# PRP-43: Tick Aggregation Engine
## Context & Motivation
**Integration Goal**: Convert high-frequency tick data into various aggregated formats (time bars, volume bars, dollar bars).
**User Requirement**: Flexible aggregation of tick data for different analysis timeframes and methods.
**Technical Challenge**: Efficiently aggregate millions of ticks while supporting multiple aggregation types.
## Requirements
### Aggregation Types
1. **Time Bars**: Fixed time intervals (1min, 5min, etc.)
2. **Volume Bars**: Fixed volume thresholds
3. **Dollar Bars**: Fixed value traded
4. **Tick Bars**: Fixed number of ticks
### Aggregation Features
1. **Streaming Aggregation**: Real-time bar formation
2. **OHLCV Calculation**: Accurate OHLC from ticks
3. **VWAP Tracking**: Volume-weighted average price
4. **Statistics**: Additional metrics per bar
## Implementation Blueprint
### Phase 1: Aggregation Framework
1. Create `src/aggregation/mod.rs`
2. Define `Aggregator` trait
3. Implement time-based aggregation
4. Add OHLC calculation logic
### Phase 2: Alternative Bars
1. Implement volume bars
2. Add dollar/value bars
3. Create tick count bars
4. Add information-driven bars
### Phase 3: Streaming Support
1. Add streaming aggregation
2. Implement partial bar updates
3. Create bar completion callbacks
4. Add backfill support
## Success Criteria
### Validation Gates
```bash
# Test aggregation
cargo test tick_aggregation
cargo test bar_formation
# Validate accuracy
cargo test aggregation_accuracy
```
### Implementation Metrics
- [ ] Process 1M ticks in < 500ms
- [ ] Support 10+ aggregation types
- [ ] Streaming latency < 1ms
- [ ] Accurate VWAP calculation
## Dependencies & References
**Prerequisites**:
- Complete PRP-41 (Tick Generator)
- Tick data structures in place
**Research Sources**:
- Advances in Financial Machine Learning (Lopez de Prado)
- Alternative bar construction methods
- Market microstructure aggregation
**Implementation Patterns**:
- Use iterator pattern for streaming
- Implement as composable transforms
- Support parallel aggregation
## Implementation Tasks
### Phase 1: Core Engine (2-3 hours)
1. Design aggregator trait
2. Implement time bars
3. Add OHLC logic
4. Test accuracy
### Phase 2: Alternative Bars (2-3 hours)
1. Add volume bars
2. Implement dollar bars
3. Create tick bars
4. Validate formations
### Phase 3: Streaming (2-3 hours)
1. Add streaming mode
2. Implement callbacks
3. Optimize performance
4. Document usage
## Risk Mitigation
- Validate against known aggregations
- Handle edge cases (gaps, halts)
- Ensure numerical precision
- Provide aggregation diagnostics
## Success Score
**8/10** - Well-defined requirements with clear implementation patterns from research.