| Evolving granular analytics for interval time series forecasting L Maciel, R Ballini, F Gomide Granular Computing 1, 213-224, 2016 | 101 | 2016 |
| Evolving fuzzy systems for pricing fixed income options L Maciel, A Lemos, F Gomide, R Ballini Evolving Systems 3, 5-18, 2012 | 65 | 2012 |
| Enhanced evolving participatory learning fuzzy modeling: an application for asset returns volatility forecasting L Maciel, F Gomide, R Ballini Evolving Systems 5, 75-88, 2014 | 53 | 2014 |
| Design a neural network for time series financial forecasting: Accuracy and robustness analysis LS Maciel, R Ballini Anales do 9º Encontro Brasileiro de Finanças, Sao Pablo, Brazil, 2008 | 45 | 2008 |
| Cryptocurrencies value‐at‐risk and expected shortfall: Do regime‐switching volatility models improve forecasting? L Maciel International Journal of Finance & Economics 26 (3), 4840-4855, 2021 | 43 | 2021 |
| Evolving possibilistic fuzzy modeling for realized volatility forecasting with jumps L Maciel, R Ballini, F Gomide IEEE Transactions on Fuzzy Systems 25 (2), 302-314, 2016 | 43 | 2016 |
| Neural networks applied to stock market forecasting: An empirical analysis LS Maciel, R Ballini Journal of the Brazilian Neural Network Society 8 (1), 3-22, 2010 | 40 | 2010 |
| Evolving fuzzy-GARCH approach for financial volatility modeling and forecasting L Maciel, F Gomide, R Ballini Computational Economics 48, 379-398, 2016 | 36 | 2016 |
| Evolving fuzzy-GARCH approach for financial volatility modeling and forecasting L Maciel, F Gomide, R Ballini Computational Economics 48, 379-398, 2016 | 36 | 2016 |
| Evolving hybrid neural fuzzy network for realized volatility forecasting with jumps R Rosa, L Maciel, F Gomide, R Ballini 2014 IEEE Conference on Computational Intelligence for Financial Engineering …, 2014 | 27 | 2014 |
| Technical analysis based on high and low stock prices forecasts: Evidence for Brazil using a fractionally cointegrated VAR model L Maciel Empirical Economics 58, 1513-1540, 2020 | 25 | 2020 |
| A fuzzy inference system modeling approach for interval-valued symbolic data forecasting L Maciel, R Ballini Knowledge-Based Systems 164, 139-149, 2019 | 22 | 2019 |
| A hybrid fuzzy GJR-GARCH modeling approach for stock market volatility forecasting L Maciel Advances in Financial Risk Management: Corporates, Intermediaries and …, 2013 | 19 | 2013 |
| MIMO evolving functional fuzzy models for interest rate forecasting L Maciel, F Gomide, R Ballini 2012 IEEE Conference on Computational Intelligence for Financial Engineering …, 2012 | 18 | 2012 |
| An evolving possibilistic fuzzy modeling approach for value-at-risk estimation L Maciel, R Ballini, F Gomide Applied Soft Computing 60, 820-830, 2017 | 16 | 2017 |
| Recursive possibilistic fuzzy modeling L Maciel, F Gomide, R Ballini 2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS), 9-16, 2014 | 16 | 2014 |
| Impacto dos contratos futuros do Ibovespa na volatilidade dos índices de ações no Brasil: uma análise na crise do subprime L Maciel, RLF Silveira, I Luna, R Ballini Estudos Econômicos (São Paulo) 42, 801-825, 2012 | 16 | 2012 |
| Exchange rate forecasting using echo state networks for trading strategies L Maciel, F Gomide, D Santos, R Ballini 2014 IEEE Conference on Computational Intelligence for Financial Engineering …, 2014 | 15 | 2014 |
| Simplified evolving rule-based fuzzy modeling of realized volatility forecasting with jumps L Maciel, F Gomide, R Ballini, R Yager 2013 IEEE Conference on Computational Intelligence for Financial Engineering …, 2013 | 14 | 2013 |
| Value-at-risk modeling and forecasting with range-based volatility models: empirical evidence LS Maciel, R Ballini Revista contabilidade & financas 28, 361-376, 2017 | 13 | 2017 |
