A self-regulated generative adversarial network for stock price movement prediction based on the historical price and tweets
H Xu, D Cao, S Li - Knowledge-Based Systems, 2022 - Elsevier
Stock price movement prediction is an important task of the financial prediction field. The
current mainstream approaches usually apply financial texts and some corresponding stock …
current mainstream approaches usually apply financial texts and some corresponding stock …
Smoothing and stationarity enforcement framework for deep learning time-series forecasting
Time-series analysis and forecasting problems are generally considered as some of the
most challenging and complicated problems in data mining. In this work, we propose a new …
most challenging and complicated problems in data mining. In this work, we propose a new …
On ensemble techniques of weight-constrained neural networks
Ensemble learning constitutes one of the most fundamental and reliable strategies for
building powerful and accurate predictive models, aiming to exploit the predictions of a …
building powerful and accurate predictive models, aiming to exploit the predictions of a …
Importance of machine learning in making investment decision in stock market
A Prasad, A Seetharaman - Vikalpa, 2021 - journals.sagepub.com
Predicting stock trends in the financial market is always demanding but satisfying as well.
With the growing power of computing and the recent development of graphics processing …
With the growing power of computing and the recent development of graphics processing …
Combining LSTM and CNN methods and fundamental analysis for stock price trend prediction
Z Nourbakhsh, N Habibi - Multimedia Tools and Applications, 2023 - Springer
Stock market trend prediction has always been a major challenge for investors. In this paper,
the combination of Convolutional Neural Network and long short-term memory methods, as …
the combination of Convolutional Neural Network and long short-term memory methods, as …
A dropout weight-constrained recurrent neural network model for forecasting the price of major cryptocurrencies and CCi30 index
Cryptocurrency is widely recognized as an alternative method for paying and exchanging
currency instead of using classic coins or gold; thus, it has infiltrated almost in all financial …
currency instead of using classic coins or gold; thus, it has infiltrated almost in all financial …
Exploring an ensemble of methods that combines fuzzy cognitive maps and neural networks in solving the time series prediction problem of gas consumption in …
This paper introduced a new ensemble learning approach, based on evolutionary fuzzy
cognitive maps (FCMs), artificial neural networks (ANNs), and their hybrid structure (FCM …
cognitive maps (FCMs), artificial neural networks (ANNs), and their hybrid structure (FCM …
The prediction of enterprise stock change trend by deep neural network model
G Ma, P Chen, Z Liu, J Liu - Computational Intelligence and …, 2022 - Wiley Online Library
This study aims to accurately predict the changing trend of stocks in stock trading so that
company investors can obtain higher returns. In building a financial forecasting model …
company investors can obtain higher returns. In building a financial forecasting model …
Stock index trend prediction based on TabNet feature selection and long short-term memory
X Wei, H Ouyang, M Liu - Plos one, 2022 - journals.plos.org
In this study, we propose a predictive model TabLSTM that combines machine learning
methods such as TabNet and Long Short-Term Memory Neural Network (LSTM) with a …
methods such as TabNet and Long Short-Term Memory Neural Network (LSTM) with a …
Forecasting the direction of daily changes in the India VIX index using machine learning
Movements in the India VIX are an important gauge of how the market's risk perception shifts
from day to day. This research attempts to forecast movements one day ahead of the India …
from day to day. This research attempts to forecast movements one day ahead of the India …