Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/182305
Editors: 
Glau, Kathrin
Scherer, Matthias
Zagst, Rudi
Year of Publication: 
2015
Series/Report no.: 
Springer Proceedings in Mathematics & Statistics 99
Abstract: 
Quantitative models are omnipresent - but often controversially discussed - in todays risk management practice. New regulations, innovative financial products, and advances in valuation techniques provide a continuous flow of challenging problems for financial engineers and risk managers alike. Designing a sound stochastic model requires finding a careful balance between parsimonious model assumptions, mathematical viability, and interpretability of the output. Moreover, data requirements and the end-user training are to be considered as well. The KPMG Center of Excellence in Risk Management conference Risk Management Reloaded and this proceedings volume contribute to bridging the gap between academia - providing methodological advances - and practice - having a firm understanding of the economic conditions in which a given model is used. Discussed fields of application range from asset management, credit risk, and energy to risk management issues in insurance. Methodologically, dependence modeling, multiple-curve interest rate-models, and model risk are addressed. Finally, regulatory developments and possible limits of mathematical modeling are discussed.
Subjects: 
Quantitative Finance
Game Theory, Economics, Social and Behav. Sciences
Finance/Investment/Banking
Actuarial Sciences
Persistent Identifier of the first edition: 
ISBN: 
978-3-319-09114-3
Creative Commons License: 
https://creativecommons.org/licenses/by-nc/3.0/legalcode
Document Type: 
Book
Document Version: 
Published Version
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