A genetic programming model to generate risk-adjusted technical trading rules in stock markets

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

@Article{Esfahanipour20118438,
  author =       "Akbar Esfahanipour and Somayeh Mousavi",
  title =        "A genetic programming model to generate risk-adjusted
                 technical trading rules in stock markets",
  journal =      "Expert Systems with Applications",
  volume =       "38",
  number =       "7",
  pages =        "8438--8445",
  year =         "2011",
  ISSN =         "0957-4174",
  DOI =          "doi:10.1016/j.eswa.2011.01.039",
  URL =          "http://www.sciencedirect.com/science/article/B6V03-52178YW-J/2/5208571320b6e5c08daf35597b9f81f4",
  keywords =     "genetic algorithms, genetic programming, Technical
                 trading rules, Risk-adjusted measures, Conditional
                 Sharpe ratio, Tehran Stock Exchange (TSE)",
  abstract =     "Technical trading rules can be generated from
                 historical data for decision making in stock markets.
                 Genetic programming (GP) as an artificial intelligence
                 technique is a valuable method to automatically
                 generate such technical trading rules. In this paper,
                 GP has been applied for generating risk-adjusted
                 trading rules on individual stocks. Among many risk
                 measures in the literature, conditional Sharpe ratio
                 has been selected for this study because it uses
                 conditional value at risk (CVaR) as an optimal coherent
                 risk measure. In our proposed GP model, binary trading
                 rules have been also extended to more realistic rules
                 which are called trinary rules using three signals of
                 buy, sell and no trade. Additionally we have included
                 transaction costs, dividend and splits in our GP model
                 for calculating more accurate returns in the generated
                 rules. Our proposed model has been applied for 10
                 Iranian companies listed in Tehran Stock Exchange
                 (TSE). The numerical results showed that our extended
                 GP model could generate profitable trading rules in
                 comparison with buy and hold strategy especially in the
                 case of risk adjusted basis.",
}

Genetic Programming entries for Akbar Esfahanipour Somayeh Mousavi

Citations