tensorquant 0.0.3

TensorFlow-Python financial library

TensorQuant

TensorQuant is a Python financial library designed to provide students with a practical, Python-based alternative to traditional C++ implementations. Leveraging Tensor arrays, TensorQuant supports pricing, intensive risk management computations, and algorithmic differentiation. It is particularly valuable in academic settings, such as the Quant-Finance Master courses at the University of Siena, where it offers students hands-on experience with financial libraries and object-oriented programming during their final year.

Many of the objects in TensorQuant draw inspiration from the renowned QuantLib library. We extend our gratitude to the QuantLib community for their foundational contributions to financial modeling. While many design patterns have been simplified for ease of understanding, TensorQuant strikes a balance between code complexity and professional architecture.

Table of Contents

• Features
• Installation
• Usage
• Contributing
• License
• Contact

Features

• Tensor Array Operations: Efficient handling and manipulation of tensor arrays for financial data.
• Risk Management: Tools for advanced risk assessment and management.
• Algorithmic Differentiation: Capabilities for automatic differentiation to aid in optimization and sensitivity analysis.
• Extensibility: Easy to extend and customize for various financial applications.
• Performance: Optimized for high-performance computations.

Installation

TBD To install TensorQuant, simply use pip:

pip install tensorquant

Or, if you prefer, clone the repository and install manually:

git clone https://github.com/andrea220/tQuant.git
cd tQuant
pip install .

Usage

TBD

Contributing

TBD

License

TensorQuant is licensed under the GPL-3.0 License. See the LICENSE file for more details.

Contact

For any questions or suggestions, feel free to reach out:

• Email: [e-mail]

Happy computing!