Nested Simulation in Portfolio Risk Measurement
研究了衍生品组合风险度量中嵌套模拟的计算效率问题，发现内层模拟只需少量试验即可获得准确估计，并给出了在固定计算预算下内外层模拟的最优分配方法，还引入了刀切法减少偏差。
Risk measurement for derivative portfolios almost invariably calls for nested simulation. In the outer step, one draws realizations of all risk factors up to the horizon, and in the inner step, one reprices each instrument in the portfolio at the horizon conditional on the 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, we question whether such short cuts are necessary. We show that a relatively small number of trials in the inner step can yield accurate estimates, and we 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. Finally, we introduce a jackknife procedure for bias reduction.