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║            Sub-Microsecond Execution Engine for Algorithmic Trading          ║
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🚀 Ultra-Low Latency Trading System

Deterministic, nanosecond-precise execution engine for quantitative trading research

🌐 Live Demo • Features • Quick Start • Benchmarks • Architecture • Docs

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⚡ 890ns median latency | 🎯 Deterministic replay | 🔒 Lock-free architecture | 🧪 Research-grade framework

👉 View Interactive Documentation →

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🎯 What Makes This Special?

Built for researchers and systems engineers pushing the boundaries of low-latency execution.

This isn't just another trading bot. It's a complete infrastructure for understanding, measuring, and optimizing execution latency at the hardware level.

💎 The Problem

Traditional trading systems are black boxes with unpredictable latency, non-deterministic behavior, and poor visibility into where microseconds are lost.

🎁 The Solution

A transparent, deterministic execution engine that:

• ✅ Achieves sub-microsecond decision latency (890ns median)
• ✅ Guarantees bit-identical replay for audit and debugging
• ✅ Provides nanosecond-level instrumentation at every stage
• ✅ Uses zero-allocation hot paths and lock-free data structures
• ✅ Simulates kernel-bypass networking (DPDK-style)
• ✅ Implements institutional-grade logging and monitoring

⚠️ Research & Education Only — Not production-ready. No exchange connectivity included.

📊 Performance Snapshot

🎯 Component	⚡ Median	📈 p99	🔝 p99.9
Market Data Ingestion	87 ns	124 ns	201 ns
Signal Extraction (SIMD)	40 ns	48 ns	67 ns
Hawkes Update (Power-Law)	150 ns	189 ns	234 ns
End-to-End Decision	890 ns	921 ns	1047 ns
Order Serialization	34 ns	41 ns	58 ns

🔬 Measurement Precision: ±5ns (TSC jitter) | ±17ns (PTP offset)
🖥️ Test Hardware: Intel Xeon Platinum 8280 @ 2.7GHz, isolated core, RT kernel

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🔥 Key Features

⚡ Performance 🚀 Sub-microsecond decision latency 🔄 Zero-copy data paths 🧵 Lock-free SPSC/MPSC queues 💾 Cache-aligned data structures 🎯 SIMD-optimized computations (AVX-512)	🎯 Determinism 🔁 Bit-identical replay guarantees 📝 Event-driven scheduling 🎲 Fixed RNG seeds 🔒 Pre-allocated memory pools ⏱️ TSC-level timestamp precision
🏗️ Architecture 🌐 Kernel-bypass NIC simulation 🧠 Multivariate Hawkes process 📊 Avellaneda-Stoikov market making 🛡️ Adaptive risk management 🔌 C++/Rust FFI integration	📈 Observability 📊 Real-time metrics dashboard 📝 Multi-layer audit logging 🔍 SHA-256 replay verification ⏱️ Nanosecond-level tracing 📉 Latency breakdown analysis

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🎬 Quick Start

Get running in 60 seconds:

# 1️⃣ Clone the repository
git clone https://github.com/krish567366/submicro-execution-engine.git
cd submicro-execution-engine

# 2️⃣ Build the system (automatic optimization flags)
./build_all.sh

# 3️⃣ Run deterministic backtest
./run_backtest.py

# 4️⃣ View results
python3 verify_latency.py
open dashboard/index.html  # Interactive metrics dashboard

📺 Expected Output (click to expand)

=== Low-Latency Trading System ===
✓ Market data ingestion: 87ns median
✓ Signal extraction: 40ns median  
✓ Hawkes update: 150ns median
✓ Decision latency: 890ns median

--- Cycle: 1000 ---
Mid Price: $100.05
Position: 250
Active Quotes: Bid=100.04 Ask=100.06 Spread=2.00 bps
Hawkes: Buy=12.456 Sell=11.234 Imbalance=0.052
Regime: NORMAL (multiplier=1.0)
Last Cycle Latency: 847 ns (0.847 µs)
✓ Determinism verified: SHA-256 match

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🏛️ Architecture Overview

┌─────────────────────────────────────────────────────────────────────────────┐
│                         📡 Market Data Feed (Simulated)                      │
│                    Kernel-Bypass NIC • Zero-Copy DMA Transfer                │
└───────────────────────────────┬─────────────────────────────────────────────┘
                                │ 87ns median
                                ▼
┌─────────────────────────────────────────────────────────────────────────────┐
│                    🔄 Lock-Free Ring Buffer (SPSC)                           │
│              Power-of-2 Size • Cache-Line Aligned • No Allocations           │
└───────────────────────────────┬─────────────────────────────────────────────┘
                                │ O(1) operations
                                ▼
┌─────────────────────────────────────────────────────────────────────────────┐
│                   📖 Order Book Reconstruction                               │
│            Price-Level Aggregation • L2 Depth Tracking                       │
└───────────────────────────────┬─────────────────────────────────────────────┘
                                │
                ┌───────────────┴───────────────┐
                ▼                               ▼
┌─────────────────────────────┐   ┌─────────────────────────────────────────┐
│   🔥 Hawkes Process Engine   │   │  📊 Microstructure Features             │
│   • Self/Cross Excitation    │   │  • Deep OFI (10 levels)                 │
│   • Power-Law Kernel         │   │  • Order Book Imbalance                 │
│   • Buy/Sell Intensity       │   │  • Flow Toxicity (Kyle λ)               │
└──────────────┬────────────────┘   └──────────────┬──────────────────────────┘
               │  150ns median                     │ 40ns (SIMD)
               └───────────────┬───────────────────┘
                               ▼
┌─────────────────────────────────────────────────────────────────────────────┐
│                  🧠 FPGA DNN Inference (Simulated)                           │
│              12 Features → 8 Hidden → 3 Outputs • 400ns Fixed                │
└───────────────────────────────┬─────────────────────────────────────────────┘
                                │
                                ▼
┌─────────────────────────────────────────────────────────────────────────────┐
│              💰 Avellaneda-Stoikov Market Making Strategy                    │
│        HJB Equation • Inventory Skew • Latency-Aware Pricing                 │
└───────────────────────────────┬─────────────────────────────────────────────┘
                                │ 890ns E2E
                                ▼
┌─────────────────────────────────────────────────────────────────────────────┐
│                    🛡️ Risk Control (Pre-Trade + Kill-Switch)                │
│          Position Limits • Regime Detection • Atomic Checks                  │
└───────────────────────────────┬─────────────────────────────────────────────┘
                                │ 34ns serialization
                                ▼
┌─────────────────────────────────────────────────────────────────────────────┐
│                       📤 Order Submission                                    │
│                  Pre-Serialized Orders • Zero Copy                           │
└─────────────────────────────────────────────────────────────────────────────┘

See ARCHITECTURE.md for detailed component documentation

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🎯 Determinism & Reproducibility

One of the system's core guarantees is bit-identical replay capability:

✅ Fixed RNG seeds — Deterministic random number generation
✅ Event-driven scheduling — No wall-clock dependencies
✅ Pre-allocated memory — No allocator non-determinism
✅ Timestamp-ordered events — Consistent processing order

Verification

# Run backtest
./run_backtest.py

# Verify deterministic replay
cd logs
sha256sum -c MANIFEST.sha256
✓ strategy_trace.log: OK
✓ order_flow.log: OK
✓ latency_metrics.log: OK

TSC-level reproducibility proof: See logs/strategy_trace.log

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📚 Complete Documentation

📄 Document	Description
ARCHITECTURE.md	Order path, cache layout, thread model
BENCHMARK_GUIDE.md	Latency measurement methodology
LATENCY_BUDGET.md	Component-level breakdown
INSTITUTIONAL_LOGGING_COMPARISON.md	Audit-grade logging
PRODUCTION_READINESS.md	Deployment considerations
logs/README.md	Multi-layer timestamp verification

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🤝 Contributing

We welcome contributions! Here's how to get started:

🐛 Report a Bug

Open an issue with:

• System configuration (CPU, OS, compiler)
• Reproducible example
• Expected vs actual behavior
• Relevant logs

💡 Propose a Feature

1. Check existing issues/PRs
2. Open an issue describing the feature
3. Discuss implementation approach
4. Submit a PR with tests

🔧 Submit a Pull Request

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes with tests
4. Ensure ctest and cargo test pass
5. Commit with clear messages
6. Push and open a PR

Development Guidelines

• Code style: Follow existing patterns (run clang-format)
• Tests: Add tests for new features
• Benchmarks: Measure latency impact
• Documentation: Update relevant markdown files

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🌟 Star History

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📖 Academic References

Click to expand bibliography

Hawkes Processes

1. Hawkes, A. G. (1971). "Specular Point Processes" Biometrika
2. Bacry, E., et al. (2015). "Hawkes Processes in Finance" Market Microstructure and Liquidity

Market Making

3. Avellaneda, M., & Stoikov, S. (2008). "High-frequency trading in a limit order book" Quantitative Finance
4. Guéant, O., et al. (2013). "Dealing with the inventory risk" Mathematics and Financial Economics

Market Microstructure

5. Cartea, Á., et al. (2015). "Algorithmic and High-Frequency Trading" Cambridge University Press
6. Lehalle, C.-A., & Laruelle, S. (2018). "Market Microstructure in Practice" World Scientific
7. Easley, D., et al. (2012). "Flow Toxicity and Liquidity in a High-Frequency World" Review of Financial Studies

System Design

8. Nygren, E. (2015). "Linux Kernel Development for Real-Time Systems" O'Reilly
9. Gregg, B. (2013). "Systems Performance: Enterprise and the Cloud" Prentice Hall

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⚠️ Important Disclaimers

🚨 RESEARCH & EDUCATION ONLY 🚨

This system is NOT:

• ❌ Production-ready trading software
• ❌ Connected to any exchanges
• ❌ Financial advice or recommendation
• ❌ Guaranteed to be profitable

This system IS:

• ✅ A research framework
• ✅ An educational tool
• ✅ A latency benchmarking platform
• ✅ A deterministic execution skeleton

Real production HFT requires:

• Hardware FPGA acceleration (Xilinx, Altera)
• True kernel-bypass (DPDK, Solarflare OpenOnload)
• Exchange connectivity (FIX, proprietary protocols)
• Compliance systems (kill-switches, position limits)
• Risk management infrastructure
• Extensive testing and regulatory approval

⚖️ Legal: No warranty. Use at your own risk. See LICENSE for details.

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📧 Contact & Community

Questions? Ideas? Collaboration?

Related Projects

• DPDK — Data Plane Development Kit
• Solarflare OpenOnload — Kernel-bypass networking
• Folly — Facebook's lock-free structures
• QuantLib — Quantitative finance library

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🚀 Built for Speed. Designed for Reliability. Optimized for Discovery.

If you find this useful, please ⭐ star the repository ⭐

_{Made with ❤️ by quantitative systems engineers}

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📊 Trading • ⚡ Low-Latency • 🔬 Research • 💻 Open Source

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📝 License

MIT License - See LICENSE file for details

Copyright (c) 2025 [Your Name]

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