So it is extraordinary than in Financial "industry" such rigor is just not only ignored but elevated to the rank of veneration for "modern portfolio" theory like Markovitz, CAPM, B&S etc. which assume normal law. Even even after LTCM sunk the attitude of the quants continue to be ... quasi-mystic because that's what mysticism means : to believe in something that doesn't exist in other industries although the conditions in financial "industry" are even more questionable than in traditional one. So these "rational" traditional quants who criticise the mysticism of chartists should also look themselves in a mirror 
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.Quote from harrytrader:
Unfortunately in nearly any undergraduate and even higher level statistical courses teachers seem to make always believe that normal laws are most often good approximations without saying that "good" can be really subjective ... like this one:
http://davidmlane.com/hyperstat/normal_distribution.html
"One reason the normal distribution is important is that many psychological and educational variables are distributed approximately normally. Measures of reading ability, introversion, job satisfaction, and memory are among the many psychological variables approximately normally distributed. Although the distributions are only approximately normal, they are usually quite close. A second reason the normal distribution is so important is that it is easy for mathematical statisticians to work with. This means that many kinds of statistical tests can be derived for normal distributions. "
Whereas when you read statistical books written not by teachers but by professional statisticians who had worked in industries like Shewart or Deming this is different. For example I have already quoted a french statistical book untitled "Statistical techniques : rational tools for making choices and decisions" written by a chief engineer of Military Air Force) you can read contrary opinion to the book-school point of view of the teacher above:
"Contrary to natural phenomenas, economical phenomenas must take into account the intervention of humans who don't always obey to random law"
Later on he says that not only it don't always obey to random law but most frequently it doesn't
Walter Shewart in 'Statistical method from the viewpoint of Quality Control'" said :
"When a 'scientist' makes an error by using statistical theory it becomes a 'scientific law', but when an industrial statistician makes such error he will sure be accused and have big problems."
Contrary to common opinions, he insist in a whole chapter that statistical rigor in industry involving series production has to be much more harsh than in science because in such cases statistical errors will have effect on millions of products and immediatly the person responsable of that will be hanged. He says that since conditions on industry is much less controllable than in science laboratories one musn't be loose with hypothesis by conveniency but on the contrary must be even more carefull with the hypothesis.
