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# PRP-41: High-Frequency Tick Data Generator
## Context & Motivation
**Integration Goal**: Generate realistic tick-level data for high-frequency trading simulations.
**User Requirement**: Create microsecond-resolution tick data with realistic market microstructure.
**Technical Challenge**: Efficiently generate millions of ticks while maintaining realistic patterns.
## Requirements
### Tick Generation
1. **Microsecond Timestamps**: High-resolution time stamps
2. **Bid-Ask Spreads**: Realistic spread dynamics
3. **Market Depth**: Level 2 order book simulation
4. **Trade Classification**: Buy/sell side identification
### Microstructure Features
1. **Quote Updates**: Separate bid/ask updates
2. **Trade Ticks**: Actual trades with size
3. **Order Flow**: Realistic order arrival rates
4. **Market Impact**: Price impact modeling
## Implementation Blueprint
### Phase 1: Tick Generator
1. Create `src/generators/tick_generator.rs`
2. Define enhanced `Tick` types
3. Implement high-frequency timestamps
4. Add bid-ask spread generation
### Phase 2: Microstructure
1. Implement order arrival process
2. Add market depth simulation
3. Create trade/quote classification
4. Add market impact model
### Phase 3: Performance
1. Optimize for millions of ticks
2. Add streaming generation
3. Implement memory-efficient storage
4. Create parallel generation
## Success Criteria
### Validation Gates
```bash
# Test tick generation
cargo test tick_generator
cargo test microstructure
# Performance benchmarks
cargo bench tick_generation
```
### Implementation Metrics
- [ ] Generate 1M ticks < 1 second
- [ ] Realistic bid-ask dynamics
- [ ] Proper timestamp ordering
- [ ] Memory usage < 100MB per million ticks
## Dependencies & References
**Research Sources**:
- Market microstructure literature
- HFT simulation papers
- Order book dynamics studies
**Performance Considerations**:
- Use Vec pre-allocation
- Consider memory pooling
- Implement streaming generation
- Use SIMD where applicable
**Existing Infrastructure**:
- Extend current Tick type
- Use existing RNG setup
- Leverage timestamp generation
## Implementation Tasks
### Phase 1: Basic Ticks (2-3 hours)
1. Enhance Tick structure
2. Add microsecond timestamps
3. Generate bid-ask spreads
4. Test generation speed
### Phase 2: Microstructure (3-4 hours)
1. Add order flow model
2. Implement depth simulation
3. Create impact model
4. Validate patterns
### Phase 3: Optimization (2-3 hours)
1. Profile performance
2. Optimize hot paths
3. Add streaming mode
4. Document usage
## Risk Mitigation
- Start with simple tick generation
- Profile before optimizing
- Validate against real tick data patterns
- Provide configuration for detail level
## Success Score
**7/10** - Performance-critical component requiring careful optimization and validation.