TensorQuant is a Python financial library that uses TensorFlow as its computational engine. Leveraging tensor arrays, TensorQuant supports pricing, intensive risk management computations, and algorithmic differentiation. You can explore examples and use cases in the playground repository with Jupyter notebooks. For detailed API references and comprehensive documentation, visit the ReadTheDocs page.
It is particularly valuable in academic settings, such as the Finance Master courses at the University of Siena, where students gain hands-on experience with financial libraries and object-oriented programming. At the same time, TensorQuant is designed to support fast prototyping, replication of academic and industry results, and professional-grade applications.
TensorQuant aims to strike a balance between ease of understanding and professional architecture: it is easy to use and extend, while remaining reliable, fast, and robust for financial modeling and risk management.
- Tensor Array Operations: Efficient handling and manipulation of tensor arrays for financial data.
- Derivative Pricing: Pricing financial derivatives.
- Algorithmic Differentiation: Automatic differentiation for optimization and sensitivity analysis.
- Stochastic Models: Simulations and solver tools for financial modeling.
- Extensibility: Easy to extend and customize for a wide range of financial applications.
To install TensorQuant, use pip:
pip install tensorquantAlternatively, clone the repository and install manually:
git clone https://github.com/andrea220/tQuant.git
cd tQuant
pip install .To get started using TensorQuant, here are some resources:
- Visit the
Playgroundfor Jupyter notebooks containing examples and use cases.
- The
ReadTheDocspage provides API references and comprehensive documentation.
- Check out the open-source code on GitHub.
TensorQuant is licensed under the GPL-3.0 License. See the LICENSE file for more information.
For any questions or suggestions, feel free to reach out:
- Email: carapelliandrea@gmail.com
Happy computing!