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Mike, thanks for the link.
I looked at the site. It looks interesting. As I mentioned in my
other posts, I really haven't advanced past a couple of MAs and one
or two other indicators. I've read about the Cycle guys, but it's
much too complex for me. I like really, really simple stuff.
Looking at his return on the Rydex funds, his timing models produced
a 26% year to date return. I've gotten 81% with my simple MAs and an
indicator or two. Last year the gap between his models and my models
(lose term) was even greater.
Everytime I compare what I'm doing with my simpleton approach, it
winds up beating the complex by a wide margin so I stick with it. All
the math in the Elliot and Gann stuff is over my head. Chaos and
fractals make me dizzy.
For cycles, I rely on these guys.
http://www.fourpillars.net/finance/predic.html
It's been really accurate and the cycles are based on tea bags or
something. I'm not sure, but it's fun to read and it's free.
JO
--- In Metastockusers@xxxxxxxxxxxxxxx, "Michael Bethell" <mdtmn@xxxx>
wrote:
> Hi Jo,
> You might find the work of Jim Curry of
interest
>
> http://cyclewave.homestead.com/MarketTurns.html
>
> Michael B
>
> -----Original Message-----
> From: manohohman [mailto:kelols@x...]
> Sent: Monday, 20 October 2003 2:17 AM
> To: Metastockusers@xxxxxxxxxxxxxxx
> Subject: [Metastockusers] Re: Hurst Exponent
>
> For all of those MS'er's who are going to ask, what's a Hurst
> Exponent. It's math concept from fractals and chaos theory. Here's
> the simplest explanation I've seen, and I've added some translation
> for you.
>
> The Hurst Exponent is a measure of the smoothness of fractal time
> series based on the asymptotic behaviour of the rescaled range of
the
> process. (Translation: it measures correlatons in a data series on
> any time scale. Simpler Translation: it measures the fractal
> dimension of a data series. Even Simpler Translation: it measures
how
> much fractals jump around--well sort of.)
>
> The Hurst exponent, H, is defined as:
>
> H:=log(R/S)/log(T)
>
> where T is the duration of the sample of data, and R/S the
> corresponding value of rescaled range.
>
> Hurst generalized an equation valid for the Brownian motion in
order
> to include a broader class of time series. In fact, Einstein
studied
> the properties of the Brownian motion and found that the distance R
> covered by a particle undergoing random collisions is directly
> proportional to the square-root of time T:
>
> R=k*T0.5
>
> where k is a constant which depends on the time-series. The
> generalization proposed by Hurst was:
>
> R/S=k*TH
>
> where H is the Hurst exponent.
>
> If H=0.5, the behaviour of the time-series is similar to a random
> walk;
>
> if H<0.5, the time-series covers less "distance" than a random walk
> (i.e., if the time-series increases, it is more probable that then
it
> will decrease, and vice-versa);
>
> if H>0.5, the time-series covers more "distance" than a random walk
> (if the time-series increases, it is more probable that it will
> continue to increase).
>
> Given a time series x(n), n=1,....N, H can be estimated by taking
the
> slope of (R/S) plotted vs. n in a log-log scale.
> H is related to the fractal dimension D:
>
> H=E+1-D
> where E is the Euclidean dimension (E=0 for a point, 1 for a line,
2
> for a surface). For one-dimensional signals, H=2-D
> H is also related to the "1/f" spectral slope:
>
> =2H+1
>
> I think this has to be programmed in C++ and then imported into MS
as
> a dll. Erik Long used to have a MS product for this. He may be out
of
> business but you can call and find out. His product for MS was
called
> Fractal Finance.
>
> He wrote an article in the May 2003 S&C called Making Sense of
> Fractals. Some code may be in there that's useful to you, but I
don't
> think so.
>
> Tetrahex
> 555 W. Madison Street
> Chicago, Illinois 60661
>
> Contact: Erik Long
> Contact number: 312.775.7468
>
>
> Some MS users have programmed a fractal noise measurement that
> approximates the Hurst and have used that successfully.
>
> Join this group and ask them for John Connors C++ code for Hurst,
or
> for an approximation of Hurst or if they know of any conversions.
> This group really loves that stuff. Find Igor. He knows about
> approximations in MS.
>
> http://groups.yahoo.com/group/Behavioral-Finance/
>
>
> I haven't really progressed past moving averages so this stuff is
way
> beyond me. I'm still trying to figure out cloning.
>
> However, many, many people have gone crazy trying to program the
> Hurst Exponent in MS, so Roy leave this one alone.
>
>
> JO
>
>
>
>
>
>
>
>
>
> --- In Metastockusers@xxxxxxxxxxxxxxx, karile <karile@xxxx> wrote:
> >
> > Hi,
> >
> > Can someone code the Hurst Exponent in Metastock ?
> >
> > Thanks for your help,
> >
> > Karile
>
>
>
>
>
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