London Seminar: Paul Bilokon: The Secrets of HFT

Please note that this event will take place IN PERSON on Friday, 31 July, 2026 in London at 6pm London time (1pm New York time).

In collaboration with Imperial College London.

Full title: The Secrets of HFT

Speaker: Paul Bilokon

Abstract: High-frequency trading is often portrayed as a mysterious contest fought at impossible speeds by secretive firms and powerful machines. But what actually happens inside an HFT system - and how did financial markets evolve into environments where nanoseconds, network routes, processor architecture, and queue position can determine success?

The Secrets of HFT takes the audience behind the screens to explore the history, technology, and strategy of high-frequency trading. We will trace the development of electronic markets, examine the networks and specialised hardware that move information at extraordinary speeds, and uncover the software architectures required to make decisions reliably under extreme latency constraints. We will then turn to the strategic layer: order-book dynamics, execution, adverse selection, competition, and risk.

Rather than treating HFT as either magic or menace, this talk presents it as a remarkable meeting point of finance, mathematics, computer science, engineering, and game theory. Designed for students, practitioners, and academics alike, it reveals how modern markets really work - and why the fastest decision is not always the smartest one.

Venue: Blackett LT2, Blackett Laboratory, Imperial College London, 180 Queen's Gate, South Kensington, London SW7 2BW

Biography: Paul Bilokon is Head of Market Making at MFT Energy, CEO at Thalesians Ltd, and Visiting Professor at Imperial College London. He is also a board member at Thalesians Marine and Turnleaf Analytics.

He has worked at major financial institutions such as Morgan Stanley, Lehman Brothers, Nomura, Citigroup, Deutsche Bank, BNP Paribas, qSpark and many others, focusing on electronic trading, market making, and high-frequency trading. In particular, he was a pioneer of electronic trading in fixed income and credit.

Paul has co-authored (with Matthew Dixon and Igor Halperin) Machine Learning in Finance: From Theory to Practice (2020, Springer), and (with Jack Jacquier, Ewan Mackie, and Aitor Muguruza) An Introduction to Python for Quantitative Finance: From Scratch to Productivity (2026, World Scientific).

He holds MSci and PhD degrees from Imperial College and MSc from the University of Oxford, where he came top of his class. His papers have been published in Journal of Applied Probability, Journal of Financial Data Science, Journal of FinTech, Journal of Parallel and Distributed Computing, Logic in Computer Science, Theoretical Computer Science, and Wilmott.

Paul is an expert developer in kdb+/q, SQL, C++, C#, Java, Python, and is now learning Rust.

Links:

Paul's academic page: https://profiles.imperial.ac.uk/paul.bilokon01