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 …
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 …
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 …
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 …
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 …
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 …
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 …
P Gupta, MK Mehlawat, AZ Khan - Expert systems with applications, 2021 - Elsevier
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 …
D Wu, X Wang, S Wu - Knowledge-Based Systems, 2022 - Elsevier
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 …