Machine Learning in Quantitative Finance and Risk Management

One-day workshop on-line
  • What Scientific Computing English Not a Seminar
  • When 02-07-2020 from 09:00 to 17:00 (Europe/Amsterdam / UTC200)
  • Where on-line
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Organised by Kees Oosterlee and Kristoffer Andersson (CWI)

Thursday July 2nd 2020

This workshop will take place, on-line, via
Meeting ID: 885 7010 0112, password: 811135

The workshop times are CET, Central European Time:

10:00 AM (Keynote) Christoph Reisinger (U. Oxford): "Deep xVA solver -- A neural network based counterparty credit risk management framework"
11:00 AM  Kristoffer Andersson (CWI): "Learning exposure profiles for portfolios of exotic derivatives"
11:50 AM Shashi Jain (IISc Bangalore): "Universal static hedging using a shallow neural network"

13:30PM Anastasia Borovykh (Imperial College, London): "To interact or not? On the convergence properties of interacting particle optimization"
14:20PM Shuaiqiang Liu (TU Delft): "Deep learning for large time-step simulations of stochastic differential equations"
15:15PM (Keynote) Yuying Li (U. Waterloo, Canada): "Asset allocation without pain: learning dynamic strategies directly from market data"

The speakers:

Christoph Reisinger is Professor of Applied Mathematics at Oxford's Mathematical Institute and Tutorial Fellow in Mathematics at St Catherine's College. He is Editor-in-Chief of The Journal of Computational Finance, and serves on the editorial board of Applied Mathematical Finance and the International Journal of Computer Mathematics.

Kristoffer Andersson is a PhD candidate in the group of Prof. Kees Oosterlee. He is currently working, in the context of a European Industrial Doctorates project, on counterparty credit risk management, XVA and optimal stopping problems, in combination with modern machine learning paradigms.

Dr Shashi Jain is currently an assistant professor in the department of management studies at Indian Institute of Science, Bangalore. He has fond memories of CWI, where he did his PhD under the guidance of Professor Kees Oosterlee. He worked as front office quant at ING, Amsterdam before taking up his current position at IISc. His research interest have primarily been on Monte Carlo methods in financial engineering, with particular focus on pricing of early exercise options. Other areas of interest include self exciting point processes with applications in market microstructure, portfolio allocation problems and real options.

Anastasia Borovykh is currently a post-doctoral researcher at Imperial College, London, working on understandable machine learning techniques.
She got her PhD in Mathematics on algorithms in financial mathematics and computational finance from the University of Bologna, Italy, 2018.

Shuaiqang Liu is a PhD candidate in the group of Prof. Kees Oosterlee. He is currently working on computational finance and machine learning, particularly developing fast data-driven numerical solvers.

Yuying Li is a professor at Cheriton School of Computer Science, University of Waterloo in Canada. Prior to joining Waterloo, she was a senior research associate in Computer Science Department at Cornell University 1988-2005. She is the recipient of the 1993 Leslie Fox first Prize in numerical analysis at Oxford England. Her main research interest includes financial data science (including supervised and unsupervised learning, clustering, anomaly detection, fraud detection, and data driven optimal decision), computational finance, and computational optimization.
Li has been an associate editor of the Journal of Computational Finance (since 2008),  the Journal of Finance and Data Science (since 2015). Li has been on the Advisory Board of the Journal of Financial Innovation since 2017. Presently, Li is the (graduate program) Director of Data Science at University of Waterloo.