Author： Alvarez Susana
Publisher： Taylor & Francis Ltd
ISSN： 0094-9655
Source： Journal of Statistical Computation and Simulation, Vol.80, Iss.1, 2010-01, pp. : 111-117
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Abstract
In this paper we use bootstrap methodology to achieve accurate estimated prediction intervals for recovery rates. In the framework of the LossCalc model, which is the Moody's KMV model to predict loss given default, a single beta distribution is usually assumed to model the behaviour of recovery rates and, hence, to construct prediction intervals. We evaluate the coverage properties of beta estimated prediction intervals for multimodal recovery rates. We carry out a simulation study, and our results show that bootstrap versions of beta mixture prediction intervals exhibit the best coverage properties.
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