THE FOURTH QUADRANT: A MAP OF THE LIMITS OF STATISTICS - By Nassim Nicholas Taleb

Statistical and applied probabilistic knowledge is the core of knowledge; statistics is what tells you if something is true, false, or merely anecdotal; it is the "logic of science"; it is the instrument of risk-taking; it is the applied tools of epistemology; you can't be a modern intellectual and not think probabilistically—but... let's not be suckers. The problem is much more complicated than it seems to the casual, mechanistic user who picked it up in graduate school. Statistics can fool you. In fact it is fooling your government right now. It can even bankrupt the system (let's face it: use of probabilistic methods for the estimation of risks did just blow up the banking system).
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The current subprime crisis has been doing wonders for the reception of any ideas about probability-driven claims in science, particularly in social science, economics, and "econometrics" (quantitative economics). Clearly, with current International Monetary Fund estimates of the costs of the 2007-2008 subprime crisis, the banking system seems to have lost more on risk taking (from the failures of quantitative risk management) than every penny banks ever earned taking risks. But it was easy to see from the past that the pilot did not have the qualifications to fly the plane and was using the wrong navigation tools: The same happened in 1983 with money center banks losing cumulatively every penny ever made, and in 1991-1992 when the Savings and Loans industry became history.
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It appears that financial institutions earn money on transactions (say fees on your mother-in-law's checking account) and lose everything taking risks they don't understand. I want this to stop, and stop now—the current patching by the banking establishment worldwide is akin to using the same doctor to cure the patient when the doctor has a track record of systematically killing them. And this is not limited to banking—I generalize to an entire class of random variables that do not have the structure we think they have, in which we can be suckers.
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And we are beyond suckers: not only, for socio-economic and other nonlinear, complicated variables, are we are riding in a bus driven by a blindfolded driver, but we refuse to acknowledge it in spite of the evidence, which to me is a pathological problem with academia. After 1998, when a "Nobel-crowned" collection of people (and the crème de la crème of the financial economics establishment) blew up Long Term Capital Management, a hedge fund, because the "scientific" methods they used misestimated the role of the rare event, such methodologies and such claims on understanding risks of rare events should have been discredited. Yet the Fed helped their bailout and exposure to rare events (and model error) patently increased exponentially (as we can see from banks' swelling portfolios of derivatives that we do not understand).

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What Is Fundamentally Different About Real Life

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My anger with "empirical" claims in risk management does not come from research. It comes from spending twenty tense (but entertaining) years taking risky decisions in the real world managing portfolios of complex derivatives, with payoffs that depend on higher order statistical properties —and you quickly realize that a certain class of relationships that "look good" in research papers almost never replicate in real life (in spite of the papers making some claims with a "p" close to infallible). But that is not the main problem with research.

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For us the world is vastly simpler in some sense than the academy, vastly more complicated in another. So the central lesson from decision-making (as opposed to working with data on a computer or bickering about logical constructions) is the following: it is the exposure (or payoff) that creates the complexity —and the opportunities and dangers— not so much the knowledge ( i.e., statistical distribution, model representation, etc.). In some situations, you can be extremely wrong and be fine, in others you can be slightly wrong and explode. If you are leveraged, errors blow you up; if you are not, you can enjoy life.
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So knowledge (i.e., if some statement is "true" or "false") matters little, very little in many situations. In the real world, there are very few situations where what you do and your belief if some statement is true or false naively map into each other. Some decisions require vastly more caution than others—or highly more drastic confidence intervals. For instance you do not "need evidence" that the water is poisonous to not drink from it. You do not need "evidence" that a gun is loaded to avoid playing Russian roulette, or evidence that a thief [is] on the lookout to lock your door. You need evidence of safety—not evidence of lack of safety— a central asymmetry that affects us with rare events. This asymmetry in skepticism makes it easy to draw a map of danger spots.

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Bottom Line: The Map

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Things are made simple by the following. There are two distinct types of decisions, and two distinct classes of randomness.

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Decisions: The first type of decisions is simple, "binary", i.e. you just care if something is true or false. Very true or very false does not matter. Someone is either pregnant or not pregnant. A statement is "true" or "false" with some confidence interval. (I call these M0 as, more technically, they depend on the zeroth moment, namely just on probability of events, and not their magnitude —you just care about "raw" probability). A biological experiment in the laboratory or a bet with a friend about the outcome of a soccer game belong to this category.

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The second type of decisions is more complex. You do not just care of the frequency—but of the impact as well, or, even more complex, some function of the impact. So there is another layer of uncertainty of impact. (I call these M1+, as they depend on higher moments of the distribution). When you invest you do not care how many times you make or lose, you care about the expectation: how many times you make or lose times the amount made or lost.
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Probability structures: There are two classes of probability domains—very distinct qualitatively and quantitatively. The first, thin-tailed: Mediocristan", the second, thick tailed Extremistan. Before I get into the details, take the literary distinction as follows:

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In Mediocristan, exceptions occur but don't carry large consequences. Add the heaviest person on the planet to a sample of 1000. The total weight would barely change. In Extremistan, exceptions can be everything (they will eventually, in time, represent everything). Add Bill Gates to your sample: the wealth will jump by a factor of >100,000. So, in Mediocristan, large deviations occur but they are not consequential—unlike Extremistan.
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Mediocristan corresponds to "random walk" style randomness that you tend to find in regular textbooks (and in popular books on randomness). Extremistan corresponds to a "random jump" one. The first kind I can call "Gaussian-Poisson", the second "fractal" or Mandelbrotian (after the works of the great Benoit Mandelbrot linking it to the geometry of nature). But note here an epistemological question: there is a category of "I don't know" that I also bundle in Extremistan for the sake of decision making—simply because I don't know much about the probabilistic structure or the role of large events.

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The Map
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Now let's see where the traps are:

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First Quadrant: Simple binary decisions, in Mediocristan: Statistics does wonders. These situations are, unfortunately, more common in academia, laboratories, and games than real life—what I call the "ludic fallacy". In other words, these are the situations in casinos, games, dice, and we tend to study them because we are successful in modeling them.
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Second Quadrant: Simple decisions, in Extremistan: some well known problem studied in the literature. Except of course that there are not many simple decisions in Extremistan.

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Third Quadrant: Complex decisions in Mediocristan: Statistical methods work surprisingly well.

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Fourth Quadrant: Complex decisions in Extremistan: Welcome to the Black Swan domain. Here is where your limits are. Do not base your decisions on statistically based claims. Or, alternatively, try to move your exposure type to make it third-quadrant style ("clipping tails").

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Related post: A focus on the exceptions that prove the rule

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Related article: Shattering the Bell Curve

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Related books:

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The Black Swan: The Impact of the Highly Improbable

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Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets

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The Misbehavior of Markets: A Fractal View of Risk, Ruin & Reward

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BFBV Newsletter (No. 2) - Professor Sanjay Bakshi

Legendary Investor Richard Feynman

As far as I know, Richard Feynman never bought a stock in his life. If he did, he never talked about it or about his “investment acumen.” But he should have...

Feynman was not only a great physicist, he was also a great teacher.
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Does it not bother you that one of the greatest men of science that the world has seen is quite happy to accept uncertainty (“I have approximate answers, and possible beliefs, and different degrees of certainty about different things, but I’m not absolutely sure of anything, and there are many things I don’t know anything about.”), while you are studying how to use the DCF model to value businesses? That’s a model which requires you to predict cash flows more than thirty years out requiring “degrees of certainty” that Feynman would have laughed at.
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Does it not bother you that a man of science can dare to say “I don’t know” while investment analysts almost never say that?

Feynman once said, “The first principle is that you must not fool yourself — and you are the easiest person to fool.”

How true! How we analysts fool ourselves so often! How often we just believe what we are told by companies and their self-interested agents and convert that nonsense into very nice-looking reports with plenty of pie charts and tables which make the whole thing look so believable!

In one of his famous lectures, Feynman was talking about the scientific method of inquiry. He said, “Looking back at the worst times, it always seems that they were times in which there were people who believed with absolute faith and absolute dogmatism in something. And they were so serious in this matter that they insisted that the rest of the world agree with them. And then they would do things that were directly inconsistent with their own beliefs in order to maintain that what they said was true.”
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The quote just above relates to cognitive dissonance. In the previous post, I listed Professor Bakshi’s advice from one of his lectures: "Learn to promptly resolve cognitive dissonance and you will acquire one of the greatest mental habits."

The Wikipedia definition:
“In psychology, cognitive dissonance is an uncomfortable feeling or stress caused by holding two contradictory ideas simultaneously. The theory of cognitive dissonance proposes that people have a fundamental cognitive drive to reduce this dissonance by modifying an existing belief, or rejecting one of the contradictory ideas.
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Often one of the ideas is a fundamental element of ego, like "I am a good person" or "I made the right decision." This can result in rationalization when a person is presented with evidence of a bad choice, or in other cases. Prevention of cognitive dissonance may also contribute to confirmation bias or denial of discomforting evidence.”
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For a discussion on negotiating cognitive dissonance, see: Cognitive Dissonance

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Related previous post: The Pleasure of finding Things out

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"Cargo Cult Science"

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Feynman Online

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Books:

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Surely You're Joking, Mr. Feynman! (Adventures of a Curious Character)

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What Do You Care What Other People Think?: Further Adventures of a Curious Character

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Genius: The Life and Science of Richard Feynman

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The Meaning of It All: Thoughts of a Citizen-Scientist

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Perfectly Reasonable Deviations From The Beaten Track: The Letters Of Richard P. Feynman

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The Pleasure of Finding Things Out: The Best Short Works of Richard P. Feynman

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Six Easy Pieces: Essentials of Physics Explained by Its Most Brilliant Teacher

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Six Not-So-Easy Pieces: Einstein's Relativity, Symmetry, and Space-Time

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The Character of Physical Law

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Josh Waitzkin @ Google

I was a little slow getting around to watching this, but it was worth the wait. Josh Waitzkin also shared an interesting definition of wisdom from Robert Thurman: "Wisdom is the tolerance of cognitive dissonance." Related to that quote is some advice from Professor Sanjay Bakshi's 5th Lecture: "Learn to promptly resolve cognitive dissonance and you will acquire one of the greatest mental habits."

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"Chess champion Josh Waitzkin visits Google's Mountain View, CA headquarters to discuss his book "The Art of Learning: A Journey in the Pursuit of Excellence." This event took place on April 10, 2008, as part of the Authors@Google series.

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Josh Waitzkin is an 8-time National Chess Champion, 13-time Tai Chi Chuan Push Hands National Champion, and Two-time Tai Chi Chuan Push Hands World Champion. In 1993 Paramount Pictures released the film Searching for Bobby Fischer, based on the highly acclaimed book of the same title written by Fred Waitzkin, documenting Josh's journey to winning his first National Championship."

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Authors@Google
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Related books:
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The Art of Learning: An Inner Journey to Optimal Performance
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Mindset: The New Psychology of Success
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Zen and the Art of Motorcycle Maintenance: An Inquiry into Values
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The Brain That Changes Itself: Stories of Personal Triumph from the Frontiers of Brain Science
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BFBV Newsletter - Professor Sanjay Bakshi

If you want to improve your persuasive skills you have to learn how to exploit other people’s availability bias. You already know that people overweigh information which is extra-vivid, recent, and experienced personally than vicariously.

First impressions count. So do last impressions. So when you make a pitch to anyone, frame it in such a way that people to whom you are pitching remember your first lines and your last lines. Often the lines in the middle don’t really matter. What people remember is how they perceived you when they first met you and when they last met you.

Frame your requests as vividly as you can. Frame them around something personal to the requestee. And frame them around something that happened recently and which is in the forefront of the requestee’s mind.
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Imagine that you have a request that you want to make to your boss. You have an idea which will, in your view, immensely benefit your company. Now there are two ways in which you can present this information to your boss. First, you can tell her how your company stands to gain if your proposal is implemented. The second way is to reverse it by framing the request in loss terms. This time, you tell your boss how your company stands to lose if it did not implement your lovely proposal.

Framing it in loss terms will significantly improve your chances of succeeding in your efforts to convince your boss, unless there are other forces at work.

That bit about “other forces at work” is somewhat important because I don’t want 113 of you in my class to approach your favorite potential employers at placement time with suggestions on how they stand to lose by not hiring you! If 113 of you frame it that way, well then there might be some very undesirable unintended consequences of your behavior!

Let me move on to contrast effect. What has that to do with framing and its influence on your persuasion skills? Lots. When you frame your request using the technique of reciprocal concessions described so well by Robert Cialdini in his book, and discussed in the class, you increase your chances of compliance. Ask for the moon, expecting to be refused and then ask for what you wanted to get in the first place.
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Another example in framing is to do with what Mr. Munger calls “reason respecting tendency.”

People like reasons when they are asked to comply with a request. I call this the “power of because.”
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The lesson is obvious for you future framers. Always give a reason for your request because it will increase its probability of compliance. When you have a good reason then provide it. When you don’t, then just invent one!”

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Related Books:

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Influence: The Psychology of Persuasion

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Yes!: 50 Scientifically Proven Ways to Be Persuasive

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Choices, Values, and Frames

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Poor Charlie's Almanack

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Seeking Wisdom

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My Investment Philosophy

Update: My philosophy has evolved since this post was first written. One day, I may include my investing checklist on this page, but it is still evolving as well. Until then, these 2 quotes best summarize the process I try to follow.

“If only one word is to be used to describe what Baupost does, that word should be: 'Mispricing'. We look for mispricing due to over-reaction.” -Seth Klarman

“In my opinion, there are two key concepts that investors must master: value and cycles. For each asset you’re considering, you must have a strongly held view of its intrinsic value. When its price is below that value, it’s generally a buy. When its price is higher, it’s a sell. In a nutshell, that’s value investing.

But values aren’t fixed; they move in response to changes in the economic environment. Thus, cyclical considerations influence an asset’s current value. Value depends on earnings, for example, and earnings are shaped by the economic cycle and the price being charged for liquidity.

Further, security prices are greatly affected by investor behavior; thus we can be aided in investing safely by understanding where we stand in terms of the market cycle. What’s going on in terms of investor psychology, and how does it tell us to act in the short run? We want to buy when prices seem attractive. But if investors are giddy and optimism is rampant, we have to consider whether a better buying opportunity mightn’t come along later.” –Howard Marks

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Buffett Warned Us in 2003, Few Listened - by Todd N Kenyon

Warren Buffet foresaw the current financial disaster more than five years ago. I pulled out his 2002 Chairman’s Letter, wherein he addresses derivatives and their potential to scuttle the entire financial system. Here are some key passages:

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“Charlie and I are of one mind in how we feel about derivatives and the trading activities that go with them: We view them as time bombs, both for the parties that deal in them and the economic system.”

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“In recent years, some huge-scale frauds and near-frauds have been facilitated by derivatives trades. In the energy and electric utility sectors, for example, companies used derivatives and trading activities to report great “earnings” – until the roof fell in when they actually tried to convert the derivatives-related receivables on their balance sheets into cash. “Mark-to-market” then turned out to be truly “mark-to-myth.””

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“Another problem about derivatives is that they can exacerbate trouble that a corporation has run into for completely unrelated reasons. This pile-on effect occurs because many derivatives contracts require that a company suffering a credit downgrade immediately supply collateral to counterparties. Imagine, then, that a company is downgraded because of general adversity and that its derivatives instantly kick in with their requirement, imposing an unexpected and enormous demand for cash collateral on the company. The need to meet this demand can then throw the company into a liquidity crisis that may, in some cases, trigger still more downgrades. It all becomes a spiral that can lead to a corporate meltdown.”

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“Charlie and I believe, however, that the macro picture is dangerous and getting more so. Largeamounts of risk, particularly credit risk, have become concentrated in the hands of relatively few derivatives dealers, who in addition trade extensively with one other. The troubles of one could quickly infect the others. On top of that, these dealers are owed huge amounts by non-dealer counterparties. Some of these counterparties, as I’ve mentioned, are linked in ways that could cause them to contemporaneously run into a problem because of a single event (such as the implosion of the telecom industry or the precipitous decline in the value of merchant power projects). Linkage, when it suddenly surfaces, can trigger serious systemic problems.”

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“In our view, however, derivatives are financial weapons of mass destruction, carrying dangers that, while now latent, are potentially lethal.”

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There’s much more, available on the Berkshire website. Warren and Charlie have made some additional comments at the 2007 annual meeting. Munger:

“As sure as God made little green apples this will lead to big trouble in due time. This will lead to a result we have been expecting for some time.”

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On the math models used by Wall Street: “They’re all crazy.” “Very smart people do very dumb things” and that just because people “have high IQs” does not prevent them from creating financial models that are “at least 50% twaddle.”

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On Berkshire’s underwriting standards: “We only write fire insurance on concrete bridges that are covered by water.”

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Buffett: “Not too many years ahead you will get disruption. Predicting when is something we can’t do…(It will reward) those with cash and guts.”

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Munger: “Will Rogers said, ‘Learn not to pee on an electrified fence without actually doing it.”

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Alas, heeding that last one would’ve saved Wall Street many times.

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The financial system is built upon leverage. Its very existence depends on lack of correlation - the requirement that bad things don’t all happen at once: that depositors don’t make a run on the bank, insurance liabilities aren’t all claimed at once, derivative contracts don’t all go the same way at the same time, mortgages don’t all default at once. However, as Buffett says and I also heard Bill Ackman paraphrase, when the stuff hits the fan, everything correlates. That’s where we are now.

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If you took on too much risk, levered up too much, didn’t prepare for the day when everything correlates… well then adios. See ya. Buh-bye.

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Buffett and Munger were not so much prescient as good students of market history and innately conservative. They’d seen it all before in one form or another. I return to Galbraith from his book “A Short History of Financial Euphoria”:

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“The rule is that financial operations do not lend themselves to innovation. What is recurrently so described and celebrated is, without exception, a small variation on an established design, one that owes it distinctive character to the aforementioned brevity of the financial memory. The world of finance hails the invention of the wheel over and over again, often in a slightly more unstable version. All financial innovation involves, in one form or another, the creation of debt secured in greater or lesser adequacy by real assets.”

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Obviously Bear, Lehman, Freddie, Fannie, AIG, WaMu, Countrywide, on and on, went with the “lesser adequacy” model.

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Related previous post: Excerpt from Buffett's 2002 Annual Letter

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Professor Sanjay Bakshi's Lectures

Professor Sanjay Bakshi has posted some of his lectures on his blog, Fundoo Professor:
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Lecture 01
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Lecture 02
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Lecture 03
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Lecture 04

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Lecture 05

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Lecture 06

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Lecture 07

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The Perils of the “Mindless Imitation of One’s Peers”

Mr. Buffett made some comments when speaking to a group from Notre Dame in 1991 that are relevant to what's going on today:

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The last thing I want to show you, before we get onto your questions, is an ad that was run June 16, 1969, for 1,000,000 shares of American Motors. This is a reproduction from the Wall Street Journal of that day. Now does anybody notice anything unusual about that ad?

[Guesses from audience.]

Everybody in that ad has disappeared. There are 37 investment bankers that sold that issue, plus American Motors, and they are all gone. Maybe that’s why they call them tombstone ads. Now the average business of the New York Stock exchange in 1969 was 11 million shares. Average volume now is fifteen times as large. Now here’s an industry whose volume has grown 15 to 1 in 20 years. Marvelous growth in the financial world. And here are 37 out of 37, and those are some of the biggest names on Wall Street, and some of them had been around the longest, and 37 out of 37 have disappeared. And that’s why I say you ought to think about [the long-term durability of a business?] because these people obviously didn’t.

These were run by people with high IQs, by people that worked ungodly hard. They were people that had an intense interest in success. They worked long hours. They all thought they were going to be leaders on Wall Street at some point, and they all went around, incidentally, giving advice to other companies about how to run their business. That’s sort of interesting.

You go to Wall Street today, and there’s some company the guy hadn’t heard of two weeks before and he’s trying to sell you. He will lay out this computer run of the next 10 years, yet he doesn’t have the faintest idea of what his own business is going to earn next week!

Here are a group of 37. And the question is, how can you get a result like that? That is not a result that you get by chance. How can people who are bright, who work hard, who have their own money in the business – these are not a bunch of absentee owners – how can they get such a bad result? And I suggest that’s a good thing to think about before you get a job and go out into the world.

I would say that if you had to pick one thing that did it more than anything else, it’s the mindless imitation of one’s peers that produced this result. Whatever the other guy did, the other 36 were like a bunch of lemmings in terms of following. That’s what’s gotten all the big banks in trouble for the past 15 years. Every time somebody big does something dumb, other people can hardly wait to copy it. If you do nothing else when you get out of here, do things only when they make sense to you. You ought to be able to write “I am going to work for General Motors because ... “I am buying 100 shares of Coca Coals stock because...” And if you can’t write an intelligent answer to those questions, don’t do it.

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Wintergreen Fund: Semi-Annual Report

The market has not discriminated between high-quality and low-quality companies; virtually every stock has declined. Generally, markets reward solid, stable companies, but this year even the best companies have suffered. The movement from easy credit to little or no available credit has restricted normal business operations and slowed down speculation. We believe companies with the following three characteristics are great long-term destinations for investor capital, even though the short-term quotations are less than favorable: solid businesses that generate cash; businesses with pricing power; and businesses with rational management who create value for their shareholders.

A favorite story of mine as a child was “The Little Engine That Could” by Watty Piper. In this story, a long train needed help to get over a large mountain. Various railroad engines that had the capacity to move the train refused to help. They said the job was too big and difficult for them, and the mountain was too steep. The engines that were designed to haul heavy freight would not attempt to move the huge train. Eventually a small engine that didn’t appear to have the necessary get-up-and-go was asked for assistance and that small engine agreed to try to help the large train. Using all of its power and repeating ‘I think I can, I think I can’, the small engine got the freight train up to the top of the mountain. As the train went down the tracks on the far side of the mountain to deliver toys and treats to the children who had been waiting, the little engine repeated the phrase, ‘I thought I could, I thought I could’.

In this global market that looks too big for anyone or anything to bring it back to a more stable environment, I think that solid analysis of companies and careful accumulation of underpriced stocks has the potential to yield great rewards. Like the little engine that put its head down and worked at its assignment, the pursuit of fundamental research coupled with an appreciation of the consistency of human behavior should identify the securities that I believe will survive and thrive in the future. Now is the time when some of these companies are on sale. Although no one knows precisely when, it is inevitable that these wild bargain prices will at some point in time come to a close. When that happens, and with the benefit of 20-20 hindsight, many investors will wish they had accumulated a bigger stake in these bargain companies.

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The Art of Short Selling

A friend (thanks Andrew) recommended an excellent book about short selling and fundamental analysis called The Art of Short Selling by Kathryn Staley. I also recommend the book and a video of a talk she gave at the Notre Dame Center for Accounting Research and Education:
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Book ----- Video

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Smart Taxes: An Open Invitation to Join the Pigou Club – By N. Gregory Mankiw

As an economics educator, I have always been fascinated by topics about which there is a large gap between the beliefs of economists and those of the general public. For example, economists are generally supportive of free trade among nations, while the public is more skeptical. Economists oppose rent control, while much of the public supports the policy.

In these and other cases where economists and mere muggles don’t see eye-to-eye, you shouldn’t be surprised to hear that I am quick to side with my fellow economists. I like to think that this reaction is more than mere professional solidarity but is, instead, a symptom of my commitment to rational thought. Unlike most people, who spend their time thinking about their children, local sports team, or favorite sitcom, economists have devoted much of their lives to thinking about such things as international trade and rent control. That fact may make us boring at cocktail parties, but it does have some offsetting benefits. It is not a stretch to believe that more thought about an issue leads to more reliable conclusions. As a result, I feel comfortable with conclusion that, regarding these issues, economists are right and the general public is just ill informed.

My topic for today is a policy about which there is a particularly large gap between economists and the public: Pigovian taxation. In particular, I want to talk about taxes on energy-related products, such as gasoline taxes. Not long ago, the economist Steve Levitt, coauthor of the best-seller Freakonomics, wrote on his blog, “For a long time I have felt the price of gasoline in the United States was way too low. Pretty much all economists believe this.” Levitt then went on to argue for higher taxes on gasoline. At about the same time, Speaker of the House Nancy Pelosi had precisely the opposite perspective. She announced “a series of hearings to address rising gas prices—focusing on the causes, the burdens they put on American families and businesses, and solutions.”

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Related site: Greg Mankiw's Blog

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CERN fires up new atom smasher to near Big Bang

It has been called an Alice in Wonderland investigation into the makeup of the universe - or dangerous tampering with nature that could spell doomsday.

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Whatever the case, the most powerful atom-smasher ever built comes online Wednesday, eagerly anticipated by scientists worldwide who have awaited this moment for two decades.
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The multibillion-dollar Large Hadron Collider will explore the tiniest particles and come ever closer to re-enacting the big bang, the theory that a colossal explosion created the universe.

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The machine at CERN, the European Organization for Nuclear Research, promises scientists a closer look at the makeup of matter, filling in gaps in knowledge or possibly reshaping theories.

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YouTube video mentioned in article: Large Hadron Rap

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Follow-up (9/10/2008) after initial start: Into the wild blue yonder

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Related previous post: Known and unknown unknowns

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Ruane, Cunniff & Goldfarb Investor Day Transcript

Ruane, Cunniff & Goldfarb Investor Day

May 16, 2008 – St. Regis Hotel, New York City

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Buffett's Best Man

IN CONTRAST TO THE showman-like Buffett, Munger shuns the spotlight. But he draws a smaller, more fanatical cult that seeks inspiration from his intellectual omnivorousness. "There are few people who consider acquiring knowledge their life's study -- he's an exemplar," says Chris Davis, of the $65 billion Davis Funds. "Buffett will understand something on a micro level," adds hedge fund star Mohnish Pabrai, "but Munger will understand how it fits into the world looking a decade out." Pabrai suggests that if you gave an IQ test to their respective fan clubs, Munger's would beat Buffett's "by quite a few points." Whoever would win, with the market choppy and both partners getting up in years, investing acolytes were eager to catch Munger on one of his rare public appearances -- and we were glad to catch him for an even rarer interview.

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When he spoke with SmartMoney, Munger was relatively humble; he brushed aside the idea that he's the man behind Buffett, allowing only that "my utility was not zero." That utility may be more important than ever if Munger's gloomy outlook turns out to be correct. "Even with the market down, every investment class, on average, is liberally priced," Munger says, and the prospects for good returns are "modest" at best. His formula for success in a tough market (or any market) flies in the face of conventional wisdom: "Load up" by making big bets on the handful of businesses that could be winners. "People say the whole secret of investing is diversification," Munger told Berkshire investors earlier this year, but that idea is "ass-backwards."

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When picking winners out of the herd, of course, it helps to have Buffett- or Munger-caliber acumen. Munger insists that involves little more than common sense -- the kind that comes from educating yourself broadly across multiple disciplines. Unlike other investors, Munger says, he and Buffett are careful not to overestimate what they know: "It's a disaster if you don't know the edge of your competency." They work hard at avoiding investing "asininities" and "possess a vast ability to dis-learn" when their assumptions prove false. And they keep enough cash on hand to act quickly -- since good investments don't swim by that often, Munger explains, "you have to be the man standing by a river with a spear." How to recognize those opportunities? That's where omnivorousness comes in. "Learn your gaps, and fill them," he says. "If you get three textbooks on a subject and skim them, it's a good start. That's what I do."
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Sadly enough, that's not what most investors do, so it's little wonder that a certain world-weariness is one of Munger's hallmarks in his fifth decade at Buffett's side. "If Aristotle were alive today, he'd be a grumpy old man," Munger sighs, explaining that the Greek philosopher would be seeing the same mistakes made over and over. "Maybe that's some of the problem with me."

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To view Mr. Munger's Caltech appearance, see this post: Video: A Conversation with Charlie Munger

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The best way to learn more about Mr. Munger and the 'Latticework of Mental Models Approach' to life and learning: Poor Charlie's Almanack

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