stonks-oracle/dashboards/starter/README.md

Starter Dashboards

Superset dashboard definitions for Stonks Oracle research, analysis, and trading review.

Dashboards

• Symbol Overview — company profiles, source health, recent documents, and market snapshots
• Sentiment Heatmap — market-wide sentiment by sector and symbol, catalyst analysis, contradiction tracking
• Prediction Accuracy — predicted signals vs realized price moves, confidence calibration, per-symbol accuracy
• Paper Trading PnL — cumulative PnL, daily performance, position snapshots, order history, and scorecards

Data Sources

These dashboards query the Trino lakehouse catalog over MinIO-backed analytical fact tables:

• lakehouse.stonks.documents — ingested document metadata
• lakehouse.stonks.document_extractions — AI extraction outputs
• lakehouse.stonks.trade_signals — aggregated trend signals
• lakehouse.stonks.market_bars — OHLCV bar data
• lakehouse.stonks.prediction_vs_outcome — prediction accuracy tracking
• lakehouse.stonks.pnl_daily — daily PnL records
• lakehouse.stonks.positions_daily — end-of-day position snapshots
• lakehouse.stonks.trade_orders — order submission records
• lakehouse.stonks.trade_fills — fill and execution records

Setup

1. Import the dashboard JSON files into Superset via the Superset UI or CLI
2. Ensure the Trino datasource is configured: trino://trino@trino:8080/lakehouse/stonks
3. Create the lakehouse views from lakehouse/views/ for additional drill-down capability

Trino Connection

The dashboards use the default Superset Trino connection configured in infra/superset/superset_config.py.