Composite Quantile Regression for the Single-Index Model

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Multitask Quantile Regression under the Transnormal Model (2016, methodology): “Although estimating optimal transformation is very difficult, we surprisingly show that we can derive the closed-form solution for optimal transformations in (2) without using any smoothing techniques as in Friedman & Stuetzle (1981), Breiman & Friedman (1985) or Stone (1985), Tibshirani (1988).”
Bayesian Tail Risk Interdependence Using Quantile Regression (2015, background): “…Du, 2008; Kuester et al., 2006; Taylor, 2008; Gerlach et al., 2011; Chen et al., 2012a,b,c); recently Adrian and Brunnermeier (2011), Chao et al. (2012), Fan et al. (2013), Hautsch et al. (2014), Chao et al. (2012) and Castro and Ferrari (2014) considered the same approach to also calculate the…”
TENET: Tail-Event driven NETwork risk (2016, methodology): “Following Fan et al. (2013), it is not hard to prove that for γn = O(1): P [ inf ‖u‖=1 { L̃n(β ∗ (1) + γnu, 0) > L̃n(β ∗) }] → 1.”