. The research presented involved developing algorithms for the implementation of linear regression for estimating CVaR as a … function of some factors. Such regression is called CVaR (superquantile) regression. The main statement of this paper is: CVaR … linear regression can be reduced to minimizing the Rockafellar error function with linear programming. The theoretical basis …

This paper presents mean-variance portfolio optimisation as a regression problem. More specifically, we examine … different types of mean-variance analysis as a series of related regression models. We use these models to leverage the variety … of inference available from least squares regression and to answers portfolio optimisation questions. In particular, we …