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Risk measurement for derivative portfolios almost invariably calls for nested simulation. In outer step one draws realizations of all risk factors up to horizon, and in inner step one re-prices each instrument in portfolio at horizon conditional on drawn risk factors. Practitioners may perceive the computational burden of such nested schemes to be unacceptable, and adopt a variety of second-best pricing techniques to avoid the inner simulation. In this paper, the author questions whether such short cuts are necessary. One shows that a relatively small number of trials in the inner step can yield accurate estimates, and analyze how a fixed computational budget may be allocated to the inner and the outer step to minimize the mean square error of the resultant estimator.
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