Swarm Intelligence (SI) is a relatively new technology that takes its inspiration from the behavior of social insects and flocking animals. In this paper, we focus on two main SI algorithms: Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). An extension of ACO algorithm and a PSO algorithm has been implemented to solve the portfolio optimization problem, which is a continuous...

The famous mean-variance portfolio selection model introduced by Markowitz in [7] is an important breakthrough in mathematical finance, which deals with uncertainties appearing in financial markets. In real financial market, there may exist two kinds of uncertainties. One is randomness and the other is impreciseness or vagueness. In this paper we study the portfolio selection problem combining ...

Markowitz cardinality constraint mean-variance (MCCMV) model is a well studied and important one in the portfolio optimization literature. It is formulated as mixed integer quadratic programming problem (MIQP) which belongs to class of NP-hard problems, thus various heuristic and meta-heuristic algorithms are applied to solve it. In this paper, two modified versions of particle swarm optimizati...

We consider a group of mean-variance investors with mimicking desire such that each investor is willing to penalize deviations of his portfolio composition from compositions of other group members. Penalizing norm constraints are already applied for statistical improvement of Markowitz portfolio procedure in order to cope with estimation risk. We relate these penalties to individuals’ wish of s...

The aim of this paper is to assess the performance of the Markowitz meanvariance framework over a thirty year time frame and address the question of; How should an investor optimally allocate their capital?. The effect of risk reduction by incorporating a Bayes-Stein estimator is also investigated. The performance of the framework is concluded by the out-ofsample performance of the mean-varianc...

The mean-variance theory of Markowitz (1952) indicates that large investment portfolios naturally provide better risk diversification than small ones. However, due to parameter estimation errors, one may find ambiguous results in practice. Hence, it is essential to identify relevant stocks to alleviate the impact of estimation error in portfolio selection. To this end, we propose a linkage cond...

In this research we study the relative performance of investment strategies scrutinizing their behaviour in an ecological competition where populations of artificial investors co-evolve. We test different variations around the canonical modern portfolio theory of Markowitz, strategies based on the naive diversification principles and the combination of several strategies. We show, among others,...

We consider the problem of selecting a portfolio of assets that provides the investor a suitable balance of expected return and risk. With respect to the seminal mean-variance model of Markowitz, we consider additional constraints on the cardinality of the portfolio and on the quantity of individual shares. Such constraints better capture the real-world trading system, but make the problem more...

In recent years portfolio optimization models that consider more criteria than the standard expected return and variance objectives of the Markowitz model have become popular. For such models, two approaches to find a suitable portfolio for an individual investor are possible. In the multiattribute utility theory (MAUT) approach a utility function is constructed based on the investor’s preferen...

Investment is one of the determining variables and has a positive effect on economic growth (GDP). Investing in stocks with large market capitalization will increase JKSE growth. IDX80 an index consisting 80 that have high liquidity, capitalization, good company fundamentals. This study aims to find combination meet criteria forming optimal portfolio based Markowitz model Single Index Model als...