@calvinfroedge@AndreasSteno Also imo you are right @calvinfroedge. Low variance and slightly higher mean is exactly what is needed to make existing things cheaper and better.
@calvinfroedge@AndreasSteno Averages matter (no pygmy math/phys geniuses) but variance is the actual driver for extreme outcomes.
Assumes Lynn and Murray were right not Hsu.
correlation based on non-stationary data yields a random variable. Corr is well defined but sample corr does not converge to it. You diff(1) to try to make it stationary.
@INArteCarloDoss@nickgiva1@CumLordeAwards Is Steno a “guru“? Why isn't anyone saying anything?
@GordonJohnson19@GLJ_Research@crossbordercap Correlations will have to be measured in non-stationary time series (i.e. changes) and then you see that central bank liquidity is only a fraction of the total explanation
This is statistics 101 mate
@WifeyAlpha You can add reversal to trend momo by fitting a 90-deg rotated S-like sigmoid on the output. This will revert the pnl allocation to zero when trend momo gets extreme. You knew that already, it works don't doubt it.