return maximization or risk minimization is goal in portfolio optimization based on mean variance theory. the structure of correlation matrices and individual variance of each asset are two main factors in optimization with risk minimization object. it’s necessary to use appropriate variance and correlation coefficient for time series with clustering volatilities feature, too. in this research,...

Our paper aims to answer the question: Can the macroeconomic condition be used to better allocate investments among different sectors of a market? Motivated by classical Markowitz portfolio theory, and prior work in attempting to incorporate exogenous economic factors in portfolio optimization [1][2][3][4], we explore three approaches to dynamically rebalance a portfolio as market or economic r...

This paper presents two meta-heuristic algorithms to solve an extended portfolio selection model. The extended model is based on the Markowitz's Model, aiming to minimize investment risk in a specified level of return. In order to get the Markowitz model close to the real conditions, different constraints were embedded on the model which resulted in a discrete and non-convex solution space. ...

This paper considers a multi-objective portfolio selection problem imposed by gaining of portfolio, divided yield and risk control in an ambiguous investment environment, in which the return and risk are characterized by probabilistic numbers. Based on the theory of possibility, a new multi-objective portfolio optimization model with gaining of portfolio, divided yield and risk control is propo...

This paper employs fuzzy set theory to solve the unintuitive problem of the Markowitz meanvariance MV portfolio model and extend it to a fuzzy investment portfolio selection model. Our model establishes intervals for expected returns and risk preference, which can take into account investors’ different investment appetite and thus can find the optimal resolution for each interval. In the empiri...

THE CURRENT PAPER BY YACINE AIT-SAHALIA and Michael W. Brandt ~henceforth AB! addresses two issues that are of central concern in portfolio choice: How can portfolio advice be made realistic while remaining tractable? How can

In this work, we study in depth the problem of Portfolio Optimization, and the application of Genetic Algorithms to solve it. We discuss the limitation of current approaches, that do not take into consideration multiple scenarios, nor transaction costs, and propose a modification of the Genetic Algorithm System for Portfolio Optimization to address these issues. A Financial Portfolio is a strat...