Titlebook: Quantitative Modeling of Operational Risk in Finance and Banking Using Possibility Theory; Arindam Chaudhuri,Soumya K. Ghosh Book 2016 Spr

敬禮

The g-and-h Distribution,ution. The concept of g-and-h distribution is presented along with some important properties of g-and-h distribution. The g-and-h distribution is fitted to the real life data. Some significant comments on the calculation of g and h parameters concludes the chapter. This chapter lays the foundation s

AWL

Probabilistic View of Operational Risk, is presented alongwith subadditivity of .. The subjective value at risk (.) is proposed. The risk and deviation measures are also discussed. The equivalence of chance and . constraints are highlighted. Some advanced properties of g-and-h distribution are discussed. Some applications on probabilisti

BOLT

Possibility Theory for Operational Risk, theory in Chap. .. The possibilistic quantification of operational risk takes care of the inherent impreciseness and vagueness present in the banking and financial data. The concepts of σ-Algebra, measurable space and measurable set, measurable function, uncertainty measure, uncertainty space, unce

金絲雀

Possibilistic View of Operational Risk,s been remodelled with possibility theory. The g-and-h distribution has been redefined as fuzzy g-and-h distribution. Similarly value at risk (.) concept is extended to fuzzy value at risk (.) and subadditivity of fuzzy . also defined. Based on fuzzy . the fuzzy subjective value at risk (.) is highl

Ceramic

Simulation Results,isk (.) as well as fuzzy versions of . and . in several optimization settings. The problem of risk control is presented using . and fuzzy . estimates along with the linear regression hedging problem. The equivalence of chance and value at risk constraints is illustrated through an example. The probl

BLA

A Case Study: Iron Ore Mining in India, theory. The mathematical modeling is performed through bilevel multiobjective optimization problem in a fuzzy environment. The datasets from iron ore (hematite) mines in the Jharkhand state sets up the computational framework. The risk is calculated using fuzzy subjective value at risk (.) constrai

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esthetician

Summary and Future Research,ia. All the theories and results are adopted from Chaudhuri (A Study of Operational Risk using Possibility Theory, Technical Report, Birla Institute of Technology Mesra, Patna Campus, 2010) and compiled in this book. The experiments are performed on several real life datasets using the MATLAB optimi

PURG

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