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Quantitative Modeling of Operational Risk in Finance and Banking Using Possibility Theory (Hardcover, 1st ed. 2016)
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Quantitative Modeling of Operational Risk in Finance and Banking Using Possibility Theory (Hardcover, 1st ed. 2016)
Series: Studies in Fuzziness and Soft Computing, 331
Expected to ship within 10 - 15 working days
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This book offers a comprehensive guide to the modelling of
operational risk using possibility theory. It provides a set of
methods for measuring operational risks under a certain degree of
vagueness and impreciseness, as encountered in real-life data. It
shows how possibility theory and indeterminate
uncertainty-encompassing degrees of belief can be applied in
analysing the risk function, and describes the parametric g-and-h
distribution associated with extreme value theory as an interesting
candidate in this regard. The book offers a complete assessment of
fuzzy methods for determining both value at risk (VaR) and
subjective value at risk (SVaR), together with a stability
estimation of VaR and SVaR. Based on the simulation studies and
case studies reported on here, the possibilistic quantification of
risk performs consistently better than the probabilistic model.
Risk is evaluated by integrating two fuzzy techniques: the fuzzy
analytic hierarchy process and the fuzzy extension of techniques
for order preference by similarity to the ideal solution. Because
of its specialized content, it is primarily intended for
postgraduates and researchers with a basic knowledge of algebra and
calculus, and can be used as reference guide for research-level
courses on fuzzy sets, possibility theory and mathematical finance.
The book also offers a useful source of information for banking and
finance professionals investigating different risk-related aspects.
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