# 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