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Multilevel Simulation of Functionals of Bernoulli Random Variables with Application to Basket Credit Derivatives

机译:Bernoulli随机变量功能的多级仿真及其在篮子信用衍生工具中的应用

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We consider N Bernoulli random variables, which are independent conditional on a common random factor determining their probability distribution. We show that certain expected functionals of the proportion L N of variables in a given state converge at rate 1/N as N → ∞. Based on these results, we propose a multi-level simulation algorithm using a family of sequences with increasing length, to obtain estimators for these expected functionals with a mean-square error of ϵ 2 and computational complexity of order ϵ −2, independent of N. In particular, this optimal complexity order also holds for the infinite-dimensional limit. Numerical examples are presented for tranche spreads of basket credit derivatives.
机译:我们考虑N个Bernoulli随机变量,它们是共同条件决定其概率分布的独立条件。我们证明,在给定状态下,变量比例L N的某些预期泛函以1 / N的速率收敛为N→∞。基于这些结果,我们提出了一种使用长度增加的序列族的多级仿真算法,以获得这些期望函数的估计量,均方误差为ϵ 2,计算复杂度为ϵ -2,独立于N特别地,该最佳复杂度顺序对于无限维极限也成立。给出了篮子信用衍生产品的部分价差的数值示例。

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