Temi di discussione del Servizio Studi The modelling of operational risk: experience with the analysis of the data collected by the Basel Committee

By Marco Moscadelli. 2004

291 citations recorded by the source corpus.

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Citations in the corpus

Multivariate models for operational risk (2010, background): “Pareto’s law is the prototypical parametric example for a heavy tailed distribution and suitable for operational risk modelling (see, e.g., Moscadelli 2004).”
Practical methods for measuring and managing operational risk in the financial sector: a clinical study (2008, methodology): “For instance, Embrechts, Klüppelberg and Mikosch (1997) recommend the use of Extreme Value Theory (EVT) to model the tail of the distribution in risk management, and so do King (2002), Moscadelli (2004), Cruz (2004) or Chavez-Demoulin, Embrechts and Neslehova (2006).”
Modelling and measuring multivariate operational risk with Lévy copulas (2008, background): “Moscadelli [17])), total OpVAR both for completely dependent and independent data.”
Quantitative models for operational risk: Extremes, dependence and aggregation (2006, background): “Numerous papers have looked at EVT applied to operational risk; see for instance Moscadelli (2004), Cruz (2004) and the references therein.”
Extreme Value Theory for Finance: A Survey (2012, background): “Work in this area can be found in Moscadelli (2004), Dutta and Perry (2006), Allen and Bali (2007), Jobst (2007), Abbate et al. (2008), Chapelle et al. (2008) and Serguieva et al. (2009).”
Operational Risk Quantification Using Extreme Value Theory and Copulas: From Theory to Practice (2009, unknown): “We refer in particular to Moscadelli (2004), De Fontnouvelle et al. (2004) and Dutta and Perry (2007).”
Applying Robust Methods to Operational Risk Modeling (2006, background): “For example, Moscadelli (2004) examines the operational loss data5 and excludes one outlier from the Retail Brokerage loss data (that consists of a total of 3,267 5The data are taken from the second Loss Data Collection Exercise (Quantitative Impact Study 3), see also BIS (2003). observations) and…”
An Academic Response to Basel 3.5 (2014, methodology): “This measure was for instance used in the analysis of operational risk data in Moscadelli (2004).”
Determining operational capital at risk: an empirical application to the retail banking (2009, background): “This finding coincides with the warning given in the study by Moscadelli (2004).”
The Quantitative Modeling of Operational Risk: Between G-and-H and EVT (2007, background): “KEYWORDS Extreme Value Theory, g-and-h Distribution, Hill Estimator, LDA, Operational Risk, Peaks Over Threshold, Second Order Regular Variation, Subadditivity, Value-at-Risk.”
An extreme value approach for modeling Operational Risk losses depending on covariates (2016, unknown): “…● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● TS 1980 1990 2000 2010 yr la m P re d$ pr ed ic t[j bl ] ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● UBL Year ● λ̂ 0.95 CI λ̂ w ith p oi nt w is e as ym pt ot ic tw o− si de d 95 % c on fid en ce in te rv…”
Multivariate extremes and the aggregation of dependent risks: examples and counter-examples (2009, unknown): “That answers to these questions are relevant for practice can for instance be seen in applied publications like Moscadelli (2004) and Aas et al. (2007).”
Additivity properties for Value-at-Risk under Archimedean dependence and heavy-tailedness (2009, background): “Influential papers from the regulatory side concerning several quantitative impact studies are Moscadelli [20], de Fontnouvelle et al.”
Model uncertainty and VaR aggregation (2013, methodology): “Such situations are no doubt present in Operational Risk data; see for instance Moscadelli (2004), Panjer (2006), Shevchenko (2011) and Bolancé et al. (2012).”