Fin Metrics

Machine learning model to understand the relationship between Stock Percent Change and Financial Key Metrics over time and predict stock price movement based on growth of the financial metrics

Table of Contents

• Architecture
• Tech stack
• Packages used
• Pre-requisites
• Installation
• Usage
• Project Report
• Contributing
• Contact

Architecture

Tech Stack

• Python
• Mage
• OpenBB
• GCP BigQuery
• H2O AutoML
• Git

Packages used

• pandas
• mage-ai
• google-cloud-bigquery
• openbb
• numpy
• lightgbm
• scikit-learn
• xgboost
• h2o

Pre-requisites

• Python: Make sure you have Python installed on your machine. You can download the latest version of Python from the official Python website: python.org

• Java: Make sure you have Java installed on your machine. You can get the latest version from Java website: java.com

• Package Manager: Install a package manager like pip or conda. Pip is the default package manager for Python and is usually pre-installed with Python. Conda is an alternative package manager that is often used for managing Python environments. You can install conda by downloading Anaconda or Miniconda from their respective websites.

• Virtual Environment (optional): It is recommended to set up a virtual environment for your Python project. Virtual environments allow you to isolate project dependencies and avoid conflicts between different projects. You can create a virtual environment using tools like venv, virtualenv, or conda.

• Data Pipelines: Some knowledge of Data Engineering and Data Pipelining concepts. On top of that, familarity with Mage Data would be beneficial

Installation

1. Clone this repository

git clone https://github.com/george-dominic/fin-metrics.git

2. Change into the project's directory

cd fin-metrics

3. Install the required dependencies by running the following command:

pip install -r requirements.txt

Usage

1. Once you are inside fin-metrics directory, initialise the mage pipeline using:

mage start metrics

This will open up Mage UI on your local browser : https://localhost:6789

2. Click on pipelines on the left tab to view all the pipelines

3. Inside pipelines you can view actions performed within each block of the pipeline

Project Report

You can peruse the complete project report here

Contributing

Efforts to better this project are most welcome, please follow these steps:

1. Fork this repository and clone it to your local machine.
2. Create a new branch for your feature or bug fix

git checkout -b your-branch-name

3. Make your changes and commit them with descriptive commit messages.
4. Push your changes to your forked repository:

git push origin your-branch-name

5. Open a pull request in this repository, describing your changes in detail.

Contact

If you have any questions, suggestions or feedback, feel free to hit me up

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Thanks you! 😄