Research with context
Combine price history, technical signals, company news, and economic data from Alpaca, Finnhub, and FRED.
OPEN-SOURCE QUANTITATIVE TOOLKIT
From market insight
to measured action.
Research markets. Put strategies to the test. Supervise your next session — in one connected Python workspace.
Python 3.12+ · Alpaca integration · MIT licensed
01 / THE GAUSS PERSPECTIVE
03Asset classes
+Build your own strategy
04Session roles
Built for a deliberate process.
From evidence to execution.
01 / THE WORKSPACE
Your process.
A clearer view.
Move between research, account oversight, and execution with a shared set of strategies and a persistent session ledger.
Validate the idea
Explore historical performance and walk-forward tests. Inspect signals, risk constraints, and account suitability.
Stay close to execution
Review session health, plans, and exposure. Use authenticated controls with a recorded operator audit.
02 / THE SESSION CYCLE
Four roles.
One continuous process.
The persistent service schedules each responsibility around the exchange calendar. Select a role to follow the flow.
EVIDENCE → REVIEW
Learn from the completed session.
PostGauss reviews completed-session evidence and screens candidates for the next research cycle.
- Input
- Completed-session evidence
- Output
- Reviewed evidence and screened candidates
- Execution
- Research only
Shadow execution is the default. Paper and live execution require the applicable approvals and readiness checks. Read the operations guide ↗
03 / STRATEGY LIBRARY
Start with the basics.
Build your own.
Explore basic strategy examples for stocks, crypto, and options, then bring your own ideas to the shared research, backtesting, and execution framework.
Build your own strategy ↗
Included strategy examples · View source to explore
Options strategies use the CLI and gated session workflow. The interactive trading menu supports underlying options research. The multi-agent analyst committee is separate from the four session roles.
04 / GET STARTED
Your next session
starts here.
Install the toolkit, add your provider credentials, and choose a workflow. Start with the offline preview to explore without keys.
01 Set up the workspace
TERMINAL / PYTHON 3.12+
git clone https://github.com/Magica-Chen/GaussWorldTrader.git
cd GaussWorldTrader
python -m venv .venv
source .venv/bin/activate
python -m pip install -r requirements.txt
cp .env.example .envEdit your local .env for connected features. Run the session service on Linux, macOS, or WSL.
02 Choose a workflow
RUN FROM THE REPOSITORY ROOT
python -m streamlit run examples/dashboard_preview.pyExplore the real dashboard with synthetic session records. No API keys or broker connection.