Quantitative models are omnipresent ābut often controversially discussedā in todays risk management practice. New regulations, innovative ļ¬nancial products, and advances in valuation techniques provide a continuous ļ¬ow of challenging problems for ļ¬nancial engineers and risk managers alike. Designing a sound stochastic model requires ļ¬nding 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 āproviding methodological advancesā and practice āhaving a ļ¬rm understanding of the economic conditions in which a given model is used. Discussed ļ¬elds 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.
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