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 …
Edge computing and sensor-cloud: Overview, solutions, and directions
Sensor-cloud originates from extensive recent applications of wireless sensor networks and
cloud computing. To draw a roadmap of the current research activities of the sensor-cloud …
cloud computing. To draw a roadmap of the current research activities of the sensor-cloud …
Predict stock prices using supervised learning algorithms and particle swarm optimization algorithm
MJ Bazrkar, S Hosseini - Computational Economics, 2023 - Springer
Forecasting the stock market has always been one of the challenges for stock market
participants to make more profit. Among the problems of stock price forecasting, we can …
participants to make more profit. Among the problems of stock price forecasting, we can …
An Empirical Study of Macroeconomic Factors and Stock Returns in the Context of Economic Uncertainty News Sentiment Using Machine Learning
Stock markets accurately reflect countries' economic health, and stock returns are tightly
related to economic indices. One popular area of financial research is the factors that …
related to economic indices. One popular area of financial research is the factors that …
Stock prices prediction using machine learning
FL Marchai, W Martin… - 2021 8th International …, 2021 - ieeexplore.ieee.org
More people invest their money in the stock market. However, this kind of investment
possesses a lot of risks. Therefore, many works have been done to build a model using …
possesses a lot of risks. Therefore, many works have been done to build a model using …
Analysis and prediction of stock market movements using machine learning
V Bhardwaj, KV Rahul, M Kumar… - 2022 4th International …, 2022 - ieeexplore.ieee.org
As vast amounts of data are generated every day in many organizations, health, education,
transport, business, marketing, communication, etc. All the data cannot be used for every …
transport, business, marketing, communication, etc. All the data cannot be used for every …
A detailed survey to forecast the stock prices by applying machine learning predictive models and artificial intelligence techniques
KV Kumar, R Anitha - 2022 International Conference on …, 2022 - ieeexplore.ieee.org
Companies often fractionalize the ownership to sell them and gain capital. Each fraction of
that ownership is called stock. The price of each stock keeps on varying due to companies' …
that ownership is called stock. The price of each stock keeps on varying due to companies' …
Advancing Financial Forecasts: Stock Price Prediction Based on Time Series and Machine Learning Techniques
CY Yang, MS Hwang, YW Tseng, CC Yang… - Applied Artificial …, 2024 - Taylor & Francis
Since the beginning of stock trading, investors and researchers have tried to find effective
ways to predict the direction of stock prices on the next day. However, predicting stock prices …
ways to predict the direction of stock prices on the next day. However, predicting stock prices …
Predicting the Trends of the Egyptian Stock Market Using Machine Learning and Deep Learning Methods
H Elsegai, HS Al-Mutawaly… - Computational Journal of …, 2025 - journals.ekb.eg
The prediction of stock price movements has remained a significant area of interest for
researchers and investors, driven by the dynamic nature of financial markets and persistent …
researchers and investors, driven by the dynamic nature of financial markets and persistent …
A Data Mining approach on the Performance of Machine Learning Methods for Share Price Forecasting using the Weka Environment
AU Devi, RV Kumar, PS Priya… - 2023 Fifth …, 2023 - ieeexplore.ieee.org
It is widely agreed that the share price is too volatile to be reliably predicted. Several experts
have worked to improve the likelihood of generating a profit from share investing using …
have worked to improve the likelihood of generating a profit from share investing using …