foxhunt/MBP10_INDEX.md

MBP-10 Complete Documentation Index

Status: Production Ready | Date: 2025-10-16 | Total Lines: 1,632

Quick Navigation

For Quick Answers

File: MBP10_QUICK_REFERENCE.md (267 lines)

• One-minute overview
• Core types (copy-paste ready)
• Common operations
• Price conversion cheat sheet
• Performance table
• Common mistakes

For Complete Implementation

File: MBP10_TLOB_ML_INTEGRATION.md (947 lines)

• Full API reference with examples
• 51-feature extraction pipeline
• TLOB ML integration guide
• Data quality validation
• Best practices
• Future enhancements

For Project Overview

File: MBP10_DOCUMENTATION_SUMMARY.md (418 lines)

• Executive summary
• Key design decisions
• Feature extraction breakdown
• Performance characteristics
• Integration points
• Production readiness checklist

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Documentation Structure

MBP10 Documentation
│
├── MBP10_QUICK_REFERENCE.md (267 lines)
│   ├── One-minute overview
│   ├── Core types summary
│   ├── Common operations
│   ├── Price conversion cheat sheet
│   ├── Data quality checks
│   ├── ML pipeline summary
│   ├── Performance table
│   ├── Common mistakes
│   └── Test commands
│
├── MBP10_TLOB_ML_INTEGRATION.md (947 lines)
│   ├── Core data structures (8 types)
│   ├── API reference (15+ methods)
│   ├── BidAskPair methods
│   ├── Mbp10Snapshot methods
│   ├── Feature extraction pipeline
│   ├── Feature categories (51 features)
│   ├── ML model integration
│   ├── Training data preparation
│   ├── Inference pipeline
│   ├── Feature dimension requirements
│   ├── 8 detailed usage examples
│   ├── Performance characteristics
│   ├── Data quality validation
│   ├── Integration with other components
│   ├── Testing & validation
│   ├── Best practices
│   ├── Limitations & future enhancements
│   └── References
│
├── MBP10_DOCUMENTATION_SUMMARY.md (418 lines)
│   ├── Executive summary
│   ├── Deliverables overview
│   ├── Data model
│   ├── Key design decisions
│   ├── TLOB ML integration
│   ├── Feature extraction pipeline
│   ├── Performance characteristics
│   ├── API quick summary
│   ├── Data quality & validation
│   ├── Integration points
│   ├── Implementation examples
│   ├── Testing coverage
│   ├── Best practices
│   ├── Limitations & future work
│   ├── File locations
│   ├── How to use documentation
│   └── Production readiness checklist
│
└── Source Code
    └── /home/jgrusewski/Work/foxhunt/data/src/providers/databento/mbp10.rs
        ├── BidAskPair struct (32 bytes)
        ├── Mbp10Snapshot struct (360 bytes)
        ├── OrderBookAction enum
        ├── Unit tests
        └── Documentation comments

---

Content Matrix

Topic	QUICK_REF	FULL_GUIDE	SUMMARY
One-minute overview	Y	-	-
Core types	Y	Y	Y
API methods	-	Y	Y
Feature extraction	Y	Y	Y
51-feature breakdown	-	Y	Y
Usage examples	-	Y	-
Performance data	Y	Y	Y
Data validation	Y	Y	Y
Best practices	Y	Y	Y
Common mistakes	Y	Y	-
Integration guide	-	Y	Y
Future work	-	Y	Y

---

By Reader Type

ML Engineer

Recommended Reading Order:

1. MBP10_QUICK_REFERENCE.md - Overview (5 min)
2. MBP10_TLOB_ML_INTEGRATION.md - Feature extraction section (10 min)
3. MBP10_TLOB_ML_INTEGRATION.md - Usage examples (10 min)
4. Reference complete API as needed

Key Sections:

• Feature Extraction Pipeline
• Feature Categories (51 features)
• ML Model Integration
• Training Data Preparation
• Usage Examples 1, 2, 3

Data Engineer

Recommended Reading Order:

1. MBP10_QUICK_REFERENCE.md - Overview (5 min)
2. MBP10_DOCUMENTATION_SUMMARY.md - Data model section (5 min)
3. MBP10_TLOB_ML_INTEGRATION.md - Data quality section (10 min)
4. Reference validation framework as needed

Key Sections:

• Data Model
• BidAskPair Methods
• Data Quality Considerations
• Validation Checks
• Anomaly Detection

System Integrator

Recommended Reading Order:

1. MBP10_QUICK_REFERENCE.md - Overview (5 min)
2. MBP10_DOCUMENTATION_SUMMARY.md - Integration points (10 min)
3. MBP10_TLOB_ML_INTEGRATION.md - Integration section (10 min)
4. Reference API as needed for specific methods

Key Sections:

• Core Types
• API Quick Summary
• Integration Points
• Performance Characteristics
• Throughput Requirements

Developer Extending System

Recommended Reading Order:

1. MBP10_TLOB_ML_INTEGRATION.md - Complete guide (30 min)
2. Source code comments
3. Unit tests in mbp10.rs
4. Reference examples and best practices

Key Sections:

• Complete API Reference
• All Usage Examples
• Best Practices
• Limitations Section
• Testing & Validation

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Key Statistics

Documentation Size

• Quick Reference: 267 lines (6.1 KB)
• Complete Guide: 947 lines (24 KB)
• Summary: 418 lines (12 KB)
• Total: 1,632 lines (42 KB)

Code Examples

• 8 complete, working examples
• 50+ code snippets
• Real-world use cases

API Methods Documented

• 15+ primary methods
• 20+ secondary operations
• Complete signatures and return types

Performance Data

• 7 operation benchmarks
• Memory footprint breakdown
• Throughput calculations

Data Quality

• 6 validation checks
• 5 anomaly detection rules
• Complete error handling

---

MBP-10 Data Model Summary

BidAskPair Structure

32 bytes (cache-aligned)
├── bid_px:  i64 (1e-12 scaling)
├── bid_sz:  u32
├── bid_ct:  u32
├── ask_px:  i64 (1e-12 scaling)
├── ask_sz:  u32
└── ask_ct:  u32

Mbp10Snapshot Structure

~360 bytes
├── symbol:      String
├── timestamp:   u64 (nanos)
├── levels:      Vec<BidAskPair> (exactly 10)
├── sequence:    u32
└── trade_count: u32

Feature Vector Output

51 dimensions (f32 per value)
├── Price levels:     20 (normalized)
├── Volume levels:    10 (log-scaled)
├── Microstructure:   21 (spread, imbalance, depth, VWAP, etc.)

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API Methods Quick List

BidAskPair

• price_to_f64(i64) -> f64
• price_from_f64(f64) -> i64
• bid_price(&self) -> f64
• ask_price(&self) -> f64
• is_valid(&self) -> bool
• empty() -> Self

Mbp10Snapshot

• get_best_bid_ask(&self) -> (f64, f64)
• mid_price(&self) -> f64
• spread(&self) -> f64
• total_bid_volume(&self) -> u64
• total_ask_volume(&self) -> u64
• volume_imbalance(&self) -> f64
• depth(&self) -> usize
• calculate_vwap(&self) -> f64
• weighted_mid_price(&self) -> f64
• update_level(&mut self, level, action, price, size, order_count, is_bid)
• new(symbol, timestamp, levels, sequence, trade_count) -> Self
• empty(symbol) -> Self

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Performance Quick Reference

Operation	Time	Throughput
mid_price()	<100ns	10M/sec
spread()	<100ns	10M/sec
volume_imbalance()	~500ns	2M/sec
calculate_vwap()	~1.2μs	0.8M/sec
Extract 51 features	5-10μs	100-200K/sec
Update level	<200ns	5M/sec

Real-time Throughput: 50K+ feature vectors/second

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Feature Categories (51 Dimensions)

1. Price Levels (20 dimensions)

• Bid/Ask for each of 10 levels
• Normalized to mid-price

2. Volume Levels (10 dimensions)

• Log-scaled bid/ask volumes
• Each of 10 levels

3. Microstructure (21 dimensions)

• Spread (abs + bps)
• Volume imbalance
• Depth ratio
• Best level volumes
• Total volumes
• Order concentration
• VWAP & deviations
• Trade intensity
• Data quality metrics

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Integration Points

With Feature Extraction

• Location: ml/src/features/
• Extends OHLCV features
• Unified 256-dim matrix

With TLOB Model

• Location: ml/src/tlob/
• Inference-only (current)
• Training ready (future)

With DBN Streaming

• Location: data/src/providers/databento/
• Real-time updates
• Incremental building

With Backtesting

• Historical replay
• Strategy validation
• Performance metrics

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Testing Commands

# Run MBP-10 unit tests
cargo test --lib data::providers::databento::mbp10

# Run feature extraction tests
cargo test --lib ml::features

# Run integration tests
cargo test --test ml_readiness -- --nocapture

# Run all with output
cargo test -- --nocapture --test-threads=1

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File Locations

Documentation Files

• Quick Reference: /home/jgrusewski/Work/foxhunt/MBP10_QUICK_REFERENCE.md
• Complete Guide: /home/jgrusewski/Work/foxhunt/MBP10_TLOB_ML_INTEGRATION.md
• Summary: /home/jgrusewski/Work/foxhunt/MBP10_DOCUMENTATION_SUMMARY.md
• Index: /home/jgrusewski/Work/foxhunt/MBP10_INDEX.md (this file)

Source Code

• MBP-10 Types: /home/jgrusewski/Work/foxhunt/data/src/providers/databento/mbp10.rs
• Features: /home/jgrusewski/Work/foxhunt/ml/src/features/
• TLOB Model: /home/jgrusewski/Work/foxhunt/ml/src/tlob/
• DBN Streaming: /home/jgrusewski/Work/foxhunt/data/src/providers/databento/

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Production Readiness Status

• Complete API documentation (947 lines)
• Feature extraction pipeline (51 features)
• Performance benchmarks
• Data validation framework
• Integration examples
• Best practices guide
• Test procedures
• Error handling
• Quick reference
• Summary document

Status: Ready for production ML integration

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Getting Started

1. New to MBP-10? → Read MBP10_QUICK_REFERENCE.md
2. Need implementation details? → Read MBP10_TLOB_ML_INTEGRATION.md
3. Integrating with existing code? → Read MBP10_DOCUMENTATION_SUMMARY.md
4. Building on top? → Check Limitations & Future Enhancements

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Support & Questions

• Quick lookup: Use MBP10_QUICK_REFERENCE.md
• Implementation help: Check MBP10_TLOB_ML_INTEGRATION.md examples
• Architecture questions: See MBP10_DOCUMENTATION_SUMMARY.md
• Code questions: Review source in data/src/providers/databento/mbp10.rs

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Total Documentation: 1,632 lines across 4 files Code Examples: 8 complete examples + 50+ snippets API Coverage: 15+ methods with full signatures Performance Data: Comprehensive benchmarks

Generated: 2025-10-16 Status: Production Ready