We investigate portfolio selection with alternative objective functions in a distributed computing environment. In particular, we optimise a portfolio's 'Omega' which is the ratio of two partial moments of the returns distributions. Since finding optimal portfolios under such performance...

We construct portfolios with an alternative selection criterion, the Omega function, which can be expressed as the ratio of two partial moments of the returns distribution. Finding Omega-optimal portfolios, in particular under realistic constraints like cardinality restrictions, requires to...

Linear regression is widely-used in finance. While the standard method to obtain parameter estimates, Least Squares, has very appealing theoretical and numerical properties, obtained estimates are often unstable in the presence of extreme observations which are rather common in financial time...

We study the empirical performance of alternative risk and reward specifications in portfolio selection. In particular, we look at models that take into account asymmetry of returns, and treat losses and gains differently. In tests on a dataset of German equities we find that portfolios...

Heuristic optimization methods and their application to finance are discussed. Two illustrations of these methods are presented: the selection of assets in a portfolio and the estimation of a complicated econometric model

Portfolio selection is about combining assets such that investors' financial goals and needs are best satisfied. When operators and academics translate this actual problem into optimisation models, they face two restrictions: the models need to be empirically meaningful, and the models need to...