Using Genetic Programming to Model Volatility in Financial Time Series   [GP] [FTS] [TS]

by

Chen, S.-H. and Yeh, C.-H.

Literature search on Evolutionary ComputationBBase ©1999-2013, Rasmus K. Ursem
     Home · Search · Adv. search · Authors · Login · Add entries   Webmaster
Note to authors: Please submit your bibliography and contact information - online papers are more frequently cited.

Info: Genetic Programming 1997: Proceedings of the Second Annual Conference (Conference proceedings), 1997, p. 58-63
Keywords:Genetic Programming, Genetic Algorithms
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.
Internet search:Search Google
Search Google Scholar
Search Citeseer using Google
Search Google for PDF
Search Google Scholar for PDF
Search Citeseer for PDF using Google

Review item:

Mark as doublet (will be reviewed)

Print entry



BibTex:
@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 Programming, Genetic Algorithms",
  pages =        "58--63",
  address =      "Stanford University, CA, USA",
  publisher_address = "San Francisco, CA, USA",
  publisher =    "Morgan Kaufmann",
  ISBN =         "1-55860-483-9",
  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.",
}