S&P 500 stock price prediction using Transformer model
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Updated
Jul 11, 2024 - Python
S&P 500 stock price prediction using Transformer model
A Python progamm that determines whether a stock has potential to increase its price based on Sentimental Analysis and recent stock patterns/growth.
A project featuring exploratory data analysis (EDA) and machine learning applications for S&P 500 stock data, utilizing Python and relevant libraries.
TrendSage aims to develop a correlation between stock and cryptocurrency predictions based on the posts or comments on Reddit and the actual market trends.
LSTM-ARIMA with Attention and multiplicative decomposition for sophisticated stock forecasting.
Real-Time Stock Price Visualization using Streamlit
Predictor for stock and ETF prices
This project, part of a bachelor's module at HTW Berlin, implemented and verified the paper "Stock Price Predictions with LSTM Neural Networks and Twitter Sentiment," focusing on Apple's stock price prediction.
Stock price recommender
Implement AI Trading Strategies with Backtrader
Starter repo for task 1 of the "JPMorgan Chase & Co" software engineering program
Stonks Rabbi is a streamlit-based application that uses the Yahoo Finance API to visualize and analyze stock trends, patterns, and performance over its listed time period. The metadata is handled through pymongo, the frontend is on streamlit, and autoARIMA, pandas, and matplotlib are used for data analytics and visualization.
A Streamlit app that predicts stock prices using historical data and displays relevant financial news and metrics. It leverages the Yahoo Finance API for historical stock data, Prophet for forecasting, Finnhub for financial metrics, and NewsAPI for news articles
Seamless Finance: Docker-Deployed APIs for Smart Investments. [WORK IN PROGRESS]
Fast-API base StockSeer-API uses different machine learning alogs to forecast closing stock prices.
Ondokuz Mayıs Üniversitesi Bilgisayar Mühendisliği Bitirme Projesi
A Discord bot that utilizes machine learning (linear regression) to predict and evaluate stock closing prices using historical data from Yahoo Finance.
This project implements a stock price prediction model using various technical indicators and an ensemble of machine learning algorithms. The model predicts the direction of price movements and provides price predictions with uncertainty bounds for the next 8 hours.
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