ABOUT THE EVENT
As various technologies continue to develop and evolve the world of Trading as we know it, there are far wider studies and deeper research being conducted that involve the study, application and use of mathematics and statistics in the world of Finance and Trading.
In this discussion, our panel of experts hailing from across the globe delve into the current trends in this domain of quant finance. With their subject matter expertise and experience shouldering key roles across eminent organizations, their thoughts on the topic yield key insights that are bound to guide you. Be sure to attend!
The event was held on:
Tuesday, September 28, 2021
9:30 AM ET | 7:00 PM IST | 9:30 PM SGT
PANELISTS
David Jessop (Head of Investment Risk, EMEA, at Columbia Threadneedle Investments)
In his presen role, David has a responsibility for overseeing the independent investment risk management process for all portfolios managed in
the EMEA region. Before joining the company, David was the Global Head of Quantitative Research at UBS.
Over his 17 years at UBS his research covered many topics but in particular he concentrated on risk analysis, portfolio construction and more recently cross asset factor investing / the application of machine learning and Bayesian techniques in
investment management.
Prior to this he was Head of Quantitative Marketing at Citigroup. David started his career at Morgan Grenfell, initially as a derivative analyst and then as a quantitative portfolio manager. David has a MA in Mathematics from Trinity College, Cambridge.
Dr. Debashis Guha (Professor and Director of Machine Learning, SP Jain School of Global Management)
Debashis Guha is Director of Machine Learning and Chair of the Centre for Research in Technology in Business at S P Jain School of Global Management. He has more than two decades of experience working in the field of Artificial Intelligence and especially its applications to economics and finance.
He is also the founder of a Bangalore based company that has provided consultancy for quantitative hedge funds across the world. He has formerly been Head of Risk Management and Quantitative Trading at Big Sky Capital, a California based hedge fund, and Partner at Global Trend Capital, another California hedge fund.
Dr Guha is a graduate of IIT Kharagpur and has a Ph.D. from Columbia University in New York.
Richard V. Rothenberg (Executive Director at Global A.I. Corporation)
Richard is an Executive Director at Global A.I. Corporation, a Big Data and Artificial Intelligence company that provides quantitative research, data-driven signals and alternative data for Institutional clients, including Hedge Funds and Governments.
Previously, Richard worked as a quantitative portfolio manager and researcher at multi-billion dollar hedge funds and global investment banks, including Deutsche Bank, Man investments and other leading institutions. Richard is a research affiliate at the Lawrence Berkeley National Laboratory – one of the world’s largest supercomputing laboratories – and an advisor at the Defense Advanced Research Projects Agency (DARPA).
Richard is a member of the Task Force on data for the Sustainable Development Goals at the United Nations Conference on Trade and Development and member of the United Nations Science, Technology, and Innovation Expert Group.
Richard holds a bachelor’s degree in Economics and Computational Finance from the Monterrey Institute of Technology, a Certificate of Quantitative Finance from the CQF Institute, and a Master’s in Management and Quantitative Finance from Columbia University in New York City.
ABOUT ALGO TRADING WEEK 2021
As we celebrate our 11th anniversary at QuantInsti, we are starting off with a new tradition - Algo Trading Week. We will be joined by industry leaders where they share their experience and words of wisdom through various educational sessions.
This will be a great learning opportunity for the aspiring algo traders and quantitative trading community. It’s your chance to connect with your favourite experts and get answers to all your questions for absolutely free.
