000 03325nam a22005295i 4500
001 978-3-319-26039-6
003 DE-He213
005 20200421112219.0
007 cr nn 008mamaa
008 151031s2016 gw | s |||| 0|eng d
020 _a9783319260396
_9978-3-319-26039-6
024 7 _a10.1007/978-3-319-26039-6
_2doi
050 4 _aQA76.9.M35
072 7 _aGPFC
_2bicssc
072 7 _aTEC000000
_2bisacsh
082 0 4 _a620
_223
100 1 _aChaudhuri, Arindam.
_eauthor.
245 1 0 _aQuantitative Modeling of Operational Risk in Finance and Banking Using Possibility Theory
_h[electronic resource] /
_cby Arindam Chaudhuri, Soumya K. Ghosh.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aCXC, 16 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Fuzziness and Soft Computing,
_x1434-9922 ;
_v331
520 _aThis 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.
650 0 _aEngineering.
650 0 _aOperations research.
650 0 _aDecision making.
650 0 _aEconomics, Mathematical.
650 0 _aStatistics.
650 0 _aComplexity, Computational.
650 1 4 _aEngineering.
650 2 4 _aComplexity.
650 2 4 _aStatistics for Business/Economics/Mathematical Finance/Insurance.
650 2 4 _aOperation Research/Decision Theory.
650 2 4 _aQuantitative Finance.
700 1 _aGhosh, Soumya K.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319260372
830 0 _aStudies in Fuzziness and Soft Computing,
_x1434-9922 ;
_v331
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-26039-6
912 _aZDB-2-ENG
942 _cEBK
999 _c57309
_d57309