首页|Modeling right-skewed financial data streams: A likelihood inference based on the generalized Birnbaum-Saunders mixture model
Modeling right-skewed financial data streams: A likelihood inference based on the generalized Birnbaum-Saunders mixture model
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NSTL
Elsevier
Finite mixture models have recently been considered for analyzing positive support economical data streams with non-normal features. In this paper, a new mixture model based on the novel class of generalized Birnbaum-Saunders distributions is proposed to enhance strength and flexibility in modeling heterogeneous lifetime data. Some characteristics and properties of this mixture model are outlined. By presenting a convenient hierarchical representation, a mathematically elegant and computationally tractable EM-type algorithm is adopted for computing maximum likelihood estimates. Theoretical formulae of well-known risk measures referring to the class of generalized Birnbaum-Saunders distributions are derived. Finally, the utility of the postulated methodology is illustrated with some real-world data examples. (C) 2020 Elsevier Inc. All rights reserved.
NSTL
Elsevier
