Blackmark Dominion.
Blackmark Dominion Research Inc. is a Canadian systematic quantitative research firm based in Richmond Hill, Ontario. We develop institutional-grade quantitative models, publish rigorous market research, and build the systematic infrastructure required for precision trading strategies. Our work spans gold market microstructure (XAU/USD), systematic macro, neural signal design, and regime detection.
Operating Principles
Four principles govern everything we build.
Empirical Discipline
Every thesis begins with data. We prioritize evidence over intuition, methodology over conviction, and reproducibility over narrative.
Methodological Rigor
We apply the standards expected in peer-reviewed academic research: out-of-sample validation, transparent assumptions, and statistical discipline.
Operational Precision
Research without execution infrastructure is academic. We build systems that translate quantitative insight into measurable edge.
Permanence
We build for decades, not quarters. Our infrastructure, methodology, and culture are designed for compounding institutional advantage.
Martin Ghanavatpour
Founder & Head of Research
Richmond Hill, Ontario
Martin Ghanavatpour founded Blackmark Dominion Research with the conviction that systematic, evidence-based research is the most reliable foundation for investment decision-making. His background spans quantitative analysis, systematic strategy development, and computational methods applied to financial markets.
Prior to founding Blackmark Dominion, Martin developed quantitative research frameworks for gold market analysis and systematic macro strategies, building the 998-feature research pipeline that now forms the core of the firm's analytical infrastructure.
His research philosophy emphasizes methodological rigor, statistical discipline, and operational precision. The best research organizations are built by people who care more about being right than appearing right.
Daniel (Pouyan) Nazarzadeh
CTO & Head of Research
Blackmark Dominion Research
Daniel (Pouyan) Nazarzadeh serves as CTO and Head of Research at Blackmark Dominion, driven by a commitment to building robust, scalable systems and applying rigorous, evidence-based methodologies to financial markets. His work focuses on the intersection of full-stack engineering, quantitative research, and AI-driven analysis.
Prior to and alongside his role at Blackmark Dominion, Daniel has developed advanced research infrastructure, including multi-factor data pipelines and machine learning models for market prediction. He played a key role in building and refining the firm’s analytical systems, contributing to the evolution of its 998-feature research framework.
His approach combines technical precision with analytical discipline, emphasizing clean system design, data integrity, and reproducibility. He believes that the strongest research and engineering teams are built on curiosity, continuous learning, and a commitment to solving complex problems with clarity and accuracy.
Infrastructure
998-Feature Alpha Pipeline
A comprehensive alpha research framework spanning technical, fundamental, microstructure, and alternative data features across multiple asset classes.
Execution Research Layer
Proprietary execution infrastructure with regime-conditional fill models, slippage estimation, and real-time validation against live execution data.
Neural Signal Architecture
Principled integration of statistical learning into the research workflow, with emphasis on interpretability, theoretical grounding, and out-of-sample validation.
Intellectual Framework
Our approach is informed by the work and philosophy of researchers and practitioners who have advanced the field of quantitative finance.
Jim Simons
Renaissance Technologies
Demonstrated that rigorous mathematical methods, applied systematically, can achieve extraordinary long-term results.
Marcos López de Prado
Quantitative Research
Pioneered modern approaches to financial machine learning, emphasizing the dangers of backtest overfitting and the importance of research hygiene.
Cliff Asness
AQR Capital Management
Built the template for transparent, research-driven systematic investing with rigorous factor analysis and open publication.
Emanuel Derman
Quantitative Finance
Brought intellectual honesty to financial modeling, emphasizing the limits of models and the importance of understanding what they cannot capture.