This work presents a disciplined convex programming framework for entropic value at risk (EVaR) based on exponential cone programming. This framework allows us to use EVaR in several convex portfolio optimization problems like maximize the EVaR adjusted return, constraints on EVaR or risk parity...

This work presents five convex reformulations of portfolio kurtosis that allows us to pose kurtosis as a parametric convex risk measure. These new reformulations are based on new formulas for estimation of portfolio moments and co-moments matrices, second order cone and semidefinite programming....

This work presents a higher moment portfolio optimization model based on L-moments and the ordered weighted average (OWA) portfolio optimization model. In the first part, we are going to show how to model the higher L-moment portfolio problem as a utility function. In the second part, we are...

This work presents a disciplined convex programming framework for Kelly criterion in portfolio optimization based on exponential cone programming. This framework allows us to incorporate mean logarithmic return in problems like maximize mean logarithmic return subject to a risk constraint,...

Quantitative asset allocation models have not been widely adopted by practitioners because they suffer from two problems: the lack of robustness and diversification of portfolios obtained through these models. To solve these problems, I developed a new portfolio selection method that can be...