How wavelets and genetic algorithms can assist Intelligent Hybrid Methodologies in handling data driven Stock Exchange daily trading

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  author =       "A Tsakonas and G. Dounias and A Merikas",
  title =        "How wavelets and genetic algorithms can assist
                 {Intelligent} {Hybrid} {Methodologies} in handling data
                 driven {Stock} {Exchange} daily trading",
  booktitle =    "Fuzzy {Sets} in {Management}, {Economics} and
  editor =       "C. Zopounidis and P. M. Pardalos and G. Baourakis",
  year =         "2001",
  publisher =    "World Scientific Publishers",
  month =        oct,
  pages =        "195--210",
  keywords =     "genetic algorithms, genetic programming, financial
                 decision support, neural networks, neuro-fuzzy systems,
  isbn13 =       "978-981-02-4753-9",
  URL =          "",
  DOI =          "doi:10.1142/9789812810892_0013",
  abstract =     "In this paper is explored the suitability of genetic
                 algorithms for constructing rule bases, as part of a
                 hybrid decision support architecture, involving neural
                 networks for wavelet-filtered daily stock rates of
                 change. Specifically, the main structure of the
                 suggested methodology combines a wavelet-based noise
                 removal system, a “multilayer perceptron feedforward
                 neural network” and finally a fuzzy system, which
                 provide the trader with both, linguistic and numerical
                 output, representing a buy/hold/sell strategy. The use
                 of wavelet filtering in data pre-processing, improves
                 the predictability of neural networks, however, it
                 involves the selection of proper wavelet bases.
                 Therefore, by applying genetic algorithms in fuzzy rule
                 bases for optimizing the decision policy, the paper
                 aims at offering a decision support, independent of the
                 selection of the wavelet basis. It is also demonstrated
                 how, based on the test results, the overall system is
                 able to make successful trend prediction, which is then
                 used to create an output similar to the policy that
                 traders would apply if foreword price movement was
                 considered to be known.",

Genetic Programming entries for Athanasios D Tsakonas Georgios Dounias A Merikas