this paper presents a new meta-heuristic solution to find the efficient frontier using the mean-variance approach. portfolio optimization problem is a quadratic programming model and, changes to np-hard if the number of assets and constraints has increased, and it cannot be solved using common mathematical methods in a reasonable time. therefore, a heuristic or meta-heuristic algorithm should b...

Comprehensive methods must be used for portfolio optimization. For this purpose, financial data of stock companies, inputs and outputs variable, the risk measure and investor’s preferences must be considered. By considering these items, we propose a method for portfolio optimization. In this paper, we used financial data of companies for screening the stock companies. We used Conditional Value ...

This study applied a prediction-based portfolio optimization model to explore the results of portfolio predicament in the Tehran Stock Exchange. To this aim, first, the data mining approach was used to predict the petroleum products and chemical industry using clustering stock market data. Then, some effective factors, such as crude oil price, exchange rate, global interest rate, gold price, an...

Financial returns exhibit stylized facts such as leptokurtosis, skewness and heavy-tailness. Regarding this behavior, in this paper, we apply multivariate generalized hyperbolic (mGH) distribution for portfolio modeling and performance evaluation, using conditional value at risk (CVaR) as a risk measure and allocating best weights for portfolio selection. Moreover, a robust portfolio optimizati...

This paper is the continuation of the paper entitled “Hereditary portfolio optimization with taxes and fixed plus proportional transaction costs I” that treats an infinite-time horizon hereditary portfolio optimization problem in a market that consists of one savings account and one stock account. Within the solvency region, the investor is allowed to consume from the savings account and can ma...

In this analysis of the risk and return of stocks in global markets, we apply several applications of robust regression techniques in producing stock selection models and several optimization techniques in portfolio construction in global stock universes.We find that (1) that robust regression applications are appropriate for modeling stock returns in global markets; and (2) mean-variance techn...

This work presents a new prediction-based portfolio optimization model that can capture short-term investment opportunities. We used neural network predictors to predict stocks’ returns and derived a risk measure, based on the prediction errors, that have the same statistical foundation of the mean-variance model. The efficient diversification effects holds thanks to the selection of predictors...

this research aims to use var as a risk measure to find the optimum portfolio in tehran stock exchange. in this research var which is calculated with parametric method by using the 15 daily returns of 100 companies from march 21, 2001 to november 22, 2007 was added to the markowitz model of portfolio optimization as additional constraint. by changing the accepted var and accepted confidence lev...

abstract portfolio definition is the most important decision for individuals and legal persons that invest in stock. the main objective of this paper is study and determination of optimal portfolio for stock of active food industrial company in tehran stock based on value at risk (var) index. for this purpose, we used weekly static of stock of active food industrial company in tehran from bahma...

In this paper a portfolio optimization algorithm based on Evolution Strategies is presented. This method makes use of artificial trading experts discovered earlier by a genetic algorithm. These experts, consisting of technical analysis rules, are trained to process financial time series and to generate trading advice. Evolution Strategies lead to the optimization of portfolio structures where i...