TensorQuant 0.0.1
Pacchetto di analisi e caricamento dati per tQuant
Requires Python: >=3.10


# tQuant

![tQuant Logo](https://img.shields.io/badge/tQuant-v0.1.0-blue.svg) ![Python](https://img.shields.io/badge/python-v3.7+-blue.svg) ![Build Status](https://img.shields.io/badge/build-passing-brightgreen.svg) ![License](https://img.shields.io/badge/license-MIT-green.svg)

**tQuant** is a Python financial library that leverages Tensor arrays for intensive risk management computations and algorithmic differentiation.

## Table of Contents

- [Introduction](#introduction)
- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)
- [Contributing](#contributing)
- [License](#license)
- [Contact](#contact)

## Introduction

`tQuant` is designed to provide financial analysts and data scientists with powerful tools for risk management and algorithmic differentiation using Tensor arrays. This library is built to handle the heavy lifting involved in complex financial computations, offering both speed and accuracy. Additionally, `tQuant` is used in academic settings, including courses at the University of Siena (UNISI), to provide students with hands-on experience in financial computation and risk management.

## 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 `tQuant`, simply use pip:

```bash
pip install tQuant
```

Or, if you prefer, clone the repository and install manually:

```bash
git clone https://github.com/yourusername/tQuant.git
cd tQuant
pip install .
``` -->

## Usage

Here you can find basic examples of how to use `tQuant`:

### General Objects
- [**`Time handles`**](https://github.com/andrea220/tQuant/blob/main/examples/time_handles.ipynb): how to use time handles.
- [**`Index`**](https://github.com/andrea220/tQuant/blob/main/examples/index.ipynb): how to create index objects.
- [**`Market data`**](https://github.com/andrea220/tQuant/blob/main/examples/market_data.ipynb): how to handle market data.

### Interest Rate and Credit:
- [**`Coupons`**](https://github.com/andrea220/tQuant/blob/main/examples/coupons.ipynb): how to handle fixed/floating coupons and legs.
- [**`Coupon pricer`**](https://github.com/andrea220/tQuant/blob/main/examples/coupons_pricer.ipynb): price and sensitivities of fixed/floating coupons and legs.
- [**`Forward rate agreement`**](https://github.com/andrea220/tQuant/blob/main/examples/fra.ipynb): price and sensitivities of Forward Rate Agreement.
- [**`Interest rate swaps`**](https://github.com/andrea220/tQuant/blob/main/examples/swap.ipynb): price and sensitivities of interest rate swaps.
- [**`Bootstrapping`**](https://github.com/andrea220/tQuant/blob/main/examples/bootstrapping.ipynb): bootstrapping example.
- [**`Credit default swaps`**](https://github.com/andrea220/tQuant/blob/main/examples/cds.ipynb): price and sensitivities of credit default swaps.
- [**`Hull and White model`**](https://github.com/andrea220/tQuant/blob/main/examples/hullwhite.ipynb): simulation of the Hull and White model.



<!-- For more detailed usage and examples, please refer to the [documentation](https://github.com/yourusername/tQuant/wiki). -->

## Contributing

<!-- We welcome contributions to `tQuant`! If you're interested in contributing, please read our [contributing guidelines](CONTRIBUTING.md) to get started. -->
TBD 

## License

`tQuant` is licensed under the GPL-3.0 License. See the [LICENSE](LICENSE) file for more details.

## Contact

For any questions or suggestions, feel free to reach out:

- **Email**: [carapelliandrea@gmail.com](mailto:carapelliandrea@gmail.com)
<!-- - **GitHub Issues**: [tQuant Issues](https://github.com/yourusername/tQuant/issues) -->

We hope `tQuant` proves to be a valuable tool in your financial analysis and risk management tasks. Happy computing!