Difference between revisions of "Fooled By Randomness"
(New page: I recently read “Fooled by Randomness”, the Hidden Role of Chance in Life and in the Markets, by Nassim Nicholas Taleb. Within this work, and somewhat randomly, Taleb cautions, “...)
Latest revision as of 15:00, 9 October 2008
I recently read “Fooled by Randomness”, the Hidden Role of Chance in Life and in the Markets, by Nassim Nicholas Taleb. Within this work, and somewhat randomly, Taleb cautions, “A book review, good or bad, can be far more descriptive of the reviewer than informational about the book itself. “ To some, this point may be obvious, it would be very difficult to write about a book and remain so detached as to be 100% objective. Taleb enjoyed a “two decade career as a qualitative trader in N.Y. and London” and currently is the Dean’s Professor in the Sciences of Uncertainty at the Isenberg School of Management of the University of Massachusetts at Amherst. Many of the anecdotes he presents come from his experience with coworkers’ bad trades. Specifically those who ‘blew up’, trading and making money along the way until that one bad series of trades that end their career. He offers a number of anecdotes about survivorship bias, a phenomenon whereby we attribute great skill to someone for his performance when in reality, randomness will produce money managers with 5-10 year winning streaks (beating the averages) in the same manner whereby if 10,000 people flipped a coin, half would get a head, then half of them would get a second head, and so on. After 10 flips, about one in 1024 flippers will have a run of ten heard in a row. Now, Taleb certainly has a good point here, but cannot explain how a Warren Buffet, who had that kind of streak by the late 80’s continued that streak another 17 years. (Or to put it another way, I used Taleb’s reasoning and did not buy Berkshire Hathaway in 1992. Since then it rose to $118,000 a return of nearly 19%/yr these past 15 years.)
He also offers an example of survivorship bias in discussing “The Millionaire Next Door.” TMND delivers a message that it’s possible to accumulate wealth by living a lifestyle beneath one’s means. A number of counter examples are offered as well. People with high incomes, moving into neighborhoods where they feel compelled to “keep up with the Joneses” and ultimately living a life of conspicuous consumption, but not saving. Taleb suggests the very way the authors went about their selection process ignored survivorship bias. What of the people who lived frugally, saving the suggested 10-15% of their income, and due to one of the standard disruptors (loss of job, divorce, injury, etc.) find themselves poor at age 62? I believe the lessons of TMND are still of value, and should not be so quickly dismissed. No one suggested that following its advice would make one immune from all tragedy. I dare say that if we took the proper samples as Taleb advises, we’d find some small percent of the group that spent more than they earned who still managed to be successful by that usual definition. On the other hand, decades of savings can be wiped out through misfortune, but his advice is still the basis of a sound start. Staying healthy, and staying married certainly would help improve one’s odds.
I enjoyed his relating a quiz given to medical doctors, borrowed from the book “Randomness” by Deborah Bennett;
A test of a disease presents a rate of 5% false positives. The disease strikes 1/1000 of the population. People are tested at random, regardless of whether they are suspected of having the disease. A patient’s test is positive. What is the probability of the patient having the disease?
Of course the answer is about 2%, since we know that of 1000 people there will be one with the disease, and nearly 50 false positives. One in fifty is 2%. Here, Taleb missed his chance to offer some further math suggesting how much accuracy such a test would need to offer. In this case even .1% false positive would make for a 50/50 confidence for our random patient. The original author states that one in five doctors got this question correct.
He also offers a tale whose moral suggests that staring at the ticker or looking at one’s portfolio too frequently, can only lead to misery. Assume one has a portfolio returning 15% per year with volatility of 10%. This would be a great return, positive in 93% of years observed. But as we move the timeline shorter, say to every quarter, only 77% of the quarters are positive, and to push further, only 67% of months show positive. A daily look at the portfolio will show positive returns on 54% of the days observed. This is the corollary of the lessons shared in my reference to MoneyChimp and discussions of investing for the long term. By looking at returns for the shorter periods we can drive ourselves to a level of worry and distraction that would scare us from the market altogether. I'd recommend this book as a worthy read. While Taleb’s style has him jumping around from the running theme of the infinite number of monkeys typing the great works back to the multiple stories of traders ‘blowing up’, his theme of “Fooled by Randomness” is woven throughout the book.
book summary by JoeTaxpayer
- This article is based on an article from Finwikian, available under the GFDL, content later converted into CC-BY-SA.