{"repo":"aakashagarwal778/qdlib","free":true,"listed":false,"github":"https://github.com/aakashagarwal778/qdlib","clone":"git clone https://github.com/aakashagarwal778/qdlib.git","description":"Quantitative Derivatives Models","language":"Jupyter Notebook","stars":15,"topics":["derivatives-pricing","quantitative-finance"],"license":"MIT","category":"trading","readme_excerpt":"qdlib --- Installation Since this is currently on TestPyPI, install it using: A structured Python library for foundational and intermediate quantitative derivatives models, numerical pricing methods, volatility models, calibration workflows, and explanatory notebooks. What this project is qdlib is designed as a clean, educational, and reusable quant library. The goal is not just to store scripts, but to organize core derivatives models in a way that is: - mathematically sound - easy to navigate - reusable as a Python package - supported by examples, tests, and notebooks This repository focuses on core pricing models and numerical methods rather than exotic contract design. Exotic options are intended to live in a separate dedicated project. --- Scope The library currently covers the following areas: - pricing foundations - lattice methods - Monte Carlo methods - PDE and ODE methods - stochastic volatility - jump models - local volatility - SABR - calibration workflows - transform methods - empirical preprocessing The emphasis throughout is on clarity, correctness, and structure. --- Repository structure --- License This project is licensed under the MIT License - see the LICENSE file for details.","default_branch":null,"files":null,"tree":[],"storefront":"/r/aakashagarwal778","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/aakashagarwal778/qdlib/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}