Data Driven Level Set Fuzzy Modeling for Cryptocurrencies Price Forecasting

Leandro Maciel, Rosangela Ballini, Fernando Gomide

2022

Abstract

The paper develops a data-driven fuzzy modeling procedure based on level set to forecast cryptocurrencies prices. Data-driven level set is a novel fuzzy modeling method that differs from linguistic and functional fuzzy models in how the fuzzy rules are built and processed. The level set-based model outputs the weighted average of output functions associated with the fuzzy rules. Output functions map the activation levels of the fuzzy rules directly in the model outputs. Computational experiments are done to evaluate the level set method to forecast the closing prices of Bitcoin, Ethereum, Litecoin and Ripple. Comparisons are made with ARIMA, ETS, MLP and naı̈ve random walk. The results suggest that the random walk outperforms most methods addressed in this paper, but it is surpassed by the level set model for Ethereum. When performance is measured by the direction of price change, the level set-based fuzzy modeling performs best amongst the remaining methods.

Paper Citation

in Harvard Style

Maciel L., Ballini R. and Gomide F. (2022). Data Driven Level Set Fuzzy Modeling for Cryptocurrencies Price Forecasting. In Proceedings of the 14th International Joint Conference on Computational Intelligence (IJCCI 2022) - Volume 1: FCTA; ISBN 978-989-758-611-8, SciTePress, pages 193-198. DOI: 10.5220/0011379400003332

in Bibtex Style

@conference{fcta22,
author={Leandro Maciel and Rosangela Ballini and Fernando Gomide},
title={Data Driven Level Set Fuzzy Modeling for Cryptocurrencies Price Forecasting},
booktitle={Proceedings of the 14th International Joint Conference on Computational Intelligence (IJCCI 2022) - Volume 1: FCTA},
year={2022},
pages={193-198},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011379400003332},
isbn={978-989-758-611-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computational Intelligence (IJCCI 2022) - Volume 1: FCTA
TI - Data Driven Level Set Fuzzy Modeling for Cryptocurrencies Price Forecasting
SN - 978-989-758-611-8
AU - Maciel L.
AU - Ballini R.
AU - Gomide F.
PY - 2022
SP - 193
EP - 198
DO - 10.5220/0011379400003332
PB - SciTePress