[HTML][HTML] Machine learning techniques and data for stock market forecasting: A literature review
In this literature review, we investigate machine learning techniques that are applied for
stock market prediction. A focus area in this literature review is the stock markets …
stock market prediction. A focus area in this literature review is the stock markets …
A survey of forex and stock price prediction using deep learning
Predictions of stock and foreign exchange (Forex) have always been a hot and profitable
area of study. Deep learning applications have been proven to yield better accuracy and …
area of study. Deep learning applications have been proven to yield better accuracy and …
Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process
The stock market has performed one of the most important functions in a laissez-faire
economic system by gathering people, companies, and flows of money for several centuries …
economic system by gathering people, companies, and flows of money for several centuries …
Predicting stock market trends using machine learning and deep learning algorithms via continuous and binary data; a comparative analysis
M Nabipour, P Nayyeri, H Jabani, S Shahab… - Ieee …, 2020 - ieeexplore.ieee.org
The nature of stock market movement has always been ambiguous for investors because of
various influential factors. This study aims to significantly reduce the risk of trend prediction …
various influential factors. This study aims to significantly reduce the risk of trend prediction …
Applications of deep learning in stock market prediction: recent progress
W Jiang - Expert Systems with Applications, 2021 - Elsevier
Stock market prediction has been a classical yet challenging problem, with the attention from
both economists and computer scientists. With the purpose of building an effective prediction …
both economists and computer scientists. With the purpose of building an effective prediction …
A comprehensive survey on deep neural networks for stock market: The need, challenges, and future directions
A Thakkar, K Chaudhari - Expert Systems with Applications, 2021 - Elsevier
The stock market has been an attractive field for a large number of organizers and investors
to derive useful predictions. Fundamental knowledge of stock market can be utilised with …
to derive useful predictions. Fundamental knowledge of stock market can be utilised with …
Deep learning for stock market prediction
The prediction of stock groups values has always been attractive and challenging for
shareholders due to its inherent dynamics, non-linearity, and complex nature. This paper …
shareholders due to its inherent dynamics, non-linearity, and complex nature. This paper …
A systematic review of stock market prediction using machine learning and statistical techniques
The stock market prediction patterns are seen as an important activity and it is more
effective. Hence, stock prices will lead to lucrative profits from sound taking decisions …
effective. Hence, stock prices will lead to lucrative profits from sound taking decisions …
A novel deep learning framework: Prediction and analysis of financial time series using CEEMD and LSTM
B Yan, M Aasma - Expert systems with applications, 2020 - Elsevier
Deep learning is well-known for extracting high-level abstract features from a large amount
of raw data without relying on prior knowledge, which is potentially attractive in forecasting …
of raw data without relying on prior knowledge, which is potentially attractive in forecasting …
Hybrid genetic algorithm method for efficient and robust evaluation of remaining useful life of supercapacitors
Supercapacitor as a clean energy storage device has been widely adopted in powering
electric motors of vehicles. Precise evaluation of aging state of supercapacitors, ie, the …
electric motors of vehicles. Precise evaluation of aging state of supercapacitors, ie, the …