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COPING WITH LONG TERM MODEL RISK IN MARKET RISK MODELS
Proceedings of the 1st International Conference on Operations Research and Enterprise Systems, 2012The recent financial crisis has shown that most market risk models – even if they deliver sufficiently accurate risk figures over short time horizons – are not able to provide reliable forecasts for risk figures over longer time horizons like three, twelve or 36 months, which are the basis for both limit management and economic capital planning.
Spangler, Manuela, Werner, Ralf
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Model Risk in Risk Models: Quantifying Statistical Uncertainty in Active Risk
The Journal of Portfolio Management, 2021Risk models commonly provide a portfolio’s ex ante active risk as a point forecast. Under the hood of risk models, this forecast relies on a bevy of statistical estimations that introduce uncertainty in the forecast. Failure to incorporate this uncertainty in the risk forecast can present an incomplete picture of the portfolio’s risk profile ...
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SSRN Electronic Journal, 2011
Large banks assess their regulatory capital for market risk using complex, firm-wide Value-at-Risk (VaR) models. In their 'bottom-up' approach to VaR there are many sources of model risk. A recent amendment to banking regulations requires additional market risk capital to cover all these model risks but, as yet, there is no accepted framework for ...
Carol Alexander, José María Sarabia
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Large banks assess their regulatory capital for market risk using complex, firm-wide Value-at-Risk (VaR) models. In their 'bottom-up' approach to VaR there are many sources of model risk. A recent amendment to banking regulations requires additional market risk capital to cover all these model risks but, as yet, there is no accepted framework for ...
Carol Alexander, José María Sarabia
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The Identifiability of the Competing Risks Model
Biometrika, 1989This paper considers the consequences for identifiability of introducing regressors into the competing risks model of multistate duration analysis. We establish conditions under which access to regressors overturns the nonidentification theorem of \textit{D. R. Cox} [Renewal theory (1962; Zbl 0103.115)] and \textit{A. Tsiatis} [Proc. Natl. Acad.
Heckman, James J., Honoré, Bo E.
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2013
The experience from the global financial crisis has raised serious concerns about the accuracy of standard risk measures as tools for the quantification of extreme downward risk. A key reason for this is that risk measures are subject to model risk due, e.g., to specification and estimation uncertainty.
Christophe M. Boucher +3 more
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The experience from the global financial crisis has raised serious concerns about the accuracy of standard risk measures as tools for the quantification of extreme downward risk. A key reason for this is that risk measures are subject to model risk due, e.g., to specification and estimation uncertainty.
Christophe M. Boucher +3 more
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Model risk in backtesting risk measures [PDF]
, 2014 Under the Basel II regulatory framework non-negligible statistical problems arise when backtesting risk measures. In this setting backtests often become infeasible due to a low number of violations leading to heavy size distortions. According to Escanciano and Olmo (2010, 2011) these problems persist when incorporating estimation and model risk by ...
Evers, Corinna, Rohde, Johannes
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Finance and Stochastics, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Carole Bernard +3 more
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Carole Bernard +3 more
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Risk logical and probabilistic models in business and identification of risk models
Informatica (Slovenia), 2016Summary: The apparatus of logical and probabilistic (LP) simulation, not very popular among mathematicians and economists, is developed and used to study risk in business. The logical operations (AND, OR, NOT) are applied to the initiating events (instead of the traditional arithmetical addition of values).
E. D. Solojentsev, V. V. Karasev
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Risk coupling analysis of subsea blowout accidents based on dynamic Bayesian network and NK model
Reliability Engineering and System Safety, 2022Zengkai Liu, Baoping Cai, Xuewei Shi
exaly