Built as cloud native, Ganymede is a fully managed platform, continuously updated with high-quality, curated, and cross validated data. Ganymede is purpose built for the financial data markets ever increasing data volumes, allowing clients to query against large data sets, including tick-by-tick, sampled, daily, corporate actions, ESG and reference data. Packed with a broad range of analytics, the solution is optimized for fast response times, supports full order book natively and allows fine grained/customizable trade and quote conditions mapping and filtering.
This repository contains Jupyter notebooks to request analytics and retrieve bespoke datasets by calling Ganymede gRPC API. Samples and building blocks are available to help you designing your bespoke analytics and data requests:
- Reference data
- Corporate actions
- Historical financial data and calculations: daily, intraday and tick data
- Best execution
- Future roll strategies and trading strategies
- Monitoring dashboards including data storage and normalization metrics
Example are organized in a per language per topic way:
There also are a few helpers to plug common development environments to Ganymede:
- Have a look here
- Ganymede portal (registered users logon page is here)
- Have a look at the documentation (API reference and tutorials)
Create an ssh key in jupyterhub :
ssh-keygen -t ed25519 -C "your_name@email_provider.com"
Get the public content of key:
cat /home/jovyan/.ssh/id_ed25519.pub
Add it to your gihub ssh keys idealy with the date so you can delete it later.
Configure the remote :
git branch --set-upstream-to=origin/prod prod
and configure the pull behaviour:
git config pull.rebase true
You can now push and pull as needed
Systemathics is a French fintech founded in 2008 developing its innovative products with the highest quality standards 100% in France. Our main mission is to provide global investors with a complete end-to-end solution to systematize alpha generation in a robust way. From data pre and post trade analysis, back-testing, risk assessment and signal generation to day-to-day execution in production and everything in between.