The Eventual Consequences of Risk Seeking or Risk Blind Behavior

On 23 January, I had the privilege of addressing a group of investors at Mumbai Stock Exchange. The event was organised by Moneylife. Here is an edited transcript of my talk.

The Eventual Consequences of Risk Seeking or Risk Blind Behavior

This is going to be a personal talk based on whatever little experience I have accumulated over 21 years of practicing value investing in India. I think many of you will disagree with what I am going to say. I don’t have a problem with that. Think of what I am going to tell you as merely strong hunches of mine which I have stumbled upon over the course of 21 years.  Following these hunches has worked well for me.

These hunches came to me slowly over a long period of painful, direct experiences as well as vicarious experiences acquired through much reading and reflection upon the causes behind the unfortunate losses faced by many investors.

On 27 October 2011, two stuntmen were shooting a scene for a movie called The Expendables 2 starring Sylvester Stallone, Arnold Schwarzenegger and Bruce Willis. One of the scenes involved throwing a live grenade in water to create an explosion.

This is what happened:

Kun Liu died in this horrible accident. He was 26 years old.

You will recall this man from TV — Steve Irwin, the crocodile hunter.

On 4 September 2006, while filming a documentary in Batt Reef, Queensland, Australia, Steve approached an 8 ft wide stingray from behind.

Much to his surprise and shock – this had never happened before — the fish reacted as if a shark was attacking, striking him several hundred times in his body with its tail spine in a few seconds. Steve initially believed he only had a punctured lung but the tail spine had pierced his heart. He bled out and died.

He was 44 years old.

Stuntmen and documentary makers aren’t the only ones who display risk seeking or risk blind behavior. Here are a few more examples.

And here some examples that many of you will relate to.

What are the eventual consequences of risk seeking behavior? That is, if you persist with behavior that’s risky, then what will happen to you?

In my view, the answer to that important question is provided by one of the principles of probability. And it’s a principle which  all of you studied in high school. That principle states that probability of one occurrence of a rare event, if you increase the number of trials tends to become 1. That is, if you keep jumping out of planes with parachutes which fail to open just 1% of the time, you will eventually get killed.

Two Questions

Now, let me pose two questions which I will then try to answer.

1. Why do people indulge in such behavior?
2. What are the “functional equivalents” of such behavior in the world of business and investing?

Well, anyone who has studied Charlie Munger knows that such lollapalooza outcomes are not caused by a single force. Rather, they occur when multiple forces working in the same direction, combine. So, let’s use this approach to answer the first question: Why do people indulge in such behavior? In fact, let’s focus on just one situation. Why do people jump red lights and die or kill someone else? This is a very interesting question.

Part of the answer is that people who jump red lights are over-confident. While they may know the risk of sudden death exists, they believe that risk doesn’t apply to them. After all, over-confidence is a natural human tendency. Ninety percent of drivers think that they are better than average drivers and better than average lovers. Can they all be right? Of course not. But let me assure you that I am an above average driver and lover and no you are not allowed to check this from my wife who is sitting in the audience.

But such a lollapalooza outcome cannot be explained by just over-confidence. There has to be more to it for sure. But what? Let’s think about that. What else can contribute to such an outcome? Well, clearly there is social proof — the biological tendency to copy similar others. There’s also loss aversion or what Charlie called deprival super reaction. The fellow who sees a light turn from green to yellow is experiencing the psychology of a near miss as in  “I am going to miss this chance, no no no that’s not acceptable, if I accelerate, I will go through.”

We know that when people face losses — in this case lost opportunity to go through a green light — they become risk seeking. It’s a like a flip switch. It happens in a flash of a second. When the switch flips, the driver is no longer rational. He is incapable of thinking that he is approaching a dangerous situation and that he must slow down. His mind is already make up. And it’s a decision that could kill him or someone else.

Now, let’s answer the second question: What are the “functional equivalents” of such behavior in the world of business and investing?

Well one that comes to mind immediately is open-outcry auctions. What happens in such situations? Well, the normaloutcome is that people go crazy as this scene from Only Fools and Horses shows.

We know this happens. But if we stop and think about the causal factors we will find more than one because such lollapalooza outcomes don’t happen because of just one thing. And an open-outcry auction situation is a very interesting social setting where multiple models from psychology like authority (where the auctioneer is a symbol of authority who not only certifies the authenticity of the object being auctioned, he also announces an initial big price which serves as an “anchor”, social proof (caused by observing other bidders bid up the price), the incentives of the auctioneer (the higher the price at which the object sold, the more the money made by the auctioneer), reciprocation/retaliation (resulting in competitive bidding), envy , low contrast effect (every new bid is a small increment over a previous bid), commitment bias (every bid and escalation of the bid is a public commitment), overconfidence, and deprival super reaction (caused by the countdown to end of auction) combine to turn this social setting into something like a death trap.

And what are the consequences of such behaviour in the world of business? Let’s take a look at just one example (there are many others) — that of Tata Steel’s disastrous  acquisition of Corus in 2006 in an competitive open-outcry auction.

Just before Tata Steel’s first bid on 20 October, 2006, the market cap of the company was about Rs 26,000 cr. Tata steel. On 31 January, 2007 Tata Steel won it’s bid for Corus after offering 608 pence per share for the target company, valuing it for about $11 billion. Eight years later, Tata Steel’s market cap stands at Rs 23,000 cr. What an amazing case of value destruction! And  Hindalco’s acquisition of Novelis was not different.

Knowing what happens to people who get into open-outcry, auction-like situations, psychologically astute people like Buffett and Munger have a no-fault rule when they get invited to auction situations.

The rule is: Don’t Go.

Now let me tell you something about no-fault rules. The idea behind having a no-fault rule to prevent horrendous losses from risk-seeking behavior like the one described above, even though following such a rule may result in a few lost opportunities. The cost of missing those opportunities is reckoned to be minuscule as compared to likely losses from indulging in risk-seeking behavior. This is an important philosophical point to keep in mind.

The Value of Vicarious Experience

If you spend enough time reading about human folly across multiple disciplines, you will get plenty of vicarious experience in the spirit of the man — Charlie Munger — who said that you don’t have to pee on an electric fence to learn not to do it.

Indeed, part of the idea behind vicarious learning is to watch people pee on electric fences from a distance and yet feel their pain and keep telling oneself — Oh boy, I never want to end up like them.

Unfortunately, despite all the reading that I’ve done, I didn’t get all the experience cheaply and vicariously. I peed on many electric fences and have plenty of scars on my body. But 21 years is a fairly long period of time to help me come up with those hunches I mentioned earlier. Those hunches helped me formulate some of my own no-fault rules and today I will share three of them with you.

No Fault Rule # 1: Stay Away from Leverage

Borrowing Money to Finance Purchase and Holding of Shares

It took three ruined holidays for me to learn this. It’s kind of spooky. Every time my family and I went on a holiday to a place whose name ended with “LI,” leverage ruined it completely.

First time this happened was when we went to ManaLI in May 2004.

The market dropped 27%.

In May 2006, my wife and I went to KasauLI and this happened.

After peeing twice on those two electric fences, my family and I decided to go to BaLI. In Jan 2008.

And each of those holidays were ruined because we would get margin calls and we would have to sell stocks and suffer huge losses in order to meet our obligations.

My wife loves traveling and she jokingly said let’s go to ChiLI to see if this “LI” thing really works.

I said let’s not take debt to finance the purchase of shares anymore. The stress — both financial and psychological — was just too much.

And that was that. After that there have been other periods of market declines but no margin calls and no stress! So this became a no-fault rule.

Derivatives

Another no-fault rule relating to leverage was to do with using derivatives.

Derivatives are a zero sum game. That’s well known. But I have a hunch that the overwhelming majority of those who deal in derivatives lose money. I would speculate that the proportion of participants who do well in derivatives is very small.

I have friends who trade in derivates and have done well but they are very few. The vast majority of investors I know have, on balance, lost money in derivatives. Some of them have blown up millions of dollars.

The other thing that bothers me about derivatives is that they do to your brain as this cartoon in Where are the Customers’ Yachts show.

If you trade derivatives, my hunch is that you’ll lose focus on what really works — long-term buying and holding of quality businesses at reasonable prices. Derivatives have the capacity to turn you from an investor into a gambler.

My own experience with derivatives was just horrible. When I shorted a stock it would go up more than 50% which would totally ruin my sleep apart from the financial pain. I would be forced to close my position. In two such situations, the stocks I shorted ultimately declined by more than 90% from their peak levels but I couldn’t benefit from that. I only proved Keynes right when he wisely said: Markets can stay irrational longer than you can stay solvent.

And the stress was just too much. The pain of putting up MTM margins every time the market moved against you caused many sleepless nights.

Warren Buffett has called derivatives financial weapons of mass destruction. In my view, they are also weapons of mental destruction.

In one special situation operation I was was bought a convertible security issued by Network 18 and simultaneously shorted the underlying common stock to lock in a return. I had a very close shave on that operation which required several roll overs of hedges. Soon after the hedge was unwound, NSE removed the security from F&O trading. Had this happened earlier, my so called hedged operation would have fallen flat on its face. My experience with derivatives proved Robert Rubin right when he said: Condoms aren’t completely safe. My friend was wearing one but was hit by a bus.

The story of LTCM blowup demonstrates what happens when you combine complexity, leverage and risk seeking behavior.

These two gentlemen (along with Fisher Black) received Nobel prize for creating the famous Black-Scholes option pricing.

Their hedge fund called Long Term Capital Management (LTCM) did exceptionally well for a while and then, over just a course of a few days, it imploded.

Warren Buffett has a fantastic lecture on this topic in which he analyses this lollapalooza outcome. I think everyone should watch that video a few times a year to see what happens to people who indulge in risk-seeking behavior and combine it with extreme leverage and complexity.

Buffett uses a wonderful metaphor of a gun with a million chambers in it with only one chamber which has a bullet in it. He then states that if someone offered to pay him any sum of money to put the gun on his temple and pull the trigger once, he will decline. No matter how high the offer, he would decline.

This is a very important principle of probability that was ignored by the founders of LTCM and also ignored by many others I described earlier. The principle is that if there is a remote loss scenario with a financial and/or reputational outcome that’s unacceptable, then no matter how low the probability of that outcome, actions that can produce that outcome must be rejected. Or, as Warren Buffett puts it

A small chance of distress or disgrace cannot, in our view, be offset by a large chance of extra returns.^[1]

This is the same point I made earlier which is that many people don’t think deeply enough about the consequences of remote loss scenarios. Instead, they only focus on weighted average expected returns which look so good because the weights of the remote loss scenario are so small in the expected value table.

And so, most of the time they make money in trades that have horrible remote loss scenarios but excellent expected returns.

Ultimately, however, the odds will catch up and it’s only a matter  time before they blow up. It’s not a question of if they will blow up. Rather, it’s a question of when. If you keep jumping out of planes with parachutes which fail to open just 1% of the time, or while pointing at your temple, keep pulling the trigger of a million-chamber gun which has just one bullet in one of the chambers, you will eventually get killed.

So, in a sense, some situations, by their very nature are what I like to calls as “Accidents waiting to happen.” And that’s exactly what happened at LTCM ultimately. In my view, those guys at LTCM were not any different from these guys at the guys who blew themselves on the boat.

Highly Leveraged Companies

So, that was my first example on leverage. But there are more. Over time, I also started appreciating the wisdom of avoiding excessive leverage in capital structures of businesses I was analysing for investment.

To arrive that this conclusion, I was deeply influenced by the writings of Charlie Munger, Warren Buffett, and Marty Whitman.

Here’s what Mr. Munger once said:

Obviously, if you leverage enough, you can get higher returns on equity, but you often have are chance of disaster. I think we are more disaster-resistant than most other places. As a friend of mine once said, “I don’t want to go back to go. I’ve been to go.”^[2]

Here’s what Mr. Buffett has written on the subject:

Huge debt, we are told, causes operating managers to focus their efforts as never before, much as a dagger mounted on the steering wheel of a car could be expected to make its driver proceed with intensified care. We’ll acknowledge that such an attention-getter would produce a very alert driver. But another certain consequence would be a deadly — and unnecessary — accident if the car hit even the tiniest pothole or sliver of ice. The roads of business are riddled with potholes; a plan that requires dodging them all is a plan for disaster.^[3]

Whenever I see a leveraged structure, I think about “potholes” — time overruns, cost overruns and far too optimistic revenue projections — and the consequences of encountering them on the fixed charges coverage ratio^[4].

And all too often, when I factor in “potholes,” projected fixed charges coverage ratio would become 1 or even less. And the consequences of that happening are almost always devastating for the value of the common stock.

As fixed charges cover moves from a higher number towards 1, the value of equity shrinks dramatically. If pre-tax owner earnings can barely cover rent on other people’s money and property, then there’s nothing left over for the poor common stockholder at the end of the queue.

Take, for example, the colossal wealth destruction in five of these large, highly leveraged Indian businesses which I happen to observe from a safe distance

The stockholders of these companies, in a sense, have gone back to go.

Many years ago I read this by Mary Whitman

For a common stock to be an attractive investment, the company ought to have a strong financial position that is measured not so much by the presence of assets as by the absence of significant encumbrances, whether a part of a balance sheet, disclosed in financial statement footnotes, or an element that is not disclosed at all in any part of financial statements.^[5]

That, and other similar advice I got from superinvestors like Buffett and Munger helped as well my own experience of observing the horrible averaged out outcome for stockholders of highly-leveraged companies, made me realize just how little margin of safety exists in such businesses.

Finally, I feel that leverage also has a moral dimension. For two reasons. One, in every single episode of financial excess, you’ll find leverage. It’s always there in some form or other. In his wonderful analysis of many episodes of past financial excess, John Galbraith writes:

All financial innovation involves, in one form or another, the creation of debt secured in greater or lesser adequacy by real assets. This was true in one of the earliest seeming marvels: when banks discovered that they could print bank notes and issue them to borrowers in a volume in excess of the hard-money deposits in the banks’ strong rooms. The depositors could be counted upon, it was believed or hoped, not to come all at once for their money. There was no seeming limit to the debt that could thus be leveraged on a given volume of hard cash. A wonderful thing. The limit became apparent, however, when some alarming news, perhaps of the extent of the leverage itself, caused too many of the original depositors to want their money at the same time. All subsequent financial innovation has involved similar debt creation leveraged against more limited assets with only modifications in the earlier design. All crises have involved debt that, in one fashion or another, has become dangerously out of scale in relation to the underlying means of payment.^[6]

Every time I read that passage in Galbraith’s book, I think  about how right he was on that one.

The second reason why I feel leverage has a moral dimension is that it attracts crooked people.

If a casino opens in an otherwise nice neighbourhood, soon you’ll start seeing a lot of sleazy, crooked characters in that neighbourhood and pretty soon crime rates will soar. In a sense, the same logic applies to leverage. If you were a sleazy, crooked businessman, why would you have an all-equity capital structure? You would want stupid, gullible people to buy your bonds or stupid, gullible, or corrupted banks to lend you money.

Now, I don’t want to take names here but I think you are getting my point.

And the reverse is also true. By and large, you will find a lot more morality in debt-free companies. Now, of course this doesn’t mean that all leveraged companies are immoral. Far from it. What it does mean is that a disproportionate number of businesses whose equity market caps gets destroyed have leverage on the crime scene.

I don’t think it’s a coincidence that the market cap of all the PSU banks now is less than that of just one HDFC Bank. This has a lot to do with the morality of those places…

No Fault Rule # 2: Seek Protection from Nature

Nature is pretty brutal place to be in. As Garrett Hardin writes, Capitalism involves

bringing potentially useful but diffusely distributed materials together, concentrated. For several thousand years human beings have been concentrating various metals from their ores (iron, copper, and so on), thus making possible the manufacture of tools and machines, which greatly increase our ability to wrest a living from nature. We never create atoms of copper or iron, but we certainly concentrate them and rearrange them into more useful configurations.^[7]

One of my key learnings as a value investor is that the closer you get to nature, the more you’re playing with fire. By “nature” I mean anything you get out of the ground — metals, minerals, oil whatever. These economics of things is so damn hard to predict accurately and these things experience just too much price volatility. Take a look at this chart which depicts the long-term movement of the Bloomberg Commodity Index which tracks the prices of 20 commodities including Aluminium, Crude Oil, Copper, Corn, Cotton, Gold, Natural Gas, Nickel, Silver, Sugar and Zinc.

That index is now back to where it was in 1991. Crude oil alone has gone from less than $10 a barrel to $140 a barrel and now at less than $30 a barrel. When it was at $140, people were talking “peak oil” and now when it’s at below $30, the world is awash in oil.

In terms of probability, the problem with such industries is to do with ranges of outcome. They become very wide. Indeed, they become so wide, that even trying to value businesses in such industries should count as speculative. But when people have elaborate excel models and minds which tend to overweight recent experiences, they end up extrapolating near term trends. If prices are going up, they assume they will stay up and when they are going down they assume that they will keep going down even more. Charlie Munger calls this type of blind extrapolation not just slightly stupid, but massively stupid.

Investors should recognise that some things, by their very nature, are just too hard to predict. The value of ONGC at at $30 per barrel oil price is going to be vastly different from its value at $140 a barrel oil price. But people who are hell bent on trying to value ONCG (or Cairn or any oil company for that matter) try to deal with the massive uncertainty by using scenario analysis. They assign subjective probabilities to pessimistic scenario like a $30 per barrel, optimistic ones at say $140 per barrel and many other scenarios in between and then compute weighted average value. That’s the functional equivalent that 6 ft. tall statistician who drowned in water which was, on average only 4 ft. deep. He forgot that range of depth was between 1 ft and 7 ft.

In my course at MDI, I give two exercises to students to check their confidence levels. I ask them to privately write down their estimate of the weight of an empty 747 jumbo jet in tons and the diameter of the moon in kilometres. I ask them to specify ranges with 90% confidence. That is, I ask them to state that “I am at least 90% sure that weight of the jumbo jet is between x tons and y tons and the diameter of the moon is between x kilometres snd y kilometres” where they have to specify x and y.

About 90% of them get it wrong despite the fact that they were free to chose very wide ranges that would guarantee that the correct answer lied within their specified range. For example, if a student is unsure about the weight of the plane (correct answer is 177 tons), she might say “I am 90% sure that it’s somewhere between 5 tons and 10,000 tons). Well, most students end up giving very narrow ranges and the correct answer falls outside their ranges more than 90% of the time.

The purpose of these exercises is to demonstrate that when it comes to thinking about natural resources, most people’s worldview is just too narrow and the world will tend to surprise them. When oil is at $30, its hard to visualize that it could go to $140 or $200 or $500. But who the hell can knowwhere it will go? Similarly, when it was at $140, it was hard to visualise that it could drop to $30 or $10 or $5.

The consequences of being wrong with one’s predictions in situations where the ranges of outcome are likely to be very wide — and that’s certainly the case when one is dealing with natural resources — can be devastating.

The problem is further compounded by financial leverage. Many of the businesses in such industries take on enormous amounts of debt for expansion during good times. Unfortunately, such times never last. And when the tide turns, many participants are found to be swimming naked.

The big lesson for investors here is that when you combine high volatility inherently present in a business model with financial leverage, you get extreme volatility in equity valuations. During good times these businesses may have reasonably strong balance sheets, and excellent profit margins. In bad times, they end up with huge debt and evaporation of profits. This swing from riches to rags is also reflected in their equity market values as the chart below shows.

Ben Graham was quite aware of the futility of trying to make predictions about the value of equity in such businesses. He wrote:

The analyst must recognize that the value of a particular kind of data varies greatly with the type of enterprise which is being studied. The five- year record of gross or net earnings of a railroad or a large chain-store enterprise may afford, if not a conclusive, at least a reasonably sound basis for measuring the safety of the senior issues and the attractiveness of the common shares. But the same statistics supplied by one of the smaller oil- producing companies may well prove more deceptive than useful, since they are chiefly the resultant of two factors, viz., price received and production, both of which are likely to be radically different in the future than in the past.^[8]

After observing many investors experience permanent capital loss because of overconfident bets on businesses that were too close to nature, I became quite averse to investing in such businesses. I looked for protection.

Now, we don’t have time to discuss all kinds of protections from ravages of nature, we can talk about just one of them. It’s a very simple idea called “buy commodities, sell brands.”

Many businesses which consume commodities to make things which are sold as branded products, have adequate protection from nature. Because of the brand and the market dominance, they enjoy pricing power which acts as a solid protective device. When input prices rise, these businesses can raise their product prices without fear of loss of unit volume or market share. And when input prices fall, they can choose to retain some or even all of the cost reduction. This ability to protect themselves from the extreme volatility of product prices allow such businesses to display far less volatility in profit margins as compared to those of their suppliers who do not possess any such protection from nature. And this reduced volatility narrows the ranges of possibilities. This makes these businesses models far more amenable to investment analysis instead of speculative guessing.

As I was preparing for this talk, I saw this tweet from The Economist and rolled my eyes.

Apparently, there’s is a global shortage of Lithium Carbonate at present and prices are soaring. No doubt the existing producers will be experiencing bumper profits. Eventually, however, those very profits have within them the seeds of future profit destruction because of strong incentives to increase production. There is little protection for Lithium Carbonate manufactures from the inherent volatility in their business model.

Why play with fire?

No Fault Rule # 3: Be Wary of Promotions

Example 1: Prediction Newsletter Scam

Imagine that one day you receive a newsletter in which you’re offered a free stock market prediction. Reliance Industries would rise by more than 10% during the course of the next month. One month later, you notice that Reliance was up by 12%. A coincidence, you think.

The next edition of the newsletter predicts that Reliance will fall by at least 10% over the next month. And lo and behold, when the month ends it turns out that Reliance was down by 11%! Still, two correct predictions don’t mean much and you wait for the next edition.

The next prediction turns out to be right. And the next one. And the next one. And the next one. This is too much, you think!

Now, let’s just step back a bit and look at what was really happening. The fellow who sent the newsletter had no clue about what will happen to Reliance. But he knew that at least one the scenarios will play out. Either the stock will rise by more than 10%, fall by more than 10% or stay range bound between -10% and +10%. And so he decides to publishes three different newsletters with three different predictions and send each of them to three different set of people. A total of 364,500 people are selected which are then divided into three equal groups of 121,500 people each. Each group gets one prediction.

Clearly, one third of the people who receive the newsletter will get the correct prediction and the publisher would know who those people are. For the next newsletter, he identifies those people and further divides them into three equal groups of 40,500 people each and sends three different predictions again. And you can see where this is headed and I summarise this in the table below.

By the end of a month after the 6^th newsletter is issued, there would be 500 people who would have received six correct predictions in a row and who, by now, would be hugely impressed by the “predictive abilities” of the publisher.

The fellow will now send  a letter to each of these people offering to send them his next prediction at a subscription price of Rs 300,000. Clearly, many people will fall for this scam and will not only part with Rs 300,000 for something useless, they will end up acting on next useless prediction and may lose even more money. Indeed, many of such gullible people will be so overconfident of making money that they might make leveraged bets that would pay off handsomely if the next prediction turned out to be true.

The funny thing about this example is that people who pay for these predictions never stop to ask themselves as to why is the fellow selling his predictions? I mean, if he is so good about his predictions, should he not use them to make money for himself? The truth of the matter is that people wan’t to be told by someone how the future will unfold, even if there is no value in the predictions. As Peter Lynch wrote:

There are 60,000 economists in the U.S., many of them employed full-time trying to forecast recessions and interest rates, and if they could do it successfully twice in a row, they’d all be millionaires by now…as far as I know, most of them are still gainfully employed, which ought to tell us something.^[9]

When I talk about this prediction newsletter scam example in my talks, many people in the audience laugh at the gullibility of the people who will fall for this scam. But, if you look carefully, you’ll find the functional equivalents of this scam. Take, for example, mutual fund advertising. How often does one get to see the performance track record of allproducts of a mutual fund company in an ad? Not very often. Most of the time, you’ll only get to see ads highlighting the performance of the best performing product. That’s the one they will promote while keeping silent about the others. They will make and promote products which are sellable at a given time instead of selling what’s right. That’s exactly the allegation made by John Bogle when he writes

Wall Street has become a place where salesmanship trumps stewardship; where marketing trumps management; and where the mutual fund industry has changed from a business in which “we sell what we make” to one in which “we make what will sell.”^[10]

A big part of the reason behind all the salesmanship is, of course, the incentives. As Charlie Munger once said

Any time you create large differences in commissions where the guy gets X% for selling A, which is some mundane thing and 10 times X for selling B, which is something toxic you know what’s going to happen.^[11]

In financial markets, if you end up buying products that are being promoted to you, you are very likely end up buying something toxic.

Investors must realise is that there is all kinds of promotional behavior in financial markets and prediction newsletter story was just one example. I will provide a few more examples but it’s very important to be able to sense when something is being pushed towards you and then you must follow Newton’s third law and push back.

Example 2: Boiler Room Operation

Here is a wonderful example from the movie “Boiler Room” which illustrates not just the power of incentives but also a confluence of models from psychology to produce a lollapalooza outcome. Watch this video.

In a typical boiler room operation the operators get a huge commission (sometimes as high as 40%) from dubious companies to promote their toxic shares to the gullible public.

In this extraordinary scene in the movie, a junior broker initially cold calls the doc and offers him “one idea and one idea only” (scarcity principle), and when he finds that his victim is a doc, he stars talking about a dubious pharma company which is in the “third stage of FDA approval.” Those words are clearly designed to invoke greed in the victim because he knows that doctors know what potential blockbuster drugs can do to the profitability of drug companies.

Once the doc bites on the bait, the junior broker tells him that he will ask a “senior broker” (authority bias) to tell him more about the prospective “investment.” Vin Diesel, who plays the role of the senior broker then steps in and uses multiple weapons of influence on the doc. He starts by telling that the stock he wants him to buy is experiencing “very high volume” (social proof). He tells him that if doesn’t buy the stock through him, he will see his colleagues get rich (envy). He pretends to open the door of his office so the sound of brokers screaming can be heard by the doc (social proof). He tells him to decide quick because he has a million other calls to make to “other doctors who are already in the know” (social proof, scarcity, envy). When the doc agrees to buy he offers to sell him no more than “2,000 shares” (anchoring effect, foot in the door technique, commitment bias). And of course he does all this because of the super power of incentives as reflected in the high commission he will make on this and subsequent sales he makes to the doc. The commissions are so high that he will do anything, no matter how unethical, to entrap the poor doctor.

The scene from Boiler Room shows just how difficult it is for customers to resist buying something that’s been heavilypromoted to them.

Example 3: IPOs

Another big example of heavily promoted merchandise in financial markets is that of new issues or Initial Public Offerings (IPO’s).

I started my career in investing in IPO’s in mid 1990’s. Now, I never buy into them. So, this is another no-fault rule that I follow. There are three reasons why I follow this no-fault rule. One, as Graham wrote:

New issues have special salesmanship behind them, which calls therefore for a special degree of sales resistance.^[12]

Two, the structure of the IPO market makes it hard to find bargains. As Buffett writes:

An intelligent investor in common stocks will do better in the secondary market than he will do buying new issues. The reason has to do with the way prices are set in each instance. The secondary market, which is periodically ruled by mass folly, is constantly setting a “clearing” price. No matter how foolish that price may be, it’s what counts for the holder of a stock or bond who needs or wishes to sell, of whom there are always going to be a few at any moment. In many instances, shares worth x in business value have sold in the market for 1/2x or less.

The new-issue market, on the other hand, is ruled by controlling stockholders and corporations, who can usually select the timing of offerings or, if the market looks unfavorable, can avoid an offering altogether. Understandably, these sellers are not going to offer any bargains, either by way of a public offering or in a negotiated transaction: It’s rare you’ll find x for 1/2x here. Indeed, in the case of common-stock offerings, selling shareholders are often motivated to unload only when they feel the market is overpaying.^[13]

Three, even if I love the business and the valuations of the business which is about to go public, I have no way of evaluating the track record of how management treats minority shareholders and my investment process requires that I have comfort on that front before I make an investment. If the business is truly outstanding then there will be multiple opportunities to own it over the many years after it’s gone public. So, I never rush into buying into heavily promoted IPO’s no matter how desirable the prospects. As for the behavior of investment bankers promoting IPO’s, I think not much has changed about their behavior since this was written in an article about them in 1894.

Firms of old standing vied one with the other in foisting unremarkable rubbish on the guileless investor.

Example 4: Over Promotional Companies with Little Substance

There used to be a company called Temptation Foods which had little substance but was crazily promotional. In fact it overdid the promotional bit so much that it’s annual reports are collectibles. Here are a few pages from them.

Even the Auditors Report was not spared!

The funny thing about this company is that it was able to sell its shares at lofty valuations to institutional investors. The company is now defunct and the stock is no longer traded but I like to cite its example to show just how important it is for investors to shield themselves from over-promotional managements of businesses with little substance.

To be sure, it’s the job of promoters to promote their businesses. When they do that, we should recognize that they are simply playing their part. As investors, our part, on the other hand, is to not get influenced by representations made by over-promotional managements.

Conclusion

In conclusion, I would like to list the three “no fault” rules I talked about:

1. No Fault Rule # 1: Stay Away from Leverage
2. No Fault Rule # 2: Seek Protection from Nature
3. No Fault Rule # 3: Be Wary of Promotions

Following these rules has helped me avoid horrendous and permanent capital losses. I hope that you’ll find them useful.

Thank you!

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[1] Warren Buffett’s Letter to Shareholders of Berkshire Hathaway Inc. in its 1999 Annual Report.

[2] Charlie Munger speaking at 2001 AGM of Wesco Financial.

[3] Warren Buffett’s Letter to Shareholders of Berkshire Hathaway Inc. in its 1990 Annual Report.

[4] Estimated pre-tax owner earnings before fixed charges/fixed charges, where fixed charges comprise of interest on debt and rent on other people’s assets.

[5] Martin Whitman in The Aggressive Conservative Investor

[6] John Kenneth Galbraith in A Short History of Financial Euphoria.

[7] Garrett Hardin in Living Within Limits: Ecology, Economics, and Population Taboos

[8] Graham and Dodd’s Security Analysis.

[9] Peter Lynch in One Up on Wall Street

[10] John Bogle in Foreword in Stewardship: Lessons Learned from the Lost Culture of Wall Street by John Taft

[11] Charlie Munger speaking at 2001 AGM of Wesco Financial

[12] Benjamin Graham in The Intelligent Investor

[13] Warren Buffett’s Letter to Shareholders of Berkshire Hathaway Inc. in its 1992 Annual Report.