A Self-Organizing Neural Fuzzy System to forecast the price of Ecopetrol shares

Author

González, José Alejandro Avellaneda ; Rey, Cynthia María Ochoa ; García, Juan Carlos Figueroa

Author_Institution

Dept. of Electron. Eng., Univ. Distrital Francisco Jose de Caldas, Bogota, Colombia

fYear

2012

Firstpage

1

Lastpage

6

Abstract

This paper shows a Self Organizing Neural Fuzzy System (SONFS) applied to Ecopetrol shares forecasting. This time series is interesting due to its volatility, becoming a complex problem for classical analysis. A statistical analysis of the residual is presented to verify its results. According to these results the model presents a good performance would allow its employment as an auxiliary tool for decision making applications with a low computational cost.

Keywords

fuzzy neural nets; petroleum; pricing; self-organising feature maps; statistical analysis; stock markets; time series; SONFS; classical analysis; decision making application; ecopetrol share price forecasting; residual statistical analysis; self-organizing neural fuzzy system; stock market; time series; volatility; Autoregressive processes; Computational modeling; Forecasting; Fuzzy systems; Organizing; Testing; Time series analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence for Financial Engineering & Economics (CIFEr), 2012 IEEE Conference on

Conference_Location

New York, NY

ISSN

PENDING

Print_ISBN

978-1-4673-1802-0

Electronic_ISBN

PENDING

Type

conf

DOI

10.1109/CIFEr.2012.6327802

Filename

6327802