Recently, different methods have been proposed for portfolio optimization and decision making on investment issues. This article aims to present a new method for portfolio formation based on Data Envelopment Analysis (DEA) and Entropy function. This new portfolio optimization method applies DEA in association with a model resulting from the insertion of the Entropy function directly into the op...

Devices that integrate multiple functions together are popular in consumer electronic markets. Examples include the cellular phone that takes digital pictures and plays MP3’s, the PDA with cell phone, and multi-function office machines. We describe these multi-function devices as fusion products since they fuse together products which traditionally stand alone in the marketplace. In this paper,...

in this paper, in order to optimize the portfolio consisting of selected industrial stocks of petroleum products, automobiles and parts, electrical industry and extraction of minerals from tehran stock exchange member, first, time – varying conditional covariance matrix has been estimated based on the following multivariate garch models: diagonal-vech (1,1), ccc (1,1) and diagonal -bekk (1,1). ...

In this paper, we first show that for classical rational investors with correct beliefs and constant absolute or constant relative risk aversion, the utility gains from structured products over and above a portfolio consisting of the risk-free asset and the market portfolio are typically much smaller than their fees. This result holds irrespectively of whether the investors can continuously tra...

A new approach to solve Chance constrained Portfolio Optimization Problems (CPOPs) without using the Monte Carlo simulation is proposed. Specifically, according to Chebyshev inequality, the prediction interval of a stochastic function value included in CPOP is estimated from a set of samples. By using the prediction interval, CPOP is transformed into Lower-bound Portfolio Optimization Problem (...

This paper analyses the stable distributional approach for portfolio optimisation. We consider a portfolio optimization problem under the assumption of normal (Gaussian) and stable (nonGaussian) distributed asset returns. We compare the results of portfolio allocations in normal and stable cases.

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...

The paper considers robust optimization to cope with uncertainty about the stock return process in one period option hedging problems. The robust approach relates portfolio choice to uncertainty, making more cautious hedges when uncertainty is high. We represent uncertainty by a set of plausible expected returns of the underlying stocks and show that for this set the robust problem is a second ...