Linear-parametric optimization, where multiple objectives are combined into a single objective using linear … linear-parametric optimization problems exactly and approximately. Transferring concepts from related areas such as multi … fashion and do not rely on specific problem structures. Second, we look at well-studied parametric optimization problems and …

-dimension, we propose a conditional variable screening test based on non-parametric regression using neural networks due to their … much predictors contribute additionally to the non-parametric regression after accounting for the latent factors. Our …

-dimension, we propose a conditional variable screening test based on non-parametric regression using neural networks due to their … much predictors contribute additionally to the non-parametric regression after accounting for the latent factors. Our …

selection. We provide semiparametric identification of the quantile parameters without imposing parametric restrictions on the …

We put forward a Dynamic Regularized Parametric (DRP) approach for active portfolio policies. We build upon the … parametric policy framework of Brandt et al. (2009) that directly links the portfolio weights to a limited set of asset …

selection. We provide semiparametric identification of the quantile parameters without imposing parametric restrictions on the …