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Selection and Interpretation |
Stocks
are selected from the TradersWeb Newsletter and other
sources. We concentrate on companies with good performance
and /or good prospects with moderate volatility. Sensitivity
to our prediction algorithms is a key parameter.
We also provide links to other sites on the Web for
news, long term and intraday price graphs and other
information useful for making trading decisions.
There are four indicators; up, dn, cu, cd. The first
two are a prediction for a price movement in the indicated
direction. The second two denote that the prediction is no
longer valid, but that a reversal is not warranted.
As an example see our
predictions for Akzo Nobel
and comments on the interpretation of the signals.
The best way to use this information is to concentrate on a
few stocks, build up your own knowledge base using our
service and then, follow your selections closely.
Experience has shown that it takes only a few minutes
per week to become a successful investor. |
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During
the semester (Spring 1999) we presented a course entitled "Financial
Application of Neural Networks" at Syracuse University,
Department of Electrical Engineering and Computer Science.
We are teaching this course again this Spring.
The purpose of the course
is to introduce the student to the application of modern
computer technology and trading algorithms and to introduce
the students to the techniques used in trading in stocks and
options.
In particular, the use of neuro-fuzzy networks to
enhance the prediction process is stressed. The network uses
recent data relevant to trading in a particular stock and
learns which technical and fundamental criteria are best
suited for a prediction. Market conditions often change
abruptly, so learning is repeated often, sometimes daily.
Study of our examples
shows that we are consistently correct in a large percentage
of our predictions. Less obvious is the fact that we are
also consistently earlier in our predictions than other
programs of a similar nature. Even one day can make a large
difference in achievable gains.
Course Syllabus
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