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All of these relate to multiple dimensions. You typically have a
sample, say of gender vs age vs weight, and use this analysis to see
if there is some relationship between the lot. This is what I am
after. What are the dimensions you are working with. Is it RSI vs MA
vs Close vs Volume? The image referred to in your other post has
three dimensions at least - x, y and pixel color and makes a lot of
sense to use. If you are looking at historical closes, then you do
not need Hotelling, just standardize it using
z = [ x - mu ] / sigma
in MSFL, something like
X = C / Ref(C,-1) - 1;
Z = ( X - Mov( X, 50, S ) / StdDev( X, 50 )
may do the trick, although this is OTC (off-the-cuff) and I am
especially not sure that the StdDev function is correct. You get what
you pay for I guess, as super would say, I also guess....
Regards
MG Ferreira
TsaTsa EOD Programmer and trading model builder
http://www.ferra4models.com
http://fun.ferra4models.com
--- In equismetastock@xxxxxxxxxxxxxxx, "formulaprimer"
<formulaprimer@xxxx> wrote:
> Also what about the following possiblity
> Variance-Stabilizing Transformations of the Correlation Coefficient
> Description
> z.transform implements Fisher's (1921) first-order and Hotelling's
> (1953) second-order transformations to stabilize the distribution of
> the correlation coefficient. After the transformation the data
> follows approximately a normal distribution with constant variance
> (i.e. independent of the mean).
>
> Hotelling's transformation requires the specification of the degree
> of freedom kappa of the underlying distribution. This depends on the
> sample size n used to compute the sample correlation and whether
> simple ot partial correlation coefficients are considered. If there
> are p variables, with p-2 variables eliminated, the degree of
> freedom is kappa=n-p+1.
>
>
> --- In equismetastock@xxxxxxxxxxxxxxx, mgf_za_1999 <no_reply@xxxx>
> wrote:
> > Sorry, I am mixing up two things here, the Hotelling transform and
> the
> > Hotelling T2 statistic. Both are inherently multidimensional,
> which
> > is why I am asking the context. I think the Hotelling transform
> > entails calculating the eigenvalues - there is this neat way of
> doing
> > that. You just keep on raising whatever matrix you are working
> with
> > to higher powers and the eigenvalues sort of fall out. It is
> called
> > the power technique if I remember correctly. I don't think it is
> > doable in MS, since, being multidimensional, you need to work with
> > matrices and so on. But again, give the context and maybe I can
> help
> > a bit.
> >
> > Regards
> > MG Ferreira
> > TsaTsa EOD Programmer and trading model builder
> > http://www.ferra4models.com
> > http://fun.ferra4models.com
> >
> > --- In equismetastock@xxxxxxxxxxxxxxx, mgf_za_1999 <no_reply@xxxx>
> wrote:
> > > Could you give the context of the Hotelling transform? I've
> never
> > > seen the Hotelling T2 statistic used in technical analysis. I
> could
> > > assist maybe, if I understand how it is used. The Hotelling T2
> stat,
> > > if this is what you refer to, is usually used in multivariate
> analysis
> > > but there is a much simpler formula that works in one dimension.
> > >
> > > Regards
> > > MG Ferreira
> > > TsaTsa EOD Programmer and trading model builder
> > > http://www.ferra4models.com
> > > http://fun.ferra4models.com
> > >
> > >
> > > --- In equismetastock@xxxxxxxxxxxxxxx, "formulaprimer"
> > > <formulaprimer@xxxx> wrote:
> > > > Does anyone have a code for Hotelling Transformfor small
> sample sizes
> > > > (e.g,: short period lengths say n<25)
> > > >
> > > > Please do not refer to a pay site for indicators. I am in a
> forum
> > like
> > > > this to get free source codes.
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