• DocumentCode
    1511535
  • Title

    Evolutionary computation and the vega risk of American put options

  • Author

    Keber, Christian ; Schuster, Matthias G.

  • Author_Institution
    Dept. of Bus. Adm., Wien Univ., Austria
  • Volume
    12
  • Issue
    4
  • fYear
    2001
  • fDate
    7/1/2001 12:00:00 AM
  • Firstpage
    704
  • Lastpage
    715
  • Abstract
    While European style options and American call options can be priced using analytical exact valuation models, closed-form solutions for the valuation of American puts have not yet been derived. The American put price as well as the corresponding greeks (e.g., delta, gamma, vega) can be calculated using numerical procedures or analytical approximations. We use a parallel implementation of the genetic programming approach and derive analytical approximations for determining the vega of an American put option because calculating vegas numerically requires even more computational effort than determining deltas or gammas. Applying our approximations to experimental data sets we can show that the genetically derived approximations outperform other approximations based on frequently used American put pricing formulas
  • Keywords
    genetic algorithms; investment; probability; stock markets; American put options; analytical approximations; evolutionary computation; genetic programming approach; vega risk; Analytical models; Closed-form solution; Concurrent computing; Context modeling; Cost accounting; Evolutionary computation; Genetic programming; Lattices; Portfolios; Pricing;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/72.935084
  • Filename
    935084