in traditional portfolio selection model coefficients often are certain and deterministic, but in real world these coefficients are probabilistic. so decision maker cannot estimate them exactly. financial optimization is one of the most attractive areas in decision under uncertainty. in the portfolio selection problem the decision maker considers simultaneously conflicting objectives such as ra...

The problem of portfolio selection in investment concerns with minimizing the risk for a prespecified level of return. In this paper, the constraint on the level of return is fuzzified and the technique of fuzzy evolutionary programming is employed to select an optimal portfolio of securities with low risk and with highly acceptable level of total return. Experimental results show the method is...

Modern portfolio theory is based on a rational investor choosing the proportions of assets in a portfolio so as to minimize risk and maximize the expected return. In this paper, we investigate the applicability of different stochastic search heuristics to the problem of finding the optimum portfolio. We compare their performance on two problems with known solutions. 1. Portfolio Optimization Gi...

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...

Our objective is to develop a methodology to detect regions in risk-return space where the out-of-sample performance of portfolios is consistent with their in-sample performance. We use the Berkowitz statistic to evaluate the accuracy of the density forecast, derived from in-sample portfolio returns, of out-of-sample portfolio returns. Defined by its coordinates in risk-return space, a portfoli...

A Bayesian network is a tool for modeling large multivariate probability models and for making inferences from such models. A Bayesian network combines traditional quantitative analysis with expert judgement in an intuitive, graphical representation. In this paper, we show how to use Bayesian networks to model portfolio risk and return. Traditional financial models emphasize the historical rela...

Portfolio selection problem deals with how to form a satisfying portfolio, taking into account the uncertainty involved in the behavior of the financial markets. Markowitz (1952) established the relationship between the mean and variance of the investment in the framework of risk-return trade-off. Since then a variety of enlarged and improved models have been developed in several directions. So...

In 2014 the main tendency of Ukrainian economy was the losing of great deposit value. In this article we wish to explore a deposit portfolio structure in macroeconomic instability. We applied two approaches to the standard optimization portfolio: risk minimization for a given maximum return and return maximization for a given maximum risk. Of the two approaches to the standard optimization prob...