gs-quant: A Python Toolkit for Quantitative Finance

Introduction

gs-quant is a robust Python toolkit for quantitative finance, developed by Goldman Sachs. It is built upon one of the world's most powerful risk transfer platforms, designed to significantly accelerate the development of quantitative trading strategies and risk management solutions. With over 25 years of experience navigating global markets, gs-quant empowers developers to facilitate derivative structuring, trading, and risk management, as well as serve as a comprehensive set of statistical packages for data analytics applications.

To access the APIs, institutional clients of Goldman Sachs will need a client ID and secret. Further information is available on the Goldman Sachs Developer portal.

Installation

To get started with gs-quant, ensure you meet the following requirements:

• Python 3.9 or greater
• Access to PIP package manager

Once the requirements are met, you can install gs-quant using pip:

pip install gs-quant

Examples

A wealth of examples, guides, and tutorials are available to help you explore and utilize gs-quant's capabilities. You can find these resources in the respective folders on the Goldman Sachs Developer website.

Why use gs-quant?

gs-quant offers a unique advantage for professionals in quantitative finance. It provides a sophisticated framework crafted by experts at Goldman Sachs, enabling rapid prototyping and deployment of complex financial models. Its integration with a powerful risk transfer platform ensures high performance and reliability for critical financial operations. Whether you are developing advanced trading strategies, managing derivatives, or performing in-depth data analytics, gs-quant provides the tools and infrastructure to elevate your work.

Links

• GitHub Repository: goldmansachs/gs-quant
• Goldman Sachs Developer Documentation: developer.gs.com/docs/gsquant/
• Support Email: gs-quant@gs.com