Advances in Risk Management (Finance and Capital Markets), by Greg N. Gregoriou

By Greg N. Gregoriou

This publication contains an edited sequence of papers approximately hazard administration and the newest advancements within the box. masking subject matters akin to Stochastic Volatility, probability Dynamics, climate Derivatives and Portfolio Diversification, this ebook could have extensive foreign allure. it really is hugely relevany for optimum portfolio allocation for either inner most and institutional traders around the world.

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However, the expected value of the portfolio across multiple scenarios is not computed by the regulator. Instead, the worst outcome across the scenarios defines the risk of a coherent risk measure. It is important to emphasize that coherent risk measures do not account for diversification. Although ADEH have a subadditivity axiom that parallels a property implied by our risk measure, their definition of risk applies A M I Y A T O S H P U R N A N A N D A M E T A L. 25 to terminal portfolio values. Thus, the portfolio weights of the underlying assets cannot be altered to exploit the benefits of diversification.

85 million. Second, this result is mainly due to the way the tail is modeled. As we rely on EVT to model the very high losses, the collection threshold has no or little impact on the fatness of the tail for the severity distribution. Finally, the choice of the collection threshold should thus not be guided by capital requirements concerns but rather by a “pro/cons” analysis of the practical implementation issues (costs, required systems, resources…) as regulatory arbitrage seems not to be applicable in this case.

1999) “Exceedances over High Thresholds: A Guide to Threshold Selection”, Extremes 1: 251–61. , Furrer, H. and Kaufmann, R. (2003) “Quantifying Regulatory Capital for Operational Risk”, Working Paper, RiskLab, ETH Zürich. , Klüppelberg, C. and Mikosch, T. (1997) Modelling Extremal Events for Insurance and Finance (Berlin: Springer-Verlag). , Jordan, J. and Rosengren, E. (2003) “Using Loss Data to Quantify Operational Risk”, Working Paper, Federal Reserve Bank of Boston. , Rosengren, E. and Jordan, J.

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