A Dynamic Look-ahead Monte Carlo Algorithm for Pricing American Options
نویسنده
چکیده
Pricing of American options can be achieved by solving optimal stopping problems. This in turn can be done by computing so-called continuation values, which we represent as regression functions defined by the aid of a cash flow for the next few time periods. We use Monte Carlo to generate data and apply nonparametric least squares regression estimates to estimate the continuation values from these data. The parameters of the regression estimates and of the underlying regression problems are chosen data-dependent. Results concerning consistency and rate of convergence of these estimates are presented, and the resulting pricing of American options is illustrated by the aid of simulated data.
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