*Tid:* **9 juni 2015 kl 9.15-10.00.**
**Seminarierummet 3721**, Institutionen för
matematik, KTH, Lindstedtsvägen 25, plan 7.
Karta!
*Föredragshållare:*
**
Oscar Hallberg and Mattias Wärmlöf Helmrich
**
**Titel:**
Operational Risk Modeling: Addressing the Reporting Threshold Problem
(Master's thesis)
**Abstract**
External loss data are typically left truncated at a reporting threshold. Ignoring this
truncation level leads to biased capital charge estimations. This thesis addresses
the challenges of recreating the truncated part of the distribution. By predicting
the continuation of a probability density function, the unobserved body of an
external operational risk loss distribution is estimated. The prediction is based on
internally collected losses and the tail of the external loss distribution. Using a
semiparametric approach to generate sets of internal losses and applying the Best
Linear Unbiased Predictor, results in an enriched external dataset that shares
resemblance with the internal dataset. By avoiding any parametrical assumptions,
this study proposes a new and unique way to address the reporting threshold
problem. Financial institutions will benefit from these findings as it permits the
use of the semiparametric approach developed by Bolancé et al. (2012) and
thereby eliminates the well known difficulty with determining the breaking point
beyond which the tail domain is defined when using the Loss Distribution
Approach. The main conclusion from this thesis is that predicting the
continuation of a function using the Best Linear Unbiased Predictor can be
successfully applied in an operational risk setting. This thesis has predicted the
continuation of a probability density function, resulting in a full external loss
distribution.
The full report (pdf)
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