Artificial intelligence applied to stock market trading: a review
FGDC Ferreira, AH Gandomi, RTN Cardoso - IEEE Access, 2021 - ieeexplore.ieee.org
The application of Artificial Intelligence (AI) to financial investment is a research area that
has attracted extensive research attention since the 1990s, when there was an accelerated …
has attracted extensive research attention since the 1990s, when there was an accelerated …
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 …
A survey on the artificial bee colony algorithm variants for binary, integer and mixed integer programming problems
Most of the optimization problems encountered in the real world are discrete type which
involves decision variables defined in the discrete search space. Binary optimization …
involves decision variables defined in the discrete search space. Binary optimization …
A survey of swarm intelligence for portfolio optimization: Algorithms and applications
O Ertenlice, CB Kalayci - Swarm and evolutionary computation, 2018 - Elsevier
In portfolio optimization (PO), often, a risk measure is an objective to be minimized or an
efficient frontier representing the best tradeoff between return and risk is sought. In order to …
efficient frontier representing the best tradeoff between return and risk is sought. In order to …
Optimal selection of stock portfolios using multi-criteria decision-making methods
In the past, investors used their own or others' experiences to achieve their goals. With the
development of financial management, investors' choices became more scientific. They …
development of financial management, investors' choices became more scientific. They …
An efficient hybrid metaheuristic algorithm for cardinality constrained portfolio optimization
Portfolio optimization with cardinality constraints turns out to be a mixed-integer quadratic
programming problem which is proven to be NP-Complete that limits the efficiency of exact …
programming problem which is proven to be NP-Complete that limits the efficiency of exact …
Support vector regression with modified firefly algorithm for stock price forecasting
J Zhang, YF Teng, W Chen - Applied Intelligence, 2019 - Springer
The support vector regression (SVR) has been employed to deal with stock price forecasting
problems. However, the selection of appropriate kernel parameters is crucial to obtaining …
problems. However, the selection of appropriate kernel parameters is crucial to obtaining …
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 …
Multi-period portfolio optimization using coherent fuzzy numbers in a credibilistic environment
In this paper, we use an extension of fuzzy numbers, called coherent fuzzy numbers, to
model asset returns and an investor's perception of the stock market (pessimistic, optimistic …
model asset returns and an investor's perception of the stock market (pessimistic, optimistic …
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 …