robertmartin8/MachineLearningStocks
Using python and scikit-learn to make stock predictions
This project helps individual traders and investors analyze historical stock data to predict which stocks are likely to outperform the market. It takes historical stock prices and financial fundamentals (like P/E ratios and debt/equity) as input, processes them, and then uses machine learning to identify stocks with the potential for higher returns. The output is a set of predictions for current stocks, indicating their likelihood of outperforming a benchmark index.
1,931 stars. No commits in the last 6 months.
Use this if you are an individual investor or trader interested in using a machine learning template to identify potentially outperforming stocks based on fundamental data.
Not ideal if you need a plug-and-play solution for live trading or a sophisticated portfolio optimization tool, as this project is primarily an educational starting point.
Stars
1,931
Forks
533
Language
Python
License
MIT
Category
Last pushed
Jun 17, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/robertmartin8/MachineLearningStocks"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
rafa-rod/pytrendseries
Detect trend in time series, drawdown, drawdown within a constant look-back window , maximum...
TimRivoli/Stock-Price-Trade-Analyzer
This is a Python 3 project for analyzing stock prices and methods of stock trading. It uses...
LeonardoBerti00/TLOB
This is the official repository for the paper TLOB: A Novel Transformer Model with Dual...
JordiCorbilla/stock-prediction-deep-neural-learning
Predicting stock prices using a TensorFlow LSTM (long short-term memory) neural network for...
jcamiloangarita/stocker
Stock Price Prediction