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Artificial
Foreteller of Stocks & Commodities
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To
demonstrate huge potentials of associative self-building neural
network in prediction, and classification we developed Artificial
Foreteller of Stock and Commodities. Associative self-building neural
network works over and accumulates vast amount of information about
market, its trends, and values of different indicators to provide
end user with trade forecast.
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Description
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Artificial
Foreteller is a new powerful system that demonstrates extraordinary
ease of use for prediction situations in trading. Both day-traders
and long-term traders can use the system. Artificial Foreteller
analyses current input values and predicts future values and
outcomes. That means Artificial Foreteller tries to predict
what will happen, and not
what already happened. In other words,
we would like to get prediction if next trade period is favorable
for trade or not. As it well known human being can operate
with not more than 7 criteria at the same time. Most of traders
choose not more than three or four most important from their
point of view indicators to analyze situation at the market.
As distinct from human being Artificial Foreteller is able
to operate as many different criteria and indicators as it
has been trained.
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Artificial
Foreteller "remembers" thousands trade situations
in its neural network and uses them for analysis of the current
one. It forms prediction based on derived from train data
set regularities and analogies among analyzed and known situations.
Artificial
Foreteller was written in VC++ and works under MS Windows98/me/NT/2000/XP.
A virtual memory storage was developed to store neural network
and let the system to create network with size more than size
of PC central memory. With help of virtual memory storage neural
network became portable and can be transferred among different
PCs.
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The
system provides users with:
- Full Graphical User Interface (GUI).
- Broad range of indicators.
- Possibility for day-trading and long-term trade.
- Trends.
- Buy/sell signals.
- Prognosis on whether next period would be favorable
for trade or not.
- Use of color to separate buy and sell periods
and favorable periods for trade from unfavorable once.
- Continuous training on base of recent trade
periods.
Artificial
Foreteller has the following structure:
- Preprocessor.
- Neural Network Builder.
- Interpreter.
- GUI.
Interested
parties can contact us at:e-mail
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