AIR-Quant Webinar Machine Learning in Finance: From Theory to Practice

AIR-Quant Webinar Machine Learning in Finance: From Theory to Practice

by Actuaries, Insurance, Risk and Quants Society

Panel Discussion

Thu, 22 Oct 2020

5:00 PM – 7:00 PM (GMT+1)

Add to Calendar

Zoom Event

-

View Map
228
Registered

Registration

Details

Machine learning is one of the hottest topics in quantitative finance and is already paving the way for big/alt data usage in modelling. We present our new textbook on machine learning for finance, which presents the topics and applications of supervised and reinforcement learning in investment management and trading using unified econometrics and stochastic control frameworks. This talk shall provide key insights from the book, some theory, some python notebooks, and lots of real-world applications using big data. We're also outline our vision for the future of machine learning in finance.

Note: For any other queries contact Peter.Vodicka@cass.city.ac.uk
Kind Regards,
AIR-Q Society

Follow us also on our LinkedIn page
LinkedIn: https://www.linkedin.com/company/cass-actuarial-insurance-risk-and-quants-society



Share with friends

Where

Zoom Event

-

Speakers

Matthew   Dixon's profile photo

Matthew Dixon

Matthew Dixon, FRM, Ph.D., is an Assistant Professor of Applied Math at the Illinois Institute of Technology and an Affiliate of the Stuart School of Business. He has published over 25 peer reviewed publications on machine learning and quant finance and has been cited in Bloomberg Markets, US News, and the Financial Times as an AI in fintech expert. He is Deputy Editor of the Journal of Machine Learning in Finance, Associate Editor of the AIMS Journal on Dynamics and Games, and is a member of the Advisory Board of the CFA Quantitative Investing Group. Over the last 20 years, Matthew has served as a quant and consultant at numerous financial institutions including Lehman Brothers, the Bank for International Settlements, SilverLake investments and various leading asset management firms. Matthew holds a PhD in Applied Math from Imperial College.



Igor  Halperin's profile photo

Igor Halperin

Igor Halperin, Ph.D., is a Research Professor in Financial Engineering at NYU, and an AI Research associate at Fidelity Investments. Igor has published more than 50 scientific articles in machine learning, quantitative finance and theoretical physics. Prior to joining the financial industry, he held postdoctoral positions in theoretical physics at the Technion and the University of British Columbia. Igor has previously served as executive director at JP Morgan. 

Paul  Bilokon's profile photo

Paul Bilokon

Paul Bilokon, Ph.D., is CEO and Founder of Thalesians Ltd. Paul has made contributions to mathematical logic, domain theory, and stochastic filtering theory, and, with Abbas Edalat, has published a prestigious LICS paper. He is a member of the British Computer Society, the Institution of Engineering and the European Complex Systems Society. Paul has previously served as Director at Deutsche Bank, where he ran the global credit and core quant teams, part of Markets Electronic Trading (MET) group. He is one of the pioneers of electronic trading in credit, including indices, single names, and cash, and has worked in e-trading, derivatives pricing, and quantitative finance at bulge bracket institutions, including Morgan Stanley, Lehman Brothers, Nomura, and Citigroup. His more than a decade-long career spans many asset classes: equities, FX spot and options, rates and credit. Paul was educated at Christchurch College, Oxford, and Imperial College.


Hosted By

Actuaries, Insurance, Risk and Quants Society | Website | View More Events

Contact the organizers