Metadata-Version: 2.4
Name: garpar
Version: 1.6.0
Summary: Generation and Analysis of Real and Artificial Portfolio Returns
Author-email: Diego N Gimenez Irusta <d.gimenez0101@unc.edu.ar>, Nadia A Luczywo <nadia.luczywo@unc.edu.ar>, Juan B Cabral <jbcabral@unc.edu.ar>
License: MIT License
        
        Copyright (c) 2021 Nadia Luczywo
        
        Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
        
Project-URL: Homepage, https://garpar.quatrope.org/
Project-URL: Repository, https://github.com/quatrope/garpar
Keywords: market simulation,informational efficiency,portfolio optimization
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Office/Business :: Financial
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: attrs>=25.0.4
Requires-Dist: h5py>=3.15.1
Requires-Dist: numpy>=2.2.6
Requires-Dist: pyportfolioopt>=1.5.6
Requires-Dist: scikit-learn>=1.7.2
Requires-Dist: seaborn>=0.13.2
Requires-Dist: pandas>=2.3.3
Dynamic: license-file

# Garpar

![logo](https://raw.githubusercontent.com/quatrope/garpar/refs/heads/master/res/logo_bw.png)

**Generación y análisis de retornos de portafolios artificiales y reales**

_Generation and analysis of artificial and real portfolio returns_

<!-- BODY -->

[![QuatroPe](https://img.shields.io/badge/QuatroPe-Applications-1c5896)](https://quatrope.github.io/)
[![Build](https://github.com/quatrope/garpar/actions/workflows/CI.yml/badge.svg)](https://github.com/quatrope/garpar/actions/workflows/CI.yml)
[![Documentation Status](https://readthedocs.org/projects/garpar/badge/?version=latest&style=flat)](https://garpar.readthedocs.io/en/latest/)
[![License](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)

**Garpar** is a comprehensive toolset for analyzing and managing financial portfolios and markets through advanced quantitative methods. It provides functionality for portfolio optimization, risk assessment, and performance analysis, integrated into the scientific Python stack. The library is open source and commercially usable.

## Key Features

- **Portfolio Construction & Rebalancing**: Build and maintain optimal portfolios with flexible rebalancing strategies
- **Risk Metrics Calculation**: Comprehensive risk assessment including variance, Value at Risk (VaR), and other standard metrics
- **Expected Returns Estimation**: Multiple methods for estimating future returns based on historical data
- **Correlation & Covariance Analysis**: Deep analysis of asset relationships and dependencies
- **Diversification Metrics**: Quantitative measures of portfolio diversification
- **Visualization Tools**: Rich set of plotting utilities for portfolio analysis
- **Market Data Handling**: Robust data validation and preprocessing capabilities
- **Entropy-Based Analysis**: Advanced information-theoretic approaches to portfolio analysis

## 💬 Help & Contact

**You can contact us at:**

- <diego.gimenez@unc.edu.ar>
- <jbcabral@unc.edu.ar>

## ☕ Support

This project is completely free of charge and open source. If you find it useful in your work or simply want to support us, you can buy us a coffee:

[!["Buy Me A Coffee"](https://www.buymeacoffee.com/assets/img/custom_images/orange_img.png)](https://www.buymeacoffee.com/leliel12)


## 📦 Code Repository & Issues

<https://github.com/quatrope/garpar>

## 📜 License

Garpar is under
[MIT License](https://raw.githubusercontent.com/quatrope/garpar/master/LICENSE.txt)

This license allows unlimited redistribution for any purpose as long as
its copyright notices and the license's disclaimers of warranty are
maintained.

## 📚 Citation

If you are using Garpar in your research, please cite:

If you use Garpar in a scientific publication, we would appreciate
citations to the following paper:

> Giménez, Diego N., Nadia Luczywo, Juan B. Cabral, and Mariana Funes. 2025.
> "Generación y diseño de herramientas para el análisis de retornos de carteras de inversión artificiales y reales."
> Revista de la Escuela de Perfeccionamiento en Investigación Operativa 33, no. 57 (2025).

Bibtex entry:

```bibtex
@article{gimenez2025generacion,
  title={Generaci{\'o}n y dise{\~n}o de herramientas para el an{\'a}lisis de retornos de carteras de inversi{\'o}n artificiales y reales},
  author={Gim{\'e}nez, Diego N and Luczywo, Nadia and Cabral, Juan B and Funes, Mariana},
  journal={Revista de la Escuela de Perfeccionamiento en Investigaci{\'o}n Operativa},
  volume={33},
  number={57},
  year={2025}
}
```

**Full Publication:** https://revistas.unc.edu.ar/index.php/epio/article/view/49002
