Comparative analysis of forecasting portfolio returns using Soft Computing technologies
Authors
Abel Rubio-Manzano, José D. Bermúdez, Enriqueta Vercher
Corresponding Author
Abel Rubio-Manzano
Available Online June 2015.
- DOI
- 10.2991/ifsa-eusflat-15.2015.88How to use a DOI?
- Keywords
- Fuzzy time series, possibilistic moments, portfolio selection, forecasting.
- Abstract
We propose using fuzzy time series (FTS) to forecast the future performance of returns on portfolios. We model the portfolio selection problem by means of possibilistic moments, and approximate the uncertainty of the return on a given portfolio by trapezoidal fuzzy numbers. Some modifications into the classical models of FTS, based on weighted operators, allow us generating trapezoidal numbers as forecasters of the performance of portfolio returns. We incorporate our proposals into classical FTS methods and analyze their effectiveness with respect to FTS models with a possibilistic interval-valued mean approach, using historical returns on assets from the Spanish stock market.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Abel Rubio-Manzano AU - José D. Bermúdez AU - Enriqueta Vercher PY - 2015/06 DA - 2015/06 TI - Comparative analysis of forecasting portfolio returns using Soft Computing technologies BT - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 617 EP - 623 SN - 1951-6851 UR - https://doi.org/10.2991/ifsa-eusflat-15.2015.88 DO - 10.2991/ifsa-eusflat-15.2015.88 ID - Rubio-Manzano2015/06 ER -