GP forecasts of stock prices for profitable trading

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

@InCollection{maboudan:2002:ECEF,
  author =       "M. Kaboudan",
  title =        "GP forecasts of stock prices for profitable trading",
  booktitle =    "Evolutionary Computation in Economics and Finance",
  publisher =    "Physica Verlag",
  year =         "2002",
  editor =       "Shu-Heng Chen",
  volume =       "100",
  series =       "Studies in Fuzziness and Soft Computing",
  chapter =      "19",
  pages =        "359--381",
  month =        "2002",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-7908-1476-8",
  DOI =          "doi:10.1007/978-3-7908-1784-3_19",
  abstract =     "This chapter documents how GP forecasting of stock
                 prices used to execute a single-day-trading-strategy
                 (or SDTS) improves trading returns. The strategy
                 mandates holding no positions overnight to minimise
                 risk and daily trading decisions are based on forecasts
                 of daily high and low stock prices. For comparison, two
                 methods produce the price forecasts. Genetically
                 evolved models produce one. The other is a naive
                 forecast where today's actual price is used as
                 tomorrow's forecast. Trading decisions tested on a
                 small sample of four stocks over a period of twenty
                 days produced higher returns for decisions based on the
                 GP price forecasts.",
}

Genetic Programming entries for Mahmoud A Kaboudan

Citations