sp500
There are 1 repository under sp500 topic.
- Language:Jupyter Notebook 532
- Language:Rust 39
hklchung / StockPricePredictor
An S&P500 Stock Index Movement Predictor built with Machine Learning models
Language:Jupyter Notebook 37- Language:Java 20
- Language:R 19
riazarbi / sp500-scraper
Constituent history of the S&P 500 from various data sources
Language:R 15snsten / SP500_Time-Series_Forecasting
S&P500 Stock Index Movement Forecastor with various Statistical and Machine Learning Models
Language:Jupyter Notebook 13cengizozel / Algorithmic-Trading-In-Python
Collection of 3 quantitative finance projects in Python that uses algorithmic trading.
Language:Jupyter Notebook 12LeonardoEmili / stock-price-forecasting
Distributed stock price forecasting system to predict S&P 500 stock prices.
Language:Jupyter Notebook 12Nayan48 / SPY-Trend-Prediction-with-Deep-Learning-Models
Developed a predictive model using LSTM networks to forecast strong daily uptrends in the SPY ETF. This project includes feature engineering, model building and hyper parameter tuning and a backtested trading strategy that outperforms the market.
Language:Jupyter Notebook 11alessandrozamberletti / sp500-forecaster
Predict stock trends using visual time windows
Language:Python 8- Financial-Markets
jidemaestri / Financial-Markets
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.
Language:Jupyter Notebook 8 - ARIMAX-Gold-and-S-P500-Time-Series
Shane-McCallum / ARIMAX-Gold-and-S-P500-Time-Series
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.
Language:Jupyter Notebook 8 Leo8216 / An-Analysis-of-PCA-and-Autoencoder-Generated-Factors-in-Predicting-SP500-Returns
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.
Language:HTML 7ArunavD / vix_strategy_backtest
Vix index is implemented in S&P500 historical data.
Language:Python 6warlockJay / Machine-Learning-on-S-P-500-Companies
Applied Basic Machine Learning on List of S&P 500 Companies using Yahoo Finance
Language:Python 6Emino21 / GPT-Sentiment-Trading-Bot
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.
Language:Python 5- Language:HTML 5
JackZhao516 / smrti_quant_alerts
Various Crypto/US Stock Alerts
Language:Python 4JonasGreim / leaflet-map-project
Map showing the location of the headquarters of the top US companies over many years. (visualization part)
Language:JavaScript 4sidmohan0 / quant-train
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.
Language:Python 4TheSnowGuru / Nostradamus-App
The app to know next day's yield prediction
Language:Python 4yfiua / quant-machine-sp500
Quant machine for S&P 500 (Annualized return: 20.60%; Sharpe ratio: 1.06; Sortino ratio: 2.05; Calmar ratio: 1.05)
Language:HTML 4adamgulyas / diversifying-with-bitcoin
Data analysis that aims to evaluate Bitcoin as a diversification instrument to a US equity portfolio.
Language:Jupyter Notebook 3AnthonyDickson / AlgoTrader
A backtesting environment and trading bots implemented in Python.
Language:Jupyter Notebook 3Map showing the location of the headquarters of the top US companies over many years. (data scraping part)
Language:Python 3- Language:R 3
alliajagbe / macrostock
Evaluating the Impact of Macroeconomic Indicators on S&P Prices
Language:Jupyter Notebook 2andrea-varesio / smart-dca-backtest
Smart Dollar Cost Averaging backtest
Language:Python 2Golden Cross strategy implementation in S&P500 and NIFTY50 historical data.
Language:Python 2automated-bots / Stock-Index-Bot
S&P500 And VIX index bot for Telegram
Language:JavaScript 2gvmossato / alstm-stock-market
📈 Previsão do Índice S&P 500 Utilizando LSTM e Mecanismos de Atenção
Language:Python 2NikolaySimakov / Fama-French-models
📈 Fama French and ML models on S&P 500 dataset
Language:Jupyter Notebook 2nisa-g / CAPM-Web-Application-Financial-Analysis
This project showcases a web application that is designed to perform CAPM calculations for different stocks. The application uses Python programming language and its libraries such as Pandas, NumPy, Streamlit and Plotly, to gather stock data from Yahoo Finance and perform calculations to determine expected returns.
Language:Python 2Sandreke / Data-Analysis-of-SP500-Stock-Features
This project consists of web scraping features of S&P 500 companies like ticker, company name, sector, headquarter, date first added and foundation year from Wikipedia with Python using BeatifulSoup and Requests libraries. Then, the web scraped data is cleaned to perform data visualization in order to deliver insights about S&P 500 companies.
Language:Jupyter Notebook 2StephanAkkerman / spy-heatmap
The popular S&P 500 heatmap / treemap open-sourced
Language:Python 2
