Expert Systems With Applications

By R. C. Cavalcante, Rodrigo C. Brasileiro, Victor L. F. Souza, J. P. Nóbrega, A. Oliveira

601 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Finance

In Management Science and Operations Research

Citations in the corpus

Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019, background): “A number of surveys were published for stock market forecasting studies based on various soft computing methods at different times [24, 25, 26, 27, 28, 29, 30, 31].”
Financial Trading Model with Stock Bar Chart Image Time Series with Deep Convolutional Neural Networks (2019, methodology): “[3] reviewed all possible prediction model techniques that are used in financial time-series data.”
Stock Price Prediction by Deep Neural Generative Model of News Articles (2018, background): “Research has also focused on technical analysis methods for identifying certain patterns in past price movements to predict future price movements [2]–[6]; this is typically founded on the belief that the same price movement patterns are often repeated, but the financial market is not a closed syste”
Threshold-based portfolio: the role of the threshold and its applications (2017, background): “Researchers have successfully modeled financial time series by focusing primarily on prediction accuracy or automatic trading rules [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16].”
AI in Finance: Challenges, Techniques, and Opportunities (2021, methodology): “Further, computational intelligence techniques and methods inspired by nature and human systems and simulating natural and human intelligence are used to model, characterize, and optimize EcoFin mechanisms, strategies, and systems, and to manage and optimize portfolio and market forecasting, and so ”
Natural language based financial forecasting: a survey (2017, background): “5 Topics concerning NLFF, inspired and adapted from the concept wheel of financial markets [22].”
A deep learning based stock trading model with 2-D CNN trend detection (2017, background): “In recent decades, computational intelligence models that can learn nonlinear relationships between input and output values have shown promise and researchers have been trying to incorporate these models in financial forecasting [1], [2].”
Applications of deep learning in stock market prediction: recent progress (2020, background): “Cavalcante et al. (2016) gives an overview of the most important primary studies published from 2009 to 2015, which cover techniques for preprocessing and clustering of financial data, for forecasting future market movements, for mining financial text information, among others.”