Stock market statistical data analysis for prices forecasting and trading decision support

Abstract

A general problems and methods for stock market statistical analysis are analyzed. A new method for stock price forecasting problem is considered based on a time series structural decomposition approach realized in special assignment of wave component auto-regression model as a superposition of harmonics with tuning frequencies. Computer simulation has been fulfilled in order to evaluate the performance of proposed method and algorithms.