Open Journal of Statistics
Volume 3, Issue 6 (December 2013)
ISSN Print: 2161-718X ISSN Online: 2161-7198
Google-based Impact Factor: 0.53 Citations
High-Dimensional Regression on Sparse Grids Applied to Pricing Moving Window Asian Options ()
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ABSTRACT
The pricing of moving window Asian option with an early exercise feature is considered a challenging problem in option pricing. The computational challenge lies in the unknown optimal exercise strategy and in the high dimensionality required for approximating the early exercise boundary. We use sparse grid basis functions in the Least Squares Monte Carlo approach to solve this “curse of dimensionality” problem. The resulting algorithm provides a general and convergent method for pricing moving window Asian options. The sparse grid technique presented in this paper can be generalized to pricing other high-dimensional, early-exercisable derivatives.
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