PyStockBot

This is a project to create a stock bot that can predict the stock price of a company using machine learning.

DISCLAIMER: In general, there is no preference given to any of these metrics, models, and resources, this is not a recommendation to use them. Besides implementing and categorizing them Uhstray.io and all contributors are not officially suggesting any opinion on any of these, Uhstray.io and any contributors are not financial advisors. Do your own due diligence and speak to a professional financial advisor before making any financial decisions.

Trading Design Architecture

Contributing Guidelines

• Review our Code of Conduct
• Check our CONTRIBUTING.MD

Installation

This project uses uv as a package manager. To install uv and the dependencies, run the following commands:

pip install -U uv

uv sync

Running the code

Run the notebooks in the following order:

1. pull_data.ipynb
2. pull_events.ipynb
3. pull_dividends_splits.ipynb
4. prepare_dataset.ipynb
5. train_model.ipynb
6. analyze_model.ipynb

Understanding the code

The code is divided into the following sections:

Understanding the data

Understanding the metrics

Resources

Data

Articles

https://machinelearningmastery.com/xgboost-for-time-series-forecasting/ https://www.kaggle.com/code/faressayah/stock-market-analysis-prediction-using-lstm/notebook

Videos

https://www.youtube.com/watch?v=vV12dGe_Fho https://www.youtube.com/watch?v=z3ZnOW-S550

Libraries

https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html https://pandas-datareader.readthedocs.io/en/latest/remote_data.html