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

Any data but iris 👁

Command line utility to display stock quotes and index data

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

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

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.

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.

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

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

Vix index is implemented in S&P500 historical data.

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

The app to know next day's yield prediction

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

Python Repository to ingest, feature engineer, train, backtest, and run a random forest model to predict the direction of the S&P500 at the start of the next day's trading session.

Official Repo of Nifty50.live

Various Crypto/US Stock Alerts

A backtesting environment and trading bots implemented in Python.

Data analysis that aims to evaluate Bitcoin as a diversification instrument to a US equity portfolio.