Understanding The Universe of the Unknown and the Unknowable (uU)
March 4th, 2012
The Delhi chapter of IAIP organized this Speaker Event in New Delhi on 4th March 2012 where Mr. Sanjay Bakshi, a deep value investor and CEO – Tactica Capital Management, delivered a very insightful, engaging and thought provoking presentation. The event was very well attended and appreciated by the members as well as non-members of the society. This event qualified for 1.5 CE credit hours.
Investment professionals have to deal with a lot of uncertainty (a wide range of possible outcomes – the unknown and the unknowable, the uU) while making investment decisions. Many people try to model uncertainty by using quantitative models and techniques such as statistical distributions, multiple linear regressions, scenario Analysis and make forecasts with various degrees of confidence. But, such people continue to be surprised more often than they expect to be and afterwards they rationalize.
In his presentation, Sanjay described how people deal with the uU these days and fail, how various Value Investors in history dealt with the same uU and succeeded, how he himself deals with the uU, and specific ways that we can adopt to create favorable odds, benefit from uncertainty and put luck in our favor in order to deal with the uU while avoiding any permanent loss of capital. Sanjay’s presentation was full of examples and anecdotes of various Value investors and leading academics and scientists.
Sanjay started the talk with an example of how people valued Internet stocks, with no hard earnings or assets, entirely based upon forecasted earnings when there was no basis for these forecasts except for their optimism. When humans are involved, the behavioral factors and biases influence every aspect of decision making. When faced with a wide range of possible outcomes, even the smartest of people fail to estimate the probabilities of worst case scenarios. People show “Availability bias” i.e. the recent past vivid in people’s memories makes them overly optimistic or pessimistic. Therefore, people tend to take to extremes – either grossly underestimating or overestimating probabilities. Therefore, techniques such as Scenario Analysis and Forecasting have proved futile despite their quantitative elegance. As an example, Sanjay showed the picture of an empty Boeing 747 jet and asked the audience to estimate a range for its weight in tons with 90% confidence. He showed yet another picture of the moon and asked to estimate its diameter in km with 90% confidence. Although some people could come up with one correct response but nobody could guess both of them right. Infact, making Investment decisions based on Forecasting and the heavy use of Quantitative finance with models, which rely on inputs estimated from historical statistical averages and assuming bell curve like distributions, has proven to be a dangerous game. It makes people overconfident with false illusions of safety.
Through various examples of social experiments, Sanjay illustrated how people’s decisions get influenced by other people’s choices. What becomes initially popular with a few people keeps on becoming more and more popular. For example, in a social experiment, a group of people were given a list of songs to listen to and rate independently. However, in a repeat experiment where people could see other people’s ratings for songs in real-time, the outcomes were very different for the songs popularity. Those songs, which got played and rated positively in the beginning, got the highest scores eventually. This showed that some people’s choice about which song to try out first from a list of songs (which is totally random) and their rating decision on the same song influenced others people’s choices. The most popular song just got “lucky” by happening to be in the right place at the right time. It also showed that the initial winner from a group of contestants gets more and more eyeballs and attention subsequently. In yet another experiment, Sanjay showed how people paid thousands of dollars to come and listen to the best violin player in the world. However, when that same violin player played the same symphony unadvertised while standing on a busy subway station, no one except a small child stopped to listen. Thus, if the same person were to be at a different place at a different time, the outcome is very different.
When techniques such as Forecasting, Scenario Analysis, Quantitative models, Charting and Technical analysis have historically failed to help understand the Unknown and the Unknowable (uU), the question arises – How can we understand the uU ? To answer this question, Sanjay went back in history and gave examples of how various enormously successful “role model” Value investors dealt with the uU.
John Templeton used to buy a variety of really cheap stocks available at prices much lower than their conservatively estimated intrinsic value. Though he knew that some of these might go belly up, he did not know which ones. He preferred debt-free companies.
Later, Benjamin Graham gave the concepts of investing with a “Margin of Safety” (buying a dollar worth of assets for 66 cents or lower), with “risk” defined as the downside risk (i.e. avoiding any permanent loss of capital). Graham found out and invested in “Cash Bargains” (stocks available for a price lower than conservatively calculated liquidation value = cash less all debt) as these offered the lowest downside risk and the highest margins of safety. Graham created odds in his favor by using both the “Margin of Safety” and “diversification” as protection against bad luck, and by not using borrowed money to prevent any forced selling. Graham bought only “Value” stocks i.e. companies with a long record of operating history (at least 10 years) with stocks selling at prices much lower than the “conservatively” calculated intrinsic values (without considering any future growth and without any forecasting or management interactions). If any growth happened, Graham would thus get it for free. Graham avoided “Value traps” (stocks whose prices were artificially kept low) and he taught how to identify these traps in his book “Security Analysis”. Moreover, he set simple rules and limits that made logical sense. For example, he would consider analyzing a stock only when the earnings yield for the stock (depending on the current stock price) was at least twice as much as the earnings yield for a high grade corporate bond. Graham also set a 3 year upper time limit for the individual stock prices to converge to conservatively calculated intrinsic values. Through these simple concepts and methods, Graham created favorable odds.
With an example of Casinos, Sanjay showed how any casino creates favorable odds for itself on every bet. In a Casino, every single bet is designed to offer odds in favor to the casino but odds against the player. Further, the casino places upper limits on the amount that can be bet by the players. And the casino diversifies its bets over a variety of people who come to play. Clearly, casino is the value investor here.
Later, Graham’s disciple, Warren Buffett, further refined and added to Graham’s strategy by emphasizing not only the long records of operating history, margin of safety, avoiding leverage, and buying at “cheap” prices, but also considering only businesses that he deeply understands and only “great” companies (i.e. companies with deep and wide moats i.e. companies which have competitive advantages and can sustain these for the long term despite competition) run by “great” people (honest and able senior management) and holding on to these companies forever. Further, Buffett partners with senior management and pampers them. Also, Buffett is open to buying “real” growth at reasonable prices unlike Graham who bought growth for free. With these added criteria, Buffett does not need as much diversification as Graham. In fact, he has said that “Risk comes from not knowing what you are doing” and “you only need a maximum of 20 investment decisions in a lifetime”. With the above added criteria, Buffett also creates favorable odds and uses small diversification (5-10 stock portfolio) as further protection against bad luck.
More recently, Nassem Taleb wrote on “black swans” (i.e. highly improbable events) of two types – positive black swans (i.e. highly improbable positive outcomes) and negative black swans (i.e. highly improbable negative outcomes). Some business models are exposed to negative black swans (i.e. if a thing goes wrong, the business takes a huge dip downwards and loses a lot, but if things go right, the business does not rise as much and gains a little). For example – Banking. In striking contrast, some business models are exposed to positive black swans (i.e. if a thing goes right, the business will be a huge hit and gain a lot, but if things go wrong, the business loses a little). For example – Film making, Book publishing, Drug discovery, Venture Capital, Private Equity. Therefore, an additional way that one can create odds in his favor is to invest only in businesses that are exposed to positive black swans and avoid businesses that are exposed to negative black swans.
It is also important to acknowledge the role of luck. For instance, most scientific discoveries were accidental (the results of chance encounters or “serendipity”) where the scientist discovered something that he was not looking for to begin with. Louis Pasteur said “Chance favors the prepared mind”. This begs the question – How do we get lucky? In his book “How to get Lucky”, Max Gunther advises that one should go to places where the events go fastest. Another way to get lucky is to create favorable odds and seek businesses exposed to positive black swans.
Charlie Munger, Warren Buffett’s partner talks about how the Harvard economist, Richard Zeckhauser, is the best bridge player in the world because he has trained his mind to make decisions unlike how the normal human mind thinks in a uU environment.
In his article “Investing in the Unknown and the Unknowable (uU)” , Richard Zeckhauser, highlights the importance of understanding the difference between risk and uncertainty. Uncertainty is simply a uU situation with a wide range of possible outcomes. And the markets hate uncertainty. As a result, stock prices of all companies in uncertainty get hammered down. Therefore, one can use uncertainty as a friend by seeking businesses exposed to positive black swans.
Sanjay concluded that the best we can do in the uU world is create favorable odds for ourselves in ways like the role model Value investors, use uncertainty as a friend by seeking out businesses exposed to positive black swans, and make sidecar investments with people who bring complementary skills and who get deals that no one else gets.
About the Speaker:
Professor Sanjay Bakshi is CEO, Tactica Capital Management, a deep value investing boutique based in Gurgaon. He also teaches courses in Behavioral Finance and Business Valuation, and Financial Shenanigans at MDI Gurgaon.
Link to the presentation: http://dl.dropbox.com/u/28494399/CFA%20Society%20Talk.pdf
Contribution by: Manan Agrawal, CFA, IAIP Volunteer