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2001
As discussed in the introductory chapter, the uncertainty associated with the future (terminal) value of a portfolio may be modelled as a random variable g[w(T)] whose probabilistic characteristics are specified by the induced probability measure P g or its associated distribution function F g .
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As discussed in the introductory chapter, the uncertainty associated with the future (terminal) value of a portfolio may be modelled as a random variable g[w(T)] whose probabilistic characteristics are specified by the induced probability measure P g or its associated distribution function F g .
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Drug Metabolism Reviews, 1982
(1982). Statistical Measures of Risk. Drug Metabolism Reviews: Vol. 13, No. 5, pp. 829-838.
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(1982). Statistical Measures of Risk. Drug Metabolism Reviews: Vol. 13, No. 5, pp. 829-838.
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Risk Measures and Comonotonicity: A Review
Stochastic Models, 2006In this paper we examine and summarize properties of several well-known risk measuresthat can be used in the framework of setting solvency capital requirements for a risky business.Special attention is given to the class of (concave) distortion risk measures.
Dhaene, J.L.M. +5 more
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Consistent measures of risk [PDF]
, 2006 In this paper we compare overall as well as downside risk measures with respect to the criteria of first and second order stochastic dominance. While the downside risk measures, with the exception of tail conditional expectation, are consistent with first order stochastic dominance, overall risk measures are not, even if we restrict ourselves to two ...
Casper G. de Vries +4 more
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, 2000 We provide a critique of the methods that have been used to derive measures of income risk and draw attention to the importance of demographic factors as a source of income risk. We also propose new measures of the contribution to total income risk of demographic and labour market factors.
Simon Burgess +3 more
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Robust risk measurement and model risk
Quantitative Finance, 2012Financial risk measurement relies on models of prices and other market variables, but models inevitably rely on imperfect assumptions and estimates, creating model risk. Moreover, optimization decisions, such as portfolio selection, amplify the effect of model error. In this work, we develop a framework for quantifying the impact of model error and for
Paul Glasserman, Xingbo Xu
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Network Security, 2018
Resilience is the capacity for a business to quickly recover from disruption. Under pressure, a resilient organisation is able to quickly adapt to challenges and maintain continuous business operations that safeguard people, assets and reputation.
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Resilience is the capacity for a business to quickly recover from disruption. Under pressure, a resilient organisation is able to quickly adapt to challenges and maintain continuous business operations that safeguard people, assets and reputation.
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Measuring Risk: Risk Analysis or Sensitivity Analysis?
IFAC Proceedings Volumes, 1995Abstract Governments in developing countries invest large amounts in public infrastructures. However, information on economic risk on the project level is hardly ever included in the assessment of a project’s feasibility. Practitioners normally restrict their analysis to one factor at a time sensitivity analysis, which is insufficient information to ...
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Essays on Measuring Model Risk of Risk Measures
2020The thesis contributes to the quantitative measurement of model risk of popular models for market risk measures (focusing on Value-at-Risk and Expected Shortfall, denoted by VaR and ES) and volatility forecasting in several ways, and it consists of three main chapters.
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The measurement of investment risk
Journal of the Institute of Actuaries, 19871.1 In the paper ‘Improving the Performance of Equity Portfolios’ by Clarkson and Plymen the authors concluded that Modern Portfolio Theory methods made no contribution whatever to improving the performance of equity portfolios and suggested that attention should be paid instead to the application of fundamental analysis, which—if carried out by ...
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