Contrasting the efficiency of stock price prediction models using various types of LSTM models aided with sentiment analysis

TL;DR

This paper compares various LSTM-based models aided by sentiment analysis to identify the most effective approach for predicting stock prices in both short and long-term scenarios.

Contribution

It introduces a comparative analysis of different LSTM models combined with sentiment data for stock price prediction, highlighting the most efficient model.

Findings

LSTM models with sentiment analysis outperform traditional models

The best model achieves higher prediction accuracy for short-term stocks

Sentiment analysis significantly improves long-term stock prediction

Abstract

Our research aims to find the best model that uses companies projections and sector performances and how the given company fares accordingly to correctly predict equity share prices for both short and long term goals.