# 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](https://developer.gs.com/docs/gsquant/) for additional information.
## Requirements
* Python 3.8 or greater
* Access to PIP package manager
## Installation
```
pip install gs-quant
```
## Examples
You can find examples, guides and tutorials in the respective folders as well as on [Goldman Sachs Developer](https://developer.gs.com/docs/gsquant/).
## Contributions
Contributions are encouraged! Please see [CONTRIBUTING](CONTRIBUTING.md) for more details.
## Help
Please reach out to `gs-quant@gs.com` with any questions, comments or feedback.
Raw data
{
"_id": null,
"home_page": "https://marquee.gs.com",
"name": "gs-quant",
"maintainer": null,
"docs_url": null,
"requires_python": null,
"maintainer_email": null,
"keywords": null,
"author": "Goldman Sachs",
"author_email": "developer@gs.com",
"download_url": "https://files.pythonhosted.org/packages/d4/d3/a5873d37d0d31233cc91358ded7234016e494bce2c0dbc65a7d4304c0c42/gs_quant-1.2.12.tar.gz",
"platform": null,
"description": "# GS Quant\n\n**GS Quant** is a Python toolkit for quantitative finance, created on top of one of the world\u2019s 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.\n\nIt 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.\n\nIn 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. \n\nPlease refer to [Goldman Sachs Developer](https://developer.gs.com/docs/gsquant/) for additional information.\n\n## Requirements\n\n* Python 3.8 or greater\n* Access to PIP package manager\n\n## Installation\n\n```\npip install gs-quant\n```\n\n## Examples\n\nYou can find examples, guides and tutorials in the respective folders as well as on [Goldman Sachs Developer](https://developer.gs.com/docs/gsquant/).\n\n## Contributions\n\nContributions are encouraged! Please see [CONTRIBUTING](CONTRIBUTING.md) for more details.\n\n## Help\n\nPlease reach out to `gs-quant@gs.com` with any questions, comments or feedback.\n",
"bugtrack_url": null,
"license": "http://www.apache.org/licenses/LICENSE-2.0",
"summary": "Goldman Sachs Quant",
"version": "1.2.12",
"project_urls": {
"Homepage": "https://marquee.gs.com"
},
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "f9e5827b0ff5ce2ac7c4c2c2b0b1ae948fb9aeeb0aa35db85161e0340f01f42c",
"md5": "5e573fee63fec9537445f0dbe5e8cf67",
"sha256": "7ab69c039e8ec6968a31601af500fabdf78b8b013528376bcf00f9678048fd06"
},
"downloads": -1,
"filename": "gs_quant-1.2.12-py3-none-any.whl",
"has_sig": false,
"md5_digest": "5e573fee63fec9537445f0dbe5e8cf67",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 1211105,
"upload_time": "2024-12-17T15:49:46",
"upload_time_iso_8601": "2024-12-17T15:49:46.243197Z",
"url": "https://files.pythonhosted.org/packages/f9/e5/827b0ff5ce2ac7c4c2c2b0b1ae948fb9aeeb0aa35db85161e0340f01f42c/gs_quant-1.2.12-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "d4d3a5873d37d0d31233cc91358ded7234016e494bce2c0dbc65a7d4304c0c42",
"md5": "85e7d8df5fc81fea505b7e6f33a5aba5",
"sha256": "13c078b5786f7c84e917b8cfd0fe11f9d7d4781f4403c1e83d4fa0315410b81f"
},
"downloads": -1,
"filename": "gs_quant-1.2.12.tar.gz",
"has_sig": false,
"md5_digest": "85e7d8df5fc81fea505b7e6f33a5aba5",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 829602,
"upload_time": "2024-12-17T15:49:48",
"upload_time_iso_8601": "2024-12-17T15:49:48.580591Z",
"url": "https://files.pythonhosted.org/packages/d4/d3/a5873d37d0d31233cc91358ded7234016e494bce2c0dbc65a7d4304c0c42/gs_quant-1.2.12.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-12-17 15:49:48",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "gs-quant"
}
JSON