Sigma Investing is a team that focuses on providing efficient investment solutions using modern decision-making techniques. This repository contains the source code for our investment report (for our client Hilary Ash).
- Python 3.8 or higher - The TOPSIS implementation is built using Python language. Please ensure to install the appropriate version: https://www.python.org/downloads/
- Pandas - A powerful data manipulation library in Python that makes it easy to work with structured data like CSV, Excel, and SQL databases:
pip install pandas - Numpy - A fundamental library for mathematical operations and support for arrays and matrices:
pip install numpy
Sigma_Investing_Sourcecodes/
├── TOPSIS/
│ ├── TOPSIS.py
│ └── TOPSIS_Results.html
├── ETF_Selection/
│ ├── ETF.csv
│ └── scoreCalculation.py
├── Industry Selection/
│ └── select.py
├── Sector Selection/
│ ├── Long_term.py
│ ├── Short_term.py
│ └── bi-directional.py
├── LICENSE/
└── README.md
-
Clone the repository to your local machine:
git clone https://github.com/LQ458/Sigma_Investing_Sourcecodes.git -
Navigate to the source code directory(projects): example:
cd Sigma_Investing_Sourcecodes/projects -
Make sure Python3 and the required middleware have been installed.
-
Execute the main Python script:
python project.py -
The output will be generated, showing the ranking of investment alternatives based on the TOPSIS method. Evaluate the results and make informed investment decisions accordingly.
For any queries or concerns related to the project, please contact the Sigma Investing team at: [email protected] or [email protected]
This project is licensed under the MIT License - see the LICENSE file for details.