Since the 1960s, lots of scholars had begun to research in the portfolio selections based on the theory of mean-variance of Markowitz portfolio and relevant methods. All of these studies are under certainly of the assumption term, and then the researchers can get efficient set of portfolio selection. However, alone with the finance environment increasing of complexity, it is becoming more compl...

the current study addresses an estimation of investor's optimal portfolio under conditions of uncertainty by using a combination of artificial neural network and markowitz models. for this purpose, such assets as stock prices, house prices, coin and bonds price are used with monthly data over the period 1378-1392. three variables including inflation uncertainty, oil uncertainty and free ma...

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...

I develop a two market agent-based model to study how global portfolio managers affect global financial crises and stability. The Markowitz model is extended by incorporating several insights from behavioral finance. Simulation results of an agent-based version of the Markowitz model reveal that global financial crises do not occur when global managers are added to the model. However, when risk...

The Markowitz model of portfolio optimization quantifies the problem in a lucid form of only two criteria: the mean, representing the expected outcome, and the risk, a scalar measure of the variability of outcomes. The classical Markowitz model uses the variance as the risk measure, thus resulting in a quadratic optimization problem. Following Sharpe’s work on linear approximation to the mean–v...

Conventionally, portfolio selection problems are solved with quadratic or linear programming models. However, the solutions obtained by these methods are in real numbers and difficult to implement because each asset usually has its minimum transaction lot. Methods considering minimum transaction lots were developed based on some linear portfolio optimization models. However, no study has ever i...