Loss Distribution Estimation, External Data and Model Averaging Loss Distribution Estimation, External Data and Model Averaging

By Ethan Cohen-Cole and Todd Prono

A subsequent version of this paper was published in Journal of Financial Risk Management 4, no. 4 (2007): 59-66.

This paper will discuss a proposed method for the estimation of loss distribution using information from a combination of internally derived data and data from external sources. The relevant context for this analysis is the estimation of operational loss distributions used in the calculation of capital adequacy. We present a robust, easy-to-implement approach that draws on Bayesian inferential methods. The principal intuition behind the method is to let the data itself determine how they should be incorporated into the loss distribution. This approach avoids the pitfalls of managerial choice on data weighting and cut-off selection and allows for the estimation of a single loss distribution.

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