GS Quant is a Python toolkit for quantitative finance that provides access to Goldman Sachs' risk transfer platform and quantitative analytics capabilities.
The toolkit addresses the need for developers to build trading strategies and risk management solutions by offering a set of tools built on decades of experience in global markets. It enables users to work with derivative products through facilities for structuring, trading, and risk analysis, while also serving as a statistical package for data analytics applications. The platform requires institutional access credentials to connect to the underlying APIs.
Adoption is restricted to institutional clients of Goldman Sachs who can obtain the necessary credentials through their sales coverage. The toolkit suits organizations that need to develop quantitative trading strategies or perform derivative risk analysis and want to leverage Goldman Sachs' established market infrastructure and pricing models. It requires Python 3.9 or greater and access to the PIP package manager for installation.
The project maintains active engagement with users through a dedicated support email address and provides documentation, examples, guides, and tutorials through the Goldman Sachs Developer portal. Development is driven by quantitative developers at Goldman Sachs who use the toolkit internally for their own trading and risk management work.
