A comprehensive review of deterministic models and applications for mean-variance portfolio optimization
CB Kalayci, O Ertenlice, MA Akbay - Expert Systems with Applications, 2019 - Elsevier
Portfolio optimization is the process of determining the best combination of securities and
proportions with the aim of having less risk and obtaining more profit in an investment …
proportions with the aim of having less risk and obtaining more profit in an investment …
[HTML][HTML] Metaheuristics for rich portfolio optimisation and risk management: Current state and future trends
Computational finance is an emerging application field of metaheuristic algorithms. In
particular, these optimisation methods are becoming the solving approach alternative when …
particular, these optimisation methods are becoming the solving approach alternative when …
Twenty years of linear programming based portfolio optimization
Markowitz formulated the portfolio optimization problem through two criteria: the expected
return and the risk, as a measure of the variability of the return. The classical Markowitz …
return and the risk, as a measure of the variability of the return. The classical Markowitz …
[HTML][HTML] A learning-guided multi-objective evolutionary algorithm for constrained portfolio optimization
Portfolio optimization involves the optimal assignment of limited capital to different available
financial assets to achieve a reasonable trade-off between profit and risk objectives. In this …
financial assets to achieve a reasonable trade-off between profit and risk objectives. In this …
Kernel search: An application to the index tracking problem
G Guastaroba, MG Speranza - European Journal of Operational Research, 2012 - Elsevier
In this paper we study the problem of replicating the performances of a stock market index, ie
the so-called index tracking problem, and the problem of out-performing a market index, ie …
the so-called index tracking problem, and the problem of out-performing a market index, ie …
A parallel variable neighborhood search algorithm with quadratic programming for cardinality constrained portfolio optimization
Over the years, portfolio optimization remains an important decision-making strategy for
investment. The most familiar and widely used approach in the field of portfolio optimization …
investment. The most familiar and widely used approach in the field of portfolio optimization …
Construction of stock portfolios based on k-means clustering of continuous trend features
How to construct a promising portfolio to reduce the risk of investment and to improve returns
has markedly attracted scholars' attention. Firstly, it is hard to choose prospective set of …
has markedly attracted scholars' attention. Firstly, it is hard to choose prospective set of …
A new method for mean-variance portfolio optimization with cardinality constraints
Several portfolio selection models take into account practical limitations on the number of
assets to include and on their weights in the portfolio. We present here a study of the Limited …
assets to include and on their weights in the portfolio. We present here a study of the Limited …
Firefly Algorithm for Cardinality Constrained Mean‐Variance Portfolio Optimization Problem with Entropy Diversity Constraint
Portfolio optimization (selection) problem is an important and hard optimization problem that,
with the addition of necessary realistic constraints, becomes computationally intractable …
with the addition of necessary realistic constraints, becomes computationally intractable …
Squirrel search algorithm for portfolio optimization
Portfolio Optimization is a standard financial engineering problem. It aims for finding the best
allocation of resources for a set of assets. This problem has been studied and different …
allocation of resources for a set of assets. This problem has been studied and different …