Stock Scanner & Screener: A yfinance-based Stock Scanner and Screener, focusing on Fundamental Properties of scanned stocks.
An attempt to predict next day's stock price movements using sentiments in tweets with cashtags. Six different ML algorithms were deployed (LogReg, KNN, SVM etc.). Main libraries used: Pandas & Numpy
Analyze NASDAQ100 stock data. Used ARIMA + GARCH model and machine learning techniques Naive Bayes and Decision tree to determine if we go long or short for a given stock on a particular day
This is our take on Portfolio Optimization with Reinforcement Learning using Q Learning.
Various Crypto/US Stock Alerts
Plugin WordPress, gera card com base na consulta Ativo/Cota via API Nasdaq symbols
Portal to share my investment experience and strategies
Usual linear regression or XGBoost? Combo! Or how I was investigating the impact of intellectual capital on NASDAQ-100 capitalization during 2 years.
Four datasets intended for use by ML models to assess whether ML can take a set of financial ratios for stocks in the Nasdaq 100 (x data) and the subsequent 12 month Share Price performance (y data) and hence predict with accuracy future Share Price returns.
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