Skew mixture models for loss distributions: a Bayesian approach

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Bayesian Tail Risk Interdependence Using Quantile Regression (2015, background): “Bernardi (2013) and Bernardi et al. (2012) propose to estimate VaR and related risk measures by fitting asymmetric mixture models to the unconditional distribution of returns.”
Modeling loss data using composite models (2015, methodology): “Eling (2012) fitted the skew-normal and skew-t distributions to the data while Bernardi et al. (2012) analyzed the data using a Bayesian approach.”