We consider second, third, fourth and fifth order stochastic dominance (SSD, TSD, FOSD and FISD, respectively) as well as decreasing absolute risk aversion (DARA) stochastic dominance (DSD). For comparison with DSD we also consider stochastic dominance (ESD) based on CARA utility functions....

Contemporary financial stochastic programs typically involve a trade-offbetween return and (downside)-risk. Using stochastic programming we characterize analytically (rather than numerically) the optimal decisions that follow from characteristic single-stage and multi-stage versions of such...

We develop a novel Mean-Max Drawdown portfolio optimization approach using buy-and-hold portfolios. The optimization is performed utilizing a multi-objective evolutionary algorithm on a sample of S&P 100 constituents. Our optimization procedure provides portfolios with better Mean-Max Drawdown...

Using a multi-stage stochastic programming method, we suggest an optimal liability-driven investment(LDI) strategy for a closed defined-benefit pension fund including real assets. The objective is to jointly optimize contribution, funding ratio, and buyout cost, subject to a constraint on...

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...

A fast method based on coordinate-wise descent algorithms is developed to solve portfolio optimization problems in which asset weights are constrained by Lq norms for 1=q=2. The method is first applied to solve a minimum variance portfolio (mvp) optimization problem in which asset weights are...

In this paper we propose a quasi-shrinkage approach for minimum-variance portfolios which does not use a quadratic loss function to derive the optimal shrinkage intensity. We develop two alternative objective functions for linear shrinkage. The first targets the reduction of portfolio variance....

Proceeding to portfolio allocation in the framework of Markowitz, a numerical inconsistency may occur when the sample covariance matrix of assets returns has to be inverted. This is mainly caused by the magnitude of its lowest eigenvalues. In this paper, we tackle the Markowitz problem as an...

In this paper we introduce a simple, yet flexible approach to construct (enhanced) index tracking portfolios. PADME (Portfolio Allocation via Density MatchEs) uses the density function of returns as a robust means of capturing investor preferences, and identifies suitable portfolios through a...