Econometrics of Risk [electronic resource] / edited by Van-Nam Huynh, Vladik Kreinovich, Songsak Sriboonchitta, Komsan Suriya.
Contributor(s): Huynh, Van-Nam [editor.] | Kreinovich, Vladik [editor.] | Sriboonchitta, Songsak [editor.] | Suriya, Komsan [editor.] | SpringerLink (Online service).
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BookSeries: Studies in Computational Intelligence: 583Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Description: X, 498 p. 94 illus., 19 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319134499.Subject(s): Engineering | Economics, Mathematical | Computational intelligence | Quality control | Reliability | Industrial safety | Econometrics | Engineering | Computational Intelligence | Quantitative Finance | Econometrics | Quality Control, Reliability, Safety and RiskAdditional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
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Springer eBooksSummary: This edited book contains several state-of-the-art papers devoted to econometrics of risk. Some papers provide theoretical analysis of the corresponding mathematical, statistical, computational, and economical models. Other papers describe applications of the novel risk-related econometric techniques to real-life economic situations. The book presents new methods developed just recently, in particular, methods using non-Gaussian heavy-tailed distributions, methods using non-Gaussian copulas to properly take into account dependence between different quantities, methods taking into account imprecise ("fuzzy") expert knowledge, and many other innovative techniques. This versatile volume helps practitioners to learn how to apply new techniques of econometrics of risk, and researchers to further improve the existing models and to come up with new ideas on how to best take into account economic risks.
This edited book contains several state-of-the-art papers devoted to econometrics of risk. Some papers provide theoretical analysis of the corresponding mathematical, statistical, computational, and economical models. Other papers describe applications of the novel risk-related econometric techniques to real-life economic situations. The book presents new methods developed just recently, in particular, methods using non-Gaussian heavy-tailed distributions, methods using non-Gaussian copulas to properly take into account dependence between different quantities, methods taking into account imprecise ("fuzzy") expert knowledge, and many other innovative techniques. This versatile volume helps practitioners to learn how to apply new techniques of econometrics of risk, and researchers to further improve the existing models and to come up with new ideas on how to best take into account economic risks.
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