GS Quant is a Python toolkit for quantitative finance, created on top of one of the world’s most powerful risk transfer platforms. Designed to accelerate development of quantitative trading strategies and risk management solutions, crafted over 25 years of experience navigating global markets.
Created by our quants, for our quants. Our analytics tools are trusted daily by over a thousand quantitative developers at Goldman Sachs to manage our global trading business.
Our business covers all asset classes. Our financial toolkit is designed from the ground up to be a complete solution for all markets, delivered through an intuitive interface.
Leverage models and datasets which have been tested and refined through decades of experience at the center of global derivatives markets. Use what we use.
Seamless access to a comprehensive range of intraday and end-of day datasets, natively in python. GS Quant provides a complete data platform and timeseries analytics package, designed around proven market models to make integration seamless.
from gs_quant.data import Dataset # Dataset for equity implied volatility vol_dataset = Dataset(Dataset.GS.EDRVOL_PERCENT_SHORT) # Get S&P 500 1m at-the-money-forward volatility vol_data = vol_dataset.get_data( ticker='SPX', tenor='1m', strikeReference='forward', relativeStrike=1 ) # Show last few values vol_data.tail()
GS Quant provides access to our proprietary derivatives pricing models and market dynamics. Compute prices and sensitivities through our risk engines, and apply complex shocks and scenarios. Fully documented instrument and risk coverage makes structuring and portfolio analytics painless.
from gs_quant.instrument import IRSwap, Currency, PayReceive from gs_quant.risk import IRDelta # Create 10y dollar swap swap = IRSwap(PayReceive.Pay, "10y", Currency.USD) # Use historical market with(PricingContext(market_data_as_of=date(2019,4,1))): # Compute derivative price price = swap.price() # Calculate rates delta delta = swap.calc(IRDelta)
Full connectivity to our streaming prices and quoting engines. Request dealable prices and execute trades to automate workflows and scale your business. Native python quote streams, seamless order submission, and trade execution through a simple interface.
from gs_quant.session import GsSession, Environment from gs_quant.markets.securities import AssetClass from gs_quant.api.gs.trades import GsTradesApi from datetime import date # Authenticate to our trading APIs GsSession.use(client_id, secret) # List recent trades trades = GsTradesApi.get_trades(AssetClass.FX, date(2019,1,1), date.today()) # Get unit price price = trades.unitPrice