identity over pure analysis. There’s four parts to this:

  • Tribes are everywhere: Countries, states, parties, companies, industries, departments, investment styles, economic philosophies, religions, families, schools, majors, credentials, Twitter communities.
  • People are drawn to tribes because there’s comfort in knowing others understand your background and goals.
  • Tribes reduce the ability to challenge ideas or diversify your views because no one wants to lose support of the tribe.
  • Tribes are as self-interested as people, encouraging ideas and narratives that promote their survival. But they’re exponentially more influential than any single person. So tribes are very effective at promoting views that aren’t analytical or rational, and people loyal to their tribes are very poor at realizing it.

Psychologist Geoffrey Cohen once showed Democratic voters supported Republican proposals when they were attributed to fellow Democrats more than they supported Democratic proposals attributed to Republicans (and the opposite for Republican voters). This kind of stuff happens everywhere, in every field, if you look for it.

It should be obvious by now why most political debates among individuals go nowhere:

  • Most individuals debating politics do not clearly distinguish between the strategy game dimension and the philosophical dimension. This is important. A genuine philosophical debate is a complex and mentally taxing endeavor requiring concentration and a high level of openness. The goal of a philosophical debate is to pursue Truth, not to “win.” What we call political “debate” is almost always strategy and tactics masquerading as philosophy.
  • Socialized minds are simply not capable of engaging in genuine philosophical debate. They do not possess the requisite level of mental complexity (though they certainly can develop it). You will never change a socialized mind with evidence and argument. You need look no further than the comments section of a website for evidence of this.
  • Self-authoring minds are more than capable of engaging in lively philosophical debate. However, they tend to grasp their mental models rather tightly (after all, these are intelligent, highly motivated individuals we are talking about). This can be perceived as either stubborn, obnoxious or even courageous, depending on the observer. As mentioned above, genuine philosophical debate is exhausting. Most people do not want to put the energy into engaging in genuine philosophical debate. Don’t waste your time trying to debate political philosophy with people who aren’t interested in working hard at the process!
  • From a distance, self-transforming minds can seem devoid of logical consistency. This is especially true from the perspective of a socialized mind, for which maintaining an identity consistent with the tribal group is of paramount importance. This is because self-transforming minds are explicitly aware not only of the need to develop mental models, but of the need to adjust them. This can make it difficult for them to relate to the more static worldviews of self-authoring and socialized minds (and vice versa). Others may view a self-transforming mind as an untrustworthy waffler.

To conclude, here is a little checklist for thinking about politics:

  • Be explicit about the dimension you are analyzing:
    • Strategic Dimension?
    • Philosophical Dimension?
  • When analyzing the strategic dimension, do not conflate “values” with strategy and tactics. This will allow you to reason more clearly.
  • If you are analyzing the philosophical dimension, account for mental complexity.
  • If you are involved in a political discussion, try to understand the level of mental complexity the other part(ies) are operating at. This will lead to richer, more fulfilling conversations. On the other end of the spectrum, it will clue you in on when it might make sense to simply disengage.
  • If you want to do deep, truthful, political analysis, you need to integrate both the strategic and philosophical dimensions.

First Principles

I have three great posts I would like to share. All deal with the subject of mental models and reasoning from first principles:

“Speculation In A Truth Chamber” (Philosophical Economics)

First, the idea behind the exercise is not for you to literally walk through it, in full detail, every time you are confronted with a question that you want to think more truthfully about. Rather, the idea is simply for you to use it to get a sense of what it feels like to be genuinely truthful about something, to genuinely try to describe something correctly, as it is, without pretenses or ulterior motivations. If you know what that state of mind feels like, if you are familiar with it, then you will be able to stop and return yourself to it as needed in your trading and investment deliberations and in your everyday life, without having to actually step through the details of the scenario.

Second, the exercise is intended to be used in situations where you actually want to get yourself to think more truthfully about a topic and where you would stand to actually benefit from doing so. Crucially, that situation does not describe all situations in life, or even most situations. There are many situations in life where extreme truthfulness can be counterproductive, creating unnecessary problems both for you and for others.

Third, all that the exercise can tell you is what you believe the most likely answer to a question is, along with your level of confidence in that belief. It cannot tell you whether you are actually correct in having that belief. You might believe that the answer to a question is X when it’s in fact Y; you might have a lot of confidence in your belief when you should only have a little. Your understanding of the subject matter could be mistaken. You could lack the needed familiarity or experience with it to have a reliable opinion. Your judgment could be distorted by cognitive biases. These are always possibilities, and the exercise cannot protect you from them. However, what it can do is make you more careful and humble as a thinker, more open to looking inward and assessing the strength and reliability of your evidence and your reasoning processes, more willing to update your priors in the face of new information–all of which will increase your odds of getting things right.

Thinking From First Principles” (Safal Niveshak)

Practicing first principles thinking is not as easy as explaining it. As Musk said, it’s mentally taxing. Thinking from first principles is devilishly hard to practice.

The first part, i.e., deconstruction, demands asking intelligent questions and having a deep understanding of the fundamental principles from various fields. And that’s why building a latticework of mental models is so important. These mental models are the fundamental principles, the big ideas, from different fields of human knowledge.

The best way to achieve wisdom, said Charlie Munger, “is to learn the big ideas that underlie reality.”

The second step is the recombination of the pieces which were identified in the first step. This is again a skill which can only be developed by deliberate practice. Any idea as an isolated piece of information doesn’t stay in the human brain for long. To be sticky, it needs to be connected with other ideas. A latticework is essentially a grid of ideas connected to each other. These connections are the glue which holds those ideas together.

If the new knowledge doesn’t find any connection or relevance to the old knowledge, it will soon be forgotten. New ideas can’t just be “stored” like files in a cabinet. They have to connect with what’s already there like pieces of a jigsaw puzzle. As you become better in finding connections between seemingly disconnected ideas, your recombination-muscle becomes stronger. Someone with a strong recombination-muscle will find it easy to practice the second step of first principles thinking.

“Playing Socratic Solitaire” (Fundoo Professor)

I am going to play a game based on ideas derived from Socrates and Charlie Munger. We will start with “Socratic Questioning” which is described as

disciplined questioning that can be used to pursue thought in many directions and for many purposes, including: to explore complex ideas, to get to the truth of things, to open up issues and problems, to uncover assumptions, to analyze concepts, to distinguish what we know from what we don’t know, to follow out logical implications of thought, or to control the discussion.

Socratic Questioning relates to “Socratic Method,” which is:

a form of inquiry and debate between individuals with opposing viewpoints based on asking and answering questions to stimulate critical thinking and to illuminate ideas.

Charlie Munger started using these two Socratic devices in a variation he called Socratic Solitaire, because, instead of a dialogue with someone else, his method involves solitary play.

Munger used to display Socratic Solitaire at shareholder meetings of Wesco Corporation. He would start by asking a series of questions. Then he would answer them himself. Back and forth. Question and Answer. He would do this for a while. And he would enthral the audience by displaying the breadth and the depth of his multidisciplinary mind.

I am going to play this game. Or at least, I am going to try. Watch me play.

If you are seriously interested in finance and investing, there is nothing more important to your development than accumulating a robust inventory of mental models. What mental models and reasoning from first principles allow you to do is see through to the true drivers of a situation, where it is often easy to get bogged down in unimportant details.

For example, if you are viewing a business through the lens of discounted cash flow valuation, here are the drivers of intrinsic value:

  • Operating margin
  • Asset turnover
  • Maintenance capex needs
  • Growth capex/reinvestment opportunities
  • Discount rate

Operating margin and asset turnover are quantitative measures reflecting the strength of your competitive advantage and, perhaps more importantly, the source of your competitive advantage.

Maintenance capex tells you how much cash the business needs to spend to keep running.

Growth capex/reinvestment opportunities give you an idea of growth potential over time.

When you combine operating margins and asset turnover (technically NOPAT x Sales/Invested Capital) you get a figure for return on capital. Return on capital is an excellent quantitative proxy for management’s skill allocating capital. Thus, it is also an excellent proxy for quality of management (though it is certainly not a be-all, end-all measure). When you combine return on capital with reinvestment opportunities you get an idea of what sustainable growth in operating income might look like.

There are lots of ways to handle the discount rate. Over time I have come to prefer an implied IRR method, where you simply “solve for” the discount rate that sets your cash flow model equal to the current stock price. You can then compare this to your hurdle rate for new investments.

DCF is one of the most important models in finance because it works with any investment that produces (or is expected to produce) cash flows in the future. At the end of the day, even an exercise as complicated as valuing a mortgage-backed security is just a variation on discounting cash flows.

All great mental models have two defining characteristics:

(1) They are robust. That is, they are applicable to a broad set of opportunities.

(2) They are parsimonious. That is, that is they demonstrate “economy of explanation.”

In my humble opinion, the most important mental models you need to understand in investing are:

  • Time Value of Money/Discounted Cash Flows
  • Capital Structure
  • Expected Value/Probabilistic Thinking
  • Optionality
  • Convexity/Linear Vs. Non-Linear Rates Of Change (e.g. compounding)
  • Investor Psychology

Conceptually that is really what it all boils down to (though the permutations are endless–for instance, a mortgage can be viewed as the combination of discounted cash flows and a call option). Now, you could of course write dozens of volumes on the nuances and applications of each of these models. That is part of what makes them robust. They are adaptable to an almost inconceivable range of circumstances.

This is something I don’t think most candidates in the CFA Program think about (they are too preoccupied with passing the exams!). The curriculum is designed to comprehensively introduce you to the most robust mental models in finance, and then to test your ability to apply those models to specific cases. Level I tests whether you understand the basic “tools” you have available to you; Level II tests more advanced uses of those tools (in exhausting detail, one might add); Level III tests your ability to apply all your tools to “real world” situations.

Maybe some day I will write up how I think about these super important mental models. In the meantime, enjoy the above linked posts!

Warfighting

Warfighting
Source: United States Marine Corps via Verdad Capital Management

I want to share a reading recommendation with you all: WarfightingThis is not a manual but rather a philosophy for decision making under uncertainty.

h/t to Verdad Capital for the link in this excellent post (actually a newsletter piece), which opines:

I also learned at Quantico that complex linear planning fails in warfare because the profession involves “the shock of two hostile bodies in collision, not the action of a living power upon an inanimate mass,” as Clausewitz reminds us. In the military-industrial exuberance of the post–Cold War decades, we invested heavily in exotic platforms such as drones, cyber capabilities, and billion-dollar strike fighters. Our low-tech but moderately street-savvy opponents in this millennium decided to fight us precisely where and how these assets were near useless. With few exceptions, the most useful equipment for this environment came from the Vietnam era and the most enduring lessons from the time of the Spartans.

Financial markets, made up of people competing for an edge, are precisely the type of environment designed to bedevil static planning. The financial environment is one where valuation multiples persistently mean revert, where income statement growth is not persistent or predictable, where GDP growth does not correlate with equity returns, where market share and moats do not lead to competitive advantage or price return.

So what are we to do in such an environment where outcomes are determined not so much by the very little we can foresee but by what might unexpectedly happen relative to the expectations embedded in the price at which the security is bought? How would we affirmatively strategize and operate differently as investors if all of our most cherished and marketed crystal balls for forecasting price returns are shattered? How should we operate amidst the chaos without operating chaotically?

In Afghanistan, I found that the most consequential assets on our side were the most robust and persistent throughout the history of warfare. An asymmetric but intelligent adversary had refused to engage us on any terms but those where war devolved to a competition of wills, where discipline, resolve, adaptability, and habituated combat-arms tactics dictated the victor, not drones or robot pack mules. Our own persistent behavioral biases were our worst enemy.

This is precisely why I am so interested in things like tail hedging. And lest you be tempted to write this off as interdisciplinary silliness, consider for a moment that life itself can be viewed as an extended exercise in decision making under uncertainty.

UPDATE: After reading and reflecting on this, it seems clear to me it is essentially providing a mental model for what war is and how it is conducted.

At first glance, war seems a simple clash of interests. On closer examination, it reveals its complexity and takes shape as one of the most demanding and trying of human endeavors. War is an extreme test of will. Friction, uncertainty, fluidity, disorder, and danger are its essential features. War displays broad patterns that can be represented as probabilities, yet it remains fundamentally unpredictable. Each episode is the unique product of myriad moral, mental, and physical forces.

Individual causes and their effects can rarely be isolated. Minor actions and random incidents can have disproportionately large—even decisive—effects. While dependent on the laws of science and the intuition and creativity of art, war takes its fundamental character from the dynamic of human interaction.

Also this bit:

War is an extension of both policy and politics with the addition of military force. Policy and politics are related but not synonymous, and it is important to understand war in both contexts. Politics refers to the distribution of power through dynamic interaction, both cooperative and competitive, while policy refers to the conscious objectives established within the political process. The policy aims that are the motive for any group in war should also be the foremost determinants of its conduct. The single most important thought to understand about our theory is that war must serve policy.

The Wisdom Tree

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.

Anyway, today I encountered the blog Safal Niveshak. which contains a beautiful illustration of The Wisdom Tree

wisdom-tree-safal-niveshak

… as well as another on on the spectrum of reading material.

reading-spectrum-safal-niveshak

Needless to say, I highly recommend following the blog.

Want To Be A Billionaire? Earn A “Useless” Degree

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.

From Sarah Churchwell in the FT:

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.

Chris Cole, who runs one of the more quantitative and conceptually challenging investment strategies I have encountered, studied freaking film. In fact, to steal a recurring concept from his research, and to build a bridge to Churchwell’s argument in the FT, I argue that studying a useless subject such as film, philosophy or English has a highly convex return profile.

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 wasta from 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…

Star_Wars_Convexity
Source: Artemis Capital Management

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.

Case Study: Integrating Fundamental & Technical Analysis To Trade Embraer

(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.)

ERJ_Chart_Annotated
Annotated ERJ chart with technical indicators. Sources: Morningstar Direct & demonetized account records

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:

  1. 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.
  2. 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.
  3. 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.

 

Trading ERJ

I was very lucky with my entry point. I always say I would rather be lucky than good. Money earned from luck spends the same as money earned from skill. And anyway no one looking at your returns can tell the difference.

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.

 

Takeaways

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.

intrinsic_value_vs_market_price
Source: Unknown (found via Google Image Search)

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.

Technically…

18117_JBLU_Technicals
Source: Morningstar Direct

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.