Journal of Risk Model Validation最新文献_第10页

Forecasting value-at-risk for frontier stock market indexes using GARCH-type models and extreme value theory: model validation for dynamic models 基于garch模型和极值理论的前沿股票市场指数风险价值预测:动态模型的模型验证

IF 0.7 4区经济学

Journal of Risk Model Validation Pub Date : 2014-12-01 DOI: 10.21314/JRMV.2014.128

Dany Ng Cheong Vee, P. Gonpot, N. Sookia

引用次数: 2

Conditioned Likelihood-Estimation of Non-Normal Distributions: Risk Estimation of Credit Portfolios in Stressed Markets 非正态分布的条件似然估计:压力市场中信贷组合的风险估计

IF 0.7 4区经济学

Journal of Risk Model Validation Pub Date : 2014-09-01 DOI: 10.21314/JRMV.2014.125

K. Oteng-Amoako

引用次数: 0

Validation of term structure forecasts with factor models 因子模型对期限结构预测的验证

IF 0.7 4区经济学

Journal of Risk Model Validation Pub Date : 2014-09-01 DOI: 10.21314/JRMV.2014.124

Alexander B. Matthies

引用次数: 0

Backtesting value-at-risk tail losses on a dynamic portfolio 对动态投资组合的风险价值尾部损失进行回测

IF 0.7 4区经济学

Journal of Risk Model Validation Pub Date : 2014-06-01 DOI: 10.21314/JRMV.2014.121

Alasdair Graham, János Pál

引用次数: 5

An analytic approach to quantify the sensitivity of CreditRisk+ with respect to its underlying assumptions 一种量化CreditRisk+相对于其基本假设的敏感性的分析方法

IF 0.7 4区经济学

Journal of Risk Model Validation Pub Date : 2014-06-01 DOI: 10.21314/JRMV.2014.120

M. Fischer, F. Kaufmann

引用次数: 2

Review, theory and implementation of convertible bonds for commercial investment 商业投资可转换债券的回顾、理论与实施

IF 0.7 4区经济学

Journal of Risk Model Validation Pub Date : 2014-06-01 DOI: 10.21314/JRMV.2014.119

R. Kunwar, Zhihui Yang, Jonathan Lai, Jerrold Cline

引用次数: 1

Modeling systematic risk and point-in-time probability of default under the Vasicek asymptotic single-risk-factor model framework Vasicek渐近单风险因素模型框架下系统风险和违约时间点概率的建模

IF 0.7 4区经济学

Journal of Risk Model Validation Pub Date : 2014-03-18 DOI: 10.21314/JRMV.2014.126

Bill Huajian Yang

{"title":"Modeling systematic risk and point-in-time probability of default under the Vasicek asymptotic single-risk-factor model framework","authors":"Bill Huajian Yang","doi":"10.21314/JRMV.2014.126","DOIUrl":"https://doi.org/10.21314/JRMV.2014.126","url":null,"abstract":"Systematic risk has been a focus for stress testing and risk capital assessment. Under the Vasicek asymptotic single risk factor model framework, entity default risk for a risk homogeneous portfolio divides into two parts: systematic and entity specific. While entity specific risk can be modelled by a probit or logistic model using a relatively short period of portfolio historical data, modeling of systematic risk is more challenging. In practice, most default risk models do not fully or dynamically capture systematic risk. In this paper, we propose an approach to modeling systematic and entity specific risks by parts and then aggregating together analytically. Systematic risk is quantified and modelled by a multifactor Vasicek model with a latent residual, a factor accounting for default contagion and feedback effects. The asymptotic maximum likelihood approach for parameter estimation for this model is equivalent to least squares linear regression. Conditional entity PDs for scenario tests and through-the-cycle entity PD all have analytical solutions. For validation, we model the point-in-time entity PD for a commercial portfolio, and stress the portfolio default risk by shocking the systematic risk factors. Rating migration and portfolio loss are assessed.","PeriodicalId":43447,"journal":{"name":"Journal of Risk Model Validation","volume":"69 1","pages":"33-48"},"PeriodicalIF":0.7,"publicationDate":"2014-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74086324","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}

引用次数: 0

A proposed framework for backtesting loss given default models 提出了一种基于默认模型的回测损失的框架

IF 0.7 4区经济学

Journal of Risk Model Validation Pub Date : 2014-02-17 DOI: 10.21314/JRMV.2014.117

Gert Loterman, M. Debruyne, K. V. Branden, T. V. Gestel, C. Mues

{"title":"A proposed framework for backtesting loss given default models","authors":"Gert Loterman, M. Debruyne, K. V. Branden, T. V. Gestel, C. Mues","doi":"10.21314/JRMV.2014.117","DOIUrl":"https://doi.org/10.21314/JRMV.2014.117","url":null,"abstract":"The Basel Accords require financial institutions to regularly validate their loss given default (LGD) models. This is crucial so banks are not misestimating the minimum required capital to protect them against the risks they are facing through their lending activities. The validation of an LGD model typically includes backtesting, which involves the process of evaluating to what degree the internal model estimates still correspond with the realized observations. Reported backtesting examples have typically been limited to simply measuring the similarity between model predictions and realized observations. It is however not straightforward to determine acceptable performance based on these measurements alone. Although recent research led to advanced backtesting methods for PD models, the literature on similar backtesting methods for LGD models is much scarcer. This study addresses this literature gap by proposing a backtesting framework using statistical hypothesis tests to support the validation of LGD models. The proposed statistical hypothesis tests implicitly define reliable reference values to determine acceptable performance and take into account the number of LGD observations, as a small sample may affect the quality of the backtesting procedure. This workbench of tests is applied to an LGD model fitted to real-life data and evaluated through a statistical power analysis.","PeriodicalId":43447,"journal":{"name":"Journal of Risk Model Validation","volume":"45 1","pages":"69-90"},"PeriodicalIF":0.7,"publicationDate":"2014-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84797633","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}

引用次数: 12

Credit scoring optimization using the area under the curve 利用曲线下面积进行信用评分优化

IF 0.7 4区经济学

Journal of Risk Model Validation Pub Date : 2014-01-01 DOI: 10.21314/JRMV.2014.116

A. Kraus, H. Küchenhoff

引用次数: 4

Estimating long-run probability of default, asset correlation and portfolio-level probability of default using Vasicek models 使用Vasicek模型估计长期违约概率、资产相关性和投资组合级违约概率

IF 0.7 4区经济学

Journal of Risk Model Validation Pub Date : 2013-12-01 DOI: 10.21314/JRMV.2013.112

Bill Huajian Yang

引用次数: 8