New evidence about the profitability of small and large stocks and the role of volume obtained using Strongly Typed Genetic Programming

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@Article{Manahov:2014:JIFMIM2,
  author =       "Viktor Manahov and Robert Hudson and Philip Linsley",
  title =        "New evidence about the profitability of small and
                 large stocks and the role of volume obtained using
                 Strongly Typed Genetic Programming",
  journal =      "Journal of International Financial Markets,
                 Institutions and Money",
  volume =       "33",
  pages =        "299--316",
  year =         "2014",
  ISSN =         "1042-4431",
  DOI =          "doi:10.1016/j.intfin.2014.08.007",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1042443114001115",
  abstract =     "We employ a special adaptive form of the Strongly
                 Typed Genetic Programming (STGP)-based learning
                 algorithm to develop trading rules based on a survival
                 of the fittest principle. Employing returns data for
                 the Russell 1000, Russell 2000 and Russell 3000 indices
                 the STGP method produces greater returns compared to
                 random walk benchmark forecasts, and the forecasting
                 models are statistically significant in respect of
                 their predictive effectiveness for all three indices
                 both in- and out-of-sample. Using one-step-ahead STGP
                 models to investigate the differences in return
                 patterns between small and large stocks we demonstrate
                 the superiority of models developed for small-cap
                 stocks over those developed for large-cap stocks,
                 indicating that small stocks are more predictable. We
                 also investigate the relationship between trading
                 volume and returns, and find that trading volume has
                 negligible predictive strength, implying it is not
                 advantageous to develop volume-based trading
                 strategies.",
  keywords =     "genetic algorithms, genetic programming, Forecasting
                 and simulation, Small Stocks, Agent-based modelling,
                 Artificial stock market, Capital asset pricing model,
                 Efficiency",
}

Genetic Programming entries for Viktor Manahov Robert Hudson Philip Linsley

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