What is this?
GS Quant is a Python toolkit for quantitative finance built by Goldman Sachs quants on top of their risk transfer platform, used for derivative structuring, trading strategy development, and risk management.
GS Quant is a Python toolkit for quantitative finance built by Goldman Sachs quants on top of their risk transfer platform, used for derivative structuring, trading strategy development, and risk management.Is it a general-purpose finance library or tied to Goldman Sachs' own platform?It's a Python library/SDK that wraps Goldman Sachs' Marquee risk platform APIs, plus a set of standalone statistical packages for data analytics.
It's a Python library/SDK that wraps Goldman Sachs' Marquee risk platform APIs, plus a set of standalone statistical packages for data analytics.How do I install and start using it?Install it via PIP; full examples, guides and tutorials are hosted on the Goldman Sachs Developer site.
Install it via PIP; full examples, guides and tutorials are hosted on the Goldman Sachs Developer site.What do I need to actually use the risk/trading features?You need Python 3.9 or greater plus pip, and to use the derivatives/trading APIs you must have a client id and secret issued to institutional Goldman Sachs clients.
You need Python 3.9 or greater plus pip, and to use the derivatives/trading APIs you must have a client id and secret issued to institutional Goldman Sachs clients.Can anyone use the full API, or is it restricted?The statistical packages are open for anyone to use, but the core API access (trading, risk, derivative structuring) is gated behind Goldman Sachs institutional client credentials obtained through sales coverage.
The statistical packages are open for anyone to use, but the core API access (trading, risk, derivative structuring) is gated behind Goldman Sachs institutional client credentials obtained through sales coverage.Who is this aimed at?It's aimed at quants, traders, and risk managers, especially those with an institutional relationship with Goldman Sachs, since the API portion requires client credentials.
It's aimed at quants, traders, and risk managers, especially those with an institutional relationship with Goldman Sachs, since the API portion requires client credentials.What kind of problems can it solve without an API key?The statistical packages included in the toolkit can be used for general data analytics applications even without API access to Goldman Sachs' trading platform.
The statistical packages included in the toolkit can be used for general data analytics applications even without API access to Goldman Sachs' trading platform.Why would someone trust this over building their own risk tools?It's built on 25 years of Goldman Sachs' experience navigating global markets and the same risk transfer platform used internally by the bank's quants.
It's built on 25 years of Goldman Sachs' experience navigating global markets and the same risk transfer platform used internally by the bank's quants.What are similar projects?awesome-quant, OpenBB, StockSharp, backtrader, abu, akshare, bytex, qlib
awesome-quant, OpenBB, StockSharp, backtrader, abu, akshare, bytex, qlibWhich topics is it in?risk-management, trading-strategies, algorithmic-trading, quantitative-finance, fintech, trading, statistics, finance, data-science, sdk, rest-api, research
risk-management, trading-strategies, algorithmic-trading, quantitative-finance, fintech, trading, statistics, finance, data-science, sdk, rest-api, research