Black Swan

Revision as of 07:59, 11 April 2019 by Admin (talk | contribs) (Chapter 11 / How to look for bird poop)

Chapter 10 / The scandal of prediction

Финансовые аналитики не умеют прогнозировать.

This refers to scientific paper by Jean Philippe Bouchaud, Experts’ earning forecasts: bias,herding and gossamer information.

He surprised me with a research paper that a summer intern had just finished under his supervision and that had just been accepted for publication; it scrutinized two thousand predictions by security analysts. What it showed was that these brokerage-house analysts predicted nothing—a naïve forecast made by someone who takes the figures from one period as predictors of the next would not do markedly worse.

Иногда дополнительная информация токсична.

This refers to scientific paper Overconfidence in case-study judgements.

In 1965, Stuart Oskamp supplied clinical psychologists with successive files, each containing an increasing amount of information about patients; the psychologists’ diagnostic abilities did not grow with the additional supply of information. They just got more confident in their original diagnosis. Granted, one may not expect too much of psychologists of the 1965 variety, but these findings seem to hold across disciplines.

Фейковые эксперты, калибровка экспертных прогнозов.

This refers to scientific paper Competence in experts: The role of task characteristics.

The psychologist James Shanteau undertook the task of finding out which disciplines have experts and which have none.

This refers to scientific paper The accuracy of extrapolation (time series) methods: Results of a forecasting competition and The M3-Competition: results, conclusions and implications.

The most interesting test of how academic methods fare in the real world was run by Spyros Makridakis, who spent part of his career managing competitions between forecasters who practice a “scientific method” called econometrics—an approach that combines economic theory with statistical measurements. Simply put, he made people forecast in real life and then he judged their accuracy. This led to the series of “M-Competitions” he ran, with assistance from Michele Hibon, of which M3 was the third and most recent one, completed in 1999. Makridakis and Hibon reached the sad conclusion that “statistically sophisticated or complex methods do not necessarily provide more accurate forecasts than simpler ones.”

Нобелевская премия за модель GARCH, валидность которой не подтверждена.

Bio of Robert Eggel in Nobel Prize.

The econometrician Robert Engel, an otherwise charming gentleman, invented a very complicated statistical method called GARCH and got a Nobel for it. No one tested it to see if it has any validity in real life. Simpler, less sexy methods fare exceedingly better, but they do not take you to Stockholm.

Экономикс - башня из слоновой кости.

Economics is the most insular of fields; it is the one that quotes least from outside itself! Economics is perhaps the subject that currently has the highest number of philistine scholars—scholarship without erudition and natural curiosity can close your mind and lead to the fragmentation of disciplines.

Chapter 11 / How to look for bird poop

Sir Karl Raimund Popper, The Misery of Historicism. Технологические нововведения и изобретения непредсказуемы, и значит будущее принципиально непредсказуемо. Это центральная мысль в книге Поппера. Ввиду принципиальных невозможности в гуманитарных науках, их следует понизить до коллекционирования марок, эстетики и развлечений.

Это мысль Поппера в BS подтверждается множеством примеров. Например двое физиков из лаборатории Bell Labs в New Jersey при установке крупногабаритной антенны никак не могли избавиться от странных шумов. Совершенно случайно они обнаружили реликтовое излучение космоса а микроволновом диапазоне, дав новый старт космогонической теории Большого Взрыва.