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Tag Archives: Piketty

Piketty, Schmugman, Qatar, Dawkins, British Airways, Saudi Arabia | Twitter

@LorenzoWVilla Very nice ‘probability’ problem from @CutTheKnotMath (  ): see below @nntaleb ” target=”_blank”>”> Permalink 9:50 AM – 12 Jun 2017 @nntaleb In other words, methods used to state that people & investors underestimate tail events by psychologists and economists are severely flawed.   Permalink 6:02 AM – 12 Jun 2017 @nntaleb The empirical […]

Inequality vs Inequality | Medium

Inequality vs Inequality There is inequality and inequality. The first is the inequality people tolerate, such as one’s understanding compared to that of people deemed heroes, say Einstein, Michelangelo, or the recluse mathematician Grisha Perelman, in comparison to whom one has no difficulty acknowledging a large surplus. This applies to entrepreneurs, artists, soldiers, heroes, the […]

@FiveThirtyEight, Salafis Jihadists, Amioun, Piketty, Averroes, Kadisha Valley, The Right | Twitter

@nntaleb Bingo! Option traders get it! When probabilities are stochastic, they become ~.50. And they don’t move fast!   Permalink 2:25 PM – 6 Aug 2016 @nntaleb 3) More technically, when the variance of the probability is v. high it converges to 50%. Kapish? (metaprobability). Permalink 2:13 PM – 6 Aug 2016 @nntaleb 2/ So […]

GMOs, Putin, Downloading, Piketty, Dupire, Monotheism, Doctorow, Daesh, Cossaks

New piece on #GMOs and precautionary principle and computational complexity first draft with @nntaleb — Yaneer Bar-Yam (@yaneerbaryam) November 25, 2015 Retweeted by NNT @nntaleb I hope you like it:My Passionate Soliloquy about Putin to the White House — Ninos Youkhana (@Nninoss) November 23, 2015 […]

On the Super-Additivity and Estimation Biases of Quantile Contributions

On the Super-Additivity and Estimation Biases of Quantile Contributions Nassim N Taleb, Raphael Douady (Submitted on 8 May 2014 (v1), last revised 12 Nov 2014 (this version, v3)) Sample measures of top centile contributions to the total (concentration) are downward biased, unstable estimators, extremely sensitive to sample size and concave in accounting for large deviations. […]