LQG Seminars

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Deep learning the limit order book: what machines can learn and what can we learn from them?

Seminar by Professor Tomaso Aste

8th June 2021

Markets are world-wide information processing systems where humans and machines interact dynamically searching for an agreement on the price of things. The Limit Order Book (LOB) is a self-organizing complex mechanism where a transaction price emerges from the interaction of many agents. The actuation of the process can be at very high speed but the orders reflect operations and computations that span a very broad range of time-scales from nanoseconds to several years. Given its relatively simple and mechanistic nature, the LOB appears to be an ideal candidate for the use of Artificial Intelligence tools to automatically learn properties, find patterns and devise strategies. The literature is starting to report some success-stories in this domain and appropriate methodologies and architectures are emerging.
In this talk Professor Aste presents some results for the prediction of transaction prices using deep learning and deep reinforcement learning of the LOB order dynamics. He will also discuss general perspectives about the increasingly complex implications about the use of artificial intelligence for the automation of trade and many other activities in the financial services industry.
Related papers
T Aste (2021) What machines can learn about our complex world-and what can we learn from them?
A Briola, J Turiel, R Marcaccioli, T Aste (2021) Deep Reinforcement Learning for Active High Frequency Trading
A Briola, J Turiel, T Aste (2020) Deep Learning Modeling of the Limit Order Book: A Comparative Perspective

 

Tomaso Aste

Professor of Complexity Science at UCL Computer Science Department

Tomaso Aste is professor of Complexity Science at UCL Computer Science Department. A trained Physicist, he has substantially contributed to research in financial systems modeling, complex structures analysis, artificial intelligence and machine learning. Prof. Aste is passionate in the investigation of the interplay between technologies, society and finance. He is founder and Head of the Financial Computing and Analytics Group at UCL, co-founder and Scientific Director of the UCL Centre for Blockchain Technologies, Member of the Board of the ESRC LSE-UCL Systemic Risk Centre and Member of the Board of the Whitechapel Think Thank. He collaborates, on FinTech topics, with the Financial Conduct Authority, The Bank of England, HMRC and the All-Party Parliamentary Group. He is leading an initiative for training to FinTech central bankers and regulators across South America. He is advisor and consultant for several financial companies, banks, FinTech firms and digital-economy start-ups. He created four Master Programmes at UCL ranging from Risk Management to the Digital Economy.
http://www.cs.ucl.ac.uk/staff/tomaso_aste
https://www.ucl.ac.uk/computer-science/research/research-groups/financial-computing-and-analytics
https://scholar.google.co.uk/citations?hl=en&user=27pUbTUAAAAJ&view_op=list_works&sortby=pubdate