feat: multiple updates - alerts, auth, sectors, rotation service, financials ingestion, task specs, and agent framework

2026-06-06 22:01:40 -04:00
parent 7cbc5c120d
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+# Task: Complete rotation ranking service
+
+## Goal
+Implement the ranking logic for sector rotation in `services/rotation_service.py`. The service currently has skeleton methods for ranking but needs the actual implementation.
+
+## Requirements
+
+### Implement ranking methods in `services/rotation_service.py`
+
+1. `rank_sectors(sector_data, timeframe="20d")` method:
+   - Accept a list of sector data dicts (from the database)
+   - Sort sectors by momentum score (descending)
+   - Assign rank_now to each sector
+   - Calculate rank_change compared to previous ranking
+   - Return ranked sector list
+
+2. `get_ranking_history(ticker, days=30)` method:
+   - Query historical rankings from the database (TimescaleDB hypertable)
+   - Return time-series of rank data for charting
+   - Use `execute_query` with parameterized queries
+
+3. `calculate_relative_strength(ticker, benchmark="SPY")` method:
+   - Calculate price ratio between sector ETF and benchmark
+   - Compute relative strength as a percentage change
+   - Return strength metric
+
+### Database interactions
+- Read from `sector_rankings` hypertable (TimescaleDB)
+- Use parameterized queries
+- Handle missing data gracefully (return empty lists)
+
+## Acceptance Criteria
+1. `rank_sectors()` returns properly ranked sector list
+2. `get_ranking_history()` returns time-series data
+3. `calculate_relative_strength()` returns strength metric
+4. All methods are async
+5. File stays under 200 lines
+
+## Files to Modify
+- `src/backend/services/rotation_service.py`
+
+## Files to Read First
+- `src/backend/services/rotation_service.py` — current state
+- `src/backend/database.py` — query patterns
+- `src/backend/tests/test_sector_rotation.py` — test expectations