I’m a huge fan of James Montier’s work on the rationale for a quantitative investment strategy and global Graham net net investing. Miguel Barbosa of Simoleon Sense has a wonderful interview with Montier, covering his views on behavioral investing and value investment. Particularly interesting is Montier’s concept of “seductive details” and the implications for investors:
Miguel: Let’s talk about the concept of seductive details…can you give us an example of how investors are trapped by irrelevant information?
James Montier: The sheer amount of irrelevant information faced by investors is truly staggering. Today we find ourselves captives of the information age, anything you could possibly need to know seems to appear at the touch of keypad. However, rarely, if ever, do we stop and ask ourselves exactly what we need to know in order to make a good decision.
Seductive details are the kind of information that seems important, but really isn’t. Let me give you an example. Today investors are surrounded by analysts who are experts in their fields. I once worked with an IT analyst who could take a PC apart in front of you, and tell you what every little bit did, fascinating stuff to be sure, but did it help make better investment decisions, clearly not. Did the analyst know anything at all about valuing a company or a stock, I’m afraid not. Yet he was immensely popular because he provided seductive details.
Montier’s “seductive details” is reminiscent of the discussion in Nicholas Taleb’s Fooled by Randomness on the relationship between the amount of information available to experts, the accuracy of judgments they make based on this information, and the experts’ confidence in the accuracy of these judgements. Intuition suggests that having more information should increase the accuracy of predictions about uncertain outcomes. In reality, more information decreases the accuracy of predictions while simultaneously increasing the confidence that the prediction is correct. One such example is given in the paper The illusion of knowledge: When more information reduces accuracy and increases confidence (.pdf) by Crystal C. Hall, Lynn Ariss, and Alexander Todorov. In that study, participants were asked to predict basketball games sampled from a National Basketball Association season:
All participants were provided with statistics (win record, halftime score), while half were additionally given the team names. Knowledge of names increased the confidence of basketball fans consistent with their belief that this knowledge improved their predictions. Contrary to this belief, it decreased the participants’ accuracy by reducing their reliance on statistical cues. One of the factors contributing to this underweighting of statistical cues was a bias to bet on more familiar teams against the statistical odds. Finally, in a real betting experiment, fans earned less money if they knew the team names while persisting in their belief that this knowledge improved their predictions.
This is not an isolated example. In Effects of amount of information on judgment accuracy and confidence, by Claire I. Tsai, Joshua Klayman, and Reid Hastie, the authors examined two other studies that further that demonstrate when decision makers receive more information, their confidence increases more than their accuracy, producing “substantial confidence–accuracy discrepancies.” The CIA have also examined the phenomenon. In Chapter 5 of Psychology of Intelligence Analysis, Do you really need more information?, the author argues against “the often-implicit assumption that lack of information is the principal obstacle to accurate intelligence judgments:”
Once an experienced analyst has the minimum information necessary to make an informed judgment, obtaining additional information generally does not improve the accuracy of his or her estimates. Additional information does, however, lead the analyst to become more confident in the judgment, to the point of overconfidence.
Experienced analysts have an imperfect understanding of what information they actually use in making judgments. They are unaware of the extent to which their judgments are determined by a few dominant factors, rather than by the systematic integration of all available information. Analysts actually use much less of the available information than they think they do.
Click here to see the Simoleon Sense interview.
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Hey Greenbackd,
what do you think about the reverse dcf? Are you thinking about exploring it in the future? As of now I am reading Expectations Investing and the article Miguel posted.
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