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THE BLACK SWAN

THE BLACK SWAN. A Black Swan is…. … Something you didn’t expect which has a strong impact. (So the more you think you know the more vulnerable you are because your confidence in predicting the likelihood of a given event will make you more vulnerable in the case where you don’t). Mediocristan.

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THE BLACK SWAN

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  1. THE BLACK SWAN

  2. A Black Swan is… … Something you didn’t expect which has a strong impact. (So the more you think you know the more vulnerable you are because your confidence in predicting the likelihood of a given event will make you more vulnerable in the case where you don’t)

  3. Mediocristan • In Mediocristan everything is constrained by boundary conditions: time, the limits of biological variation, the limits of hourly compensation, etc. • Random variation of attributes exists in Mediocristan, and can be usefully described by Gaussian probability models (e.g. the bell curve) • Because overall constraints are in effect for all occurrences no single data point will have any great effect on the mean or average of the whole. • Examples: height of people, calories eaten per day, wages earned by cab drivers.

  4. Extremistan • Extremistan is the land of scalability: variation within distributions is unconstrained and unpredictable. • Generators of events produce distributions with very large or very small extreme values, relatively frequently. And those extreme values often affect the sum of attribute values in a sample distribution+ the mean value of such distributions. • The probability of occurrence of extreme values varies greatly from Gaussian models. • In fact, many attribute value distributions in Extremistan do not fit any known models well. • Examples: booksales, wealth, website hits. • Since extreme occurrences can greatly affect statistical properties of distributions from Extremistan, it is hard to make reliable inferences from sample data.

  5. Two examples Sample 100.000 Mexicans: • Height (Mediocristan): most extreme occurrence will move the average only 0.001% • Wealth (Extremistan): most extreme occurrence will move the average 467% • Getting Carlos Slim in your sample is a 3-4 sigma event (less than 0.1% chance), but it will blow your model of ‘mexican wealth’ wide open.

  6. The Barbell Approach • Extreme conservatism + extreme risk taking. Taleb makes money Taleb makes money Taleb makes money Taleb makes money

  7. … if you can’t barbell: • Have respect for time and nondemonstrative knowledge • Avoid optimization: learn to love redundancy • Avoid prediction of small-probability payoffs • Beware the ‘atypicality’ of remote events • Beware moral hazard with bonus payments • Avoid some risk metrics • Positive or negative black swans? • Do not confuse absence of volatility with absence of risk • Beware presentations of risk numbers

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