The Basel Committee's 2014 revision of its operational risk capital framework, along with the multi-billion-dollar settlements that financial institutions had to make with financial authorities, has made operational risk the key focus of risk management. The Journal of Operational Risk stimulates active discussions of practical approaches to quantify, model and manage this risk, also discussing current issues in the discipline, and is essential reading for keeping practitioners and academics informed of the latest research in operational risk theory and practice.
The Journal of Operational Risk considers submissions in the form of research papers and forum papers, on topics including, but not limited to:
- Modelling and management of operational risk
- Recent advances in techniques used to model operational risk, for example: copulas, correlation, aggregate loss distributions, Bayesian methods and extreme value theory
- Pricing and hedging of operational risk and/or any risk transfer techniques
- Data modelling external loss data, business control factors and scenario analysis
- Models used to aggregate the different types of data
- Causal models that link key risk indicators and macroeconomic factors to operational losses
- Regulatory issues, such as Basel II or any other local regulatory issue
- Enterprise risk management
- Cyber risk
- Big data
Abstracting and Indexing: Scopus; Web of Science - Social Science Index; EconLit; Econbiz; and Cabell’s Directory
Impact Factor: 0.394
5-Year Impact Factor: 0.519
In this paper, the authors present an alternative quantification technique, so-called exposure-based operational risk (EBOR) models, which aim to replace historical severity curves by measures of current exposures and use event frequencies based on…
In this paper, the authors present a way to address multivariate distortion risk measures and give some examples of distortion functions and distributions where the final expression has a closed form.
In this paper, the author constructs a capital model for operational risk based on the observation that operational losses can, under a certain dimensional transformation, converge into a single, universal distribution.
In this paper, the author presents a simple probabilistic model for aggregating very large losses into a loss collection.
Bridging networks, systems and controls frameworks for cybersecurity curriculums and standards development
This paper proposes a risk management framework designed to facilitate the alignment, integration and streamlining of professional practice standards and computer science/cybersecurity educational curriculums by bridging NPNATFs, SNIFs and RMCPFs.
In this paper, the authors study tail dependence by defining the conditions required for all the methods used to perform and to quantify their efficiency and accuracy.
In this paper, the authors propose a method of allocating operational risk regulatory capital using a closed-form Shapley method, applicable to a large number of business units (BUs).
In this paper, the authors discuss the hazard generated by OpRisk driven by natural and human-made disasters, and argue the position of the LDA as the most-fitted statistical approach to deal with it.
Standardized measurement approach extension to integrate insurance deduction into operational risk capital requirement
The SMA proposed in BCBS (2016) presents several issues: in particular, its two components are not sufficient to discriminate banking institutions by risk profile, thus penalizing the more virtuous ones. This paper describes a possible solution to extend…
In this paper, the authors address the issue of an efficient people-risk capital allocation for financial institutions.
A note on the standard measurement approach versus the loss distribution approach–advanced measurement approach: the dawning of a new regulation
This paper presents a nonexhaustive review of the literature on operational risk quantification under a combination of the loss distribution approach model – the most commonly used of the AMA models – and extreme value theory.
In this paper, the author presents an easy-to-implement, fast and accurate method for approximating extreme quantiles of compound loss distributions (frequency + severity), which are commonly used in insurance and operational risk capital models.
This paper discusses key features of fighting behavioral risk in the business line of operations as the central hub for all transactions in a bank.
By comparing the Libor and FX benchmark manipulation scandals, this paper describes how misbehavior emerged independently in both of these markets and the conditions that permitted the misconduct to survive and thrive.
The issues with the standardized measurement approach and a potential future direction for operational risk capital modeling
This paper discusses the criticism and praise the SMA and AMA have received, respectively, in many recent articles.
This paper proposes a new risk-based regime-switching model for stock prices to examine the impact of operational risk events on stock prices.
This paper focuses on the parametric estimators of risk measures and uses Hampel’s infinitesimal approach to derive the robustness properties.
This paper applies classical theory to determine if limiting distributions exist for WCvM test statistics under a simple null hypothesis.
Various approximations of the total aggregate loss quantile function with application to operational risk
This paper investigates the mechanics of the empirical aggregate loss bootstrap distribution.
In this paper, a structural model is presented for estimating losses associated with the mis-selling of retail banking products. It is the first paper to consider factor-based modeling for this operational/conduct risk scenario.