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I think when applying Jurik's JMA you must think of it in terms of
non-linear statistical analysis. IE: Whereas a straight line can be drawn
through a data set using a least squares regression, JMA is a non-linear
regression using a proprietary error correcting technique. Infact, if you
look at "R-squared" as being a measurement of how "well" data fits a
linear regression line, (I believe Mark took this approach) you might also
perceive that Jurik's CFB is a non-linear R-Squared measurement,
especially if you do a "CFB ratio" and use 0 and 1 as your min and max
values and compare this to the TS R-squared indicator. (or even ADX for
that matter, although I prefer R-squared to ADX.)
I have had much more success in building indicators and breakout lines
since I have adopted this viewpoint. I even have a VIDYA that uses CFB
ratio that goes from 0 to 1 instead of using R-squared or CMO as the
standard VIDYA does. Much of my NN work requires smoothing and detrending
data before it becomes useful as an input. JMA is an excellent tool for
this and should often be considered when creating oscillators and
indicators (that are "way" lagged anyway) - it often allows you to reduce
the "lookback" and maintain smoothness (although now, I don't use
oscillators for trading - I have more success by just drawing trendlines.
HA HA!).
Bob Perry
San Jose, CA
rudolf stricker <lists@xxxxxxxxxxx> wrote:
> Lag in many or most indicators is a consequence of some immanent
> integration effects. Therefore, lag can be reduced considerably by
> applying some amount of differentiation to the indicator.
>
> mfg rudolf stricker
> | Disclaimer: The views of this user are strictly his own.
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