Fat Tails

“Micro-Mooc on a paper by Taleb and Tetlock (one manifestation of the LUDIC FALLACY). There are serious statistical 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. Yet much of the economics and decision making literature confuses the two. 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.”

The paper is here: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2284964
More general Fat Problems with Tails: http://www.fooledbyrandomness.com/FatTails.html

From Nassim Nicholas Taleb Facebook Page:

Friends, I am presenting this document (summary of recent work) explaining what is wrong with economics models at a conference in France (which is not fully infected with the Anglo-American disease).
Please let me know if you find mistakes as I cut/pasted from *Fat Tails & Fragility*.

https://dl.dropboxusercontent.com/u/50282823/Problems%20with%20Economics.pdf

A Brief Exposition of Violations of Scientific Rigor In Current Economic Modeling

Nassim Nicholas Taleb
NYU-Poly Institute

July 2013

This is a brief summary of the problems discussed in philosophical terms in The Black Swan and Antifragile with a more mathematical exposition in Fat Tails and Antifragility (2013). Most of the text was excerpted from the latter book.

Note that this is not a critique of modern economic modeling from outside, but from within, using mathematics to put the methods claimed under scrutiny.

The message is simple: focus on measurable robustness to model error and convex heuristics, instead of relying on “scientific” measurements and models. For these measurements tend to cause blowups. And we can measure fragility, not quite statistical risks.