Current and Historical Lists of S&P 500 components since 1996

Market Breadth Monitor

An S&P500 Stock Index Movement Predictor built with Machine Learning models

Constituent history of the S&P 500 from various data sources

Command line utility to display stock quotes and index data

Any data but iris 👁

Collection of 3 quantitative finance projects in Python that uses algorithmic trading.

S&P500 Stock Index Movement Forecastor with various Statistical and Machine Learning Models

Distributed stock price forecasting system to predict S&P 500 stock prices.

This repo is about Economy & Financial Markets. Here you can see data about Argentinian Stocks Market, S&P 500, Dow Jones, Brazilian Stocks Market and other economic metrics such as GDP, Gold value, etc.

The purpose of this repository is to test the hypothesis that the S&P 500 index has an exogenous relationship to the price of Gold; specifically that as the S&P index falls, the value of Gold will increase.

Predict stock trends using visual time windows

Abstract: The S&P500 is difficult to predict. Multi-factor models provide a useful framework for making returns predictions and for controlling portfolio risk. This paper explores a three-step process in predicting PCA and Autoencoders factors to generate multi-factor models from the S&P500 component securities.

Vix index is implemented in S&P500 historical data.

This project focuses on the design and implementation of a trading bot using OpenAI's GPT for sentiment analysis of financial news. The bot integrates sentiment analysis in trading strategies for S&P 500 stocks.

Quant machine for S&P 500 (Annualized return: 20.60%; Sharpe ratio: 1.06; Sortino ratio: 2.05; Calmar ratio: 1.05)

Official Repo of Nifty50.live

Historical options data for three major U.S. equity ETFs: SPY (S&P 500), IWM (Russell 2000), and QQQ (Nasdaq-100). The dataset spans January 2008 to December 2025 and includes over 53 million option contracts with Greeks, implied volatilities, and market microstructure variables.

Quantitative research tool analyzing stock performance around US Thanksgiving. 354 stocks, 8,293 observations (2000-2024). Statistical significance testing included.

Applied Basic Machine Learning on List of S&P 500 Companies using Yahoo Finance