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IMPORTANCE SAMPLING FOR A MIXED POISSON MODEL OF PORTFOLIO CREDIT RISK

机译:混合泊松模型的重要性抽样信用风险

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Simulation is widely used to estimate losses due to default and other credit events in financial portfolios. The challenge in doing this efficiently results from (i) rare-event aspects of large losses and (ii) complex dependence between defaults of multiple obligors. We discuss importance sampling techniques to address this problem in two portfolio credit risk models developed in the financial industry, with particular emphasis on a mixed Poisson model. We give conditions for asymptotic optimality of the estimators as the portfolio size grows.
机译:仿真广泛用于估算由于财务投资组合中的违约和其他信用事件导致的损失。在大量损失的稀有事件方面和(ii)多个债务人的违约者之间的复杂依赖性的罕见事件方面,挑战我们讨论了重要的抽样技术,以解决金融业发展的两个投资组合信用风险模型中的这个问题,特别强调了混合泊松模型。随着投资组合大小的增长,我们为估计的渐近最优性提供条件。

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