Evaluating Risk Measures Using the Normal Mean-Variance Birnbaum-Saunders Distribution
DOI10.1007/978-3-030-42196-0_8OpenAlexW3048707456MaRDI QIDQ5050412
Wan-Lun Wang, Mehrdad Naderi, Ahad Jamalizadeh, Tsung I. Lin
Publication date: 15 November 2022
Published in: Emerging Topics in Statistics and Biostatistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-030-42196-0_8
portfolioEM algorithmcoherencenormal distributionAkaike information criterionBayesian information criterionkurtosismoment generating functionrisk measuresmodified Bessel functionskew-normal distributionvalue at riskskew-\(t\) distributionBirnbaum-Saunders distributionKolmogorov-Smirnov testEsscher premiumgeneralized inverse Gaussian distribution\(t\) distributionJarque-Bera testgeneralized hyperbolic distributionstock market returnstail-value at risklog-returnsentropic measureslower partial momentprobability of shortfallnormal-inverse Gaussian distributionmaximized likelihood estimationexceeding ratiomean absolute relative errornormal mean-variance Birnbaum-Saunders distributionprobability of outperformancetarget shortfall
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