Title :
A model for stock price forecasting based on ARMA systems
Author :
Anaghi, M.F. ; Norouzi, Yaser
Author_Institution :
Dept. of Electr. Eng., Amirkabir Univ. of Technol., Tehran, Iran
Abstract :
The Prediction of the future values of a stock market signal on the basis of its past and present data series, is one of the most necessities of all financial applications. In this study, one special stock market signal is considered and analyzed using “ARMA” model with different number of poles and zeros, in order to estimate the values for the next days` prices. The estimated and the actual data for the next day is compared and the amount of error for each system is calculated, resulting into selection of most efficient model.
Keywords :
autoregressive moving average processes; forecasting theory; pricing; stock markets; ARMA systems; autoregressive moving average model; data series; financial applications; next day price values estimation; pole and zero; stock market signal; stock price forecasting model; Autoregressive processes; Computational modeling; Forecasting; Hidden Markov models; Mathematical model; Predictive models; Stock markets; Autoregressive Moving Average(ARMA); Concepts of Price and Return; Error in Mean Square sense; White Gaussian Noise(WGN) signal;
Conference_Titel :
Advances in Computational Tools for Engineering Applications (ACTEA), 2012 2nd International Conference on
Conference_Location :
Beirut
Print_ISBN :
978-1-4673-2488-5
DOI :
10.1109/ICTEA.2012.6462880
