Channalyze 1.0.0
A World 1st, Channalyze is our new technical analysis module for predicting market movement through the recombination of recently-stable cycles and their correlation with channels. Tests show a predictability of around 90% (yes, that right, 90% ...
Last update
16 Aug. 2010
Licence
Free to try |
$979.11
OS Support
Windows
Downloads
Total: 569 | Last week: 1
Ranking
#819 in
Accounting & Billing Software
Publisher
Qudos Market Insight
Channalyze Publisher's Description
A World 1st, Channalyze is our new technical analysis module for predicting market movement through the recombination of recently-stable cycles and their correlation with channels.
Tests show a predictability of around 90% (yes, that right, 90% !) for direction and extent of movement 10 days into the future on many stocks. The predictable stocks are readily separated from those that are passing through a more random phase in their history.
Channalyze is the professionals' and enthusiasts choice alike: it's so simple to use, innovative and unique in the market place.
Channalyze Enables You To:
1) Determine which securities are passing through a phase when their major cycles are stable
2) Determine when these stable cycles are like to change direction
3) Add these cycles together to predict major market turning points
4) Categorize cycles into low, medium and high wavelengths
5) Add the stable cycles within each of these three wavelength categories to predict short, medium and long-term movements
6) Confirm these movements by Channel Analysis
Followers of Brian Millard's methods will understand that trends are represented by centered moving averages. The difficulty is that centered averages terminate half a span back in time. This of course means that the direction of the trend is not known either in this gap or into the immediate future. Channalyze makes the assumption that trends can be decomposed into individual cycles. It is possible, with some error, to predict the future path of individual cycles into the near future. Thus by focussing on individual cycles, each one can be predicted into the future, and then summed to provide a good estimation of future movement.
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