FinBERT-LSTM: Deep Learning based stock price prediction using News Sentiment Analysis

Natural Language (NLP): Sentiment Analysis and Bitcoin Return Prediction Using FinBERT

Stock Sentinel is a web app providing stock market investors with sentiment analysis and news aggregation. It uses FinBERT for sentiment analysis and offers stock information, similar stocks suggestions, summaries, and news stories. With real-time insights, it helps users make informed investment decisions. Installation is easy with cloning, depend

FinBERT is a pre-trained NLP model to analyze the sentiment of the financial text. It is built by further training the BERT language model in the finance domain, using a large financial corpus and thereby fine-tuning it for financial sentiment classification. For the details, please see FinBERT: Financial Sentiment Analysis with Pre-trained Language Models. The project was deployed on the flask. Providing an indicator to buy, hold or sell stock based on the sentiment predicted for the following news headline/article.

A Deep Learning Sentiment Analysis on News Headlines using FinBERT (Python)

REST API for sentiment analysis in financial news using FinBERT pre-trained model.

I create code that can collect appropriate data for a stock (e.g. company announcements) and use a subsidiary of BERT, finbert, to perform sentiment analysis. This analyis serves as an indicator for that company's stock. I then implement a backtester, and test it.

Programming with torch is becoming fun day by day. And with that finetuning a LLM is becoming interesting too! I have fine tuned FinBERT LLM an opensource finance transformer model to give stock market prediction based on the news headlines or financial articles with the help of sentiment analysis on the text input.

A Flask application of Twitter sentiment analysis by using FinBERT, which is a pre-trained NLP model trained on the financial corpus.

Sentiment Analysis of financial news using FinBERT.

This project aims to analyze the sentiment of financial news headlines.

Source code for 'Enhancing TinyBERT for Financial Sentiment Analysis Using GPT-Augmented FinBERT Distillation.' Demonstrates knowledge distillation for optimizing sentiment analysis in finance.

Forecasting Nasdaq-100 trends using financial sentiment analysis and transformer-based deep learning models (Informer, LSTM, FinBERT).

Transfer entropy analysis pipeline for studying causal information flow between financial news sentiment and STOXX 50 stock returns. Implements complete workflow from Eikon data collection through FinBERT sentiment analysis to transfer entropy computation using IDTxl.

FinAgent Insights is an AI-powered financial platform that delivers real-time data, personalized advice, and risk assessments. It uses GPT-4 and FinBERT for advanced financial insights and sentiment analysis, helping users make informed decisions. The platform also integrates educational content to enhance understanding of stock movements and marke

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Sentiment analysis using a fine-tuned FinBert model from Hugging Face Transformers

Predicts stock price movement using news/Reddit sentiment analysis with FinBERT and machine learning

An LSTM model to predict stock price trends using FinBERT sentiment analysis on financial news.

A FinBERT based sentiment analysis using web scraping and data cleaning techniques in Python, with a streamlit dashboard. Have applied LSTM, XGBoost, Random Forest for some sentiment analysis exercises as well.

Sentiment analysis of financial tweets using FinBERT to predict short-term stock market movements. Includes data preprocessing, fine-tuning, and model evaluation.

This repository contains a complete end-to-end workflow for analyzing Indian market news using NLP, FinBERT sentiment analysis, synthetic market data generation, event studies, and volatility impact analysis.

A full-stack web app that scrapes the top 100 posts from r/stocks and performs sentiment analysis using an MLP model with FinBERT embeddings. Built with FastAPI & React (Vite).

In this project, we combine historical stock price data with sentiment analysis of financial news using FinBERT to predict stock prices for Apple Inc. (AAPL) using a Long Short-Term Memory (LSTM) neural network.

FinBERT-based sentiment analysis system for cryptocurrency and financial news. Automates data ingestion, NLP processing, and correlation analysis every 3 hours. Deployed on a Linux server using MongoDB, SSH, and crontab for end-to-end automation.

In this project, I have developed a sentiment analysis tool using advanced NLP models to analyze financial news headlines and predict short-term stock price movements. By leveraging transformer-based models like FinBERT, we can extract nuanced sentiment from finance-specific texts.

Repository contains the code and data for the paper "Enhancing Stock Market Return Predictions from 10-K Filings: Leveraging the Loughran–McDonald Dictionary and Sentiment Analysis with BERT". The project introduces a novel NLP pipeline that integrates sentiment analysis using FinBERT to predict stock market returns from 10-K annual reports.

This project developed a real-time trading system combining text sentiment and speech emotion analysis using FinBERT and Wav2Vec models. It transcribes and analyzes financial audio sources, offering a dual-layered analysis to provide nuanced insights for more informed trading decisions, advancing AI-driven FinTech strategies.

A Final Year Project using NLP and time-series analysis to collect data from Reddit, Twitter/X, and financial news. Applies transformer models (e.g. FinBERT) to analyse sentiment and visualise correlations with asset price movements in an interactive dashboard.

Classification of Financial News using finbert into positive, negative or neutral