SEED Seminar at UCL
Filtering information with networks: understanding market structure and predicting market changes
Thu, 13 Sep 2018
10:00 - 11:00
66-72 Gower Street
Statistical Validation Methods for Complex Systems 2018
The 1st International Workshop Statistical Validation Methods for Complex Systems, organised by Dr. Fabio Caccioli and Dr. Giacomo Livan, will be hosted by the Conference on Complex Systems on 27 September 2018.
P2P FINANCIAL SYSTEMS 2018
The 4th International Workshop P2P FINANCIAL SYSTEMS 2018 will be hosted by the Federal Reserve Bank of Cleveland on 26-27 July 2018
P2P FINANCIAL SYSTEMS 2017
The 3rd International Workshop P2P FINANCIAL SYSTEMS 2017 will be hosted by UCL on 20-21 July 2017.
P2P FINANCIAL SYSTEMS 2016
The 2nd International Workshop P2P FINANCIAL SYSTEMS 2016 will be hosted by FCA at UCL 8-9 September 2016
P2P FINANCIAL SYSTEMS 2015
P2P FINANCIAL SYSTEMS 2015
Opportunities • Risks • Market Dynamics • Regulation
29-30 January 2015
Event web page:
IEEE Computational Intelligence for Financial Engineering & Economics
Mar 27-28, 2014, London, UK
Event web page:
Financial Computing and Analytics Research Seminar 5th March 2014
The Financial Computing and Analytics research seminars are aimed at exploring the interface between academia and the financial industry, and our next seminar is presented by two distinguished speakers whose complementary work is positioned within that challenging interface.
When and where: Wednesday 5th March from 4pm in Auditorium Chandler 118, University College London, Chandler House, 2 Wakefield Street, London WC1N 1PF.
Presenter: Edward Tsang, CCFEA, University of Essex
Title: Directional Changes: a new way to look at market dynamics
Abstract: This talk explains a new concept called Directional Changes and how it helps to study financial markets. When history is recorded, one does not report the situation at the end of each day, each month or each year. One records significant events. Yet most researchers record market price movements with snapshots; for example, daily closing prices are used. Richard Olsen proposed an event-based approach to summarize price movements, based on a concept called Directional Changes. A directional change is defined by a threshold that the observer cares about, e.g. 5%. An r% directional change is basically a price change of r% from the last peak or bottom price. For any given threshold, the observer will summarize price movements by linking up the extreme points between directional changes. This new concept provides traders with new perspectives to the market, as demonstrated by Olsen Ltd in foreign exchange trading. It also enables researchers to discover new regularities in markets.
Presenter bio: Edward Tsang holds a first degree in Finance and a MSc and PhD degree in Computer Science. He is the Director of Centre for Computational Finance and Economic Agents (CCFEA), an interdisciplinary research centre which he co-founded in October 2002. He has international reputation in artificial intelligence. He is well known for his research in constraint satisfaction (a branch of combinatorial optimisation for decision support and scheduling) and computational finance and economics. His book on constraint satisfaction is the most cited literature on the subject. He founded the Technical Committee in Computation Finance and Economics in IEEE's Computational Intelligence Society in 2004. Edward Tsang's research is highly industry-relevant. He has given consultation to GEC Marconi, British Telecom, Honda Europe, Causeway, Old Mutual Asset Managers, Allianz RAS and other organizations.
Presenter: Richard Olsen, Olsen Ltd & CCFEA, University of Essex
Title: From an event-based definition of time to the discovery of scaling laws
Abstract: In time series analysis a researcher's choice of time scale impacts his observations. I argue that we need to change the approach and replace the exogenous time scale with an intrinsic time scale. I introduce an event based definition of time and show how this approach brings to light scaling laws that have not been reported before. The scaling laws can be used to develop a new class of economic and financial models. The talk concludes with a pitch to rethink the foundations of classical economics and come up with a relativity theory of economics.
Presenter bio: Dr Richard Olsen holds a Licentiate in Law from the University of Zurich, a Master's in Economics from Oxford University, and a PhD from the University of Zurich. He worked in banking as a researcher and foreign exchange dealer before founding Olsen and Associates in 1985. Olsen is the Chairman and co-Founder of OANDA, a leading provider of currency-related tools and services; in 2001 OANDA opened FXTrade, the first fully automated online foreign exchange trading platform. For more than 20 years Olsen has led research in the emerging field of "high-frequency finance." Unlike pure R&D shops, Olsen has developed real-time trading models based on their research and put their theories to the ultimate test—in the marketplace.
Supported by the Analytics Network of the OR Society.
UCL/IEEE Spring School in Financial Computing and Analytics 2014
Executive Suit, First Floor, Front Engineering Building, Malet Street/Malet Place, London, WC1E 6BT University College London, United Kingdom
March 29 – March 30, 2014
Dr Tomaso Aste, Head Financial Computing and Analytics Group, University College London, United Kingdom
Dr Antoaneta Serguieva, Member Financial Computing and Analytics Group, University College London, United Kingdom; Member Computational Finance and Economics Technical Committee, IEEE Computational Intelligence Society
Prof Uzay Kaymak, Chair Computational Finance and Economics Technical Committee, IEEE Computational Intelligence Society
Lecturers and topics (alphabetically):
Dr Tomaso Aste, Reader in Computational Finance; Head Financial Computing and Analytics Group, University College London: Financial dependency and causality networks
Prof Michael Dempster, Professor Emeritus at the Centre for Mathematical Sciences, University of Cambridge; Founder of the Centre for Financial Research at the University of Cambridge; Managing Director of Cambridge Systems Associates Ltd: The true use of complex OTC derivatives
Dr Guido Germano, Senior Lecturer, Member Financial Computing and Analytics Group, University College London: Fourier methods for the pricing of exotic derivatives
Prof Jessica James, Visiting Professor, Financial Computing and Analytics Group, University College London; Managing Director, Head Quantitative Solutions Group, Commerzbank: Inefficiencies in foreign exchange data
Prof Uzay Kaymak, Chair IEEE CIS Computational Finance and Economics Technical Committee;Professor of Information Systems, Eindhoven University of Technology, The Netherlands: Fuzzy systems in Value-at-Risk estimation
Prof Alexander Lipton, Visiting Professor, Department of Mathematics, Imperial College London; Managing Director, Enterprise Capital Management, Bank of America Merrill Lynch, New York: Three-dimensional Brownian motion and its applications to CVA and trading
Prof Dietmar Maringer, Professor of Computational Management Science, University of Basel, Switzerland: Operationalizing dynamic portfolio strategies under non-standard price process assumptions and realistic market constraints with genetic programming
Dr Christoph Reisinger, Lecturer in Mathematical Finance, Oxford-Man Institute of Quantitative Finance, University of Oxford: Numerical solution of PDEs
Students £150; Non-students £300
The spring school is limited to 30 places, provided on first booked basis.
There will be IEEE student grants to be announced in due course, for a small amount covering partially registration and travel expenses.
Dr Antoaneta Serguieva (General Chair CIFEr 2014); Financial Computing and Analytics Research Group; University College London, Gower Street, London WC1E 6BT, UK
tel: +44-203-108-1063; email: firstname.lastname@example.org
Ms Dawn Bailey (Treasurer CIFEr 2014); Finance Manager, Department of Computer Science; University College London, Gower Street, London WC1E 6BT, UK
tel: +44 (0)20 7679 1315; email: email@example.com