987e5e6ac2
Removed across 66 files:
- 49 instances of "// use crate::safe_operations; // DISABLED"
- 11 instances of "// use error_handling::{...}; // crate doesn't exist"
- 2 instances of "// use crate::Optimizer; // not available"
- 5 disabled test placeholder blocks (/* ... */) in ensemble/
- 1 disabled From impl in lib.rs (38 lines)
- 1 disabled test module in model.rs (113 lines)
- 1 disabled code block in integration/distillation.rs (41 lines)
- Various other disabled imports with explanation comments
All of this code references modules/crates that were removed during
prior refactoring waves and is preserved in git history. Removing it
reduces noise and makes the codebase easier to navigate.
1922 lib tests passing, compilation clean.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
114 lines
4.3 KiB
Rust
114 lines
4.3 KiB
Rust
//! # Advanced Microstructure ML Module
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//!
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//! Comprehensive machine learning enhanced market microstructure analysis for
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//! high-frequency trading alpha generation. All components target <25μs latency
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//! with advanced ML models for superior prediction accuracy.
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//!
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//! ## Core ML Models (7 Advanced Models)
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//!
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//! - **Order Flow Imbalance Predictor**: LSTM-Transformer hybrid for OFI prediction
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//! - **Liquidity Provision Optimizer**: Multi-output neural network for optimal liquidity provision
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//! - **Spread Predictor**: Time series transformer for bid-ask spread forecasting
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//! - **Market Impact Estimator**: Temporal CNN for price impact estimation
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//! - **Adverse Selection Detector**: Deep learning model for toxicity detection
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//! - **Price Discovery Model**: Information flow analysis and efficiency measurement
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//! - **Hidden Liquidity Detector**: Pattern recognition for dark pools and icebergs
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//!
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//! ## Integration Components
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//!
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//! - **ML Ensemble**: Unified ensemble combining all 7 models for robust predictions
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//! - **Training Pipeline**: Comprehensive training system with unified data providers
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//! - **Portfolio Integration**: Seamless integration with Portfolio Transformer
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//! - **Performance Optimization**: Sub-25μs inference with real-time deployment
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//!
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//! ## Classical Microstructure Analytics
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//!
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//! - **VPIN Calculator**: Volume-synchronized probability of informed trading
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//! - **Kyle's Lambda**: Price impact measurement and information asymmetry detection
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//! - **Amihud Illiquidity**: Liquidity measurement via price impact per volume
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//! - **Roll Spread Estimator**: Bid-ask spread estimation from price autocovariance
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//! - **Hasbrouck Information Share**: Price discovery attribution analysis
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//!
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//! ## Performance Targets
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//!
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//! - ML Inference latency: <25μs for ensemble predictions
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//! - Classical calculation latency: <25μs for all metrics
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//! - Throughput: 100K+ calculations/second
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//! - Memory efficiency: Zero-allocation hot paths
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//! - Integer arithmetic: 10,000x scaling for financial precision
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// VPIN Implementation Module
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pub mod vpin_implementation;
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// Re-export VPIN types for public API
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// DO NOT RE-EXPORT - Use explicit imports at usage sites
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#[cfg(test)]
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mod tests {
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use crate::microstructure::vpin_implementation::{RingBuffer, TradeDirection};
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#[test]
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fn test_trade_direction_classification() {
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// Test Lee-Ready algorithm
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let direction = TradeDirection::classify_lee_ready(
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105000, // trade price (10.50)
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104000, // bid (10.40)
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106000, // ask (10.60)
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104500, // prev price (10.45)
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);
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assert_eq!(direction, TradeDirection::Buy);
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// Test tick rule
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let direction = TradeDirection::classify_tick_rule(105000, 104000);
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assert_eq!(direction, TradeDirection::Buy);
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}
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// TODO: Fix test_volume_bucket - requires MarketDataUpdate struct definition
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/*
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#[test]
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fn test_volume_bucket() {
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let mut bucket = VolumeBucket::new(0, 1000, 1000000);
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// Test implementation needed after MarketDataUpdate is defined
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}
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*/
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#[test]
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fn test_ring_buffer() {
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let mut buffer = RingBuffer::new(3);
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buffer.push(1);
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buffer.push(2);
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buffer.push(3);
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assert_eq!(buffer.len(), 3);
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assert_eq!(buffer.get(0), Some(&1));
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assert_eq!(buffer.get(1), Some(&2));
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assert_eq!(buffer.get(2), Some(&3));
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buffer.push(4);
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assert_eq!(buffer.len(), 3);
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assert_eq!(buffer.get(0), Some(&2));
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assert_eq!(buffer.get(1), Some(&3));
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assert_eq!(buffer.get(2), Some(&4));
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}
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// TODO: Re-enable when utils module is implemented
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// #[test]
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// fn test_utils_functions() {
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// let prices = vec![100000, 101000, 99000, 102000];
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// let returns = utils::calculate_returns(&prices);
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// assert_eq!(returns.len(), 3);
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//
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// let values = vec![1000, 2000, 3000, 4000, 5000];
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// let ma = utils::moving_average(&values, 3);
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// assert_eq!(ma.len(), 3);
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// assert_eq!(ma[0], 2000); // (1000 + 2000 + 3000) / 3
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//
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// let cov = utils::autocovariance(&values, 1);
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// assert!(cov > 0); // Should be positive for trending series
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//
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// let sqrt_val = utils::fast_sqrt(10000);
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// assert_eq!(sqrt_val, 100);
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// }
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} // end tests module
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