Risk Budgeted portfolio optimization problem centering on the twin objectives of maximizing expected portfolio return and minimizing portfolio risk and incorporating the risk budgeting investment strategy, turns complex for direct solving by classical methods triggering the need to look for metaheuristic solutions. This work explores the application of an extended Ant Colony Optimization algori...

We evaluate conditional value-at-risk (CVaR) as a risk measure in data-driven portfolio optimization. We show that portfolios obtained by solving mean-CVaR and global minimum CVaR problems are unreliable due to estimation errors of CVaR and/or the mean, which are aggravated by optimization. This problem is exacerbated when the tail of the return distribution is made heavier. We conclude that CV...

In this paper, we developed a new robust model of multi-period portfolio problem. One of the key concerns in any asset allocation problem is how to cope with uncertainty about future returns. There are some approaches in the literature for this purpose including stochastic programming and robust optimization. Applying these techniques to multi-period portfolio problem may increase the problem s...

Markowitz model is the first modern formulation of portfolio optimization problem. Relyingon historical return of stocks as basic information and using variance as a risk measure aretow drawbacks of this model. Since Markowitz model has been presented, many effortshave been done to remove theses drawbacks. On one hand several better risk measures havebeen introduced and proper models have been ...

Portfolio optimization (selection) problem is an important and hard optimization problem that, with the addition of necessary realistic constraints, becomes computationally intractable. Nature-inspired metaheuristics are appropriate for solving such problems; however, literature review shows that there are very few applications of nature-inspired metaheuristics to portfolio optimization problem...

Dr. V. J.Sebastian (Corresponding author) Institute of Management Technology Gaziabad, Delhi, India E-mail: [email protected] Abstract Portfolio optimization, in case of finance, is the tradeoff between risk and return to maximize profit or return from the portfolio. Financial regulations are country specific and it depends upon the economic conditions prevailing in the country. The portfolio of...

This study first reviews fuzzy random Portfolio selection theory and describes the concept of portfolio optimization model as a useful instrument for helping finance practitioners and researchers. Second, this paper specifically aims at applying possibility-based models for transforming the fuzzy random variables to the linear programming. The harmony search algorithm approaches to resolve the ...

The portfolio optimization problem has become a standard financial engineering problem since the pioneering work of Markowitz on Modern Portfolio Theory. It aims to find an optimal allocation of capital among a set of assets by simultaneously minimizing the risk and maximizing the return of the investment. In the theoretical case of linear constraints, this problem is basically solved by quadra...

‎Linear semi-infinite programming problem is an important class of optimization problems which deals with infinite constraints‎. ‎In this paper‎, ‎to solve this problem‎, ‎we combine a discretization method and a neural network method‎. ‎By a simple discretization of the infinite constraints,we convert the linear semi-infinite programming problem into linear programming problem‎. ‎Then‎, ‎we use...