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Artificial Foreteller of Stocks & Commodities


 

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.

 

Description

Screenshot with bar charts for intraday tradingArtificial 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.

 

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.

 

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:

  1. Preprocessor.
  2. Neural Network Builder.
  3. Interpreter.
  4. GUI.

Interested parties can contact us at:e-mail

 

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Preprocessor

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