The Psychology of Human

Misjudgment- V

Bias # 8Overoptimism

&Overconfidence

Myron Scholes Robert merton

Members of LTCM's board of directors included Myron S. Scholes and Robert C. Merton, who shared the 1997 Nobel Memorial Prize in Economic Sciences for a "new method to determine the value of derivatives".

2 Nobel laureates who blew upWhy do smart people do dumb things?

Beginning of 1998:

Equity: $4.72 billionDebt: $124.5 billion

total assets: $129 billion

debt to equity: more than 25 to 1

The company used complex mathematical models to take advantage of fixed income arbitrage deals (termed convergence trades) with government bonds. Differences in the government bonds' present value are minimal, so any difference in price should be eliminated by arbitrage. Price differences between a 30 year treasury bond and a 29 and three quarter year old treasury bond should be minimal—both will see a fixed payment roughly 30 years in the future. However, small discrepancies arose between the two bonds because of a difference in liquidity. By a series of financial transactions, essentially amounting to buying the cheaper 'off-the-run' bond (the 29 and three quarter year old bond) and shorting the more expensive, but more liquid, 'on-the-run' bond (the 30 year bond just issued by the Treasury), it would be possible to make a profit as the difference in the value of the bonds narrowed when a new bond was issued.

Low spread.Leverage required to make money.

The value of $1000 invested in the hedge fund Long-Term Capital Management, of $1,000 invested in the Dow Jones Industrial Average, and of $1,000 invested monthly in U.S. Treasuries at constant maturity.

http://en.wikipedia.org/wiki/Long-Term_Capital_Management

Buffett video on LTCM

Leverage is where overconfidence can be found

What models is he talking about?Overconfidence, Physics Envy

Recall his gun metaphor. Why do metaphors matter so much?

Would you like to jump out of this plane with this parachute which opens 99% of

the time?

Modern Risk Management Practices Advocate that you should jump

Modern risk management practices (e.g. VAR) assume that we live in a world best described by a bell curve where outliers are extremely rare, and that resulted in management practices that were far more risky than was previously imagined

VAR: A statistical tool that roughly says most of the you won’t lose more than x in a day or year. But its’ silent on what happens rest of the time. Also, its findings are based on history.

“Even in 1965, perhaps we could have

judged there to be a 99%

probability that higher leverage would lead to nothing but

good.

Buffett in 1989 letter.

“We wouldn't have liked those 99:1 odds - and never will. A small chance of distress or disgrace cannot, in our view, be offset by a large chance of extra returns.”

Role of derivatives: financial instruments of mass destruction.examples: Wockhardt, textile companies in south india, hedge fund blow ups, banks blow up.

Role of max loss exposure in risk management.

“It’s never happened before, so it can’t ever happen.”

The market can stay Irrational

longer than you can stay

solvent - keynes

It’s not physics.

Victor Niederhoffer

http://en.wikipedia.org/wiki/Victor_Niederhoffer

The Mouse with one hole is quickly cornered

"The mouse with one hole is quickly cornered." That is key. There are certain decisions you make in life that are irreversible, that lead you into a path you can't get out of, and unless you have more than one escape clause, the adversary can gang up on you and destroy you. What else? I didn't have a proper foundation. I was not sufficiently private in my activities. I was playing poker with men named Doc. I must've made a hundred errors on that one, but those are five or six that come to mind. - Niederhoffer

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

why I don’t like banks

Or highly leveraged companies.

Except when they are in bankruptcy

Wait Until You Shake Your Head

It’s easy to lend money and fool yourself into believing that you’ll make a good rate of return. It reminds me of a story about two men in a sword fight. One of them takes a big swipe on the other one’s neck whereupon the other one says “You missed me.”

The swiper says, “Wait until you shake your head.”

Story as told by Charlie Munger.

The Opera House was formally completed in 1973, having cost $102 million. The original cost estimate in 1957 was $7 million. The original completion date set by the government was 26 January 1963. Thus, the project was completed ten years late and over-budget by more than fourteen times.

http://en.wikipedia.org/wiki/Sydney_Opera_House

Be wary of grandiose projections made by managements

When the city of Montreal was selected to host the 1976 Summer Olympics, the mayor announced that the entire Olympiad would cost $120 million and that the track and field events would take place in a stadium with a first-of-its-kind retractable roof. The games went off as planned, of course, but the stadium did not get its roof until 1989. And oh yes: the roof ended up costing $120 million, or almost as much as was budgeted for the entire Olympics.

The Company was formed on 13 August 1986 with the objective of financing, building and operating a tunnel between England and France. The Company let a contract for the construction of the tunnel to TransManche Link. The tunnel cost around £9.5bn to build, about double its original estimate of £4.7bn. The tunnel, which was financed partly from investment by shareholders and partly from £8bn of debt, was officially opened on 6 May 1994. In its first year of operation the Company lost £925m because of disappointing revenues from passengers and freight together with heavy interest charges on its £8bn of debt.

The noida toll bridge

Look what overconfidence does.Look for leverage if you want to look for overconfidence.The interest on the debt was more than the gross revenues!

How can you finance a project with debt where you have to make money from largely unpredictable consumer behavior? This was the first toll bridge...

Remember Feynman who remarked how difficult physics would have been if particles had feelings?

Recall that this is a “man on a roll” we found in a previous class.

Hw just won a lot of money in the casino. What will do next? Walk out with his winnings? Hell no! He will go back to the table and play more thinking “This is the just the beginning of my streak.” His behavior will ultimately ruin him.

Last time when we talked of him, he was high on dopamine. Dopamine produced over-confidence.

We saw these people earlier - happy people who just became rich - in the movie Dot Con

Normal human tendency90% of

drivers think that they are better than

average drivers

Why do people buy

lottery tickets?

Why do people buy lottery tickets? Or indulge in day trading?

74% of investors in a survey said that their own funds will consistently outperform the market Reality? Only a handful actually do

Only 37% of managers believe that mergers create value for buyers. But when it came to their own mergers and acquisitions, 58% said their deals will create value

Give high and low estimates for the average weight of an empty Boeing 747 aircraft. Choose numbers far enough apart to be 90 percent certain that the true answer lies somewhere in between. Ans: 177 tons

If you are 90% sure, then you should be comfortable betting $9 against prospect of willing just $1 that the real is within your chosen range.

Give high and low estimates for the diameter of the earth’s moon in kms. Again, choose numbers far enough apart to be 90 percent certain that the true answer lies somewhere in between. Ans: 3,476 kms

If you are 90% sure, then you should be comfortable betting $9 against prospect of willing just $1 that the real is within your chosen range.

Because most people who attempt to answer these questions don’t recognize how little they really know about the subjects or how difficult it is to bracket high and low estimates so that there’s a sufficiently strong chance that the real answer will fall somewhere in between. As a result, most people fail to spread their estimates far enough apart to account for their ignorance.

How do we demonstrate overconfidence?

1. Request subjects to evaluate their confidence in a statement. Group together all the statements with a given level of confidence (e.g., 90%) and compare that to the actual frequency of being correct.2. Test subjects with multiple-choice questions and then elicit their level of confidence in their answer on a scale from chance to 100% (total certainty). Compare this to the true accuracy of the answers.3. Give subjects a question with a numerical answer, and get them to choose a confidence interval such that they have a particular level of confidence that the true answer is in that range; e.g., "Pick a low number and a high number such that you are 90% confident that the population of Bulgaria is between those numbers." - we did this a while ago.4. Offer subjects the opportunity to bet on the correctness of their answers with chances that are favorable, if their judgements of accuracy are correct. They lose money if they are overconfident. If you are 90% sure, then you should be comfortable betting $9 against prospect of willing just $1 that the real is within your chosen range.

If human confidence had perfect calibration, judgements with 100% confidence would be correct 100% of the time, 90% confidence correct 90% of the time, and so on for the other levels of confidence. By contrast, the key finding is that confidence exceeds accuracy so long as the subject is answering hard questions about an unfamiliar topic. In a spelling task, subjects were correct about 80% of the time when they were "100% certain".

Put another way, the error rate was 20% when subjects expected it to be 0%.

Terrance Odean and Brad M. Barber of the University of California analyzed the trading records of more than 60,000 investors at a large brokerage firm. They found that individuals who trade stocks most frequently post exceptionally poor investment results.

Its very difficult to accurately predict consumer behavior

This is Joshua Bell.

http://en.wikipedia.org/wiki/Joshua_Bell

He is playing Vivaldi Four Seasons.

http://www.youtube.com/watch?v=iNcYT7jpH9E

People pay hundreds of dollars to watch him play.

One day Joshua Bell played the violin at a subway station in Washington D.C - incognito - on behalf of The Washington Post.

See this: http://www.youtube.com/watch?v=hnOPu0_YWhw

Read this: http://www.washingtonpost.com/wp-dyn/content/article/2007/04/04/AR2007040401721.html

Now this is not a controlled experiment. One can claim that the commuters were busy, had other stuff on their minds etc etc.

http://en.wikipedia.org/wiki/Trading_Places

Two guys - one born rich - one a poor conman -were swapped by two brothers who entered a bet...

This is one of best controlled experiments in social science I have read about..

http://www.nytimes.com/2007/04/15/magazine/15wwlnidealab.t.htmlWeb-based experiment. More than 14,000 participants registered at Music Lab (www.musiclab.columbia.edu), and were asked to listen to, rate and, if they chose, download songs by bands they had never heard of. Some of the participants saw only the names of the songs and bands, while others also saw how many times the songs had been downloaded by previous participants. This second group — “social influence” condition — was further split into eight parallel “worlds” such that participants could see the prior downloads of people only in their own world. All the artists in all the worlds started out identically, with zero downloads — but because the different worlds were kept separate, they subsequently evolved independently of one another.

You should see the parallels with Darwin’s Theory of Evolution as you read about this story.

In all the social-influence worlds, the most popular songs were much more popular (and the least popular songs were less popular) than in the independent condition.

At the same time, however, the particular songs that became hits were different in different worlds, just as cumulative-advantage theory would predict. Introducing social influence into human decision making, in other words, didn’t just make the hits bigger; it also made them more unpredictable.

When people tend to like what other people like, differences in popularity are subject to what is called “cumulative advantage,” or the “rich get richer” effect. This means that if one object happens to be slightly more popular than another at just the right point, it will tend to become more popular stil.

As a result, even tiny, random fluctuations can blow up, generating potentially enormous long-run differences among even indistinguishable competitors...

Thus, if history were to be somehow rerun many times, seemingly identical universes with the same set of competitors and the same overall market tastes would quickly generate different winners: Madonna would have been popular in this world, but in some other version of history, she would be a nobody, and someone we have never heard of would be in her place.

Oil went from $10 to $140. Who could have predicted either of these outcomes?

The Value of ONGC is VASTLY different if you assume a $10 a barrel world as compared to the value in a $140 a barrel world.

Excel can make you go nuts.

The definition of value is very precise. There is no ambiguity about it. All one has to do is to take the future cash flows and then bring them back to the present value using discount factor which is the opportunity cost of capital derived from a very precise model called the Capital Asset Pricing Model. You punch in the numbers in that model and out comes the cost of capital and then you punch that number in another excel model containing future cash flows and the precise formulas in that excel model will tell you instantly what that business is worth.

The sheer number of assumptions in a valuation model are mind boggling

Extrapolation, ignorance of diseconomies of scale, ignorance of competition, regulation.

Minor changes in inputs can make a vast difference in the final valuation number

In some cases, most of the value is comprised in cash flows which will occur several years from now. So we have to worry about forecast degradation. Increasing the discount factor is not the way to do it!

Underneath all that precision of that “precise model” is the defective man with all his biases. What biases creep into the excel valuation models?

“It’s stupid the way people extrapolate the past- and not

slightly stupid, but massively stupid.”

“I don’t think you can stick numbers on a

highly speculative

business where the

whole industry is

going to change in 5 years and

have it mean anything.”

“If you say, “I am going to stick an extra 6% on the interest rate to allow for that” I think that’s nonsense. It may look mathematical, but its mathematical gibberish in my view. . .”

Buffett does not think about cost of capital the way academic finance thinks about the subject.

“the test used by most

CEOs – is that the cost of capital is

about ¼ of 1% below the

return promised by

any deal that the CEO

wants to do!”

Thats why Excel Models can be used to rationalize almost any desired behavior!

“Any business craving of the

leader, however

foolish, will be quickly

supported by detailed rate-of-return and

strategic studies

prepared by his troops.”

Man is not a rational animal; rather man is a rationalizing one…

And Excel is a beautiful tool which helps him do just that!

You don’t even need “Goal Seek” function because its already built into the human user!

P/E Multiples in a high growth business are extremely sensitive to growth rates.

What happened to Infosys?

This is the best Indian company, with the best business model, with the best management which is competent, honest, and prudent. There is no debt, the earnings have grown and grown. And yet, people did not make any money from march 2000 over the next ten years or so. And this happened while India experienced the biggest bull market in its history. How did this happen?

the earnings did not fall but the growth rate of earnings did. And the valuation in March 2000 implied explosive growth to continue. That did not happen.

The result?

Growth stocks are extremely vulnerable to errors in predictions about growth.

“The combination of precise

formulas with highly imprecise

assumptions can be used to establish,

or rather to justify,

practically any value one wishes, however high, for

a really outstanding

company.”

“People calculate too much and think

too little.”

“If I taught a course in

investments, my final exam would be to value this Internet stock.”

“And if they came up with an answer, they'd flunk. And if they came up with a blank sheet of paper, I'd probably give them a B. “And if they said how the hell could you ask something so dumb? I’d give them an A.”

Bill Maher on Think Tanks and Predictions:

http://www.youtube.com/watch?v=VcJohfS4vTQ

See his movie Religious. He teaches you to be skeptical.

http://www.youtube.com/watch?v=fg8WlXZxAgQ

“There are two classes of forecasters:Those who don't

know and those who don't know they don't know.”- Galbraith

the statistician who drowned in

water which was, on average, only

4 feet deep

Financial modelers use scenario analysis and then apply subjective probabilities to each scenario to arrive at the “expected value”That’s the functional equivalent of the statistician who drowned in water which was, on average, only 4 feet deep!He forgot that the RANGE of depth was between 3 feet and 10 feet!

Nassim Taleb

“The worst case scenario is often more consequential than the forecast itself.”

October 2007

14 December 2008 mail:What a difference a year makes

Just more than 1 year ago Royal Bank of Scotland (RBS) paid $100bn for ABN Amro (80% cash).

For this amount today, RBS could buy:

Citibank $22.5bn,Morgan Stanley $10.5bn,Goldman Sachs $21.0bn,Merrill Lynch $12.3bn,Deutsche Bank $13.0bn andBarclays $12.7bn,And still have $8bn change !

Wealth Destruction on a Massive Scale? A Study of Acquiring-Firm ...

“Pascal’s observation seems apt: “It has struck me that all men’s misfortunes spring from the single cause that they are

unable to stay quietly in one room.”

- Buffett

While deals often fail in practice, they

never fail in projections - if the

CEO is visibly panting over a

prospective acquisition,

subordinates and consultants will

supply the requisite projections to rationalize any

price.

Decision Weights

Gambles with modest monetary stakes

estimates for gains

The possibility effect: unlikely events are considerably overweighted. For example, the decision weight that corresponds to a 2% chance is 8.1.

Frequency-Magnitude

People do not focus on both the frequency AND the magnitude. But they should. I could be 70% sure the market would rise, and still be short the market.

Rare events get mispriced.

Kelly Criteria Link

Kelly formula tells you how much of your bankroll should be invested in a given opportunity. There are only two inputs. Edge and Odds.

http://en.wikipedia.org/wiki/Kelly_criterion

Kelly works in bell curve situations like black jack, or dice. But the financial world is not best described by bell curves. In the financial worlds we deal with extremely uncertain outcomes, and extremely unpredictable and irrational human behavior. If you use models from the bell curve world in a world where black swans proliferate, you will make errors. What will happen if you overestimate your edge? You will over invest.

Scene from 21

Scene from 21

There is extreme wisdom in the idea that diversification is protection against ignorance and if you are not ignorant then your need to diversify goes down. Mr. Munger put it in these words:

“It is not given to human beings to have such talent that they can just know everything about everything all the time. But it is given to human beings who work hard at it – who look and sift the world for a mispriced bet – that they can occasionally find one. And the wise ones bet heavily when the world offers them that opportunity. They bet big when they have odds. And the rest of the time, they don't. It's just that simple.”

But what if you over-estimate your odds of success - a tendency that is pervasive?

Of course if people were rational, there wont be so many startups.

“If people were not overconfident, for example, significantly fewer people would ever start a new business: most entrepreneurs know the odds of success are against them, yet they try anyway. That their optimism is misplaced—that they are overconfident—is evidenced by the fact that more than two-thirds of small businesses fail within four years of inception. Put another way, most small-business owners believe that they have what it takes to overcome the obstacles to success, but most of them are wrong.

http://en.wikipedia.org/wiki/Animal_spirits_(Keynes)

“animal spirits - a spontaneous urge to action rather than

inaction, and not as the outcome of a weighted average of

quantitative benefits multiplied by quantitative probabilities.”- Keynes

"Even apart from the instability due to speculation, there is the instability due to the characteristic of human nature that a large proportion of our positive activities depend on spontaneous optimism rather than mathematical expectations, whether moral or hedonistic or economic. Most, probably, of our decisions to do something positive, the full consequences of which will be drawn out over many days to come, can only be taken as the result of animal spirits - a spontaneous urge to action rather than inaction, and not as the outcome of a weighted average of quantitative benefits multiplied by quantitative probabilities."

http://en.wikipedia.org/wiki/Animal_spirits_(Keynes)

Some people just don’t

give up

http://www.youtube.com/watch?v=45mMioJ5szc

The main benefit of optimism is

resilience in the face of setbacks.

Optimistic bias plays a role—sometimes the dominant role—whenever individuals or institutions voluntarily take on significant risks. More often than not, risk takers underestimate the odds they face, and do invest sufficient effort to find out what the odds are. Because they misread the risks, optimistic entrepreneurs often believe they are prudent, even when they are not. Their confidence in their future success sustains a positive mood that helps them obtain resources from others, raise the morale of their employees, and enhance their prospects of prevailing. When action is needed, optimism, even of the mildly delusional variety, may be a good thing. - Kahneman

Optimism Bias

“Optimistic bias is a significant source of risk taking. In the standard rational model of economics, people take risks because the odds are favorable—they accept some probability of a costly failure because the probability of success is sufficient. We proposed an alternative idea. When forecasting the outcomes of risky projects, executives too easily fall victim to the planning fallacy. In its grip, they make decisions based on delusional optimism rather than on a rational weighting of gains, losses, and probabilities. They overestimate benefits and underestimate costs. They spin scenarios of success while overlooking the potential for mistakes and miscalculations. As a result, they pursue initiatives that are unlikely to come in on budget or on time or to deliver the expected returns—or even to be completed. In this view, people often (but not always) take on risky projects because they are overly optimistic about the odds they face.

This idea probably contributes to an explanation of why people litigate, why they start wars, and why they open small businesses.” - Kahneman

Optimism Bias

“Optimism is normal, but some fortunate people are more optimistic than the rest of us. If you are genetically endowed with an optimistic bias, you hardly need to be told that you are a lucky person—you already feel fortunate. An optimistic attitude is largely inherited, and it is part of a general disposition for well-being, which may also include a preference for seeing the bright side of everything. If you were allowed one wish for your child, seriously consider wishing him or her optimism. Optimists are normally cheerful and happy, and therefore popular; they are resilient in adapting to failures and hardships, their chances of clinical depression are reduced, their immune system is stronger, they take better care of their health, they feel healthier than others and are in fact likely to live longer. A study of people who exaggerate their expected life span beyond actuarial predictions showed that they work longer hours, are more optimistic about their future income, are more likely to remarry after divorce (the classic “triumph of hope over experience”), and are more prone to bet on individual stocks. Of course, the blessings of optimism are offered only to individuals who are only mildly biased and who are able to “accentuate the positive” without losing track of reality. Optimistic individuals play a disproportionate role in shaping our lives. Their decisions make a difference; they are the inventors, the entrepreneurs, the political and military leaders—not average people. They got to where they are by seeking challenges and taking risks. They are talented and they have been lucky, almost certainly luckier than they acknowledge.” -Kahneman

The prevalent tendency to underweight or ignore distributional information is perhaps the major source of error in forecasting. -Bent Flyvbjerg.

Planning Fallacy: Plans and forecasts that

1. are unrealistically close to best-case scenarios2. could be improved by consulting the statistics of similar cases

Using the “inside view” and not the “outside view”

“Pallid” statistical information is routinely discarded when it is incompatible with one’s personal impressions of a case. In the competition with the inside view, the outside view doesn’t stand a chance. The preference for the inside view sometimes carries moral overtones. I once asked my cousin, a distinguished lawyer, a question about a reference class: “What is the probability of the defendant winning in cases like this one?” His sharp answer that “every case is unique” was accompanied by a look that made it clear he found my question inappropriate and superficial.

Insensitivity to base rates

Identify an appropriate reference class.

Obtain the statistics of the reference class

Use the statistics to generate a baseline prediction.

Use specific information about the case to adjust the baseline

prediction, if there are particular reasons to expect the optimistic bias to be more or less pronounced in this project than

in others of the same type.

How to overcome planning fallacy.

But what about Bugsy?

http://en.wikipedia.org/wiki/Benjamin_Bugsy_Siegel

Bugsy trailer.

Snapshot of movie’s end

Bugsy last Scene

He was over-leveraged, over-confident, and dead.

Watch this movie. Its about a man you would think as totally crazy. But he created Las Vegas. People thought he was crazy. And he was. The world needs a lot of people Bugsy. They drive capitalism. Warren Buffett would never do anything as crazy as a Bugsy because Warren Buffett is RATIONAL.

So what do you want to be like? Rational like Warren Buffett or crazy like Warren Beatty (who plays the role of Bugsy in the movie)?

Why We need Bugsy

“Significant effort is required to find the relevant reference category, estimate the baseline prediction, and evaluate the quality of the evidence. The effort is justified only when the stakes are high and when you are particularly keen not to make mistakes. Furthermore, you should know that correcting your intuitions may complicate your life. A characteristic of unbiased predictions is that they permit the prediction of rare or extreme events only when the information is very good. If you expect your predictions to be of modest validity, you will never guess an outcome that is either rare or far from the mean. If your predictions are unbiased, you will never have the satisfying experience of correctly calling an extreme case. You will never be able to say, “I thought so!” when your best student in law school becomes a Supreme Court justice, or when a start-up that you thought very promising eventually becomes a major commercial success. Given the limitations of the evidence, you will never predict that an outstanding high school student will be a straight-A student at Princeton. For the same reason, a venture capitalist will never be told that the probability of success for a start-up in its early stages is “very high.” The objections to the principle of moderating intuitive predictions must be taken seriously, because absence of bias is not always what matters most. A preference for unbiased predictions is justified if all errors of prediction are treated alike, regardless of their direction. But there are situations in which one type of error is much worse than another. When a venture capitalist looks for “the next big thing,” the risk of missing the next Google or Facebook is far more important than the risk of making a modest investment in a start-up that ultimately fails. The goal of venture capitalists is to call the extreme cases correctly, even at the cost of overestimating the prospects of many other ventures.” - Kahneman

Thank You