Bankruptcy theory development and classification via genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Lensberg:2005:EJOR,
  author =       "Terje Lensberg and Aasmund Eilifsen and 
                 Thomas E. McKee",
  title =        "Bankruptcy theory development and classification via
                 genetic programming",
  journal =      "European Journal of Operational Research",
  year =         "2006",
  volume =       "169",
  pages =        "677--697",
  number =       "2",
  abstract =     "Bankruptcy is a highly significant worldwide problem
                 with high social costs. Traditional bankruptcy risk
                 models have been criticised for falling short with
                 respect to bankruptcy theory building due to either
                 modelling assumptions or model complexity.

                 Genetic programming minimises the amount of a priori
                 structure that is associated with traditional
                 functional forms and statistical selection procedures,
                 but still produces easily understandable and
                 implementable models. Genetic programming was used to
                 analyse 28 potential bankruptcy variables found to be
                 significant in multiple prior research studies,
                 including 10 fraud risk factors. Data was taken from a
                 sample of 422 bankrupt and non-bankrupt Norwegian
                 companies for the period 1993-1998. Six variables were
                 determined to be significant.

                 A genetic programming model was developed for the six
                 variables from an expanded sample of 1136 bankrupt and
                 non-bankrupt Norwegian companies. The model was 81%
                 accurate on a validation sample, slightly better than
                 prior genetic programming research on US public
                 companies, and statistically significantly better than
                 the 77% accuracy of a traditional logit model developed
                 using the same variables and data. The most significant
                 variable in the final model was the prior auditor
                 opinion, thus validating the information value of the
                 auditor's report. The model provides insight into the
                 complex interaction of bankruptcy related factors,
                 especially the effect of company size. The results
                 suggest that accounting information, including the
                 auditor's evaluation of it, is more important for
                 larger than smaller firms. It also suggests that for
                 small firms the most important information is liquidity
                 and non-accounting information.

                 The genetic programming model relationships developed
                 in this study also support prior bankruptcy research,
                 including the finding that company size decreases
                 bankruptcy risk when profits are positive. It also
                 confirms that very high profit levels are associated
                 with increased bankruptcy risk even for large companies
                 an association that may be reflecting the potential for
                 management to be {"}Cooking the Books{"}.",
  owner =        "wlangdon",
  URL =          "http://www.sciencedirect.com/science/article/B6VCT-4D5P6FY-8/2/b08574948226f93f16a6013ffef1cd19",
  month =        "1 " # mar,
  keywords =     "genetic algorithms, genetic programming, Going
                 concern, Bankruptcy, Fraud risk",
  DOI =          "doi:10.1016/j.ejor.2004.06.013",
}

Genetic Programming entries for Terje Lensberg Aasmund Eilifsen Thomas E McKee

Citations