經濟資本模型驗證方法-wenkub

　

【正文】 ht extend to the management and systems environment within which the model is operated ? It is advisable that validation processes are designed alongside development of the models, rather than chronologically ? This interpretation of validation is consistent with the Basel Committee (2021) in relation to the Basel II Framework – However, that was phrased in terms of the IRB parameters amp。 developed in the context of assessment of risk estimates for use in minimum capital requirements – Validation of EC differs to an IRB model as the output is a distribution rather than a single predicted forecast against which actual outes may be pared Fitness for Purpose of EC Models (continued) ? EC are conceptually similar to VaR models, but several differences force validation methods to differ in practice from those used in VaR – Long time horizon, high confidence levels, and the scarcity of data ? Full internal EC models are not used for Pillar 1 minimum capital requirements, so fitness for purpose needs to cover a range of uses – Most of which and perhaps all these uses are internal to the firm in question ? Note that EC models and regulatory capital serve different objectives amp。 relative quantification ? Properties of an EC model for which only weaker validation processes are available include: – Conceptual soundness amp。 how these vary over time ? Some EC models are of risk aggregation models where estimates for individual categories are bined to generate a single risk figure – There may be no best or unique way to do this aggregation ? Since many of these assumptions may be untestable, it may be impossible to be certain that a model is conceptually sound ? While the conceptual underpinnings may appear coherent and plausible, they may in practice be no more than untested hypotheses ? Opinions may reasonably differ about the strength or weakness of any particular process in respect of any given property Validation of EC Models: Introduction to Range of Practice ? While we will describe the types of validation processes that are in use or could be used, note that the list is not prehensive ? We do not suggest that all techniques should or could be used by banks ? We wish to demonstrate that there is a wide range of techniques potentially covered by our broad definition of validation ? This is creating a layered approach, the more (fewer) of which that can be provided, the more (less) fort that validation is able to provide evidence for or against the performance of the model ? Each validation process provides evidence for (or against) only some of the desirable properties of a model ? The list presented below moves from the more qualitative to the more quantitative validation processes, and the extent of use is briefly discussed Validation of EC Models: Range of Practice in Qualitative Approaches ? The philosophy of the use test as incorporated into the Basel II framework: if a bank is actually using its risk measurement systems for internal purposes, then we can place more reliance on it ? Applying the use test successfully will entail gaining a careful understanding of which model properties are being used and which are not ? Banks tend to subject their models to some form of qualitative review process, which could entail: ? Review of documentation or development work ? Dialogue with model developers or model managers ? Review and derivation of any formulae or algorithms ? Comparison to other firms or with publicly available information ? Qualitative review is best able to answer questions such as: ? Does the model work in theory? ? Does the model incorporate the right risk drivers? ? Is any theory underpinning it conceptually wellfounded? ? Is the mathematics of the model right? Range of Practice in Qualitative Approaches to Validation (continued) ? Extensive systems implementation testing is standard for productionlevel risk measurement systems prior to implementation ? ., user acceptance testing, checking of model code, etc. ? These processes could be viewed as part of the overall validation effort, since they would assist in evaluating whether the model is implemented with integrity ? Management oversight is the involvement of senior management in the validation process ? ., reviewing output from the model amp。 and cannot be altered without fundamentally changing the model ? To illustrate, these assumptions could be about: ? Fixed model parameters (PDs, correlations or recovery rates) ? Distributional assumptions (margins, copulae amp。 algorithms the bank claims to use correctly are understood by staff who develop, maintain, operate and validate the model ? The bank is using in practice the modeling framework that it purports to ? Computer code is correct, efficient and welldocumented ? Data claimed to be used by the bank to obtain its results is in fact being used ? However, this technique is rarely sufficient to validate models, and in practice there is little evidence of it being used by banks for either validation or to explore the degree of accuracy of their models ? Note that replication simply by rerunning a set of algorithms to produce an identical set of results would not be sufficient model validation due diligence Range of Practice in Quantitative Validation: Benchmarking ? Benchmarking the parison of a bank?s EC model to alternative models on the bank?s portfolio ? ., to a vendor model after standardization of parameters ? Among the most monly used forms of quantitative validation used internally ? A limitation of benchmarking is it only provides relative assessments and provides little assurance that any model accurately reflects reality or about the absolute levels of capital ? Therefore, as a validation technique, benchmarking is limited to providing parison of one