Tom J. Espel

Quantitative research and risk management with a focus on electronic and illiquid assets.

Quick links: Bio, Research and Teaching, Bookshelf and Earbuds


Tom is a quantitative analyst who specializes in research and risk management of electronic and illiquid assets. He has worked in London and Hong Kong for six years in foreign exchange, both in alpha research and market-making pricing as well as high-frequency trading.

In addition to his work, Tom has been invited as a guest lecturer in quantitative finance and is actively publishing articles in the field of digital and illiquid asset management.

Tom is a quantitative analyst who specializes in research and risk management of electronic and illiquid assets. His expertise is in the area of applied Mathematics, market econometrics and practical applications of machine learning. Tom is a member of the HKSI (MHKSI).

He has worked in London and Hong Kong for six years in foreign exchange, both in alpha research and market-making pricing as well as high-frequency trading. His professional achievements include his contribution to the creation of the systematic risk management system for illiquid emerging market currencies at HSBC. Tom was promoted to Vice President in 2023 and his team received the FX Market Asia award for e-trading in 2024.

In addition to his work, Tom has been invited as a guest lecturer in quantitative finance and is actively publishing articles in the field of digital and illiquid asset management.

Tom holds an MSc in Mathematics and Finance from Imperial College London, an MEng in Electrical and Electronic Engineering from CentraleSupelec (a member Grande Ecole of the Paris-Saclay University) and a BSc in Applied Economics from Paris Dauphine University. Before his Grande Ecole, he studied Mathematics, Physics and Chemistry in preparatory class, and was selected to compete to join the French delegation to the International Chemistry Olympiad.

In his spare time, Tom is a keen photographer and a music enthusiast. He completed a WSET Level 3 Award in Wines and is a certified personal trainer and nutrition coach.


The Hong Kong Securities and Investment Institute (HKSI Institute) works closely with government, local regulatory bodies, industry practitioners and our members to reinforce, raise and promote professional standards for the financial services industry.

  • MHKSI (Member)
  • Member No. M14172
  • Licensing Examination (Paper 1) in 2023

The Chartered Institute for Securities & Investment is the leading professional body for securities, investment, wealth and financial planning professionals.

  • MCSI (Member)
  • Member No. 253637
  • CISI Level 3 Certificate in Derivatives in 2019

IEEE is the world’s largest technical professional organization dedicated to advancing technology for the benefit of humanity. IEEE is a leading developer of international standards that underpin many of today's telecommunications, information technology, and power-generation products and services.

  • Associate
  • Member No. 93851893
  • Registered since 2015

Research and Teaching

Research Interests

Selected Publications

ORCiD Google Scholar
  • Articles - PrePrints

  • [Accepted FTC2024] Espel, T.J., 2024. Impact of US Bitcoin ETF Introduction on BTC and ETH Intraday Regime Seasonality.
    Link to SSRN
  • Espel, T., Katz, L. and Robin, G., 2017. Proposal for protocol on a quorum blockchain with zero knowledge. French Central Bank. Cryptology ePrint Archive.
    Link to IACR
  • Miscellanea

  • Espel, T., 2018. A Quantitative Approach to Non-Deliverable Forwards. MSc Thesis, Imperial College London.
  • Espel, T., 2017. [In French] Drone Avoidance Algorithms : A Probabilistic Approach. Research dissertation, CentraleSupelec Paris.
    View file


Bookshelf and Earbuds

I'm often asked for material to get started on some quantitative finance topics; so here are my recommended reads and listens, in no particular order.

Reading List

  • Quant - Applied Maths

  • Stochastic Calculus for Finance

    Pr Shreeve is often credited as having created the first modern quantitative finance curriculum at Carnegie Mellon University. He published two books, the Stochastic Calculus for Finance series, from those lectures and the second volume dedicated to continuous-time models is one of the most known and most used books at the graduate level in quantitative finance.

    Shreve, S.E., 2010. Continuous-Time models, Stochastic calculus for finance / Steven E. Shreve. Springer, New York, NY.
  • Analysis of Financial Time Series

    Analysis of Financial Time Series is a practical catalogue of most of the common concepts and techniques in quantitative finance. I recommend this book to anyone interested in the field, it's an investment that will yield over and over again. I have found myself referring back to this book on multiple occasions, Tsay's style is clear and the book is well-organised for easy referencing.

    Tsay, R.S., 2010. Analysis of financial time series, 3rd ed. ed, Wiley series in probability and statistics. Wiley, Cambridge, Mass.
  • Quant - Liquidity

  • Market Microstructure (Equities)

    Lehalle and Laruelle conduct a detailed analysis of the market microstructure properties of European equities. The book only has a few chapters and is better read from start to finish to capture the authors' perspective. This is one of my favourite books in the field of liquidity fragmentation, and the ideas from this book can be applied to any asset class.
    Both first and second editions are good, the second includes updates for regulations, covers more modern topics and a foreword by Almgren.

    Lehalle, C.-A., Laruelle, S., 2018. Market microstructure in practice, Second edition. ed. World Scientific, Singapore.
  • Market Liquidity

    In this book, Olivier Guéant introduces most of the mathematical tools needed in the day-to-day of algorithmic trading: Almgren-Chriss, alongside numerical methods; Avellaneda-Stoikov; and there is also one chapter about options. The proofs are clear, elegant and concise.

    Guéant, O. 2016. The Financial Mathematics of Market Liquidity: From Optimal Execution to Market Making, First Edition. ed. CRC press, Taylor & Francis Group, New York.
  • Quant - Other

  • The Black Swan

    This book, part of Taleb's Incerto series, does not need an introduction. 😃
    The other titles in the series are Fooled by Randomness, The Bed of Procrustes (closer to a philosophical essay) and Antifragile.

    Nassim, N.T., 2007. The black swan: the impact of the highly improbable. NY: Random House.
  • Flash Boys

    Michael Lewis is my favourite author on finance-related topics. His works are mostly nonfiction but they read like novels. Flash Boys is the true story of the birth of high-frequency stock trading in the US.

    Lewis, M., 2014. Flash boys: A Wall Street Revolt. WW Norton & Company.
  • Machine Learning

  • Deep Learning (a.k.a. "the" Goodfellow)

    The authors are among the most famous experts in the field. Deep Learning is a comprehensive catalogue of models, with mathematical concepts. There is a free version of the book available online.

    Goodfellow, I., Bengio, Y. and Courville, A., 2016. Deep learning. MIT press.
  • Reinforcement Learning (Sutton, Barto)

    This book is the foundation of modern reinforcement learning and is still the reference in the field. Any of the two editions is an excellent introduction to that specific class of algorithms.

    Sutton, R.S., Barto, A., 2020. Reinforcement learning: an introduction, Second edition. ed, Adaptive computation and machine learning. The MIT Press, Cambridge, Massachusetts London, England.
  • A Probabilistic Perspective

    Murphy's book is a comprehensive study of machine learning models and is, in my humble opinion, a must-have for anyone who uses such models in high-stakes contexts. Its compelling probabilistic interpretation of models, alongside the broad range of algorithms, make it a perfect companion when choosing which implementation suits best a given problem. The book is very dense and I recommend a digital edition if possible.

    Murphy, K.P., 2013. Machine learning: a probabilistic perspective 4. print. (fixed many typos). ed, Adaptive computation and machine learning series. MIT Press, Cambridge, Mass.

Podcasts and Shows

  • Finance

  • Flirting with Models

    Probably the podcast of quantitative finance. I think it's the best one out there, and most of the influential practitioners in the field end up being interviewed by Corey Hoffstein. Flirting With Models is a great podcast which balances the at times very technical content and makes it accessible. It airs about every other week.

  • Patrick Boyle

    Patrick Boyle's podcast On Finance is entertaining and informative. He's a professional fund manager and his perspective on a very broad range of events in the financial world is very informative. He has a YouTube channel but it can be listened to as a podcast with audio only.

    YouTube Podcast
  • Chat with Traders

    Chat with Traders is one of the best-known and longest-running podcasts that relate to trading and finance. The episodes are in-depth interviews, most episodes stretch beyond one hour, of traders who share their journey, tips and techniques.

  • Other

  • Asianometry

    Jon's video essays are hands down some of the best-researched and most accurate in the fields of both the electronics industry and the broader Asian economies. The content is technical and of incredible quality.

    YouTube Website
  • How I Built This

    Guy Raz interviews twice a week entrepreneurs who share their journey. It's a very inspirational podcast and the guests come from a broad range of industries and experiences.