SMFT-2

Comprehensive system for stock market traders and investors, consists of the 5 modules. Technical indicators processor determines which indicator should be trusted more for particular market conditions and specific shares using back-testing simulation. It composes the forecast from indicators signals with weights accordingly to predictive ability of each indicator using Neural Network (NN). The pattern similarity module searches for the best matches by scanning all historical data and ranks them on the basis of maximum correlation and minimum deviation within given period using EOD prices and volume data. NN is used to apply candlesticks pattern to predict the next candlestick (day or week in width).

Module Waves analyzes waves and predicts a future high or low price similar to Elliott Wave theory of recurrent stock market price structures; the software takes into consideration all extracted waves. Due to employing NN it enables identifying both the price and date of extremes.

Cycle predicting module is designed to reveal cycles, build forecast, and find optimal timing to buy and sell. Additional analysis includes such cycles as, month of year, day of month, and day of week. It operates automatically when creating the NN, training it, and mapping to classify a new input vector. The software provided with free data Downloader, as well as, input data can be downloaded for free.