Faramarz Shemirani: A Visionary Leader in Algorithmic Trading and Quantitative Finance
Faramarz Shemirani stands out as a world-leading quant in the development of automated algorithmic trading platforms. With a career spanning over three decades, Shemirani has been at the forefront of pioneering high-frequency trading (HFT) technologies, AI-driven quant models, and groundbreaking risk prediction engines in both traditional finance and the emerging DeFi landscape. His expertise, enriched by a robust educational foundation and vast industry experience, makes him a distinguished figure in the quantitative finance community globally.
Early Education and Academic Background
Faramarz Shemirani’s educational journey laid the foundation for his remarkable contributions to quantitative finance and engineering. He earned a Bachelor of Science with Honours in Mechanical Engineering from the University of Leeds between 1981 and 1984. He then advanced his studies at The University of Manchester, securing a Master of Science in Thermodynamics and Fluid Mechanics. His academic pinnacle was a Ph.D. in Computational Fluid Dynamics from Nottingham Trent University, where he honed skills that would later underpin his sophisticated algorithmic modelling and quantitative analytics. This rigorous scientific background is reflected in his systematic and analytical approach to financial engineering.
Nationality and Early Career
Faramarz Shemirani is British-Iranian, combining the global perspectives of two culturally rich backgrounds. Early in his career, he ventured into engineering roles, notably with British Gas Technology Ltd., where he served for over a decade. His work involved pioneering real-time appliance diagnostics, graphical system development, and fire prediction modelling using advanced computational simulations—skills that seamlessly transitioned into quantitative finance.
Pioneering High-Frequency Trading
Royal Bank of Canada (RBC) and Early HFT Development
Shemerani’s most notable early financial innovation was at Royal Bank of Canada (RBC), where from 2000 to 2006 he played a key role as Vice President in Global Derivatives, focusing on high-frequency trading. He designed and developed some of the world’s earliest and most sophisticated HFT systems, including low-latency, resilient connectivity platforms supporting trading across major European stock exchanges and the New York Stock Exchange. His systems utilised advanced algorithms and object-oriented programming in C++ and C, and employed FIX protocol for seamless exchange connectivity. This pioneering work set standards for subsequent developments in automated trading globally.
Contributions at Other Global Financial Institutions
After RBC, Shemirani held senior consulting quant positions with various prestigious institutions, including BNP Paribas, Bank of America Merrill Lynch, Credit Suisse, Barclays UK, Deutsche Bank, Daiwa Capital Markets Europe Ltd, and LONDON TRADING EXCHANGE AND CLEARING LIMITED. In these roles, he specialised in developing complex trading systems, risk management tools, and exchange connectivity modules.
At BNP Paribas, he led the quant development of the Incremental Risk Charge (IRC) Engine, integrating risk simulations and calibration components for credit instruments. At Daiwa Capital Markets, he designed and developed a live distributed quant system for exotic derivatives pricing with integrated risk validation, showcasing his capability in combining financial theory with cutting-edge software engineering.
His time at LONDON TRADING EXCHANGE AND CLEARING LIMITED included developing collateral risk components and implementing GPU-accelerated model validation, reinforcing his strong engineering acumen alongside financial expertise.
Innovation in Cryptocurrency and Decentralised Finance
AGY Family Office and Crypto High-Frequency Trading
From 2016 to 2020, Shemirani served as Quant Team Lead and System Architect at AGY Family Office in Dubai, focusing on high-frequency cryptocurrency trading. Here, he broke new ground by integrating novel AI algorithms—using deep learning, neural networks, temporal differencing, and reinforcement learning—into crypto HFT platforms. He led the full AI development lifecycle from design to deployment, ensuring robust exchange connectivity and fail-safe operation across leading cryptocurrency exchanges. This pioneering work positioned him as a visionary leader in the convergence of AI and financial trading technologies.
Minterest Labs and DeFi Risk Prediction
Between 2021 and 2023, Shemirani worked at Minterest Labs in Estonia as Director of Predictive Risk. He designed and developed the world’s first automated collateral risk prediction engine for collateralised assets in DeFi lending—a revolutionary tool addressing risk in the rapidly evolving decentralised finance ecosystem. He also led quantitative development and data science initiatives for price feature discovery, blockchain data capture, and analytics. His models accurately forecasted yield curves, liquidation events, and other critical DeFi dynamics, underscoring his forward-looking approach and adaptability to emerging financial paradigms.
Technical Skills and Expertise
Throughout his career, Faramarz Shemirani has demonstrated mastery in a variety of technical disciplines:
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Programming languages: Python, C++, C, Perl, SQL
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Quantitative analytics and finance: Algorithmic trading, risk modelling, derivatives pricing, Monte Carlo simulations
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AI and Machine Learning: Deep learning, reinforcement learning, neural networks
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System design and architecture: Low-latency trading systems, exchange connectivity (FIX protocol), distributed systems, GPU acceleration
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Blockchain and DeFi: Smart contract risk analytics, collateral risk engines
His unique blend of engineering rigour and quantitative finance expertise enables him to bridge complex mathematical models with practical, high-performance software systems.
Leadership and Impact
Shemerani’s leadership roles have involved directing development teams, managing end-to-end project delivery, and fostering innovation. He has consistently driven the design and deployment of systems that push the boundaries of speed, accuracy, and resilience in financial markets. His work has impacted major global banks and family offices alike, enhancing their ability to operate in fast-moving, highly competitive environments.
Summary
Faramarz Shemirani’s career embodies the evolution of quantitative finance over the past three decades—from early high-frequency trading in traditional markets to cutting-edge AI and blockchain-enabled platforms. His educational background in engineering and computational fluid dynamics provides a strong analytical foundation that complements his practical experience across multiple top-tier financial institutions and emerging fintech ventures.
As a British-Iranian leader with a global outlook, Shemirani continues to innovate in quantitative finance and algorithmic trading, particularly within cryptocurrency and decentralised finance sectors. His pioneering spirit and technical excellence make him a role model for future generations of quants and financial engineers.
