Neural Network Prediction and Decision Making System for Investment Assets

Cesar Valencia N, Alfredo Sanabria, Hernando González A, Carlos Arizmendi P, David Orjuela C

Producción científica: Capítulo en Libro/InformeContribución a la conferencia

Resumen

The problem is to test the weak hypothesis of efficient markets through three neural networks that can predict the trends of investment assets such as: The Dow Jones, gold and Euro dollar, according to theories of technical analysis to automate positions of both long and short investment in the Spot market. With regard to forecasting time series, multiple approaches have been tested, through statistical models such as [1–3], where forecasts are made from different information sources with characteristics differentiated (sasonality, tendency, periodicity), however, other actors have begun to gain strength by getting the first places in international competitions, this is the case of Neural Networks, in works published as [4–6] the results have shown that this type of model offers a real opportunity to work with time series of different characteristics.

Idioma originalInglés estadounidense
Título de la publicación alojadaAETA 2019 - Recent Advances in Electrical Engineering and Related Sciences
Subtítulo de la publicación alojadaTheory and Application
EditoresDario Fernando Cortes Tobar, Vo Hoang Duy, Tran Trong Dao
EditorialSpringer
Páginas262-272
Número de páginas11
Volumen685
Edición2020
ISBN (versión impresa)9783030530204
DOI
EstadoPublicada - ago. 11 2020
Evento6th International Conference on Advanced Engineering Theory and Applications, AETA 2019 - Bogota, Colombia
Duración: nov. 6 2019nov. 8 2019

Serie de la publicación

NombreLecture Notes in Electrical Engineering
Volumen685 LNEE
ISSN (versión impresa)1876-1100
ISSN (versión digital)1876-1119

Conferencia

Conferencia6th International Conference on Advanced Engineering Theory and Applications, AETA 2019
País/TerritorioColombia
CiudadBogota
Período11/6/1911/8/19

Áreas temáticas de ASJC Scopus

  • Ingeniería industrial y de fabricación

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