I knoew when I saw that title it would trigger me! Sure did: Number two, the Bootstrap. It is the "Stationary Bootstrap" because it can only be used on statio

I knoew when I saw that title it would trigger me! Sure did: Number two, the Bootstrap. It is the "Stationary Bootstrap" because it can only be used on stationary data (for very obvious reasons). Problem is that tests for stationarity are very poor. I have seen it used in academic finance to prove technical analysis. Yes, really (A clue to the clueless - except in very special circumstances technical analysis does not work). Completely inappropriate to bootstrap financial returns data as they are not stationary. I am talking about White's Reality Check: which was devised by Herbert White who was a Distinguished Professor of Economics at the University of California. It is completely bananas, (final return data is not stationary. Bootstrapping it gives random noise. Duh!). When I looked at it about decade ago the paper it was developed in (two papers actually) were among the most cited in the field. I am not convinced that it can be used in stationary data, though I only have experience debunking it, not making good use of it. If something seems too good to be true.... And the bootstrap promises to take your too small number of data and make it into a lot of data. I see the paper here did not bother with stationarity. I stopped reading there. I cannot bear the myths and self deception statisticians tell themselves. I did it as a graduate student for far too long.