On the Difference between Binary Prediction and True Exposure with Implications for Forecasting Tournaments and Decision Making Research
Nassim Nicholas Taleb
NYU-Poly; Université Paris I Panthéon-Sorbonne - Centre d'Economie de la Sorbonne (CES)
Philip E. Tetlock
University of California, Berkeley - Organizational Behavior & Industrial Relations Group; University of Pennsylvania - Management Department
November 27, 2013
There are serious differences between predictions, bets, and exposures that have a yes/no type of payoff, the "binaries", and those that have varying payoffs, which we call the "vanilla". Real world exposures tend to belong to the vanilla category, and are poorly captured by binaries. Vanilla exposures are sensitive to Black Swan effects, model errors, and prediction problems, while the binaries are largely immune to them. The binaries are mathematically tractable, while the vanilla are much less so. Hedging vanilla exposures with binary bets can be disastrous -- and because of the human tendency to engage in attribute substitution when confronted by difficult questions, decision-makers and researchers often confuse the vanilla for the binary.
Number of Pages in PDF File: 6
Keywords: Predictions, Risk, Decision, Judgment and Decision Making, Fat Tailsworking papers series
Date posted: June 26, 2013 ; Last revised: November 28, 2013
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