We consider the global optimization of two problems arising from financial applications. The first problem originates from the portfolio selection problem when high-order moments are taken into account. The second issue we address is the problem of scenario generation. Both problems are non-convex, large-scale, and highly relevant in financial engineering. For the two problems we consider, we a...

We investigate the problem of power utility maximization considering risk management and strategy constraints. The aim of this paper is to obtain admissible dynamic portfolio strategies. In case the floor is guaranteed with probability one, we provide two admissible solutions, the option based portfolio insurance in the constrained model, and the alternative method and show that none of the sol...

in this paper, in order to optimize the portfolio consisting of selected industrial stocks of petroleum products, automobiles and parts, electrical industry and extraction of minerals from tehran stock exchange member, first, time – varying conditional covariance matrix has been estimated based on the following multivariate garch models: diagonal-vech (1,1), ccc (1,1) and diagonal -bekk (1,1). ...

The Research and De®elopment Pipeline management problem has far-reaching economic implications for new-product-de®elopment-dri®en industries, such as pharmaceutical, biotechnology and agrochemical industries. Effecti®e decision-making is required with respect to portfolio selection and project task scheduling in the face of significant uncertainty and an e®er-constrained resource pool. The her...

This paper analyses the stable distributional approach for portfolio optimisation. We consider a portfolio optimization problem under the assumption of normal (Gaussian) and stable (nonGaussian) distributed asset returns. We compare the results of portfolio allocations in normal and stable cases.

This paper provides an overview of the one-stage R&D portfolio optimization problem. It provides a novel problem model that can be solved with stochastic combinatorial optimization methods. Current solution methods are reviewed an a new method, Stochastic Gradient Portfolio Optimization (SGPO), is proposed. We proved global convergence under certain conditions. SGPO is numerically compared to c...

The paper considers robust optimization to cope with uncertainty about the stock return process in one period option hedging problems. The robust approach relates portfolio choice to uncertainty, making more cautious hedges when uncertainty is high. We represent uncertainty by a set of plausible expected returns of the underlying stocks and show that for this set the robust problem is a second ...

The investment portfolio with stochastic returns can be represented as a maximum flow generalized network with stochastic multipliers. Modern portfolio theory (MPT) [1] provides a myopic short horizon solution to this network by adding a parametric variance constraint to the maximize flow objective function. MPT does not allow the number of securities in solution portfolios to be specified. Int...