Journal of Risk Model Validation

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 the following, but not limited to, topics:

  • 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)

Abstracting and Indexing: Scopus; Web of Science - Social Science Index; EconLit; and Cabell’s Directory

Journal Metrics:
Impact Factor: 0.188
5-Year Impact Factor: 0.355
CiteScore: 0.25

 

Value-at-risk bounds for multivariate heavy tailed distribution: an application to the Glosten–Jagannathan–Runkle generalized autoregressive conditional heteroscedasticity model

This paper aims to derive VaR bounds for the portfolios of possibly dependent financial assets for heavy tailed Glosten–Jagannathan–Runkle generalized autoregressive conditional heteroscedasticity processes using extreme value theory copulas.

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