Nonparametric tests for jump detection via false discovery rate control: a Monte Carlo study

IF 0.4 4区经济学 Q4 BUSINESS, FINANCE

Journal of Risk Model Validation Pub Date : 2019-09-10 DOI:10.21314/jrmv.2019.209

Kaiqiao Li, Kang He, Lizhou Nie, Wei Zhu, Pei-Fen Kuan

引用次数: 0

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通过错误发现率控制的跳跃检测的非参数检验:蒙特卡罗研究

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来源期刊

Journal of Risk Model Validation BUSINESS, FINANCE-

CiteScore

1.20

自引率

28.60%

发文量

期刊介绍： As monetary institutions rely greatly on economic and financial models for a wide array of applications, model validation has become progressively inventive within the field of risk. The Journal of Risk Model Validation focuses on the implementation and validation of risk models, and aims to provide a greater understanding of key issues including the empirical evaluation of existing models, pitfalls in model validation and the development of new methods. We also publish papers on back-testing. Our main field of application is in credit risk modelling but we are happy to consider any issues of risk model validation for any financial asset class. The Journal of Risk Model Validation considers submissions in the form of research papers on topics including, but not limited to: Empirical model evaluation studies Backtesting studies Stress-testing studies New methods of model validation/backtesting/stress-testing Best practices in model development, deployment, production and maintenance Pitfalls in model validation techniques (all types of risk, forecasting, pricing and rating)