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Genetic Algorithm for Feature Selection Applied to Financial Time Series Monotonicity Prediction: Experimental Cases in Cryptocurrencies and Brazilian Assets

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Author(s):
Contreras, Rodrigo Colnago ; da Silva, Vitor Trevelin Xavier ; da Silva, Igor Trevelin Xavier ; Viana, Monique Simplicio ; dos Santos, Francisco Lledo ; Zanin, Rodrigo Bruno ; Martins, Erico Fernandes Oliveira ; Guido, Rodrigo Capobianco
Total Authors: 8
Document type: Journal article
Source: Entropy; v. 26, n. 3, p. 22-pg., 2024-03-01.
Abstract

Since financial assets on stock exchanges were created, investors have sought to predict their future values. Currently, cryptocurrencies are also seen as assets. Machine learning is increasingly adopted to assist and automate investments. The main objective of this paper is to make daily predictions about the movement direction of financial time series through classification models, financial time series preprocessing methods, and feature selection with genetic algorithms. The target time series are Bitcoin, Ibovespa, and Vale. The methodology of this paper includes the following steps: collecting time series of financial assets; data preprocessing; feature selection with genetic algorithms; and the training and testing of machine learning models. The results were obtained by evaluating the models with the area under the ROC curve metric. For the best prediction models for Bitcoin, Ibovespa, and Vale, values of 0.61, 0.62, and 0.58 were obtained, respectively. In conclusion, the feature selection allowed the improvement of performance in most models, and the input series in the form of percentage variation obtained a good performance, although it was composed of fewer attributes in relation to the other sets tested. (AU)

FAPESP's process: 19/21464-1 - Deep neural networks and deep feature selection for spoofing detection in voice authentication systems
Grantee:Rodrigo Colnago Contreras
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 21/12407-4 - Improving biometric voice authentication systems: robustness in facing short-term dysphonies
Grantee:Rodrigo Capobianco Guido
Support Opportunities: Regular Research Grants
FAPESP's process: 22/05186-4 - Improving Biometric Voice Authentication Systems: Robustness in Facing Short-Term Dysphonies
Grantee:Rodrigo Colnago Contreras
Support Opportunities: Scholarships in Brazil - Technical Training Program - Technical Training
FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:Francisco Louzada Neto
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
FAPESP's process: 23/06611-3 - Sales Intelligence with Data Mining
Grantee:Monique Simplicio Viana
Support Opportunities: Scholarships in Brazil - Technical Training Program - Technical Training