Resumen

ARANGO, Adriana; VELASQUEZ, Juan D.  y  FRANCO, Carlos J.. FUZZY LOGIC TECHNIQUES FOR STOCK MARKET INDEXES FORECASTING: A LITERATURE REVIEW. Rev. ing. univ. Medellín [online]. 2013, vol.12, n.22, pp.117-126. ISSN 1692-3324.

Market index forecasting is an important task in financial engineered because is a necessary and important input in decision making. This study aims to assess the state of the art on the progress of market index forecasting using methodologies based on fuzzy inference and neuro-fuzzy neural networks, emphasizing the case of the Colombian stock market index (IGBC). We employed the systematic literature review methodology for answer four research questions. There is an important trend about the use of methodologies based on fuzzy inference for forecasting market indexes, explained by the accuracy of the forecasts in comparison with other traditional methodologies. Most of the research is focused on ''fuzzy time series'' methodologies and ANFIS, but, there are other promising approaches that have not been evaluated yet. There is a lack of research on the forecasting of the Colombian stock market index.

Palabras clave : Systematic literature review; nonlinear time series; stock indexes; fuzzy logic; ANFIS.

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