Neural network prediction and decision making system for investment assets

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

Research output: EventsScientific eventspeer-review

Abstract

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.

Original languageEnglish
Pages262-272
Number of pages11
DOIs
StatePublished - 2021
Event6th International Conference on Advanced Engineering Theory and Applications, AETA 2019 - Bogota, Colombia
Duration: 6 Nov 20198 Nov 2019

Conference

Conference6th International Conference on Advanced Engineering Theory and Applications, AETA 2019
Country/TerritoryColombia
CityBogota
Period6/11/198/11/19

Keywords

  • Assests
  • Decision making
  • Invesment
  • Neural network
  • Prediction

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