“ Portfolio Optimization Under Fractional Stochastic Environments ”

Multi-period project portfolio selection under risk considerations and stochastic income

This paper deals with multi-period project portfolio selection problem. In this problem, the available budget is invested on the best portfolio of projects in each period such that the net profit is maximized. We also consider more realistic assumptions to cover wider range of applications than those reported in previous studies. A novel mathematical model is presented to solve the problem, con...

Multivariate tempered stable model with long-range dependence and time-varying volatility

High-frequency financial return time series data have stylized facts such as the long-range dependence, fat-tails, asymmetric dependence, and volatility clustering. In this paper, a multivariate model which describes those stylized facts is presented. To construct the model, a multivariate ARMA-GARCH model is considered along with fractional Lévy process. The fractional Lévy process in this pap...

Introducing a Relational Network DEA Model with Stochastic Intermediate measures for Portfolio Optimization

Using Genetic Algorithm in Solving Stochastic Programming for Multi-Objective Portfolio Selection in Tehran Stock Exchange

Investor decision making has always been affected by two factors: risk and returns. Considering risk, the investor expects an acceptable return on the investment decision horizon. Accordingly, defining goals and constraints for each investor can have unique prioritization. This paper develops several approaches to multi criteria portfolio optimization. The maximization of stock returns, the pow...

One-Stage R&D Portfolio Optimization with an Application to Solid Oxide Fuel Cells

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...