[PDF] Top 20 Robust Mean-Variance Portfolio Selection Problem Including Fuzzy Factors

... random factors derived from statistical analysis of historical data and ambiguous factors such as the psychological aspect of investors and lack of received efficient ... See full document

... of portfolio models under randomness and ...and fuzzy programming problems, respectively, and there are some basic studies using a stochastic programming approach, goal programming approach, ...and ... See full document

... in portfolio selection problems which arise frequently in financial management contexts, different financial attributes, such as profitability, mean rate of profit, and risk factors in a form ... See full document

... two factors with the MV portfolio selection problem in the regime-switching ...the portfolio selection with bankruptcy state, but do not consider the factor of exit ... See full document

... continuous-time portfolio selection problemunder inflation in an incomplete ...inflation factors affected by the market are random, which can be described by m + 1 Brownian ... See full document

... standard mean-variance model which laid the foundation of the optimal portfolio ...the variance measured ...important factors in the financial market, and neglecting it could lead to ... See full document

... The mean-variance model originally introduced by Markowitz [1] plays an important role in the development of modern portfolio selection ...theory. Portfolio optimization (PO) consists ... See full document

... terminal mean return, seeks to minimize the variance of the return with multiple stocks and a ...the mean returns of individual assets are explicitly affected by underlying Gaussian economic ... See full document

... scheduling problem, ...problems portfolio selection problems ...well-known mean–variance models and these models have been improved in both theory and algorithm [3, ...selecting ... See full document

... of portfolio models under randomness and ...and fuzzy programming problems, respectively, and there are some basic studies using the fuzzy programming approach to treat ambiguous factors ... See full document

... multi-period portfolio selection problem which was based on a mean semi-variance model and had to cope with transaction costs and transaction ...the problem to the dominant ... See full document

... and variance of each asset are assumed to be known, and in this case, the mean-variance model is equivalent to a quadratic convex programming ...optimal portfolio is analytically ...and ... See full document

... developed fuzzy models. Kumar et al. [13] used a fuzzy mixed integer goal programming approach to solve the vendor selection problem in case of multiple ...a fuzzy decision making ... See full document

... So this paper introduces the optimal foreign exchange risk hedging model following a standard portfolio theory. The results indicate that a lower level of risk can be achieved, given a specified level of expected ... See full document

... in portfolio optimization as are based on linear assumption and are therefore good for quadratic objective functions (deterministic) with a single objective (Roudier, ... See full document

... portfolio selection. Huang (2006), for example, developed a bi-objective portfolio selection model to maximize in- vestors ’ returns and the likelihood of achieving a specified return ... See full document

... Weights constraints are used by (almost) all portfolio managers. However, a few of them have a critical view on their constraints. Generally, they consider several sets of weights constraints and show their impact ... See full document

... for portfolio choice; in his model the agent minimizes over a set of probability measures obtained by "-contamination of a reference measure; Krasker shows how some commonly held portfolios (portfolios without ... See full document

... using mean- variance-skewness model with negative data. Mean-variance non-linear framework and mean- variance-skewness non- linear framework had been proposed based on Data ... See full document

... objective mean variance optimization model fails to satisfy the investors with multiple investment ...multi-objective portfolio optimization model is considered in this ...simultaneously. ... See full document