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> Comparing that to a 12EMA...
> From my perspective, X1 and X2 actually appear smoother.
So they should, Preston - both x1 & x2 are SMAs (Simple Moving
Averages). Same data/period SMAs are always smoother than EMAs.
There is little or no benefit in using Exp/Log over Mov(DataArray,
Periods,S).
jose '-)
--- In equismetastock@xxxxxxxxxxxxxxx, pumrysh <no_reply@xxxx> wrote:
>
> MG,Jose,
>
> Not so quick to the cubicle!
> There was a coding error. The fix is below:
> y:=C;
> n:=12;
> x1:=Exp(Sum(Log(y),n)/n);
> x2:=Exp(Mov(Log(y),n,S));
> x1;x2
>
> That being said, there is a slight difference between x1 and x2 when
> compared. Comparing that to a 12EMA of the close there is still
> another difference. From my perspective, X1 and X2 actually appear
> smoother. So we have a new way of writing an exponential moving
> average.
>
> Finally, MG I've used the sum method to derive a SMA before.
> I always enjoy new methods of writing moving averages.
>
> Thanks to both of you for the mental stimulus.
>
> Preston
>
>
> --- In equismetastock@xxxxxxxxxxxxxxx, "Jose Silva"
> <josesilva22@xxxx> wrote:
> >
> > > 1000 * exp( Cum( log( y / 1000 ) ) )
> >
> > In *theory*, this would be quite useful in accumulating large
> values
> > (such as Volume), but unfortunately MetaStock cannot handle large
> > values for the Exp() function, so there is no advantage here.
> >
> > Here is an example:
> > Exp(Cum(Log(V/1000)))*1000
> >
> >
> > > Exp( Sum( Log( y ), n ) / n )
> > > or simply
> > > Exp( Mov( Log( y, n, S ) ) )
> >
> > Neither of these is an improvement on Mov(y,n,S).
> >
> >
> > MG, back to your modeling cubicle with you...
> >
> >
> > jose '-)
> > http://www.metastocktools.com
> >
> >
> >
> > --- In equismetastock@xxxxxxxxxxxxxxx, "MG Ferreira" <quant@xxxx>
> > wrote:
> > >
> > > OK, here is a quick, off the cuff example. The Cum function
> > >
> > > Cum(y)
> > >
> > > gives
> > >
> > > y1 + y2 + y3 + ...
> > >
> > > What if you want
> > >
> > > y1 * y2 * y3 * ...
> > >
> > > Well, use
> > >
> > > exp( Cum( log( y ) )
> > >
> > > This will generally give an overflow quickly, unless you use
> > > smallish values, so you may need to rescale it to get it to
work,
> > > ie calculate
> > >
> > > 1000 * exp( Cum( log( y / 1000 ) ) )
> > >
> > > If you think the Cum function is useful, then this must appeal
to
> > > you as well!
> > >
> > > Another example, the geometric average. The simple moving
average
> > > is defined as
> > >
> > > ( y1 + y2 + y3 + ... + yn ) / n
> > >
> > > Of course, in MSFL we all use
> > >
> > > Mov(y,n,S)
> > >
> > > to calculate this, but we could also use
> > >
> > > Sum(y,n) / n
> > >
> > > to get the answer the brute-force way.
> > >
> > > The geometric moving average, which may actually be more
> applicable
> > > to markets due to the exponential growth often seen in prices,
> > > is defined as
> > >
> > > ( y1 x y2 x y3 x ... x yn ) ^ ( 1 / n )
> > >
> > > To do this in MSFL, use
> > >
> > > Exp( Sum( Log( y ), n ) / n )
> > >
> > > or simply
> > >
> > > Exp( Mov( Log( y, n, S ) ) )
> > >
> > > Regards
> > > MG Ferreira
> > > TsaTsa EOD Programmer and trading model builder
> > > http://www.ferra4models.com
> > > http://fun.ferra4models.com
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