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GS Quant — Goldman Sachs Quantitative Finance Toolkit

Goldman Sachs's open-source Python library for derivatives pricing, risk analytics, and systematic trading.

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GS Quant — Goldman Sachs Quantitative Finance Toolkit

gs-quant is Goldman Sachs's open-source Python toolkit for quantitative finance, supporting derivatives pricing, risk analytics, backtesting, and portfolio construction. Built on top of GS's internal quant infrastructure and open-sourced for the community under Apache-2.0.

Key features

  • Derivatives pricing: options, swaps, swaptions, FX, rates, equities
  • Risk analytics: delta, gamma, vega, theta; scenario analysis and stress tests
  • Data access via Marquee API (GS market data; API key required for live data)
  • Portfolio construction and optimization with risk constraints
  • Backtesting engine with transaction costs

Quick start

pip install gs-quant
from gs_quant.instrument import EqOption
from gs_quant.common import OptionType, OptionStyle
from gs_quant.session import GsSession

GsSession.use()  # uses env var GS_CLIENT_ID / GS_CLIENT_SECRET
option = EqOption(".SPX", expiration_date="3m", strike_price="ATMF",
                  option_type=OptionType.Call, option_style=OptionStyle.European)
option.resolve()
print(option.price())
npx ai-supply add gs-quant-goldman-sachs

Curated mirror of the open-source gs-quant (Apache-2.0). Get it from the source.

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