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Keywords:

  • American options;
  • consistency;
  • least squares estimates;
  • nonparametric regression;
  • robustness;
  • regression-based Monte Carlo methods

In many applications of regression-based Monte Carlo methods for pricing, American options in discrete time parameters of the underlying financial model have to be estimated from observed data. In this paper suitably defined nonparametric regression-based Monte Carlo methods are applied to paths of financial models where the parameters converge toward true values of the parameters. For various Black–Scholes, GARCH, and Levy models it is shown that in this case the price estimated from the approximate model converges to the true price.