The problem of optimal portfolio selection has attracted a great attention in the finance and optimization field. The future stock price should be predicted in an acceptable precision, and a suitable model and criterion for risk and the expected return of the stock portfolio should be proposed in order to solve the optimization problem. In this paper, two new criterions for the risk of stock pr...

in traditional portfolio selection model coefficients often are certain and deterministic, but in real world these coefficients are probabilistic. so decision maker cannot estimate them exactly. financial optimization is one of the most attractive areas in decision under uncertainty. in the portfolio selection problem the decision maker considers simultaneously conflicting objectives such as ra...

The stochastic nature of financial markets is a barrier for successful portfolio management. Besides traditional Markowitz’s model, many other portfolio selection models in Bayesian and Non-Bayesian frameworks have been developed. Starting with the basic Markowitz model, several cardinal models are used to find optimum portfolios with select stock set. Having developed the regression model of t...

One of the popular methods for optimizing combinational problems such as portfolio selection problem is swarmbased methods. In this paper, we have proposed an approach based on Quantum-Behaved Particle Swarm Optimization (QPSO) for the portfolio selection problem. The particle swarm optimization (PSO) is a well-known population-based swarm intelligence algorithm. QPSO is also proposed by combin...

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...

the present study is an attempt toward evaluating the performance of portfolios and asset selectionusing cross-efficiency evaluation. cross-efficiency evaluation is an effective way of ranking decisionmaking units (dmus) in data envelopment analysis (dea). conventional dea models assume nonnegativevalues for inputs and outputs. however, we know that unlike return and skewness, varianceis the on...

A commonly used approach in long-run event-studies is the calendar time portfolio (CTP) approach developed by Jaffe (1974) and Mandelker (1974) and advocated by Fama (1998). For each calendar month we compute the return of an equally-weighted portfolio of companies that unionized in the last T months, where T is either 18 or 24 in our study. The return of this “unionization portfolio” is denote...

Many portfolio managers measure performance with reference to a benchmark. The difference in return between a portfolio and its benchmark is the active return of the portfolio. Portfolio managers and their clients want to know what caused this active return. Performance attribution decomposes the active return. The two most common approaches are the Brinson-Hood-Beebower (hereafter referred to ...

Many portfolio managers measure performance with reference to a benchmark. The difference in return between a portfolio and its benchmark is the active return of the portfolio. Portfolio managers and their clients want to know what caused this active return. Performance attribution decomposes the active return. The two most common approaches are the Brinson-Hood-Beebower (hereafter referred to ...

The paper analyses the determinants of cross-sectional stock returns at the London Stock Exchange in the last 26 years. It ®nds that portfolio strategies based on low values of earning per share (EPS), market to book value (MTBV), market value (MV) and return on equity (ROE) signi®cantly outperform the index. Do size and value (S&V) strategy premia disappear when risk-adjusted or do they reveal...