000 | 03824nam a22006135i 4500 | ||
---|---|---|---|
001 | 978-3-319-26039-6 | ||
003 | DE-He213 | ||
005 | 20220801221922.0 | ||
007 | cr nn 008mamaa | ||
008 | 151031s2016 sz | s |||| 0|eng d | ||
020 |
_a9783319260396 _9978-3-319-26039-6 |
||
024 | 7 |
_a10.1007/978-3-319-26039-6 _2doi |
|
050 | 4 | _aTA352-356 | |
050 | 4 | _aQC20.7.N6 | |
072 | 7 |
_aTBJ _2bicssc |
|
072 | 7 |
_aGPFC _2bicssc |
|
072 | 7 |
_aTEC009000 _2bisacsh |
|
072 | 7 |
_aTBJ _2thema |
|
072 | 7 |
_aGPFC _2thema |
|
082 | 0 | 4 |
_a515.39 _223 |
100 | 1 |
_aChaudhuri, Arindam. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _958709 |
|
245 | 1 | 0 |
_aQuantitative Modeling of Operational Risk in Finance and Banking Using Possibility Theory _h[electronic resource] / _cby Arindam Chaudhuri, Soumya K. Ghosh. |
250 | _a1st ed. 2016. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016. |
|
300 |
_aXVI, 190 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, _x1860-0808 ; _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 |
_aDynamics. _958710 |
|
650 | 0 |
_aNonlinear theories. _93339 |
|
650 | 0 |
_aStatistics . _931616 |
|
650 | 0 |
_aOperations research. _912218 |
|
650 | 0 |
_aSocial sciences—Mathematics. _931863 |
|
650 | 1 | 4 |
_aApplied Dynamical Systems. _932005 |
650 | 2 | 4 |
_aStatistics in Business, Management, Economics, Finance, Insurance. _931719 |
650 | 2 | 4 |
_aOperations Research and Decision Theory. _931599 |
650 | 2 | 4 |
_aMathematics in Business, Economics and Finance. _931864 |
700 | 1 |
_aGhosh, Soumya K. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _958711 |
|
710 | 2 |
_aSpringerLink (Online service) _958712 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783319260372 |
776 | 0 | 8 |
_iPrinted edition: _z9783319260389 |
776 | 0 | 8 |
_iPrinted edition: _z9783319374185 |
830 | 0 |
_aStudies in Fuzziness and Soft Computing, _x1860-0808 ; _v331 _958713 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-319-26039-6 |
912 | _aZDB-2-ENG | ||
912 | _aZDB-2-SXE | ||
942 | _cEBK | ||
999 |
_c80201 _d80201 |