Goal
Research how ARGUS should generate analytics reports from market data, metrics and charts.
Why
ARGUS should not only display analytics in a dashboard, but also create reusable reports that summarize data, metrics and insights.
Before implementing reporting, the project should compare practical reporting options and decide what fits the current architecture.
Research questions
- What should an ARGUS report contain?
- selected currency pair or asset
- date range
- data source
- cumulative return
- strongest / weakest movement
- rolling volatility
- charts
- short interpretation notes
- Which report formats are useful?
- Markdown
- HTML
- PDF
- CSV/Excel export
- Power BI connection later
- Which tools or frameworks fit best?
- Markdown templates
- Jinja2
- pandas export
- Plotly/NiceGUI export options
- Power BI / external BI later
- Should reports be generated from live data, stored data or both?
- How could reports later connect to AI-assisted summaries?
Acceptance criteria
Goal
Research how ARGUS should generate analytics reports from market data, metrics and charts.
Why
ARGUS should not only display analytics in a dashboard, but also create reusable reports that summarize data, metrics and insights.
Before implementing reporting, the project should compare practical reporting options and decide what fits the current architecture.
Research questions
Acceptance criteria
Note
Priority: Should