We consider the problem of estimating the conditional quantile of a time series <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$\{ Y_t\}$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mrow> <mo stretchy="false">{</mo> <msub> <mi>Y</mi> <mi>t</mi> </msub> <mo stretchy="false">}</mo> </mrow> </math> </EquationSource> </InlineEquation> at time <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$$t$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi>t</mi> </math> </EquationSource> </InlineEquation> given covariates <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$$\varvec{X}_{t}$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <msub> <mrow> <mi mathvariant="bold-italic">X</mi> </mrow> <mi>t</mi> </msub> </math> </EquationSource> </InlineEquation>, where <InlineEquation ID="IEq4"> <EquationSource Format="TEX">$$\varvec{X}_{t}$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <msub> <mrow> <mi mathvariant="bold-italic">X</mi> </mrow> <mi>t</mi> </msub> </math> </EquationSource> </InlineEquation> can be either exogenous variables or lagged variables of <InlineEquation ID="IEq5"> <EquationSource Format="TEX">$${ Y_t}$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <msub> <mi>Y</mi>...</msub></math></equationsource></equationsource></inlineequation></equationsource></equationsource></inlineequation></equationsource></equationsource></inlineequation></equationsource></equationsource></inlineequation></equationsource></equationsource></inlineequation>

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>

The behaviour of market agents has been extensively covered in the literature. Risk averse behaviour, described by Von Neumann and Morgenstern (Theory of games and economic behavior. Princeton University Press, Princeton, <CitationRef CitationID="CR16">1944</CitationRef>) via a concave utility function, is considered to be a cornerstone...</citationref>