Hedging without sweat: a genetic programming approach

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@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