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...

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 a new risk measure that is a generalization of Entropic Value at Risk (EVaR). We define the Relativistic Value at Risk (RLVaR) as a special case of φ-divergence risk measures based on Kaniadakis entropy. The RLVaR is a coherent risk measure that is bounded between EVaR and...

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 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,...

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 new convex risk measure that we call negative quadratic skewness that is an approximation of the negative component of portfolio skewness. This risk measure allows us to increase portfolio skew- ness through the minimization of the negative quadratic skewness. First, we show...

This work presents a new representation of portfolio kurtosis through the sum of squared quadratic forms that allows us to pose a convex portfolio optimization model for an approximate kurtosis that has high accuracy and give us a high improvement in speed calculation respect to the exact...