A Machine Learning Model for Stock Market Prediction

TL;DR

This paper proposes a machine learning model designed to predict stock market trends, aiming to assist investors and analysts in making informed decisions based on future stock values.

Contribution

It introduces a novel machine learning approach tailored for stock market prediction, improving accuracy over existing models.

Findings

The model achieves higher prediction accuracy than traditional methods.

It demonstrates robustness across different stock datasets.

The approach offers potential for real-time trading applications.

Abstract

Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on a financial exchange.