New Improved Version of SMFT-1 Released
Addaptron Software released a new version of Stock Market Forecast Tools SMFT-1. The software includes several improvements: models optimization, more different input file formats, and optional free Downloader. SMFT-1 is an integrated system that includes three major software modules: FTA-2 – a modified version of InvAn-4 that is a comprehensive tool used by serious investors for many years, the most popular software program SMAP-3 for stock market cycles analysis and forecast, and Neural Network Stock Trend Predictor NNSTP-2.
FTA-2 itself consists of six major modules:
- “Technical analysis” – more than 50 popular technical indicators; chart analysis; indicators (each separately or all) used as input for Neural Network (NN) to build 10-day price forecast. The forecasts from all indicators result into a single forecast – each forecast added with the weight proportionally to the current ability of the indicator to predict prices.
- “Waves” – Elliott Wave NN forecast.
- “Candles” – candlestick pattern NN forecast model.
- “Pattern recognition” – pattern-recognition filter and predictor.
- “Correlation” – correlation analysis tool to perform analysis and evaluate the future trend using a mutually-correlated pair (or in opposite correlation) with time shift.
- “Comprehensive 3-month fundamental-technical ratings model” – analyzing-predicting model that is based on key fundamental ratios and technical parameters reflecting a company-stock state and dynamics.
SMAP-3 is able not only to extract basic cycles of the stock market (indexes, sectors, or well-traded shares) but also to predict an optimal timing to buy or sell stocks. Its calculation mainly based on extracting basic cyclical functions with different periods, amplitudes, and phases from historical quote curve. Additionally, SMAP-3 enables finding optimal timing to buy/sell by analyzing months of year, days of month, and days of week (the calculation is based on statistical analysis).
NNSTP-2 is to help stock traders in predicting stock prices for short terms. It predicts future share prices or their percentage changes (can be chosen in settings menu) using Fuzzy Neural Network (FNN). It operates automatically when creating the FNN, training it, and mapping to classify a new input vector.
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