Multi-source data ensemble for energy price trend forecasting
DD de Castilho Braz, MR dos Santos… - … Applications of Artificial …, 2024 - Elsevier
Price trend prediction is critical across sectors, including finance, energy, and supply chains,
guiding strategic decision-making. Machine Learning's rise, fueled by abundant data and …
guiding strategic decision-making. Machine Learning's rise, fueled by abundant data and …
Machine learning approach for trend prediction to improve returns on brazilian energy market
MR Santos, DDC Braz, AC Carvalho… - 2022 IEEE Latin …, 2022 - ieeexplore.ieee.org
The Free Energy Market in Brazil has changed a lot since its implementation in the late
1990s. Its expansion has accelerated in recent years, making operations more complex …
1990s. Its expansion has accelerated in recent years, making operations more complex …
Improving portfolio optimization using weighted link prediction in dynamic stock networks
D Castilho, J Gama, LR Mundim… - … Science–ICCS 2019: 19th …, 2019 - Springer
Portfolio optimization in stock markets has been investigated by many researchers. It looks
for a subset of assets able to maintain a good trade-off control between risk and return …
for a subset of assets able to maintain a good trade-off control between risk and return …
Designing financial strategies based on artificial neural networks ensembles for stock markets
J de Mello Assis, ACM Pereira… - 2018 international joint …, 2018 - ieeexplore.ieee.org
Before the advent of computers and Internet, the stock market investors perform their
operations based mainly on intuition. With the growth of investments and online stock …
operations based mainly on intuition. With the growth of investments and online stock …
Major Issues in High-frequency Financial Data Analysis: A Survey of Solutions
L Zhang, L Hua - Available at SSRN 4834362, 2024 - papers.ssrn.com
We review recent articles that focus on the main issues identified in high-frequency financial
data analysis. The issues to be addressed include nonstationarity, low signal-to-noise ratios …
data analysis. The issues to be addressed include nonstationarity, low signal-to-noise ratios …
Data-driven learning from dynamic pricing data-classification and forecasting
MH Christensen, DC Nozal… - 2019 IEEE Milan …, 2019 - ieeexplore.ieee.org
Inspired by recent advances in data driven methods from deep-learning, this paper shows
how neural networks can be trained to extract valuable information from smart meter data …
how neural networks can be trained to extract valuable information from smart meter data …
Modelagem e aplicação de técnicas de aprendizado de máquina para negociação em alta frequência em bolsa de valores
EJ da Silva - 2015 - repositorio.ufmg.br
Algoritmos de negociação (algotrading) têm desempenhado um papel importante no
mercado de ações eletrônico. Entretanto, esses algoritmos, sem qualquer poder de …
mercado de ações eletrônico. Entretanto, esses algoritmos, sem qualquer poder de …