goldmansachs / Gs Quant
Licence: apache-2.0
Python toolkit for quantitative finance
Stars: ✭ 556
Projects that are alternatives of or similar to Gs Quant
Fastquant
fastquant — Backtest and optimize your trading strategies with only 3 lines of code!
Stars: ✭ 457 (-17.81%)
Mutual labels: jupyter-notebook, trading-strategies
Machine Learning Asset Management
Machine Learning in Asset Management (by @firmai)
Stars: ✭ 1,060 (+90.65%)
Mutual labels: jupyter-notebook, trading-strategies
Sgx Full Orderbook Tick Data Trading Strategy
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
Stars: ✭ 733 (+31.83%)
Mutual labels: jupyter-notebook, trading-strategies
Zerodha live automate trading using ai ml on indian stock market Using Basic Python
Online trading using Artificial Intelligence Machine leaning with basic python on Indian Stock Market, trading using live bots indicator screener and back tester using rest API and websocket 😊
Stars: ✭ 131 (-76.44%)
Mutual labels: jupyter-notebook, trading-strategies
Machine Learning For Trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
Stars: ✭ 4,979 (+795.5%)
Mutual labels: jupyter-notebook, trading-strategies
Alphatrading
An workflow in factor-based equity trading, including factor analysis and factor modeling. For well-established factor models, I implement APT model, BARRA's risk model and dynamic multi-factor model in this project.
Stars: ✭ 144 (-74.1%)
Mutual labels: jupyter-notebook, trading-strategies
Bitmex Simple Trading Robot
Simple BitMEX trading robot.
Stars: ✭ 100 (-82.01%)
Mutual labels: jupyter-notebook, trading-strategies
Quantitative Notebooks
Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
Stars: ✭ 356 (-35.97%)
Mutual labels: jupyter-notebook, trading-strategies
Stock analysis for quant
Different Types of Stock Analysis in Python, R, Matlab, Excel, Power BI
Stars: ✭ 525 (-5.58%)
Mutual labels: jupyter-notebook, trading-strategies
Curve Text Detector
This repository provides train＆test code, dataset, det.&rec. annotation, evaluation script, annotation tool, and ranking.
Stars: ✭ 551 (-0.9%)
Mutual labels: jupyter-notebook
Handson Ml
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
Stars: ✭ 23,798 (+4180.22%)
Mutual labels: jupyter-notebook
Competitive Data Science
Materials for "How to Win a Data Science Competition: Learn from Top Kagglers" course
Stars: ✭ 551 (-0.9%)
Mutual labels: jupyter-notebook
Probabilistic Programming And Bayesian Methods For Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Stars: ✭ 23,912 (+4200.72%)
Mutual labels: jupyter-notebook
Torch Residual Networks
This is a Torch implementation of ["Deep Residual Learning for Image Recognition",Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun](http://arxiv.org/abs/1512.03385) the winners of the 2015 ILSVRC and COCO challenges.
Stars: ✭ 553 (-0.54%)
Mutual labels: jupyter-notebook
Machine Learning Notes
My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接
Stars: ✭ 5,390 (+869.42%)
Mutual labels: jupyter-notebook
Flowtron
Flowtron is an auto-regressive flow-based generative network for text to speech synthesis with control over speech variation and style transfer
Stars: ✭ 546 (-1.8%)
Mutual labels: jupyter-notebook
Tf Dann
Domain-Adversarial Neural Network in Tensorflow
Stars: ✭ 556 (+0%)
Mutual labels: jupyter-notebook
Ada Build
The Ada Developers Academy Jump Start program, which is intended for anyone who is interested in beginning their journey into coding.
Stars: ✭ 551 (-0.9%)
Mutual labels: jupyter-notebook
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.
Please refer to Goldman Sachs Developer for additional information.
Requirements
- Python 3.6 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.
Contributions
Contributions are encouraged! Please see CONTRIBUTING.MD for more details.
Help
Please reach out to [email protected] with any questions, comments or feedback.
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].