{"title":"New runs-based approach to testing value at risk forecasts","authors":"Marta Małecka","doi":"10.1002/for.3115","DOIUrl":null,"url":null,"abstract":"<p>The reformed Basel framework has left value at risk (VaR) as a basic tool of validating risk models. Within this framework, VaR independence tests have been regarded as critical to ensuring stability during periods of financial turmoil. However, until now, there is no consent among researchers regarding the choice of the appropriate test. The available procedures are either inaccurate in finite samples or need to rely on Monte Carlo simulations. To remedy these problems, we propose a new method for testing VaR models, based on the distribution of the number of runs. It outperforms the existing methods in two main aspects: First, it is exact in finite samples and thus allows for perfect control over the Type 1 error; second, its distribution is available in a closed form, so it does not require simulations before implementation. We show that it is the most adequate current procedure for testing low-level VaR series, which corresponds to today's regulatory standards.</p>","PeriodicalId":47835,"journal":{"name":"Journal of Forecasting","volume":"43 6","pages":"2021-2041"},"PeriodicalIF":3.4000,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Forecasting","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/for.3115","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
The reformed Basel framework has left value at risk (VaR) as a basic tool of validating risk models. Within this framework, VaR independence tests have been regarded as critical to ensuring stability during periods of financial turmoil. However, until now, there is no consent among researchers regarding the choice of the appropriate test. The available procedures are either inaccurate in finite samples or need to rely on Monte Carlo simulations. To remedy these problems, we propose a new method for testing VaR models, based on the distribution of the number of runs. It outperforms the existing methods in two main aspects: First, it is exact in finite samples and thus allows for perfect control over the Type 1 error; second, its distribution is available in a closed form, so it does not require simulations before implementation. We show that it is the most adequate current procedure for testing low-level VaR series, which corresponds to today's regulatory standards.
改革后的巴塞尔框架将风险价值(VaR)作为验证风险模型的基本工具。在这一框架内,风险价值独立性测试被认为是确保金融动荡时期稳定的关键。然而,直到现在,研究人员对选择适当的测试方法还没有达成一致意见。现有的程序要么在有限样本中不准确,要么需要依赖蒙特卡罗模拟。为了解决这些问题,我们提出了一种基于运行次数分布的 VaR 模型检验新方法。它在两个主要方面优于现有方法:首先,它在有限样本中是精确的,因此可以完美地控制第一类误差;其次,它的分布以封闭形式存在,因此在实施前无需进行模拟。我们证明,它是目前测试低水平 VaR 系列的最适当程序,符合当今的监管标准。
期刊介绍:
The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.