Sánchez-Gómez, Claudia

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Investment Portfolio Optimization Using Technical Indicators and White-Box Models
(IEEE, 2024-12-04)
Caro Reyna Luis Fernando
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Arcos Bravo David Gamaliel
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Quantitative trading has revolutionized in recent years with the integration of machine learning. However, most proposals are complex models that often need help with model understanding and feature importance identification. This study presents a methodology for optimizing investment portfolios using the XGBoost algorithm and a comprehensive set of technical indicators. The primary objective is to maximize returns by accurately predicting stock prices and selecting the most profitable stocks. Our proposal is based on decision trees, eliminating the need for recurrent neural networks or time series representations of data and enabling white-box machine learning models that are easier to interpret. We tried our proposal with real data corresponding to a collection of stocks of the 500 most influential companies in the United States of America, utilizing historical data such as open prices, highest and lowest prices, and trading volume. Experimental results demonstrated that our approach successfully identified the most profitable stocks, outperforming random portfolios and showing significant profit accumulation over time. This approach recognizes the most feasible indicators and facilitates the automatic design of investment portfolios and the analysis of the importance of technical indicators in complex data.
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Optimización del balanceo de un mecanismo plano mediante redistribución de masas
(2022)
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Juan Cisneros-Barba
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Miguel Carrasco
9 2
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Selecting crackling product based on sensory analysis by different statistical data approaches
(2017)
G. Sanchez-Gutierrez
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G. Rodriguez-Serrano
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H. Escalona-Buendia
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11 1
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Determinación de la aceptación de alimentos mediante reacciones fisiológicas del consumidor: un enfoque basado en aprendizaje automático
(2021)
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12 2
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Estimating the Maximum Power of a Concentrator Photovoltaic Module through Random Forest
(2023)
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Pedro M. Rodrigo
25 2
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I3GO+ at RICATIM 2017: A semi-supervised approach to determine the relevance between images and text-annotations
(2017)
Jose Ortiz-Bejar
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Eric S. Tellez
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Mario Graff
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Sabino Miranda-Jimenez
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Daniela Moctezuma
Scopus© Citations 1 12 1
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Optimal Design of Sliding Mode Control Combined with Positive Position Feedback
(2018)
Enríquez-Zárate, J.
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Trujillo, Leonardo
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Hernández, C.
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This work focuses on the application of a discontinuous controller combined with a type of modal control using hybrid optimization techniques to tune the parameters of the controller. The case study is a civil structure with three floors, on which the performance of the control scheme is evaluated by applying an external harmonic force at the ground floor of the structure. The active control is designed to reduce the displacement of the civil structure and the vibrations of the overall system. The Differential Evolution method with the Interior Point Algorithm are used to tune the parameters of the proposed controller, with the goal of maximizing performance relative to hand-tuned parameters. The numerical results are presented comparing the performance of the control in open and closed loop, considering the optimized values of the control parameters.
12 1
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Consumer Acceptances Through Facial Expressions of Encapsulated Flavors Based on a Nanotechnology Approach
(2018)
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Gutiérrez, Sebastián
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Bryan Lopez
Scopus© Citations 2 10 1
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Visual Impairment Simulator Based on the Hadamard Product
(2016)
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Edwige E. Pissaloux
Scopus© Citations 7 6 1
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Analysis of Meat Color Change using Computer Vision
(2020)
Gustavo Meza
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Scopus© Citations 1 16 1

Sánchez-Gómez, Claudia

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