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C23
Independent Researcher — Market Microstructure
certurk23
Quantitative Infrastructure Engineer · HFT Research · Market Microstructure Analysis
NASDAQ / NYSE Arca C++ / Systems Programming VPIN · OBI · Hurst Equinix NY4/NY5 Kernel Bypass
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Overview
Research
Infrastructure

Lab Overview

The certurk23 Quant Lab is an independent quantitative research environment focused on the intersection of market microstructure theory and high-frequency infrastructure engineering. The lab operates at the boundary between academic research and production HFT systems, with a focus on reproducible, empirically grounded analysis of US equity market dynamics.

Research covers the full stack — from nanosecond-level NIC kernel bypass and NUMA-aware memory allocation, up to statistical microstructure models such as VPIN, Order Book Imbalance (OBI), and Hurst Exponent estimation on live order flow data from NASDAQ and NYSE Arca matching engines.

All production systems operate within Equinix NY4/NY5 co-location facilities, with direct cross-connects to NASDAQ Carteret and NYSE Mahwah. The end-to-end latency budget of sub-800 ns wire-to-order is maintained under continuous benchmarking with hardware timestamps.

Research Areas

📊
Order Flow Toxicity
Development and backtesting of VPIN-based toxicity metrics on real-time NASDAQ ITCH 5.0 feeds. Focus on regime detection and latency-sensitive signal generation.
VPINITCH 5.0C++
🌑
Dark Pool Mechanics
Analysis of ATS/dark pool fragmentation, ping-order IOI strategies, and cross-venue mid-point adverse selection using co-integrated price processes.
ATSDark PoolsAdverse Selection
HFT Infrastructure
Kernel bypass networking (Solarflare OpenOnload), hugepage memory allocation, NUMA-aware data structure design, and RDTSC-based hardware timestamping.
OpenOnloadHugepagesNUMA
📐
Statistical Microstructure
Hurst Exponent estimation for long-range dependence in order flow, Order Book Imbalance (OBI) as a short-term price impact predictor, and Amihud illiquidity ratios.
HurstOBIAmihud

Research Timeline

2026
Dark Pool Fragmentation Study — ATS Cross-Venue Latency Arbitrage
Quantitative analysis of hidden liquidity discovery in US ATS venues. Implementation of cross-venue latency integral model for mid-point adverse selection measurement. Infrastructure deployed on Equinix NY4/NY5.
2025
VPIN Kernel Optimization — Sub-800 ns Processing Pipeline
Full redesign of tick data processing pipeline. Migration from standard Linux networking to OpenOnload kernel bypass. Latency reduction from ~12 µs to 740 ns P99 on NASDAQ ITCH data streams.
2024
Hurst Exponent & Long-Range Order Flow Dependence
Empirical study of H > 0.5 persistent order flow regimes in SPY and QQQ. Development of rolling R/S estimation with adaptive window sizing for real-time regime classification.
2023
certurk23 Quant Lab — Founded
Initial focus on market microstructure theory and VPIN methodology. First co-location deployment at Equinix NY4. Core C++ infrastructure framework established.

Research Notes & Publications

Probability of Informed Trading (VPIN) and Flow Toxicity on NASDAQ
certurk23 Quant Lab · 2026 · Research Note
VPINMarket MicrostructureNASDAQ
Fragmented Liquidity: The Mechanics of Dark Pool Discovery
certurk23 Quant Lab · 2026 · Research Note
Dark PoolsATSAdverse Selection
Institutional Adverse Selection & Zero-Knowledge Telemetry Architecture
certurk23 Quant Lab · 2025 · Technical Report
Adverse SelectionZK ArchitectureAES-256-GCM
HFT Infrastructure: Kernel Bypass, Hugepages & Sub-800 ns Latency Budget
certurk23 Quant Lab · 2025 · Technical Report
OpenOnloadHugepagesLatency

Contact & Collaboration

The certurk23 Quant Lab is open to research collaboration with academic institutions, independent quantitative researchers, and technology partners working on market microstructure, low-latency systems, or statistical finance.

All research outputs are published on this portal. For collaboration inquiries, reach out via GitHub at github.com/certurk23. The lab does not accept unsolicited trading strategy proposals or investment-related inquiries.

This research environment operates under an independent, non-commercial mandate. All findings are provided for academic and heuristic purposes only, and do not constitute financial advice under any regulatory jurisdiction.