An Endogenous Feedback and Entropy Analysis in Machine Learning Model for Stock’s Return Forecast

作     者：Edson Vinicius Pontes Bastos Jorge Junio Moreira Antunes Lino Guimaraes Marujo Peter Fernandes Wanke Roberto Ivo da Rocha Lima Filho 

作者机构：Instituto Alberto Luiz Coimbra de Pos-Graduação e Pesquisa de Engenharia-COPPEUniversidade Federal do Rio de Janeiro(UFRJ)Rio de Janeiro21941-598Brasil Instituto de Pos-Graduacao em Administracao-CoppeadUniversidade Federal do Rio de Janeiro(UFRJ)21941-918Brasil 

出 版 物：《Intelligent Automation & Soft Computing》 (智能自动化与软计算（英文）)

年 卷 期：2023年第36卷第6期

页      面：3175-3190页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Forecast endogeneity neural networks differential evolution stochastic optimization 

摘      要：Stock markets exhibit Brownian movement with random,non-linear,uncertain,evolutionary,non-parametric,nebulous,chaotic characteristics and dynamism with a high degree of *** an algorithm to predict returns for decision-making is a challenging *** addition,the choice of vari-ables that will serve as input to the model represents a non-triviality,since it is possible to observe endogeneity problems between the predictor and the predicted ***,the goal is to analyze the endogenous origin of the stock return prediction model based on technical *** this,we structure a feed-for-ward neural *** evaluate the endogenous feedback between the pre-dicted returns and technical analysis indicators based on the generated *** is possible to predict the *** high accuracy of the model indicates that,during the test period,there is a hit rate close to 76%.Regarding endogeneity,the term of interest and the return are the variables that influence the largest number of *** results will help investors build investment strategies based on this expert system applied to forecasting.