Тип публикации: статья из журнала
Год издания: 2023
Идентификатор DOI: 10.1016/j.amc.2022.127700
Ключевые слова: fuzzy logic system, neural networks, portfolio insurance, portfolio optimization, time-varying linear programming
Аннотация: It is well known that minimum-cost portfolio insurance (MPI) is an essential investment strategy. This article presents a time-varying version of the original static MPI problem, which is thus more realistic. Then, to solve it efficiently, we propose a powerful recurrent neural network called the linear-variational-inequality primaПоказать полностьюl-dual neural network (LVI-PDNN). By doing so, we overcome the drawbacks of the static approach and propose an online solution. In order to improve the performance of the standard LVI-PDNN model, an adaptive fuzzy-power LVI-PDNN (F-LVI-PDNN) model is also introduced and studied. This model combines the fuzzy control technique with LVI-PDNN. Numerical experiments and computer simulations confirm the F-LVI-PDNN model's superiority over the LVI-PDNN model and show that our approach is a splendid option to accustomed MATLAB procedures. © 2022 Elsevier Inc.
Журнал: Applied Mathematics and Computation
Выпуск журнала: Vol. 441
Номера страниц: 127700
ISSN журнала: 00963003
Издатель: Elsevier Inc.