Literature review: Machine learning techniques applied to financial market prediction
BM Henrique, VA Sobreiro, H Kimura - Expert Systems with Applications, 2019 - Elsevier
The search for models to predict the prices of financial markets is still a highly researched
topic, despite major related challenges. The prices of financial assets are non-linear …
topic, despite major related challenges. The prices of financial assets are non-linear …
Applications of neuro fuzzy systems: A brief review and future outline
This paper surveys neuro fuzzy systems (NFS) development using classification and
literature review of articles for the last decade (2002–2012) to explore how various NFS …
literature review of articles for the last decade (2002–2012) to explore how various NFS …
Fuzzy broad learning system: A novel neuro-fuzzy model for regression and classification
A novel neuro-fuzzy model named fuzzy broad learning system (BLS) is proposed by
merging the Takagi-Sugeno (TS) fuzzy system into BLS. The fuzzy BLS replaces the feature …
merging the Takagi-Sugeno (TS) fuzzy system into BLS. The fuzzy BLS replaces the feature …
Deep direct reinforcement learning for financial signal representation and trading
Can we train the computer to beat experienced traders for financial assert trading? In this
paper, we try to address this challenge by introducing a recurrent deep neural network (NN) …
paper, we try to address this challenge by introducing a recurrent deep neural network (NN) …
Improving financial trading decisions using deep Q-learning: Predicting the number of shares, action strategies, and transfer learning
G Jeong, HY Kim - Expert Systems with Applications, 2019 - Elsevier
We study trading systems using reinforcement learning with three newly proposed methods
to maximize total profits and reflect real financial market situations while overcoming the …
to maximize total profits and reflect real financial market situations while overcoming the …
Developing a deep learning framework with two-stage feature selection for multivariate financial time series forecasting
Intelligent financial forecasting modeling plays an important role in facilitating investment-
related decision-making activities in financial markets. However, accurate multivariate …
related decision-making activities in financial markets. However, accurate multivariate …
Predicting stock market using machine learning: best and accurate way to know future stock prices
D Sheth, M Shah - International Journal of System Assurance Engineering …, 2023 - Springer
Dissatisfaction is the first step of progress, this statement serves to be the base of using
Artifcial Intelligence in predicting stock prices. A great deal of people dreamed of predicting …
Artifcial Intelligence in predicting stock prices. A great deal of people dreamed of predicting …
Computational intelligence and feature selection: rough and fuzzy approaches
The rough and fuzzy set approaches presented here open up many new frontiers for
continued research and development Computational Intelligence and Feature Selection …
continued research and development Computational Intelligence and Feature Selection …
[HTML][HTML] Feature selection and deep neural networks for stock price direction forecasting using technical analysis indicators
This paper analyzes the factor zoo, which has theoretical and empirical implications for
finance, from a machine learning perspective. More specifically, we discuss feature selection …
finance, from a machine learning perspective. More specifically, we discuss feature selection …
Electricity price and demand forecasting in smart grids
A Motamedi, H Zareipour… - IEEE Transactions on …, 2012 - ieeexplore.ieee.org
In future smart grids, consumers of electricity will be enabled to react to electricity prices. The
aggregate reaction of consumers can potentially shift the demand curve in the market …
aggregate reaction of consumers can potentially shift the demand curve in the market …