Stock NeuroMaster 1.33

Stock market prediction based on neural networks and advanced technical analysis

Stock NeuroMaster is a stock prediction tool based on Neural Networks with advanced technical analysis module. Supported data sources: CSV, Metastock database and free online stock quotes. Maximize your profit by predicting the best BUY/SELL moments.



Software Specs

Publisher:............ StockNeuroMaster

License:............... Shareware

Price:................... $190

Expire: ................ 14

File size:.............. 2.98 MB

Downloads:......... 1578

Release date:...... 16 Apr 2009

Last update:........ 03 Jun 2011

Language:............ English

Publisher review for Stock NeuroMaster 1.33:

Review by: StockNeuroMaster
Stock NeuroMaster is a charting software for traders, investors and brokers, with stock prediction module based on Neural Networks, detailed trading statistics, very easy-to-use interface, free online stock quotes. It maximizes your trading profit and minimizes losses by predicting the best BUY/SELL moments for your favorite stocks.
Advanced technical analysis module offer the most important indicators. Data importing module allows you to create models using CSV data files or Metastock database. Stock NeuroMaster is highly tailored and specially developed for both professional stock traders and beginners.
Requirements:
Pentium 300MHz, 64MB of RAM, Internet access

Operating system:
Win95,Win98,WinME,WinXP,Windows2000,Windows2003

Limitations:
Evaluation version is fully functional

Release notes:
Major Update

Whats new in version 1.33:
1. Modernization and optimization of stock prediction module. 2. Added new modern models based on current stock market situation. 3. Fixed bug: problem with a previous stock signals after update of model. 4. Many minor bugs are fixed.

Download Stock NeuroMaster 1.33

Stock NeuroMaster screenshots:

Stock NeuroMaster 1.33 screenshot. Click to enlarge!

Stock NeuroMaster download tags:

stock trader investor market stock prediction stock forecasting market neural networks signals

Copyright information:

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