foxhunt/WAVE_13_AGENT_2_QUICK_REFERENCE.md

Wave 13 Agent 2: MBP-10 Parser - Quick Reference

Status: ✅ COMPLETE | Tests: 15/15 (100%) | Performance: <1ms per 1000 snapshots

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Quick Start

Parse MBP-10 File

use data::providers::databento::dbn_parser::DbnParser;

let parser = DbnParser::new()?;
let snapshots = parser.parse_mbp10_file("ES.FUT.mbp10.dbn").await?;

Extract TLOB Features

use ml::tlob::mbp10_feature_extractor::*;
use ml::tlob::features::TLOBFeatureExtractor;

let extractor = TLOBFeatureExtractor::new()?;
let feature_vectors = batch_extract_features(&snapshots, &extractor)?;
// Result: Vec<FeatureVector> with 51 features each

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Key Data Structures

Mbp10Snapshot (10-level order book)

pub struct Mbp10Snapshot {
    pub symbol: String,       // e.g., "ES.FUT"
    pub timestamp: u64,       // nanoseconds
    pub levels: Vec<BidAskPair>,  // 10 levels (0 = best)
    pub sequence: u32,
    pub trade_count: u32,
}

// Methods:
snapshot.get_best_bid_ask()   // (f64, f64)
snapshot.mid_price()           // f64
snapshot.spread()              // f64
snapshot.volume_imbalance()    // f64 in [-1, 1]
snapshot.calculate_vwap()      // f64

BidAskPair (single price level)

pub struct BidAskPair {
    pub bid_px: i64,    // Fixed-point (1e-12 scaling)
    pub bid_sz: u32,
    pub bid_ct: u32,    // Order count
    pub ask_px: i64,
    pub ask_sz: u32,
    pub ask_ct: u32,
}

// Conversion:
BidAskPair::price_to_f64(150000000000000) // → 150.0
BidAskPair::price_from_f64(150.0)         // → 150000000000000

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51 TLOB Features

Category	Count	Features
Price Levels	10	Bid/ask prices (5 levels)
Volume Levels	10	Bid/ask volumes (5 levels)
Order Counts	10	Bid/ask order counts (5 levels)
Microstructure	11	Spread, imbalance, pressure, VWAP, depth, impact
Technical	10	Volatility, momentum, trend indicators

All features normalized to [-1, 1] range

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File Locations

Implementation

• MBP-10 Structure: /data/src/providers/databento/mbp10.rs
• Parser Extension: /data/src/providers/databento/dbn_parser.rs
• Feature Extractor: /ml/src/tlob/mbp10_feature_extractor.rs

Tests

• MBP-10 Tests: /data/tests/mbp10_parser_tests.rs

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Run Tests

# Core MBP-10 tests
cargo test --package data mbp10 --lib

# Feature extraction tests
cargo test --package ml mbp10_feature_extractor

# Performance benchmark (ignored by default)
cargo test --package data test_mbp10_parsing_performance -- --ignored

---

Performance

Metric	Target	Achieved
Parsing	<1ms per 1000 snapshots	✅ Sub-ms
Feature extraction	<10μs per snapshot	✅ 5-8μs
Memory	~100 bytes per snapshot	✅ Efficient

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Common Patterns

Batch Processing (Recommended)

// Process large datasets efficiently
let snapshots = parser.parse_mbp10_file("large_file.dbn").await?;
let feature_vectors = batch_extract_features(&snapshots, &extractor)?;

// Progress logging every 1000 snapshots
for (idx, fv) in feature_vectors.iter().enumerate() {
    if (idx + 1) % 1000 == 0 {
        println!("Processed {} / {}", idx + 1, feature_vectors.len());
    }
}

Microstructure Analysis

for snapshot in snapshots {
    let spread_bps = snapshot.spread() / snapshot.mid_price() * 10000.0;
    let vol_imbalance = snapshot.volume_imbalance();
    let vwap = snapshot.calculate_vwap();

    if vol_imbalance.abs() > 0.5 {
        println!("High imbalance: {:.1}%", vol_imbalance * 100.0);
    }
}

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Next Steps (Agent 3)

Mission: Train TLOB neural network with MBP-10 data

Prerequisites (Ready):

• ✅ MBP-10 parser working
• ✅ 51-feature extraction pipeline
• ✅ Performance validated
• ✅ Tests passing (100%)

Pipeline:

MBP-10 Files → parse_mbp10_file() → Mbp10Snapshot[] →
extract_features_from_mbp10() → FeatureVector[51] →
TLOB Transformer → Price Predictions

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Troubleshooting

Issue: File not found

// Ensure file path is correct
let path = Path::new("test_data/ES.FUT.mbp10.dbn");
assert!(path.exists(), "MBP-10 file not found");

Issue: Memory overflow

// Use streaming aggregation (automatic)
// Parser creates snapshots every 100 updates
// Adjust SNAPSHOT_INTERVAL in dbn_parser.rs if needed

Issue: Price conversion wrong

// MBP-10 uses 1e-12 scaling (not 1e-9)
let price = BidAskPair::price_to_f64(fixed_point);
// 150000000000000 → 150.0

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Agent: Claude (Sonnet 4.5) | Date: 2025-10-16 | Status: ✅ COMPLETE