Hedging without sweat: a genetic programming approach

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@Article{Lensberg:2013:QFL,
  author =       "Terje Lensberg and Klaus Reiner Schenk-Hoppe",
  title =        "Hedging without sweat: a genetic programming
                 approach",
  journal =      "Quantitative Finance Letters",
  year =         "2013",
  volume =       "1",
  pages =        "41--46",
  keywords =     "genetic algorithms, genetic programming, Hedging,
                 Transaction costs, Closed-form approximations",
  publisher =    "Taylor \& Francis",
  DOI =          "doi:10.1080/21649502.2013.813166",
  size =         "6 page",
  abstract =     "Hedging in the presence of transaction costs leads to
                 complex optimisation problems. These problems typically
                 lack closed-form solutions, and their implementation
                 relies on numerical methods that provide hedging
                 strategies for specific parameter values. In this
                 paper, we use a genetic programming algorithm to derive
                 explicit formulae for near-optimal hedging strategies
                 under nonlinear transaction costs. The strategies are
                 valid over a large range of parameter values and
                 require no information about the structure of the
                 optimal hedging strategy.",
  notes =        "Author affiliations NHH Norwegian School of Economics,
                 Norway University of Leeds, UK",
}

Genetic Programming entries for Terje Lensberg Klaus Reiner Schenk-Hoppe

Citations