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 ...

Investment decision making is one of the key issues in financial management. Selecting the appropriate tools and techniques that can make optimal portfolio is one of the main objectives of the investment world. This study tries to optimize the decision making in stock selection or the optimization of the portfolio by means of the artificial colony of honey bee algorithm. To determine the effect...

We study the viability of different robust optimization approaches to multiperiod portfolio selection. Robust optimization models treat future asset returns as uncertain coefficients in an optimization problem, and map the level of risk aversion of the investor to the level of tolerance of the total error in asset return forecasts.We suggest robust optimization formulations of the multiperiod p...

Multiobjective portfolio optimization problem is the portfolio process of the highest expected return among the various financial commodities of the capital market to meet the expected return objectives. And one of the most important and common management issues lies in determining the best portfolio out of a given set of investment proposals. As we know, modern portfolio theory provides a well...

The main purpose of this research is portfolio optimization in Tehran securities exchange using the black hole algorithm and the Gravitational Research algorithm. We also propose an algorithm named Hybrid Algorithm which combines the two algorithms above to cover the weaknesses of these two algorithms. Finally we compare the results with the Markowitz model and choose the optimal algorithm.<br ...

In this paper, we consider the problem of a decision maker who is concerned with the management of a portfolio over a finite horizon. The portfolio optimization problem involves portfolio rebalancing decisions in response to new information on market future prices of the risky assets. Rebalancing decisions are manifested in the revision of holdings through sales and purchases of assets. We assu...

In this paper we present a framework, i.e. a concept and design as well as results with a prototypical implementation of a metaheuristic-based decision support system PM-DSS c © for portfolio optimization and managing investment guidelines. PM-DSS c © can be used for active as well as passive fund management. 1 The general problem In this paper we present a framework, i.e. a concept and design ...

Ever since the inception of Markowitz’s modern portfolio theory, static portfolio optimization techniques were gradually phased out by dynamic portfolio management due to the growth of popularity in automated trading. In view of the intensive computational needs, it is common to use machine learning approaches on Sharpe ratio maximization for implementing dynamic portfolio optimization. In the ...