thedatarati

With intelligent design, we will be able to predict the behaviour of a consumer. Is this true? How much can we trust the numbers? Is understanding randomness worth our time?

http://www.edge.org/3rd_culture/taleb04/taleb_index.html

Quantitative economics, particularly finance, has not been a particularly introspective or empirical science. Wilfredo Pareto had the intuition of type 2 uncertainty in the social world (Black Swan style) more than 100 years ago with his nonGaussian distribution. Shamefully mainstream economists ignored him because his alternative did not yield "tangible" answers for academic careers. Financial economists built "portfolio theory" that is based on our ability to measure the financial risks. They used the Bell-Shaped (and similar) distribution which proliferated in academia and yielded a handful of Nobel medals.

Everything reposes on probabilities being stationary, i.e. not changing after your observe them, assuming what you observed was true. They were all convinced of measuring risks as someone would measure the temperature. It led to series of fiascos, including the blowup of a fund called Long-term Capital Management, co-founded by two Nobel economists. Yet it has not been discredited — they still say "we have nothing better" and teach it in Business Schools. This is what I call the problem of gambling with the wrong dice. Here you have someone who is extremely sophisticated at computing the probabilities on the dice, but guess what? They have no clue what dice they are using and no mental courage to say "I don't know".

Is it worth our struggle to comprehend the incomprehensible?

Labels: predictive modelling, randomness