A Genetic Type-2 fuzzy logic based system for financial applications modelling and prediction

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "Dario Bernardo and Hani Hagras and Edward Tsang",
  title =        "A Genetic Type-2 fuzzy logic based system for
                 financial applications modelling and prediction",
  booktitle =    "IEEE International Conference on Fuzzy Systems (FUZZ
  year =         "2013",
  month =        jul,
  keywords =     "genetic algorithms, genetic programming, type-2 fuzzy
  DOI =          "doi:10.1109/FUZZ-IEEE.2013.6622310",
  ISSN =         "1098-7584",
  abstract =     "Following the global economic crisis, many financial
                 organisations around the World are seeking efficient
                 frameworks for predicting and assessing financial
                 risks. However, in the current economic situation,
                 transparency became an important factor where there is
                 a need to fully understand and analyse a given
                 financial model. In this paper, we will present a
                 Genetic Type-2 Fuzzy Logic System (FLS) for the
                 modelling and prediction of financial applications. The
                 proposed system is capable of generating summarised
                 optimised type-2 FLSs based financial models which are
                 easy to read and analyse by the lay user. The system is
                 able to use the summarised model for prediction within
                 financial applications. We have performed several
                 evaluations in two distinctive financial domains one
                 for the prediction of good/bad customers in a credit
                 card approval application and the other domain was in
                 the prediction of arbitrage opportunities in the stock
                 markets. The proposed Genetic type-2 FLS has
                 outperformed white box financial models like the
                 Evolving Decision Rule (EDR) procedure (which is based
                 on Genetic Programming (GP) and decision trees) and
                 gave a comparable performance to black box models like
                 neural networks while the proposed system provided a
                 white box model which is easy to understand and analyse
                 by the lay user.",
  notes =        "Also known as \cite{6622310}",

Genetic Programming entries for Dario Bernardo Hani Hagras Edward P K Tsang