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)
In this paper, the authors investigate the four most commonly used risk measures – return volatility, beta, value-at-risk and stressed value-at-risk – of a TSM trading strategy.
The author of this paper proposes a prudent methodology to correct for potential biases in LGD estimations due to historical price appreciations, appraisal biases and wear-and-tear or potential damage to the house.
The authors propose a naive model to forecast ex ante value-at-risk (VaR), using a shrinkage estimator between realized volatility estimated on past return time series as well as implied volatility quoted in the market.
This paper explores the aggregation of different single ratings to a ‘consensus rating’ to get a higher precision of a debtor’s default probability. It builds upon the methodology published by Grün et al, 2013 and Lehmann and Tillich, 2016.
The authors of this paper use power series distributions to develop a novel and flexible zero-inflated Bayesian methodology.
The authors of this paper address some issues to do with IFRS 9 and explain how to determine if an instrument has suffered serious deterioration in credit risk.
A correlated structural credit risk model with random coefficients and its Bayesian estimation using stock and credit market information
Using historical equity and credit market data, this paper illustrates the validation of a structural correlated default model applied to Black–Cox setups.
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.
Rating-transition-probability models and Comprehensive Capital Analysis and Review stress testing: methodologies and implementation
This paper introduces a risk component called the credit index, that represents the systematic risk part of a portfolio by a list of macroeconomic variables.
A point-in-time–through-the-cycle approach to rating assignment and probability of default calibration
This paper proposes a methodology for constructing TTC rating grades and assessing the resulting degree of PIT-ness.
Value-at-risk estimation with the Carr–Geman–Madan–Yor process: an empirical study on foreign exchange rates
This paper investigates the performance of the CGMY distribution in estimating the risk of FX rates.
Testing value-at-risk models in emerging markets during crises: a case study on South Eastern European countries
This paper examines the applicability of a wide range of VaR models in emerging markets, focusing on South Eastern European countries.
Research on equity release mortgage risk diversification with financial innovation: reinsurance usage
This paper examines the risk diversification of ERMs via the reinsurance strategy.
Dynamic credit score modeling with short-term and long-term memories: the case of Freddie Mac’s database
This paper investigates the two mechanisms of memory, short-term memory and long-term memory, in the context of credit risk assessment.
This paper discusses a VaR time-scaling approach based on fitting a distribution function so as to apply a Monte Carlo simulation to determine long-term VaR.
This paper investigates a sample of 142 live hedge funds via a DEA sensitivity analysis using a super-efficiency model.
This paper develops optimal bounds of the expectation equity-to-asset ratio.
This paper proposes a loss function-based framework for the comparative measurement of the sensitivity of quantile downside risk measures to breaks in volatility or distribution.
This paper demonstrates how cash outflows due to credit lines can be modeled in a liquidity stress test.
In this paper, the authors show how one can use a certain class of models for modeling portfolios such as large corporates, banks and insurance companies.
A mean-reverting scenario design model to create lifetime forecasts and volatility assessments for retail loans
The authors of this paper develop a modeling framework that can incorporate mean-reverting scenarios into any scenario-based forecasting model.
Stress testing and model validation: application of the Bayesian approach to a credit risk portfolio
The authors of this paper develop a Bayesian-based credit risk stress-testing methodology.
Risk model validation for BRICS countries: a value-at-risk, expected shortfall and extreme value theory approach
The authors of this paper employ value-at-risk (VaR) and expected shortfall (ES) as risk measures to assess the competency of several volatility models, based on the stock indexes of the BRICS countries (Brazil, Russia, India, China and South Africa)...
Comprehensive Capital Analysis and Review stress tests: is regression the only tool for loss projection?
The authors of this paper present a cross-sectional stress test analysis of major US banks.