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"kut2k2" <kut2k2@xxxx> wrote:
"The problem here is that sometimes you *want* significant lag."
Pfff.... Only a non-trader would come up with such a ridiculous
statement. Any amount of trading lag in the markets is absolutely
deadly.
".. the key is to find the best data-adaptive smoothing factor
possible."
No amount of adaptive smoothing is going to compensate for the fact
that a lagging indicator is based on two-dimensional historical data,
meaning it fails to consider the bigger picture - major market
influences. Price action is generally composed of only 30% local
influences, and at least another 30% of major market influences - the
rest being market noise.
If one's aim is a successful trading career, the key is actually to
think outside the square and concentrate on doing something different
from the other 90% of traders. Don't waste time with trying to build
a better mouse trap, if you want to win the rat race.
jose '-)
--- In amibroker@xxxxxxxxxxxxxxx, "kut2k2" <kut2k2@xxxx> wrote:
>
> --- In amibroker@xxxxxxxxxxxxxxx, "Corey Saxe" <res1wgwl@xxxx>
wrote:
> > From Stocks & Commodities V. 18:7 (July 2000) (pp. 20-29): Optimal
> Detrending by John F. Ehlers
> >
> > modified optimum elliptic filter in TradeStation EasyLanguage:
> > Smooth = 0.13785*(2*Price - Price[1]) + 0.0007*(2*Price[1] -
> > Price[2]) + 0.13785*(2*Price[2] -Price[3]) + 1.2103*Smooth[1] -
> > 0.4867*Smooth[2]
> >
> > Or, algebraically:
> >
> > Smooth = 0.13785 (2 x Price - Price[t-1]) + 0.0007 (2 x Price[t-1]
> > - Price[t-2]) + 0.13785 (2 x Price[t-2] - Price[t-3]) + 1.2103
> >
> > (Smooth[t-1] - 0.4867 x Smooth[t-2])
> >
> > where Price=(High+Low)/2
> >
> >
> >
> > -CS
> >
> > ----- Original Message -----
> >
> > From: raven4ns
> > To: amibroker@xxxxxxxxxxxxxxx
> > Sent: Saturday, October 23, 2004 7:58 AM
> > Subject: [amibroker] re:Ehlers Modified Optimal Elliptal filter
> >
> >
> >
> > Hello,
> > Does anyone know where I might find this filter? I was looking
> > at the new Jurik MA and this certainly looked like a reasonable
> > substitute. Thank you.
> >
> > Tim
>
> I'm not convinced this filter is all that "optimal". According to
> Ehlers:
>
> "... I have been curious about how to design an optimum smoothing
> filter. I set one criterion to be that the smoother could have no
> more than a one bar lag. An elliptic filter provides the maximum
> amount of smoothing under the constraint of a given lag. So, using
> MATLAB, I designed an elliptic filter ..."
>
> The problem here is that sometimes you *want* significant lag.
Here's
> the sitch: most filters affect both signal and noise. Filtering
noise
> is good: that's what you want to get rid of. But filtering signal is
> bad: that's where lag and attenuation comes from. So in areas of
low
> signal-to-noise ratio, you want a lot of filtering, and in areas of
> high SNR, you want little or no filtering. The only way to
accomplish
> this for non-stationary, non-linear time series like financial data
is
> with an adaptive moving average. Most AMAs are basically variable
> EMAs, but Jurik denies this is what his AMA is. Maybe so. For the
rest
> of us "home-brewers", the key is to find the best data-adaptive
> smoothing factor possible.
>
> Good trading,
> kut2k2
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