{"title":"Procyclicality of capital and portfolio segmentation in the advanced internal ratings-based framework: an application to mortgage portfolios","authors":"José J. Canals-Cerdá","doi":"10.21314/jrmv.2018.191","DOIUrl":"https://doi.org/10.21314/jrmv.2018.191","url":null,"abstract":"","PeriodicalId":43447,"journal":{"name":"Journal of Risk Model Validation","volume":"45 1","pages":"1-27"},"PeriodicalIF":0.7,"publicationDate":"2018-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84640193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimal allocation of model risk appetite and validation threshold in the Solvency II framework","authors":"LiYi Lin, M. Heemskerk, P. Dekker","doi":"10.21314/JRMV.2018.193","DOIUrl":"https://doi.org/10.21314/JRMV.2018.193","url":null,"abstract":"","PeriodicalId":43447,"journal":{"name":"Journal of Risk Model Validation","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2018-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76860540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evaluating the risk performance of online peer-to-peer lending platforms in China","authors":"Chong Wu, Dong Zhang, Ying Wang","doi":"10.21314/jrmv.2018.187","DOIUrl":"https://doi.org/10.21314/jrmv.2018.187","url":null,"abstract":"","PeriodicalId":43447,"journal":{"name":"Journal of Risk Model Validation","volume":"55 1","pages":"63-87"},"PeriodicalIF":0.7,"publicationDate":"2018-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80700167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Shrunk volatility value-at-risk: an application on US balanced portfolios","authors":"Stefano Colucci","doi":"10.21314/JRMV.2018.183","DOIUrl":"https://doi.org/10.21314/JRMV.2018.183","url":null,"abstract":"","PeriodicalId":43447,"journal":{"name":"Journal of Risk Model Validation","volume":"13 1","pages":"1-62"},"PeriodicalIF":0.7,"publicationDate":"2018-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80999364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Smoothing algorithms by constrained maximum likelihood: methodologies and implementations for Comprehensive Capital Analysis and Review stress testing and International Financial Reporting Standard 9 expected credit loss estimation","authors":"Bill Huajian Yang","doi":"10.21314/JRMV.2018.189","DOIUrl":"https://doi.org/10.21314/JRMV.2018.189","url":null,"abstract":"","PeriodicalId":43447,"journal":{"name":"Journal of Risk Model Validation","volume":"5 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2018-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82495011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The recent Fundamental Review of the Trading Book (FRTB) resulted in revised standards for capital requirements for market risks in a bank’s trading book. As part of the ruleset, default risk needs to be measured and capitalized through a dedicated Default Risk Charge (DRC). With the DRC as an extreme tail risk measure at 99.9% confidence level for portfolio default losses at a one-year horizon, there is inherent model risk associated with the reflection of joint defaults. Wilkens and Predescu (2017) proposed an overall framework for modeling the DRC that is based on a Gaussian factor copula model to capture the coincidence of defaults. This paper assesses the resulting model risk by analyzing alternative copulas (Gaussian, Student t, and Clayton) and the influence on the DRC figures with the help of a set of example portfolios. The copula choice can affect the DRC considerably, especially for directional and less diversified portfolios; the influence on typical larger-scale, diversified portfolios is much less pronounced. The uncertainty arising from the calibration of any copula from only a few data points – as implied by the regulation – is at least of equal importance as the selection of the dependence model itself.
{"title":"Model Risk in the Fundamental Review of the Trading Book: The Case of the Default Risk Charge","authors":"S. Wilkens, Mirela Predescu","doi":"10.2139/SSRN.3053426","DOIUrl":"https://doi.org/10.2139/SSRN.3053426","url":null,"abstract":"The recent Fundamental Review of the Trading Book (FRTB) resulted in revised standards for capital requirements for market risks in a bank’s trading book. As part of the ruleset, default risk needs to be measured and capitalized through a dedicated Default Risk Charge (DRC). With the DRC as an extreme tail risk measure at 99.9% confidence level for portfolio default losses at a one-year horizon, there is inherent model risk associated with the reflection of joint defaults. Wilkens and Predescu (2017) proposed an overall framework for modeling the DRC that is based on a Gaussian factor copula model to capture the coincidence of defaults. This paper assesses the resulting model risk by analyzing alternative copulas (Gaussian, Student t, and Clayton) and the influence on the DRC figures with the help of a set of example portfolios. The copula choice can affect the DRC considerably, especially for directional and less diversified portfolios; the influence on typical larger-scale, diversified portfolios is much less pronounced. The uncertainty arising from the calibration of any copula from only a few data points – as implied by the regulation – is at least of equal importance as the selection of the dependence model itself.","PeriodicalId":43447,"journal":{"name":"Journal of Risk Model Validation","volume":"38 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2018-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73624718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A central limit theorem formulation for empirical bootstrap value-at-risk","authors":"P. Mitic, Nicholas Bloxham","doi":"10.21314/jrmv.2018.182","DOIUrl":"https://doi.org/10.21314/jrmv.2018.182","url":null,"abstract":"","PeriodicalId":43447,"journal":{"name":"Journal of Risk Model Validation","volume":"15 1","pages":"49-83"},"PeriodicalIF":0.7,"publicationDate":"2018-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87056205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As far as Probability of Default (PD) prediction is concerned, the model performance is typically measured with the Gini coefficient and/or the Kolmogorov-Smirnov (KS) statistic. For Loss Given Default (LGD) models, there are no standard performance measures, though, and more than 15 different measures are used, including Mean Square Error (MSE), Mean Absolute Error (MAE), coefficient of determination (R-squared) as well as correlation coefficients between the observed and predicted LGD. However, some measures cannot be readily recommended for LGD models, even though they have been used for this purpose. It is argued that there are measures that should only be employed for specific types of models. It is also pointed out that some measures can be applied interchangeably to avoid information redundancy. Moreover, the Area Under the Receiver Operating Characteristic Curve (AUC) is critically discussed in the LGD context. Four new measures are then proposed: Mean Area Under the Receiver Operating Characteristic Curve (MAUROC), Mean Accuracy Ratio (MAR), Mean Enhanced Lin-Lin Error (MELLE) and a generalized lift. The review is illustrated using an empirical example.
{"title":"Underperforming performance measures? A review of measures for loss given default models","authors":"K. Bijak, L. Thomas","doi":"10.21314/JRMV.2018.186","DOIUrl":"https://doi.org/10.21314/JRMV.2018.186","url":null,"abstract":"As far as Probability of Default (PD) prediction is concerned, the model performance is typically measured with the Gini coefficient and/or the Kolmogorov-Smirnov (KS) statistic. For Loss Given Default (LGD) models, there are no standard performance measures, though, and more than 15 different measures are used, including Mean Square Error (MSE), Mean Absolute Error (MAE), coefficient of determination (R-squared) as well as correlation coefficients between the observed and predicted LGD. However, some measures cannot be readily recommended for LGD models, even though they have been used for this purpose. It is argued that there are measures that should only be employed for specific types of models. It is also pointed out that some measures can be applied interchangeably to avoid information redundancy. Moreover, the Area Under the Receiver Operating Characteristic Curve (AUC) is critically discussed in the LGD context. Four new measures are then proposed: Mean Area Under the Receiver Operating Characteristic Curve (MAUROC), Mean Accuracy Ratio (MAR), Mean Enhanced Lin-Lin Error (MELLE) and a generalized lift. The review is illustrated using an empirical example.","PeriodicalId":43447,"journal":{"name":"Journal of Risk Model Validation","volume":"4 1","pages":"1-28"},"PeriodicalIF":0.7,"publicationDate":"2018-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79392875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The validation of filtered historical value-at-risk models","authors":"Pedro Gurrola-Perez","doi":"10.21314/JRMV.2018.185","DOIUrl":"https://doi.org/10.21314/JRMV.2018.185","url":null,"abstract":"","PeriodicalId":43447,"journal":{"name":"Journal of Risk Model Validation","volume":"3 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2018-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90457215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Validation of profit and loss attribution models for equity derivatives","authors":"D. Madan, King Wang","doi":"10.21314/JRMV.2018.184","DOIUrl":"https://doi.org/10.21314/JRMV.2018.184","url":null,"abstract":"","PeriodicalId":43447,"journal":{"name":"Journal of Risk Model Validation","volume":"42 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2018-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81034902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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