A collection of tools, scripts, and resources for quantitative finance, covering financial modeling, trading strategies, and data analysis.

• Introduction
• Installation
• Usage
• License

Quantitative finance leverages mathematical models, statistical techniques, and computational tools to analyze financial markets and develop trading strategies. This repository provides a structured collection of scripts and resources to support research, modeling, and algorithmic trading. The backbone of this project is quant accessor that is built on top of pandas.DataFrame to add functionalities relevant to financial data analysis. The backtest module helps with performance backtesting and risk decomposition. The Portfolio class is a customizable framework to create portfolios that account for rebalancing.

To set up the project, follow these steps:

1. Clone the repository:

   git clone https://github.com/nakulrandad/Quant-Finance.git
   cd Quant-Finance

2. Create and activate a virtual environment:

   uv venv
   source .venv/bin/activate

3. Install the package:

   • Standard Installation:

     uv pip install .

   • For Development (Editable Mode):

     uv pip install -e .[dev]

The analysis folder contains some sample analysis to showcase some of the functionalities of quant package. This package is actively under development and any feedback and/or contribution would be highly appreciated.

This repository is licensed under the MIT License. See the LICENSE file for details.