The paper studies stochastic optimization of an intertemporal consumption model to allocate financial assets between risky and risk-free assets. We use a stochastic optimization technique, in which utility is maximized subject to a self-financing portfolio constraint. The papers in literature...

In this short note, we consider mean-variance optimized portfolios with transaction costs. We show that introducing quadratic transaction costs makes the optimization problem more difficult than using linear transaction costs. The reason lies in the specification of the budget constraint, which...

In this contribution we propose a dynamic tracking error problem and we consider the problem of monitoring at discrete point the shortfall of the portfolio below a set of given reference levels of wealth. We formulate and solve the resulting dynamic optimization problem using stochastic...

Dynamic programming is the essential tool in dynamic economic analysis. Problems such as portfolio allocation for individuals and optimal economic growth are typical examples. Numerical methods typically approximate the value function. Recent work has focused on making numerical methods more...

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,...

We propose a new, highly effective and easy-to-implement algorithm for solving large-scale mean-variance optimization problems --- with weight upper bound constraints and without short sales --- when the size of mean-variance portfolios is much smaller than the number of assets, which is almost...

This work presents the ordered weighted average or OWA portfolio optimization model. This general model allows us to express various classical portfolio optimization models like Gini mean difference, conditional value at risk, weighted conditional value at risk, tail Gini and minimax as...

Investors typically measure an asset’s potential to diversify a portfolio by its correlations with the portfolio’s other assets, but correlation is useful only if it provides a good estimate of how an asset’s returns co-occur cumulatively with the other asset returns over the investor’s...

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...