Furlaneto, Dennis CarnelossiOliveira, Luiz S.Menotti, DavidCavalcanti, George Darmiton da Cunha2018-01-242018-01-242017FURLANETO, D. C. et al. Bias effect on predicting market trends with EMD. Bias effect on predicting market trends with EMD. Expert Systems With Applications, v. 1, p. 19-26, 2017. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0957417417302087>. Acesso em: 16 jan. 2018. 0957-4174http://www.repositorio.ufop.br/handle/123456789/9334Financial time series are notoriously difficult to analyze and predict, given their non-stationary, highly oscillatory nature. In this study, we evaluate the effectiveness of the Ensemble Empirical Mode Decom- position (EEMD), the ensemble version of Empirical Mode Decomposition (EMD), at generating a rep- resentation for market indexes that improves trend prediction. Our results suggest that the promising results reported using EEMD on financial time series were obtained by inadvertently adding look-ahead bias to the testing protocol via pre-processing the entire series with EMD, which affects predictive re- sults. In contrast to conclusions found in the literature, our results indicate that the application of EMD and EEMD with the objective of generating a better representation for financial time series is not suffi- cient to improve the accuracy or cumulative return obtained by the models used in this study.en-USrestritoFinanceTime seriesMachine learningTrend predictionArtigo publicado em periodicohttp://www.sciencedirect.com/science/article/pii/S0957417417302087https://doi.org/10.1016/j.eswa.2017.03.053