Using Genetic Programming to Model Volatility in Financial Time Series

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{chen:1997:GPmvfts,
  author =       "Shu-Heng Chen and Chia-Hsuan Yeh",
  title =        "Using Genetic Programming to Model Volatility in
                 Financial Time Series",
  booktitle =    "Genetic Programming 1997: Proceedings of the Second
                 Annual Conference",
  editor =       "John R. Koza and Kalyanmoy Deb and Marco Dorigo and 
                 David B. Fogel and Max Garzon and Hitoshi Iba and 
                 Rick L. Riolo",
  year =         "1997",
  month =        "13-16 " # jul,
  keywords =     "genetic algorithms, genetic programming",
  pages =        "58--63",
  address =      "Stanford University, CA, USA",
  publisher_address = "San Francisco, CA, USA",
  publisher =    "Morgan Kaufmann",
  ISBN =         "1-55860-483-9",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/gp1997/chen_1997_GPmvfts.pdf",
  size =         "6 pages",
  abstract =     "RGP tested by using Nikkei 255 and S&P 500 as an
                 example",
  notes =        "GP-97 Fixed size sliding window of the original time
                 series. BGP used to learn first window, then whole pop
                 used with second window (ie as population seed).
                 Fitness = sum of errors squared also serves to give
                 estimate of volatility.",
}

Genetic Programming entries for Shu-Heng Chen Chia Hsuan Yeh

Citations