[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 …
Systematic analysis and review of stock market prediction techniques
DP Gandhmal, K Kumar - Computer Science Review, 2019 - Elsevier
Prediction of stock market trends is considered as an important task and is of great attention
as predicting stock prices successfully may lead to attractive profits by making proper …
as predicting stock prices successfully may lead to attractive profits by making proper …
Mean–variance portfolio optimization using machine learning-based stock price prediction
W Chen, H Zhang, MK Mehlawat, L Jia - Applied Soft Computing, 2021 - Elsevier
The success of portfolio construction depends primarily on the future performance of stock
markets. Recent developments in machine learning have brought significant opportunities to …
markets. Recent developments in machine learning have brought significant opportunities to …
An empirical study on modeling and prediction of bitcoin prices with bayesian neural networks based on blockchain information
Bitcoin has recently attracted considerable attention in the fields of economics, cryptography,
and computer science due to its inherent nature of combining encryption technology and …
and computer science due to its inherent nature of combining encryption technology and …
Multi-step-ahead stock price index forecasting using long short-term memory model with multivariate empirical mode decomposition
Accurate and reliable multi-step-ahead forecasting of stock price indexes over long-term
future trends is challenging for capital investors and decision-makers. This study developed …
future trends is challenging for capital investors and decision-makers. This study developed …
A survey on evolutionary machine learning
Artificial intelligence (AI) emphasises the creation of intelligent machines/systems that
function like humans. AI has been applied to many real-world applications. Machine …
function like humans. AI has been applied to many real-world applications. Machine …
The best of two worlds: Forecasting high frequency volatility for cryptocurrencies and traditional currencies with Support Vector Regression
This paper provides an evaluation of the predictive performance of the volatility of three
cryptocurrencies and three currencies with recognized stores of value using daily and hourly …
cryptocurrencies and three currencies with recognized stores of value using daily and hourly …
Predicting Ethereum prices with machine learning based on Blockchain information
With the growing interest in cryptocurrency and its fundamental algorithm, studies of
cryptocurrency price predictions have been actively conducted in various academic …
cryptocurrency price predictions have been actively conducted in various academic …
Mid-term electricity demand forecasting using improved variational mode decomposition and extreme learning machine optimized by sparrow search algorithm
T Gao, D Niu, Z Ji, L Sun - Energy, 2022 - Elsevier
Mid-term electricity demand forecasting plays an important role in ensuring the operational
safety of the power system and the economic efficiency of grid companies. Most studies …
safety of the power system and the economic efficiency of grid companies. Most studies …
Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model
The present study proposes a new hybrid evolutionary Adaptive Neuro-Fuzzy Inference
Systems (ANFIS) approach for monthly streamflow forecasting. The proposed method is a …
Systems (ANFIS) approach for monthly streamflow forecasting. The proposed method is a …