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In this paper we propose the GHADA risk management model that is based on the generalized hyperbolic (GH) distribution and on a nonparametric adaptive methodology. Compared to the normal distribution, the GH distribution possesses semi-heavy tails and represents the financial risk factors more...
Persistent link: https://www.econbiz.de/10003035074
Persistent link: https://www.econbiz.de/10003772400
In this paper we propose the GHADA risk management model that is based on the generalized hyperbolic (GH) distribution and on a nonparametric adaptive methodology. Compared to the normal distribution, the GH distribution possesses semi-heavy tails and represents the financial risk factors more...
Persistent link: https://www.econbiz.de/10005862343
Persistent link: https://www.econbiz.de/10004868772
In this paper we propose the GHADA risk management model that is based on the gener- alized hyperbolic (GH) distribution and on a nonparametric adaptive methodology. Com- pared to the normal distribution, the GH distribution possesses semi-heavy tails and repre- sents the financial risk factors...
Persistent link: https://www.econbiz.de/10005677905
Persistent link: https://www.econbiz.de/10010274106
Persistent link: https://www.econbiz.de/10003036527
Persistent link: https://www.econbiz.de/10002732876
How can we measure and compare the relative performance of production units? If input and output variables are one dimensional, then the simplest way is to compute efficiency by calculating and comparing the ratio of output and input for each production unit. This idea is inappropriate though,...
Persistent link: https://www.econbiz.de/10012966215
Risk management technology applied to high dimensional portfolios needs simple and fast methods for calculation of Value-at-Risk (VaR). The multivariate normal framework provides a simple off-the-shelf methodology but lacks the heavy tailed distributional properties that are observed in data. A...
Persistent link: https://www.econbiz.de/10010319191