We propose simultaneous mean-variance regression for the linear estimation and approximation of conditional mean functions. In the presence of heteroskedasticity of unknown form, our method accounts for varying dispersion in the regression outcome across the support of conditioning variables by...

Estimation or mis-specification errors in the portfolio loss distribution can have a considerable impact on risk measures. This paper investigates the sensitivity of tail-related risk measures including the Value-at-Risk, expected shortfall and the expectile-quantile transformation level in an...

In linear regression of Y on X(2 Rp) with parameters (2 Rp+1); statistical inference is unreliable when observations are obtained from gross-error model, F;G = (1??)F +G; instead of the assumed probability F;G is gross-error probability, 0 < < 1: When G is unit mass at (x; y); Residual's Inuence...

We propose simultaneous mean-variance regression for the linear estimation and approximation of conditional mean functions. In the presence of heteroskedasticity of unknown form, our method accounts for varying dispersion in the regression outcome across the support of conditioning variables by...