Ratings-based credit risk modelling: An empirical analysis

Banks have recently developed new techniques for gauging the credit risk associated with portfolios of illiquid and defaultable instruments. These techniques could revolutionise banks' management of credit risk and could in the longer term serve as a more risk-sensitive basis for calculating regulatory capital on banks' loan books than in Basel 2, the new regulatory capital framework. In this paper we implement a popular credit risk model that exploits the information in credit ratings to determine a portfolio's value-at-risk. Using price data on large eurobond portfolios, we assess, on an out-of-sample basis, how well the model tracks the risks it is supposed to measure.     

Measuring and modelling risk in a naturalistic setting

Two studies were undertaken to investigate risk perception in a military context. A questionnaire elicited cadets’ (n = 136) ratings of three categories of critical incidents (threats, constraints, and suffering among civilians) on nine qualitative risk dimensions adapted from the ‘Psychometric risk paradigm’ along with perceived personal risk, general risk, security and anticipated anxiousness. Factor analyses of average responses to the nine dimensions revealed two components: dread and new risk, the former strongly correlated with anticipated anxiousness and perceived personal and general risk. In a prospective survey, peacekeepers in Kosovo (n = 766) reported frequencies of exposure to threats, constraints, and suffering among civilians, and rated their personal risk of injury, the general risk and their trust in security relative to the peacekeeping operation. The fitness of a path model relating risk perception to risk exposure was estimated with reference to data collected after two, four and six months of deployment. Results were systematic across measurements and fit-indices in suggesting support for the model. The results confirm and extend findings from previous studies on risk perception by showing the impact of both risk characteristics (qualitative dimensions) and actual risk exposure (frequencies) on subjective risk perceptions.     

A novel dual-weighted fuzzy proximal support vector machine with application to credit risk analysis

In this paper, a novel dual-weighted fuzzy proximal support vector machine (FPSVM) model hybridizing fuzzy set theory (FST) and proximal support vector machine (PSVM) is proposed for credit risk analysis. In the proposed model, the fuzzy memberships are introduced into both objective function and constraint conditions of PSVM model to make full use of the information of data. Due to the introduction of fuzzy set theory, the FPSVM model shows fine generalized ability and great practical value. For verification purpose, two publicly available credit datasets are used to test the effectiveness of the proposed FPSVM method. Experimental results show that the proposed FPSVM outperforms other SVM models listed in this study, indicating that the proposed FPSVM model has rather good discriminatory power and it can be used as a promising tool for other classification tasks.     

An adaptive hierarchical fuzzy logic system for modelling of financial systems

In this paper an intelligent hierarchical fuzzy logic system using genetic algorithms for the prediction and modelling of interest rates in Australia is developed. The proposed system uses a hierarchical fuzzy logic system in which a genetic algorithm is used as a training method for learning the fuzzy rules knowledge bases that are used for prediction of interest rates in Australia. A hierarchical fuzzy logic system is developed to model and predict three‐month (quarterly) interest rate ?uctuations. The system is further trained to model and predict interest rates for six‐month and one‐year periods. The proposed system is developed with ?rst two, three, then four and ?nally ?ve hierarchical knowledge bases to model and predict interest rates. A novel architecture called a feed forward fuzzy logic system using fuzzy logic and genetic algorithms is also developed to predict interest rates. A back‐propagation hierarchical neural network system is also developed to predict interest rates for three‐month, six‐month and one‐year periods. The results obtained from these two systems are then compared with the hierarchical fuzzy logic system results and conclusions are drown on the accuracy of all systems for prediction of interest rates in Australia. Copyright © 2004 John Wiley & Sons, Ltd.     

The emperor has no clothes: Limits to risk modelling

This paper considers the properties of risk measures, primarily value-at-risk (VaR), from both internal and external (regulatory) points of view. It is argued that since market data is endogenous to market behavior, statistical analysis made in times of stability does not provide much guidance in times of crisis. In an extensive survey across data classes and risk models, the empirical properties of current risk forecasting models are found to be lacking in robustness while being excessively volatile. For regulatory use, the VaR measure may give misleading information about risk, and in some cases may actually increase both idiosyncratic and systemic risk.     

Time varying country risk: an assessment of alternative modelling techniques

Three different techniques for the estimation of a time-varying beta are investigated: a bivariate GARCH model, the Schwert and Seguin approach, and the Kalman filter method. These approaches are applied to a set of monthly Morgan Stanley country index data over the period 1970 to 1995 and their relative performances compared. In-sample forecast tests of the performance of each of these methods for generating conditional beta suggest that the GARCH-based estimates of risk generate the lowest forecast error although these are not necessarily significantly less than those generated by the other techniques considered.     

Electricity spot price modelling with a view towards extreme spike risk

Sums of Lévy-driven Ornstein–Uhlenbeck processes are appropriate for modelling electricity spot price data. In this paper we present a new estimation method with particular emphasis on capturing the high peaks, which is one of the stylized features of such data. After introducing our method we show it at work for the EEX Phelix Base electricity price index. We also present a small simulation study to demonstrate the performance of our estimation procedure.     

Enterprise risk management in financial groups: analysis of risk concentration and default risk

In financial groups, enterprise risk management is becoming increasingly important in controlling and managing the different independent legal entities in the group. The aim of this paper is to assess and relate risk concentration and joint default probabilities of the group’s legal entities in order to achieve a more comprehensive picture of a financial group’s risk situation. We further examine the impact of the type of dependence structure on results by comparing linear and nonlinear dependencies using different copula concepts under certain distributional assumptions. Our results show that even if financial groups with different dependence structures do have the same risk concentration factor, joint default probabilities of different sets of subsidiaries can vary tremendously.

中国信保发布2016年《国家风险分析报告》和《全球投资风险分析报告》

《国家风险分析报告》——国家风险参考评级15国调升、13国调降;主权信用风险显著国家28个 2016年《国家风险分析报告》根据中国信保自主研发的评级体系,发布了全球192个主权国家的国家风险参考评级、主权信用风险评级以及相关评级报告,其中主权信用风险评级为中国信保首次对外发布.     

Translational benchmark risk analysis

Translational development - in the sense of translating a mature methodology from one area of application to another, evolving area - is discussed for the use of benchmark doses in quantitative risk assessment. Illustrations are presented with traditional applications of the benchmark paradigm in biology and toxicology, and also with risk endpoints that differ from traditional toxicological archetypes. It is seen that the benchmark approach can apply to a diverse spectrum of risk management settings. This suggests a promising future for this important risk-analytic tool. Extensions of the method to a wider variety of applications represent a significant opportunity for enhancing environmental, biomedical, industrial, and socio-economic risk assessments.     

Translational benchmark risk analysis

Translational development – in the sense of translating a mature methodology from one area of application to another, evolving area – is discussed for the use of benchmark doses in quantitative risk assessment. Illustrations are presented with traditional applications of the benchmark paradigm in biology and toxicology, and also with risk endpoints that differ from traditional toxicological archetypes. It is seen that the benchmark approach can apply to a diverse spectrum of risk management settings. This suggests a promising future for this important risk‐analytic tool. Extensions of the method to a wider variety of applications represent a significant opportunity for enhancing environmental, biomedical, industrial, and socio‐economic risk assessments.     

A rule-based fuzzy reasoning system for assessing the risk of management fraud

Detecting management fraud and assessing the risk of management fraud are significant issues confronting the auditing profession. Considerable theoretical and empirical research (Loebbecke, Eining, and Willingham, 1989; Bell, Szykowny, and Willingham, 1993; Fanning, Cogger, and Srivastava, 1995; and Hansen, McDonald, Messier, and Bell, 1996) has been accomplished investigating these issues. Building on this research, we demonstrate the construction of a rule-based fuzzy reasoning system to assess the risk of management fraud. The paper illustrates how fuzzy sets can be used intuitively to measure red flags on a categorical or interval scale, how different red flags can be combined using fuzzy rules, and how a single measure of the risk of management fraud can be derived. The knowledge base for this fuzzy reasoning system is developed by using the causal model of management fraud developed by Loebbecke, Eining and Willingham (1989), the empirical investigation of this model by Bell, Szykowny, and Willingham (1993), other researchers’ efforts and the authors’ judgments, using XpertRule software. The fuzzy reasoning system is tested using the fraud data provided by KPMG Peat Marwick. We discuss methods to magnify the knowledge base of this fuzzy reasoning system to make it a viable auditing tool, the costs and benefits of building a fuzzy reasoning system, and further extensions of this research. Copyright © 1998 John Wiley & Sons, Ltd.     

A fully parametric approach to return modelling and risk management of hedge funds

This paper examines the empirical properties of hedge fund returns and proposes a fully parametric model capable of adequately describing both univariate and multivariate return properties. The suggested model is based on the multivariate extension of the Normal Inverse Gaussian (NIG) distribution and will be shown to be capable of capturing the characteristic distributional features of hedge fund returns. Drawing on recent research in the area of Generalized Hyperbolic distributions and their calibration, we will elaborate on the application of the NIG-model for risk management purposes, and highlight the differences between the NIG and the Gaussian model.      

Understanding,modelling and managing longevity risk: key issues and main challenges

This article investigates the latest developments in longevity-risk modelling, and explores the key risk management challenges for both the financial and insurance industries. The article discusses key definitions that are crucial for the enhancement of the way longevity risk is understood, providing a global view of the practical issues for longevity-linked insurance and pension products that have evolved concurrently with the steady increase in life expectancy since s. In addition, the article frames the recent and forthcoming developments that are expected to action industry-wide changes as more effective regulation, designed to better assess and efficiently manage inherited risks, is adopted. Simultaneously, the evolution of longevity is intensifying the need for capital markets to be used to manage and transfer the risk through what are known as Insurance-Linked Securities (ILS). Thus, the article will examine the emerging scenarios, and will finally highlight some important potential developments for longevity-risk management from a financial perspective with reference to the most relevant modelling and pricing practices in the banking industry.     

An Evolving Conceptual Framework?

The history of the conceptual framework (CF) exercise indicates more a search for a rationale for current practice than a re-affirmation of the legal, social and economic (especially financial) framework within which accounting is to function, and the necessary shape of a compatible system of accounting. Interestingly, issues similar to those presaging the formation of the American Institute of Certified Public Accountants' Wheat and Trueblood Committees (antecedents of the formation of the Financial Accounting Standards Board in 1973 and its CF project in 1976) are evident again today. Such events led to a reconsideration of the effectiveness of CFs in their current form as 'constitutions'. Arguably, the framework of concepts underpinning ordinary, everyday commerce is the CF of accounting. The quest for a unique constitution-based CF of accounting, independent of observables, has been misplaced, insofar it is unnecessary. Arguably, if more attention had been given to the function of accounting the futility of the CF exercise could have been avoided.