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...

We consider the problem of optimally selecting a large portfolio of risky loans, such as mortgages, credit cards, auto loans, student loans, or business loans. Examples include loan portfolios held by financial institutions and fixed-income investors as well as pools of loans backing mortgageand asset-backed securities. The size of these portfolios can range from the thousands to even hundreds ...

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...

recently, the economic crisis has resulted in instability in stock exchange market and this has caused high volatilities in stock value of exchanged firms. under these conditions, considering uncertainty for a favorite investment is more serious than before. multi-objective portfolio selection (return, liquidity, risk and initial cost of investment objectives) using minmax fuzzy goal programmin...

In this work, a new approach to selection in multiobjective evolutionary algorithms (MOEAs) is proposed. It is based on the portfolio selection problem, which is well known in financial management. The idea of optimizing a portfolio of investments according to both expected return and risk is transferred to evolutionary selection, and fitness assignment is reinterpreted as the allocation of cap...

In portfolio selection models, uncertainty plays an important role. The parameter’s uncertainty leads to getting away from optimal solution so it is needed to consider that in models. In this paper we presented a two-stage robust model that in first stage determines the desired percentage of investment in each industrial group by using return and risk measures from different industries. One rea...

The portfolio selection problem (PSP) uses mathematical approaches to model stock exchange investments. Its aim is to find an optimal set of assets to invest on, as well as the optimal investments for each asset. In this paper, a portfolio selection problem (FPSP) with fuzzy objective function coefficient (FPSP) a multiple objective problem including uncertainties is investigated. The FPSP is c...

a r t i c l e i n f o a b s t r a c t Keywords: Growth optimal portfolio Threshold rebalancing Proportional transaction cost Discrete-time stock market We investigate how and when to diversify capital over assets, i.e., the portfolio selection problem, from a signal processing perspective. To this end, we first construct portfolios that achieve the optimal expected growth in i.i.d. discrete-tim...

In this paper we discuss multiperiod portfolio selection problems related to a speci…c provisioning problem. Our results are an extension of Dhaene et al. (2005), where optimal constant mix investment strategies are obtained in a provisioning and savings context, using an analytical approach based on the concept of comonotonicity. We derive convex bounds that can be used to estimate the provisi...

Fund managers highly prioritize selecting portfolios with a high Sharpe ratio. Traditionally, this task can be achieved by revising the objective function of the Markowitz mean-variance portfolio model and then resolving quadratic programming problems to obtain the maximum Sharpe ratio portfolio. This study presents a closed-form solution for the optimal Sharpe ratio portfolio by applying Cauch...