Analyzing the Credit Default Swap Market Using Cartesian Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "Laleh Zangeneh and Peter J. Bentley",
  title =        "Analyzing the Credit Default Swap Market Using
                 Cartesian Genetic Programming",
  booktitle =    "International Workshop on Advances in Machine Learning
                 for Computational Finance",
  year =         "2009",
  address =      "London",
  month =        "20-21 " # jul,
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 Genetic Programming, Credit Default Swap, Regression",
  URL =          "",
  URL =          "",
  size =         "10 pages",
  abstract =     "The credit default swap has become well-known as one
                 of the causes of the 2007-2010 credit crisis but more
                 research is vitally needed to analyst and define its
                 impact more precisely and help the financial market
                 transparency. This paper uses cartesian genetic
                 programming as a discovery tool for finding the
                 relationship between credit default swap spreads and
                 debts and studying the arbitrage channel. (Arbitrage is
                 the practice of taking advantage of a price difference
                 between markets.) To our knowledge this work is the
                 first attempt toward studying the credit default swap
                 market via an evolutionary process and our results
                 prove that cartesian genetic programming is human
                 competitive and it has the potential to become a
                 regression discovery tool in credit default swap

Genetic Programming entries for Laleh Zangeneh Peter J Bentley