Introduction
Quantitative Risk Management (QRM for short) is a relatively new field of mathematical research on the scientific firmament. As a field of science, QRM concentrates on the axiomatisation, the measurement and the analysis of risk in a rather broad context. Examples range from the construction of dykes, over the development of new medical compounds to the calculation of risk capital for insurance companies and banks. The quantification of risk and the societal challenges concerning “living with risks” are well known to all; how high do we need to build a sea dyke in order to protect a geographic area and its inhabitants, or what are prudent regulatory guidelines in order to safeguard a stable financial system? It is immediately clear that an overview of the field is out of the question, the various acronyms encountered stand proof of this: besides QRM, ERM (Enterprise-wide Risk Management), GRM (Global RM), IRM (Integrative RM), and no doubt others. A broad overview of the...
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References and Further Reading
Acerbi C, Tasche D (2002) On the coherence of expected shortfall. J Banking Finance 26:1487–1503
Artzner P, Delbaen F, Eber J-M, Heath D (1999) Coherent measures of risk. Math Finance 9:203–228
Bingham NH, Kiesel R (2002) Semi-parametric modelling in finance: theoretical foundations. Quan Finance 2:241–250
Coles S (2001) An introduction to statistical modeling of extreme values. Springer, London
Embrechts P (2009) Copulas: a personal view. J Risk Insur 76: 639–650
Embrechts P, Klüppelberg C, Mikosch T (1997) Modelling extremal events for insurance and finance. Springer, Berlin
Embrechts P, Lambrigger DD, Wüthrich MV (2009) Multivariate extremes and the aggregation of dependent risks: examples and counter-examples. Extremes 12:107–127
Föllmer H, Schied A (2004) Stochastic finance: an introduction in discrete time, 2nd edn (de Gruyter Studies in Mathematics 27). Walter de Gruyter, Berlin
Joe H (1997) Multivariate models and dependence concepts. Chapman & Hall, London
Li D (2001) On default correlation: a copula function approach. J Fixed Income 9:43–54
McNeil AJ, Frey R, Embrechts P (2005) Quantitative risk management: concepts, techniques, tools. Princeton University Press, Princeton
Melnick EL, Everitt BS (eds) (2008) Encyclopedia of quantitative risk analysis and assessment, vol 4. Wiley, Chichester
Nelsen RB (2007) An introduction to copulas, 2nd edn. Springer, New York
Panjer HH (2006) Operational risk: modeling analytics. Wiley, London
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Embrechts, P. (2011). Quantitative Risk Management. In: Lovric, M. (eds) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04898-2_466
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DOI: https://doi.org/10.1007/978-3-642-04898-2_466
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