Expectile regression, as a general M smoother, is used to capture the tail behaviour of a distribution. Let (X <Subscript>1</Subscript>,Y <Subscript>1</Subscript>),…,(X <Subscript> n </Subscript>,Y <Subscript> n </Subscript>) be i.i.d. rvs. Denote by v(x) the unknown τ-expectile regression curve of Y conditional on X, and by v <Subscript> n </Subscript>(x) its kernel smoothing estimator. In this paper, we...</subscript></subscript></subscript></subscript></subscript>

Generalized quantile regressions, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to...

Let (X1; Y1), …, (Xn; Yn) be i.i.d. rvs and denote v(x) be the unknown τ - expectile regression curve of Y conditional on X. An expectile-smoother vn(x) is a localized, nonlinear estimator of v(x). The strong uniform consistency rate is established under general conditions. In many...

A good description of the dynamics of interest rates is crucial to price derivatives and to hedge corresponding risk. Interest rate modelling in an unstable macroeconomic context motivates one factor models with time varying parameters. In this paper, the local parameter approach is introduced...