By Kathrin Glau, Matthias Scherer, Rudi Zagst
Quantitative versions are omnipresent –but usually controversially mentioned– in todays probability administration perform. New laws, cutting edge ﬁnancial items, and advances in valuation thoughts supply a continuing ﬂow of tough difficulties for ﬁnancial engineers and possibility managers alike. Designing a valid stochastic version calls for ﬁnding a cautious stability among parsimonious version assumptions, mathematical viability, and interpretability of the output. furthermore, info specifications and the end-user education are to be regarded as well.
The KPMG heart of Excellence in threat administration convention danger administration Reloaded and this court cases quantity give a contribution to bridging the distance among academia –providing methodological advances– and perform –having a ﬁrm figuring out of the commercial stipulations during which a given version is used. mentioned ﬁelds of software variety from asset administration, credits hazard, and effort to threat administration concerns in coverage. Methodologically, dependence modeling, multiple-curve curiosity rate-models, and version chance are addressed. ultimately, regulatory advancements and attainable limits of mathematical modeling are discussed.
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Extra info for Innovations in Quantitative Risk Management: TU München, September 2013
Kemmer Association of German Banks, Burgstr. de M. de © The Author(s) 2015 K. Glau et al. 1007/978-3-319-09114-3_2 19 20 U. Gaumert and M. Kemmer point for explaining and commenting on the current debate. Much of the following applies to other types of internal models as well. Banks and supervisors learned many lessons from the sometimes unsatisfactory performance of VaR models in the crisis—one of the root causes of the loss of confidence by investors in model results. This led, at bank level, to a range of improvements in methodology, and also to the realisation that not all products and portfolios lend themselves to internal modelling.
Nonetheless, it is most certainly possible to standardise models in a way which will reduce their complexity and improve the comparability of their results but will not compromise their suitability for internal use. Here are a few suggestions35 : • Develop a market standard for IRC models to avoid variation as a result of differences in the choice of model (proposed standard established by supervisors: see Trading Book Review). • Reduce the amount of flexibility in how historical data are used.
In addition to the code of “moral ethics” discussed in Sect. 8, the following additional incentive to use models appropriately could be considered. Establishing a link between traders’ bonuses and model backtesting results could serve to improve the alignment of interests. This idea is also closely connected with the issue of strengthening the use test concept (see Sect. 5). Trade repositories already collect key data, including calculated market values, relating to all derivative contracts, irrespective of whether they are centrally cleared or not.