The pricing of moving window Asian options with an early exercise feature is considered as one of the most complex problems in numerical finance. The computational challenge is created by the unknown optimal exercise strategy and the high dimensionality that is required for its approximation. We use the Least Squares Monte Carlo approach together with Sparse Grid type basis functions to combine two simple and well established methods. The resulting algorithm provides a convergent and practical method for pricing the moving window Asian option as well as other high-dimensional, exercisable securities, which to our knowledge have not yet been solved with reasonable accuracy.     «

The pricing of moving window Asian options with an early exercise feature is considered as one of the most complex problems in numerical finance. The computational challenge is created by the unknown optimal exercise strategy and the high dimensionality that is required for its approximation. We use the Least Squares Monte Carlo approach together with Sparse Grid type basis functions to combine two simple and well established methods. The resulting algorithm provides a convergent and practical m...     »