Stock market forecasting using computational intelligence: A survey
Stock market plays a key role in economical and social organization of a country. Stock
market forecasting is highly demanding and most challenging task for investors, professional …
market forecasting is highly demanding and most challenging task for investors, professional …
Deep learning-based feature engineering for stock price movement prediction
W Long, Z Lu, L Cui - Knowledge-Based Systems, 2019 - Elsevier
Stock price modeling and prediction have been challenging objectives for researchers and
speculators because of noisy and non-stationary characteristics of samples. With the growth …
speculators because of noisy and non-stationary characteristics of samples. With the growth …
Cryptocurrency forecasting with deep learning chaotic neural networks
We implement deep learning techniques to forecast the price of the three most widely traded
digital currencies ie, Bitcoin, Digital Cash and Ripple. To the best of our knowledge, this is …
digital currencies ie, Bitcoin, Digital Cash and Ripple. To the best of our knowledge, this is …
MLP-based Learnable Window Size for Bitcoin price prediction
Over the past few years, Bitcoin price prediction has been changed to a big challenge for
investors on cryptocurrencies. In this regard, Neural Networks as a strong structure for …
investors on cryptocurrencies. In this regard, Neural Networks as a strong structure for …
Stock price prediction using news sentiment analysis
S Mohan, S Mullapudi, S Sammeta… - 2019 IEEE fifth …, 2019 - ieeexplore.ieee.org
Predicting stock market prices has been a topic of interest among both analysts and
researchers for a long time. Stock prices are hard to predict because of their high volatile …
researchers for a long time. Stock prices are hard to predict because of their high volatile …
Deep Learning-based Integrated Framework for stock price movement prediction
Y Zhao, G Yang - Applied Soft Computing, 2023 - Elsevier
Stock market prediction is a very important problem in the economics field. With the
development of machine learning, more and more algorithms are applied in the stock market …
development of machine learning, more and more algorithms are applied in the stock market …
Evaluating the performance of machine learning algorithms in financial market forecasting: A comprehensive survey
With increasing competition and pace in the financial markets, robust forecasting methods
are becoming more and more valuable to investors. While machine learning algorithms offer …
are becoming more and more valuable to investors. While machine learning algorithms offer …
A novel data-driven stock price trend prediction system
This paper proposes a novel stock price trend prediction system that can predict both stock
price movement and its interval of growth (or decline) rate within the predefined prediction …
price movement and its interval of growth (or decline) rate within the predefined prediction …
A new decomposition ensemble model for stock price forecasting based on system clustering and particle swarm optimization
Y Guo, J Guo, B Sun, J Bai, Y Chen - Applied Soft Computing, 2022 - Elsevier
Accurate forecasting of stock prices has been a challenge in the securities market, while the
stock price time series tend to be non-stationary, non-linear, and highly noisy. At present, the …
stock price time series tend to be non-stationary, non-linear, and highly noisy. At present, the …
[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 …