Combining Ordinal Financial Predictions with Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Tsang:2000:COF,
  author =       "Edward P. K. Tsang and Jin Li",
  title =        "Combining Ordinal Financial Predictions with Genetic
                 Programming",
  volume =       "1983",
  year =         "2000",
  booktitle =    "Intelligent Data Engineering and Automated Learning -
                 IDEAL 2000: Data Mining, Financial Engineering, and
                 Intelligent Agents",
  series =       "Lecture Notes in Computer Science",
  editor =       "Kwong Sak Leung and Lai-Wan Chan and Helen Meng",
  pages =        "532--537",
  address =      "Shatin, N.T., Hong Kong, China",
  month =        "13-15 " # dec,
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-41450-9",
  ISSN =         "0302-9743",
  CODEN =        "LNCSD9",
  bibdate =      "Tue Sep 10 19:08:58 MDT 2002",
  acknowledgement = ack-nhfb,
  URL =          "http://www.cs.bham.ac.uk/~jxl/cercialink/web/publication/TsangLi-Ideal2000.pdf",
  DOI =          "doi:10.1007/3-540-44491-2_77",
  size =         "6 pages",
  abstract =     "Ordinal data play an important part in financial
                 forecasting. For example, advice from expert sources
                 may take the form of bullish, bearish or sluggish, or
                 buy or do not buy. This paper describes an application
                 of using Genetic Programming (GP) to combine investment
                 opinions. The aim is to combine ordinal forecast from
                 different opinion sources in order to make better
                 predictions. We tested our implementation, FGP
                 (Financial Genetic Program-ming), on two data sets. In
                 both cases, FGP generated more accurate rules than the
                 individual input rules.",
}

Genetic Programming entries for Edward P K Tsang Jin Li

Citations