Forecasting Exchange Rates with Fuzzy Granular Evolving Modeling for Trading Strategies

DOI

10.2991/eusflat.2013.40How to use a DOI?

Keywords

Granular Computing Evolving Systems Exchange Rates Trading Forecasting

Abstract

This paper addresses a fuzzy set based evolving modeling (FBeM) approach and the task of forecasting exchange rates in order to perform trading strategies. FBeM is a granular computing technique that uses fuzzy information granules to model nonstationary functions providing functional and linguistic approximations. As an application, this work considers the BRL/USD exchange rate for the period from January 2000 to October 2012. Caparisons in terms of goodness of fit and based on trading performance indicators includes the granular model against a Multi-Layer Perceptron (MLP), an autoregressive moving average (ARMA), a naïve strategy and some state-of-the-art evolving fuzzy systems. Computational results suggest that the FBeM model statistically outperforms the alternative approaches.

Copyright

© 2013, 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/).

Download article (PDF)

TY  - CONF
AU  - Leandro Maciel
AU  - Fernando Gomide
AU  - Rosangela Ballini
PY  - 2013/08
DA  - 2013/08
TI  - Forecasting Exchange Rates with Fuzzy Granular Evolving Modeling for Trading Strategies
BT  - Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13)
PB  - Atlantis Press
SP  - 276
EP  - 283
SN  - 1951-6851
UR  - https://doi.org/10.2991/eusflat.2013.40
DO  - 10.2991/eusflat.2013.40
ID  - Maciel2013/08
ER  -