經(jīng)濟資本模型驗證方法(留存版)

　　

【正文】 rical experience – Sensitivity to risk amp。 using the results in business decisions ? Senior management knowing how the model is used amp。 overall calibration of the model is an important consideration Technical Challenges in Assessing the Adequacy of an EC Model ? A fundamental difficulty faced in EC modeling is the lack of data to estimate high quantiles in the tails of the loss distribution leads to a very high degree of uncertainty ? One approach to dealing with this problem is Bayesian techniques, which bine expert assessments with available data ? See Kiefer amp。 validation practices for economic capital purposes Range of Practice in Quantitative Validation: Stress Testing ? Stress testing covers both stressing of the model and parison of model outputs to stress losses ? The outputs of the model might be examined under conditions where model inputs and model assumptions might be stressed ? This process can reveal model limitations or highlight capital constraints that might only bee apparent under stress ? While stress testing of regulatory capital models, particularly IRB models, is monly undertaken by banks, there is more limited evidence of stress testing of economic capital models ? Through a plementary programme of stress testing, the bank may be able to quantify the likely losses that the firm would confront under a range of stress events ? Comparison of stress losses against modelbased capital estimates may provide a modest degree of fort of the absolute level of capital ? Banks report some use of this stress testing technique to validate the approximate level of model output Range of Practice in Validation: Additional Considerations ? We have not mentioned internal audit, but validation of the overall implementation framework and process should also be subject to independent and periodic review ? This work should be made by parties within the banking anization that are independent of those accountable for the design and implementation of the validation process ? A possibility is that internal audit would be in charge of undertaking this review process, and as such it could be viewed as prising a part of the management oversight process discussed previously ? The list of validation tools also does not address the issue of adequate internal standards relevant for validation ? Examples of such standards include: ? A description of the issues that need to be addressed as part of validation ? The standards that capital models are expected to achieve ? A series of quantitative thresholds that models need to meet ? Warning indicators for particular monitoring metrics ? Assessment against model development standards Supervisory Concerns and Expectations in the Validation of EC Models ? Given the inherent limitations of EC model validation, there is an emphasis on effective reporting to avoid misuse or misunderstanding ? A recognition of intrinsic difficulty in evaluation of high quantiles of loss over long periods, data scarcity amp。 may reasonably differ in some details of implementation ? BCBS?s Validation Principle 1 refers to predictive ability of credit rating systems, an emphasis on performance of model forecasts ? The natural evolution of this principle for EC is that validation is concerned with the predictive properties of those models – ., embody forwardlooking estimates of risk amp。 outputs are interpreted ? This should take account of the specific implementation framework adopted and the assumptions underlying the model and its parameterization ? Data quality checks refer to the processes designed to provide assurance of the pleteness, accuracy and appropriateness of data used to develop, validate and operate the model ? ., Review of: data collection and storage, data cleaning of errors, extent of proxy data, processes that need to be followed to convert raw data into suitable model inputs, and verification of transaction data such as exposure levels ? While not traditionally viewed by the industry as a form of validation, increasingly forming a major part of supervisory thinking Range of Practice in Qualitative Approaches to Validation (concluded) ? As all models rest on premises of various kinds, varying in the degree to which obvious, we have examination of assumptions ? Certain aspects of an EC model are 39。 Jacobs (2021, forthing) ? However, this is putationally demanding, and also requires the elicitation of a prior distribution from an expect, which is very involved ? But if the prior is diffuse, then much uncertainty still remains ? As we don?t see this used in practice currently, we will not further pursue this approach here ? As noted previously, traditional backtesting procedures as applied in market risk VaR models are impractical in an EC model setting ? An alternative approach is to try to assess the accuracy of the EC output by approximating a statistical measure of uncertainty ? ., through resampling or bootstrap methods (Efron et al, 1986) ? But thin data in the tails implies confidence bounds are likely to be wide . EC Model Validation Example: Alternative Risk Aggregation Models ? “Models for Risk Aggregation and Sensitivity Analysis: An Application to Bank Economic Capital”, by Hulusi Inanoglu and Michael Jacobs, OCC 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 accura