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Hey Manohohman,
I would like to thank you for your brilliant "exposé" about Hurst
Exponent (also for the links).
I have the Tradestation code for Hurst Exponent but unfortunately, I am
not a expert in MS code.
Thanks for your help,
Karile
manohohman wrote:
>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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>
>
>
>
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