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A cooment with regards to your comments on the Hurst "Like" DE AFL I
posted in the library ... There really are no predictions beyond
current bar, there are only extensions of the CMA "based" DE's up to
the current bar ... The idea behind this AFL is that the shorter
length DE's tend to collect near the bottom at lows and near the at
highs of the longer length DE channels ...
As far as some of the other methodologies you mention ... I find
both Trig Fit's and NON Ehler's Maximum Entropy Methods to be very
interesting in their predictions ... However, I am not in a position
to post code for either of these at this time ...
--- In amibroker@xxxxxxxxxxxxxxx, "Tom Tom" <michel_b_g@xxx> wrote:
>
> From: tomy_frenchy <michel_b_g@xxx>
>
>
> Hello,
>
> After the technicals post about quotes predictions (hurst,
polyfit) on
> amibroker software, i was asking me if someone here explore
different
> prediction technics and if he could give us his feedback on
accuracy of
> prediction depending the forecast tools. It will be very nice.
>
> 1- Prediction with AR model
>
> For now I am working on AR (Auto-Regressive model) prediction. I
post code
> here : http://www.amibroker.com/library/detail.php?id=757
>
> You will find a jpg picture joined to this mail. The data before
the
> vertical bar are those used to compute the AR coefficient and
behind the
> vertical bar are those predicted (and out-of-sample). The data
before the
> verticale bar colored in blue are predicted too (because of CMA
for
> denoising who lag) but are in-sample. So i resume (sorry for my
english
> don't be affraid ; ) ) :
>
> Green : computed CMA in-sample, Blue: predicted with AR model in-
sample,
> Red: predicted with AR model out-sample
>
> Prevision are sometimes good (if data present enough cyclic
pattern and
> number of AR coeff is enough high to take in consideration the
patterns).
> Somtimes they are wrong too, as always héhé : ))
>
> CMA is used here with what i call a false "T3 zerolag". So it
denoise the
> data and keep the averaging synchronized with the data.
>
>
>
> 2- Prediction with PolyFit / Hurst CMA
>
> Thanks to Fred for this very nice code :
> http://www.amibroker.com/library/detail.php?id=741
>
> Thanks too to Andy for this code :
> http://www.amibroker.com/library/detail.php?id=753
>
> CMA is used here (manually (hurst de) or automaticaly (cycle
highlighter))
> to extract one (cycle highlighter) or differents (hurst de) MA
with
> different periods wich keeps synchronized with data, and
prediction is made
> with polyfit.
>
> More information on the recent post named "Hurst Channel's".
>
>
>
> 3- Prediction with EMA/DEMA/TEMA (seems not interesting to go to
higher
> order prediction)
>
> I posted code for DEMA prediction here :
> http://finance.groups.yahoo.com/group/amibroker/message/102710
>
> Principe: an EMA or DEMA or TEMA is computer. From this is
computer a linear
> regression or higher order regression. Data are predicted using
the result
> of this regression.
>
> Forecasting is very poor and can indicate only the trend to come.
It cannot
> show future turning point and other variation, nor show
pattern/cycle
> repetition.
>
> More information : http://www.duke.edu/~rnau/411avg.htm ,
>
http://espse.ed.psu.edu/edpsych/faculty/rhale/statistics/statlets/use
rmanual/sect6_3_3.htm
>
>
>
> 4- Prediction with different CMA automaticaly computed (CMA,
downsampling
> and interpolation, trigfit)
>
> Post about his can be found here :
> http://finance.groups.yahoo.com/group/amibroker/message/102530
>
> For now it seems a very interresting approach. It could take
automaticaly
> pattern in consideration and is more consistent than AR prediction
i think
> wich sometimes can provides some divergent prediction (like
polyfit with
> high order).
>
> Fred could you tell us more about this work and maybe post some
code about
> it ? Will be very nice.
>
>
>
> 5- Another prediction tehnics
>
> We can find non-linear prediction (Kalman, Network prediction,
etc...)...
> seems hard to compute. Someone try this ?
>
> For linear prediction : ARMA, ARIMA, Trigonometric Fit, ARCH,
GARCH (for
> volatility prediction)
>
> Based on spectral analizis to extract cycle :
>
> for several cycle : FFT (different version exist depending speed,
> resolution), Density Spectrum Power,
>
> Prony, Pisarenko, Wavelet
>
> for the main cycle : MESA (Ehlers Dominant Cycle Period), CMA
>
> Pisarenko method seems to offer better resolution from FFT and
less
> constrain, but suffer that is is more difficult for computing it.
>
>
>
>
>
> So can you provide us some information on your work on prediction
with
> amibroker. Tips, code, experience, trading result in applying
prediction and
> anything who can help to go forward in this topic is welcome.
>
> Cheers,
>
> Mich.
>
> _________________________________________________________________
> Retrouvez tout en un clin d'?il avec Windows Desktop Search !
> http://desktop.msn.fr/
>
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