Valuing American Derivatives by Least Squares Methods
Least Squares estimators are notoriously known to generate sub-optimal exercise decisions when determining the optimal stopping time. The consequence is that the price of the option will be underestimated. We show how to use variance reduction techniques to extend some recent Monte Carlo estimators for option pricing and assess their performance in finite samples. Finally, we extend the Longstaff and Schwartz (2001) method to price American options under stochastic volatility. This is the first study to implement and apply the Glasserman and Yu (2004b) methodology to price Asian options and basket options.
|Date of creation:||Apr 2008|
|Date of revision:||Sep 2008|
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- Luciano Fratocchi & Alberto Onetti & Alessia Pisoni & Marco Talaia, 2007. "Location of value added activities in hi-tech industries. The case of pharma-biotech firms in Italy," Economics and Quantitative Methods qf0708, Department of Economics, University of Insubria.
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- Lars Stentoft, 2004. "Assessing the Least Squares Monte-Carlo Approach to American Option Valuation," Review of Derivatives Research, Springer, vol. 7(2), pages 129-168, 08.
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- Philip Protter & Emmanuelle Clément & Damien Lamberton, 2002. "An analysis of a least squares regression method for American option pricing," Finance and Stochastics, Springer, vol. 6(4), pages 449-471.
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