A systematic review of fundamental and technical analysis of stock market predictions

IK Nti, AF Adekoya, BA Weyori - Artificial Intelligence Review, 2020 - Springer
The stock market is a key pivot in every growing and thriving economy, and every investment
in the market is aimed at maximising profit and minimising associated risk. As a result …

Survey of stock market prediction using machine learning approach

A Sharma, D Bhuriya, U Singh - 2017 International conference …, 2017 - ieeexplore.ieee.org
Stock market is basically nonlinear in nature and the research on stock market is one of the
most important issues in recent years. People invest in stock market based on some …

Predicting stock market trends using machine learning algorithms via public sentiment and political situation analysis

W Khan, U Malik, MA Ghazanfar, MA Azam, KH Alyoubi… - Soft Computing, 2020 - Springer
Stock market trends can be affected by external factors such as public sentiment and
political events. The goal of this research is to find whether or not public sentiment and …

An integrated TOPSIS crow search based classifier ensemble: In application to stock index price movement prediction

R Dash, S Samal, R Dash, R Rautray - Applied Soft Computing, 2019 - Elsevier
Predicting future stock index price movement has always been a fascinating research area
both for the investors who wish to yield a profit by trading stocks and for the researchers who …

Stock price prediction using machine learning on least-squares linear regression basis

CC Emioma, SO Edeki - Journal of Physics: Conference Series, 2021 - iopscience.iop.org
Predicting the future of a stock price is a difficult task due to the high level of randomness in
the movement of prices. This research aims to use a machine-learning algorithm to estimate …

Prediction of stock market by principal component analysis

M Waqar, H Dawood, P Guo… - … and security (CIS), 2017 - ieeexplore.ieee.org
The categorization of high dimensional data present a fascinating challenge to machine
learning models as frequent number of highly correlated dimensions or attributes can affect …

Applying machine learning models on blockchain platform selection

C Dubey, D Kumar, AK Singh, VK Dwivedi - International Journal of …, 2024 - Springer
Recently, technology like Blockchain is gaining attention all over the world today, because it
provides a secure, decentralized framework for all types of commercial interactions. When …

Stock market prediction using subtractive clustering for a neuro fuzzy hybrid approach

SK Chandar - Cluster Computing, 2019 - Springer
Stock market prediction is the challenging area for the investors to yield profits in the
financial markets. The investors need to understand the financial markets which are more …

Analysis and control of variability by using fuzzy individual control charts

İ Kaya, M Erdoğan, C Yıldız - Applied Soft Computing, 2017 - Elsevier
The detection of changes in a process within shortest time provides significant benefits in
terms of cost and quality. When considering the cost which would show up because of …

[PDF][PDF] Using machine learning classifiers to predict stock exchange index

MA Ghazanfar, SA Alahmari, YF Aldhafiri… - … Journal of Machine …, 2017 - researchgate.net
Predicting stock exchange index is an attractive research topic in the field of machine
learning. Numerous studies have been conducted using various techniques to predict stock …