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)
Abstracting and Indexing: Scopus; Web of Science - Social Science Index; EconLit; Econbiz; and Cabell’s Directory
Impact Factor: 0.485
5-Year Impact Factor: 0.429
An optimized support vector machine intelligent technique using optimized feature selection methods: evidence from Chinese credit approval data
This paper focuses on feature selection methods for support vector machine (SVM) classifiers, checking their optimality by comparing them with some statistical and baseline methods.
This paper incorporates volatility forecasting via the exponentially weighted moving average model into traditional tolerance limits for pair-trading strategies, and illustrates how the proposed method helps uncover arbitrage opportunities via the daily…
On the mathematical modeling of point-in-time and through-the-cycle probability of default estimation/ validation
In this paper, the authors focus on PD estimation and validation. They provide the mathematical modeling for both point-in-time (PIT) and through-the-cycle (TTC) PD estimation, and discuss their relationship and application in our banking system.
In this paper, the author's aim is to empirically analyze the numerical quantification of model risk, yielding exact buffers in currency amounts (for a given model uncertainty).
In this paper, the author looks at the efficacy of risk measures on energy markets and across several different stock market indexes, and calculates both the value-at-risk (VaR) and the expected shortfall (ES) on each of these data sets as well as on…
A comprehensive evaluation of value-at-risk models and a comparison of their performance in emerging markets
This paper aims to evaluate the performance of different value-at-risk (VaR) calculation methods, allowing the authors to identify models that are valid for use in emerging markets.
This paper examines the credit exposure evaluation properties of interest rate derivatives to manage counterparty credit risk, working with the real-world probability.
This paper aims to reflect the current state of the discussion on the validation of market risk forecasts by means of backtesting.
Procyclicality of capital and portfolio segmentation in the advanced internal ratings-based framework: an application to mortgage portfolios
This paper investigates the procyclicality of capital in the advanced internal ratings based (A-IRB) Basel approach for retail portfolios, and identifies the fundamental assumptions required for stable A-IRB risk weights over the economic cycle.
In this paper, the authors obtain analytic expressions of different actuarial and statistical quantities for a general class of composite models derived from the McDonald’s family of probability distributions.
In this paper, the authors derive an analytical solution for sub-SCR VTs starting with a model risk appetite (MRA) that defines acceptable errors for an insurer’s total SCR.
In this paper, the authors adopt a new method of predicting VaR, to estimate balanced portfolios’ VaR.
The objective of this paper is to select effective risk indicators and thus establish a risk index system of P2P platforms so as to evaluate the risk performance of these platforms in China.
The predictability implied by consumption-based asset-pricing models: a review of the theory and empirical evidence
This paper examines whether two well-known models, Campbell and Cochrane’s habit model and Bansal and Yaron’s long-run risks model, can produce significant return predictability.
Smoothing algorithms by constrained maximum likelihood: methodologies and implementations for Comprehensive Capital Analysis and Review stress testing and International Financial Reporting Standard 9 expected credit loss estimation
In this paper, the author proposes smoothing algorithms that are based on constrained maximum likelihood for rating-level PD and for rating migration probability.
This paper reviews the ways of measuring the performance of LGD models that have been previously used in the literature and also suggests some new measures.
In this paper, the importance of the empirical bootstrap (EB) in assessing minimal operational risk capital is discussed, and an alternative way of estimating minimal operational risk capital using a central limit theorem (CLT) formulation is presented.
This paper assesses the model risk associated with the copula choice for the calculation of the Default Risk Charge (DRC) measure.
In this paper, the authors examine the problem of validating and calibrating FHS VaR models, focussing in particular on the Hull and White (1998) approach with EWMA volatility estimates, given its extended use in the industry.
The aim of this paper is to validate profit and loss attribution generated by daily movements of option prices as seen through their Black–Scholes (Black and Scholes 1973) and Merton (1973) implied volatilities.