{"id":1264,"date":"2012-12-01T21:01:24","date_gmt":"2012-12-01T15:31:24","guid":{"rendered":"http:\/\/teekhapan.wordpress.com\/?p=1264"},"modified":"2012-12-01T21:01:24","modified_gmt":"2012-12-01T15:31:24","slug":"in-short-run-even-playboy-bunnies-can-beat-fund-managers","status":"publish","type":"post","link":"https:\/\/vivekkaul.com\/2012\/12\/01\/in-short-run-even-playboy-bunnies-can-beat-fund-managers\/","title":{"rendered":"In short run, even Playboy bunnies can beat fund managers"},"content":{"rendered":"

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Michael J. Mauboussin<\/b>\u00a0is Chief Investment Strategist at Legg Mason Capital Management in the United States. He is also the author of bestselling books on investing like \u00a0Think Twice: Harnessing the Power of Counterintuition\u00a0<\/i>and\u00a0More Than You Know: Finding Financial Wisdom in Unconventional Places<\/i>. His latest book\u00a0The Success Equation: Untangling Skill and Luck in Business, Sports, and Investing\u00a0<\/i>(Harvard Business Review Press, Rs 995)\u00a0<\/i>has just come out.In this freewheeling interview with\u00a0Vivek Kaul<\/b>, he talks about how short term outcomes have a good dose of luck attached to them and how as people get more skillful at doing a particular thing, luck becomes the deciding factor. This is the second and the concluding part of the interview.
\nWhat is the undersampling of failure?<\/b>
\nUndersampling failure means that when we review the past to see what may work in the future, we have a tendency to dwell on success and not examine failure. Think of it this way. Say companies could choose one of two strategies, risky or safe. Of the companies that choose the risky strategy, some succeed wildly and others fail. Of the companies that choose the safe strategy, some are mildly successful and others mildly disappointing, but all stay in business. In other words, the outcomes for the risky strategy have high variance and the outcomes for the safe strategy have a low variance.\u00a0Now you\u2019re a new company coming along and want to be successful. So you study the records of companies and see that the wildly successful ones are those that selected the risky strategy. You don\u2019t see the companies that chose the risky strategy and failed because they are dead. That is undersampling failure. The question is not: which strategy did the successful companies pursue? The question is: what are the outcomes of\u00a0all<\/i>\u00a0of the companies that chose this strategy?\u00a0A related point is that the success of a strategy only occurs with some probability. Major variables, including the tastes of consumers, the actions of competitors, and technological change, are simply impossible to fully anticipate.
\nCan you give us an example?
\n<\/b>Michael Raynor, a consultant at Deloitte, offers the example of Sony\u2019s MiniDisc. He argues that Sony\u2019s strategy was brilliantly conceived, yet the product totally flopped. There are no sure things.<\/div>\n
You write that \u201corganizations tends to overestimate the degree to which the star\u2019s skills are transferrable\u201d…
\n<\/b>This argument is an extension of the work done by Boris Groysberg, a professor at Harvard Business School. Groysberg has studied many cases in which stars switch organizations and found that in most cases their performance deteriorates. So skill is not as portable as we tend to think.\u00a0One example he provides is that that of executives from General Electric. GE is well known to have among the best management training programs in the world. Further, rising to the ranks of GE management undoubtedly requires skill. Groysberg studied 20 executives who left GE over a two decade span and who took leadership positions at other companies. What he found was that those who went to firms organizationally very similar to GE tended to do quite well, while those that went to firms that were different fared poorly. So it\u2019s not just skills that matter, but the match between skills and the environment.<\/div>\n
You talk about the\u00a0Playboy\u00a0Playmates selecting stocks that generated greater returns than the broader market. Could you take our readers through that story?\u00a0<\/b><\/div>\n
As a promotional stunt, a trading company asked former\u00a0Playboy\u00a0Playmates to pick 10 stocks at the beginning of 2006. The best of the Playmates did much better than the market, and a higher percentage of Playmates outperformed the market than did professional money managers. Right away, this should cause you to ponder an important question. How can a handful of presumably untrained individuals outperform diligent and dedicated professionals? In how many fields can amateurs beat the professionals?<\/div>\n
What is the broader point you were trying to make?<\/b><\/div>\n
The broader point I was making is that in fields where there is a good dose of luck, short-term outcomes do little to reveal differential skill. Over a longer period, you would most certainly expect the pros to do better than the amateurs. But it is common in business and investing to use evaluation periods that are simply too short to allow for any kind of concrete conclusions about differences in skill.<\/div>\n
What is the paradox of skill?\u00a0<\/b><\/div>\n
The paradox of skill says that as skill improves in an activity that includes both skill and luck, then luck becomes more important in determining outcomes. So more skill leads to more luck, the paradox.The paradox of skill says that as competitors in a field become more skillful, luck becomes more important in determining results. The key to this idea is what happens when skill improves in a field. There are two effects. First, the absolute level of ability rises. And second, the variance of ability declines.<\/div>\n
Could you explain through an example?\u00a0<\/b><\/div>\n
Let me give one example from athletics and then turn to investing. The paradox of skill makes a specific, testable prediction in sports that are measured against a clock. You should see absolute times improve, bumping into the limits of human physiology, and you see relative times cluster, which means that the finishers are all bunched. This is precisely what we see in swimming and marathons.\u00a0Men today run the race about 26 minutes faster than they did 80 years ago. But in 1932, the time difference between the man who won and the man who came in 20th<\/sup>\u00a0was close to 40 minutes. Today that difference is well under 10 minutes.<\/div>\n
And the investing example?<\/b><\/div>\n
The idea applies well to investing and has been the subject of discussion for decades. For example, Charles Ellis wrote a famous essay in 1975 called \u201cThe Loser\u2019s Game,\u201d which makes the same essential point. Ellis argued that in the 1950s and 1960s, institutional investors could outwit individuals because there was a wide range of skill. But as the markets became dominated by institutions, the difference in skill narrowed making the game harder to win.In investing, the idea is that skilled investors are very efficient at reflecting information into asset prices. So only new information, which is by definition random, should affect stock prices. Hence, stocks follow a \u201crandom walk.\u201d This is a statement of the efficient market hypothesis.\u00a0Now, the efficient market hypothesis is not accurate. Stock price movements do not follow random walks, and there is differential skill. But the basic point remains true. Because prices capture the skill of investors, luck is very important in determining results\u2014especially in the short term.<\/div>\n
You write \u201cpeople who work in businesses where social influence operates are often paid for good luck, although they generally don\u2019t suffer symmetrically from bad luck.\u201d Can you explain this statement in the context of the financial crisis.\u00a0<\/b><\/div>\n
I think this idea is why some many people were so upset by the financial crisis. The basic idea is that gains are privatized when times are good and socialized when times are bad. In other words, executives make lots of money in good times and taxpayers have to bail out companies in bad times. That feels deeply unfair.<\/div>\n
This is also relevant in equity based compensation. Stock price moves reflect changes in the expectations of a company\u2019s prospects plus macro factors such as interest rates, tax rates, regulation, the perceived equity risk premium, and so forth. Ideally, you want to pay executives for superior performance, but the macro factors can swamp the company-specific factors. In bull markets, that means executives are getting paid handsomely for good luck. In bear markets, it means that even those executives who are skillful fare poorly. Neither outcome serves the core purpose.\u00a0So the ideal is to figure out how to pay executives for good skill. Indexing options or restricted stock units is a solid first step in achieving this goal.<\/div>\n
\u201cPoor quality makes a company uncompetitive but so does quality that is too high. The relationship between quality and value is not all clear,\u201d you write. Why do you say that?\u00a0<\/b><\/div>\n
This boils down to what a company\u2019s governing objective should be. What\u2019s essential is that a company cannot optimize multiple factors at the same time. Quality is a good example. If the quality of a company\u2019s goods or services is too low, customers won\u2019t want to do business. On the other hand, if quality is too high, leading to prices that are too high, then customers won\u2019t want to do business. So the trick for managers is to find a balance between price and value that makes the customers happy\u00a0and<\/i>\u00a0creates value for the company.<\/div>\n
In the book, I give the example of a company that was determined to win a prestigious quality award and succeeded. The problem was that the expense the company incurred for the award was greater than the price increases it could charge its customers. So while the customers happily enjoyed the higher quality, the company\u2019s finances suffered. It eventually filed for bankruptcy.<\/div>\n
That sounds very similar to what happened to Kingfisher Airlines in India. Moving on, can you tell us what is the luck-skill continuum?\u00a0<\/b><\/div>\n
Imagine a continuum where on one side results are determined solely through luck, think roulette wheels and lotteries, and on the other side solely by skill, such as chess matches and running races. Most activities in life are between these extremes, and knowing where an activity lies can be very helpful. For example, as you move from the skill to the luck side, you need an increasingly large sample size in order to detect skill because luck dilutes the signal.Another way to think about this is cause and effect. On the skill side of the continuum, outcomes correlate exactly with skill. Think of a great performance by a pianist. Just hearing the music indicates the skill of the musician. Cause and effect are tightly linked, and feedback is clear.<\/div>\n
By contrast, outcomes correlate with skill only loosely on the luck side of the continuum. Success or failure comes with an attached probability. For example, even if you play your cards right in a card game, luck ensures that you\u2019ll lose some of the time. This means that feedback is much more difficult since a good process can lead to a bad outcome or a bad process can lead to a good outcome. The way to deal with that is to focus on the process, not the outcome, when luck is involved. A good process provides the best chance for a good result over time.<\/div>\n
You point out that one can reduce the influence of luck by effectively tying cause to effect. Could you explain through an example?
\n<\/b>There\u2019s an old saying in advertising that half of a company\u2019s advertising budget is wasted, it\u2019s just that no one knows which half it is. The broader point is that no one has been able to effectively measure the effect of advertising spending.\u00a0That is changing, and that is what I meant when I discussed better understanding cause and effect. Take online advertising as an example. One large retailer tested their advertising using a control group. In other words, they showed advertising to some people and compared the results to a demographically similar group that didn\u2019t see the ads. By comparing results, they could see the effectiveness of the ads.\u00a0This type of analysis is spreading fast, in large part because technology today allows it. It has also spread to realms including politics. Politicians in the U.S. used to spend money without knowing the payoff, measured in votes. Political scientists now have ways to measure the efficacy of spending much more accurately.
\nThe interview <\/a>originally appeared on www.firstpost.com on December 1, 2012.<\/div>\n
\n(Vivek Kaul is a writer. He can be reached at\u00a0vivek.kaul@gmail.com<\/a>)\n<\/div>\n

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Michael J. Mauboussin\u00a0is Chief Investment Strategist at Legg Mason Capital Management in the United States. He is also the author of bestselling books on investing like \u00a0Think Twice: Harnessing the Power of Counterintuition\u00a0and\u00a0More Than You Know: Finding Financial Wisdom in Unconventional Places. His latest book\u00a0The Success Equation: Untangling Skill and Luck in Business, Sports, and … <\/p>\n

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