Taleb's "fooled by randomness"

Reading "Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets" (Nassim Nicholas Taleb) in the midst of Peru was a pleasant thing. Basically, Taleb, a "post-trader" gives an interesting account of how human judgement is fallible, especially because we tend to fall in the apophenia trap. I particularly cherished the part about the author's habits concerning information gathering/data farming:

"My aim, as a pure amateur fleeing the boredom of business life, was merely to develop intuitions for these events - the sort of intuitions that amateurs build away from the overly detailed sophistication of the professional researcher. (...) When I see an investor monitoring his portfolio with live prices on his cellular telephone or his handheld, I smile and smile. (...) I reckon that I am not immune to such an emotional defect. But I deal with it by having no access to information, except in rare circumstances. Again, I prefer to read poetry. If an event is important enough, it will find its way to my ear. (...) This explains why I prefer not to read the newspaper (outside of the obituary), why I never chitchat about markets, and, when in a trading room, I frequent the mathematicians and the secretaries, not the traders. It explains why it is better to read the New yorker on Mondays than the Wall Street Journal every morning (from the standpoint of frequency, aside from the massive gap in intellectual class between the two publications). (...) Some so-called wise and rational persons often blame me for "ignoring" possible valuable information in the daily newspaper and refusing to discount the details of the noise as "short-term events." Some of my employers have blamed me for living on a different planet. My problem is that I am not rational and I am extremely prone to drown in randomness and to incur emotional torture. I am aware of my need to ruminate on park benches and in cafés away from information, but I can only do so if I am somehow deprived of it."

I quite enjoyed the last part since it's exactly the reason why I walk around in cities or take so much trains: to have time to ruminate from different "information-filled" places: the internet, my apartment and newsstands+book-shops.

Moreover, his list of "bias" in foresight is also insightful. Although he applies it to trading, it definitely outreach this domain. Some of the bias:

  • "When you look at the past, the past will always be deterministic, since only one single information took place. Our mind will interpret most events not with the preceding ones in mind, but the following ones. (...) The "hindsight" bias, the "I knew it along" effect. (...) A mistake is not something to be determined after the fact, but in the light of the information until that point.
  • Survivorship bias: we are trained to take advantage of the information that is lying in front of our eyes, ignoring the information we don't see (...) we tend to mistake one realization among all possible random histories as the most representation among all possible random histories as the most representative ones, forgetting that there may be others. In a nutshell, the survivorship bias implies that the highest performing realization will be the most visible. Why? Because the loser do not show up.
  • Ergodicity: time will eliminate the annoying effect of randomness (...) under certain conditions, very long sample path would end up resembling each others.
  • Prospect theory: looking at differences, not absolutes, and resetting to a specific reference point.
  • Affect heuristic, risk-as-feeling theory: people react to concrete and visible risks, not abstract ones.
  • Belief in the law of small numbers: inductive fallacies; jumping to general conclusions to quickly
  • Overconfidence: risk-taking out of an underestimation of the odds
  • Mistaking mean and median"

Also of great interest to me is the discussion about the importance of exceptions and outliers, which is also the topic of his second book:

"People in most fields outside of it do not have problems eliminating extreme values from their sample, when the difference in payoff between different outcomes is not significant, which is generally the case in education and medicine. A professor who computes the average of his students' grades removes the highest and lowest observations, which he would call outliers and takes the average of the remaining ones, without his being an unsound practice. A casual weather forecaster does the same with extreme temperature - an unusual occurrence might be deemed to skew over the results. (...) So people in finance borrow the technique an ignore the infrequent events, not noticing that the effect of a rare event can bankrupt a company. (...) As a skeptic, I reject a sole time series of the past as an indication of future performance; I need a lot more than data. My major reason is the rare events but I have plenty of others. (...) The problem is that we read too much into shallow recent history, with statements like "this has never happened before" but not from history in general (things that never happened before in one area tend to eventually happen)."

The reason why I mention this is that I am especially interested in the role of exceptions, outliers in design as I already discussed here. Why do I blog this? Quite liked the book, both for the content and the way the author describes his thoughts with this grecosyrian/mediterranean who went to anglo/french board school and university, which makes it a tad poetic in terms of references and examples. Certainnly a good reference about foresight and some elements to draw concerning thinking habits.