• DocumentCode
    924219
  • Title

    Valuation of American options via basis functions

  • Author

    Lai, Tze Leung ; Wong, Samuel Po-Shing

  • Author_Institution
    Dept. of Stat., Stanford Univ., CA, USA
  • Volume
    49
  • Issue
    3
  • fYear
    2004
  • fDate
    3/1/2004 12:00:00 AM
  • Firstpage
    374
  • Lastpage
    385
  • Abstract
    After a brief review of recent developments in the pricing and hedging of American options, this paper modifies the basis function approach to adaptive control and neuro-dynamic programming, and applies it to develop: 1) nonparametric pricing formulas for actively traded American options and 2) simulation-based optimization strategies for complex over-the-counter options, whose optimal stopping problems are prohibitively difficult to solve numerically by standard backward induction algorithms because of the curse of dimensionality. An important issue in this approach is the choice of basis functions, for which some guidelines and their underlying theory are provided.
  • Keywords
    adaptive control; dynamic programming; function approximation; neural nets; pricing; stock markets; American options valuation; actively traded American options; adaptive control; basis functions; complex over-the-counter options; function approximation; neurodynamic programming; nonparametric pricing formulas; optimal stopping problems; option pricing; simulation-based optimization strategies; Adaptive control; Cost accounting; Councils; Finance; Functional programming; Guidelines; Multidimensional systems; Pricing; Spline; Standards development;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.2004.824466
  • Filename
    1273637