The authors thank Zizhen Huang and anonymous referees for various suggestions substantially improving the presentation of the results.
ON THE CONSISTENCY OF REGRESSION-BASED MONTE CARLO METHODS FOR PRICING BERMUDAN OPTIONS IN CASE OF ESTIMATED FINANCIAL MODELS
Article first published online: 11 FEB 2013
© 2013 Wiley Periodicals, Inc.
How to Cite
Fromkorth, A. and Kohler, M. (2013), ON THE CONSISTENCY OF REGRESSION-BASED MONTE CARLO METHODS FOR PRICING BERMUDAN OPTIONS IN CASE OF ESTIMATED FINANCIAL MODELS. Mathematical Finance. doi: 10.1111/mafi.12025
- Article first published online: 11 FEB 2013
- Manuscript received Febuary 2012; final revision received October 2012.
- American options;
- least squares estimates;
- nonparametric regression;
- 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.