An Initial Investigation of Choice Function Hyper-Heuristics for the Problem of Financial Forecasting

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@InProceedings{Kampouridis:2013:CEC,
  article_id =   "1239",
  author =       "Michael Kampouridis",
  title =        "An Initial Investigation of Choice Function
                 Hyper-Heuristics for the Problem of Financial
                 Forecasting",
  booktitle =    "2013 IEEE Conference on Evolutionary Computation",
  volume =       "1",
  year =         "2013",
  month =        jun # " 20-23",
  editor =       "Luis Gerardo {de la Fraga}",
  pages =        "2406--2413",
  address =      "Cancun, Mexico",
  keywords =     "genetic algorithms, genetic programming, EDDIE",
  DOI =          "doi:10.1109/CEC.2013.6557857",
  abstract =     "Financial forecasting is a vital area in computational
                 finance. This importance is reflected in the literature
                 by the continuous development of new algorithms. EDDIE
                 is well-established genetic programming financial
                 forecasting tool, which has successfully been applied
                 to a variety of international datasets. Recently, we
                 introduced hyper-heuristics to EDDIE. This was the
                 first time in the literature that hyper-heuristics were
                 used for financial forecasting. Results showed that
                 this introduction significantly benefited the
                 performance of the algorithm. However, an issue was
                 encountered in the way that low level heuristics were
                 selected during the search process, because it was
                 considered to be a static way. To address this issue,
                 in this paper we further improve our algorithm by
                 introducing a Choice Function, which is a score based
                 technique that offers a more dynamic selection of the
                 low-level heuristics. This paper presents preliminary
                 results, after having tested the Choice Function
                 approach with 10 datasets. These results show that the
                 introduction of the Choice Function is beneficial to
                 EDDIE, thus making it a very promising tool for future
                 investigation on financial forecasting problems.",
  notes =        "CEC 2013 - A joint meeting of the IEEE, the EPS and
                 the IET.

                 Also known as \cite{6557857}",
}

Genetic Programming entries for Michael Kampouridis

Citations