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github.com/goldmansachs/gs-quant @release-2.0.10 sqlite

repository ↗ · DeepWiki ↗ · release release-2.0.10 ↗
6,281 symbols 26,431 edges 389 files 1,730 documented · 28%
README

GS Quant

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.

It is created and maintained by quantitative developers (quants) at Goldman Sachs to enable the development of trading strategies and analysis of derivative products. GS Quant can be used to facilitate derivative structuring, trading, and risk management, or as a set of statistical packages for data analytics applications.

In order to access the APIs you will need a client id and secret. These are available to institutional clients of Goldman Sachs. Please speak to your sales coverage or Marquee Sales for further information.

Please refer to Goldman Sachs Developer for additional information.

Requirements

  • Python 3.9 or greater
  • Access to PIP package manager

Installation

pip install gs-quant

Examples

You can find examples, guides and tutorials in the respective folders on Goldman Sachs Developer.

Help

Please reach out to gs-quant@gs.com with any questions, comments or feedback.

Core symbols most depended-on inside this repo

date
called by 2259
gs_quant/markets/markets.py
append
called by 465
gs_quant/markets/portfolio.py
get
called by 405
gs_quant/api/api_cache.py
get
called by 256
gs_quant/markets/index.py
get
called by 189
gs_quant/tracing/tracing.py
apply
called by 153
gs_quant/risk/transform.py
extend
called by 138
gs_quant/markets/portfolio.py
date_range
called by 137
gs_quant/markets/historical.py

Shape

Method 2,928
Function 2,496
Class 790
Route 67

Languages

Python97%
TypeScript3%

Modules by API surface

gs_quant/test/timeseries/test_measures.py197 symbols
gs_quant/timeseries/measures.py160 symbols
gs_quant/markets/optimizer.py152 symbols
gs_quant/markets/securities.py151 symbols
docs/_build/html/_static/jquery-3.5.1.js112 symbols
gs_quant/markets/report.py109 symbols
gs_quant/tracing/tracing.py107 symbols
gs_quant/models/risk_model.py107 symbols
gs_quant/entities/entity.py97 symbols
gs_quant/risk/results.py84 symbols
docs/_build/html/_static/jquery.js83 symbols
gs_quant/timeseries/measures_rates.py82 symbols

Dependencies from manifests, versioned

aenum
cachetools
certifi
dataclasses_json
deprecation
httpx0.28.1 · 1×
inflection
lmfit
more_itertools
nest-asyncio

For agents

$ claude mcp add gs-quant \
  -- python -m otcore.mcp_server <graph>

⬇ download graph artifact