PorQua is an advanced Python library for portfolio optimization and index replication, designed as part of the GeomScale project. It provides efficient tools for financial data analysis, portfolio management, and asset selection.
Clone the repository:
git clone https://github.com/GeomScale/PorQua.git
cd PorQuapython -m unittest test/tests_quadratic_program.py💡 Here are some notebooks showing potential use cases of the PorQua library.
| Feature | Example |
|---|---|
| Backtesting a portfolio strategy using historical data | 🔗 Backtesting |
| Evaluating different quadratic programming (QP) solvers | 🔗 Compare solver |
| Index Replication (Using LSTM model) | 🔗 Index replication |
| Time series forecasting using LSTM model | 🔗 LSTM for prediction |
| Time series forecasting using linear regression and XGBoost | 🔗 ML forecasting |
| Probit and Logit ordinal regression models | 🔗 Ordinal regression |
You may redistribute or modify the software under the GNU Lesser General Public License as published by Free Software Foundation, either version 3 of the License, or (at your option) any later version. It is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY.