The CQF Institute and Wilmott present their fourth annual Quant Insights conference this November. Held in the heart of Canary Wharf, London’s modern financial center, the conference will bring together leading practitioners to explore AI, machine learning and risk.
Two internationally recognized brands; CQF Institute & Wilmott partners for the most topical quant conference of the year.
Quant Insights will have talks from experts in their field and a panel session discussing AI, machine learning and risk.
The conference offers an opportunity to network with like-minded professionals in the quant community.
Delegates can follow and participate in the conference proceedings from anywhere in the world with online tickets.
Paul is the founder of the Certificate in Quantitative Finance and Wilmott.com and he is internationally renowned as a leading expert on quantitative finance. His research work is extensive, with more than 100 articles in leading mathematical and finance journals, as well as several internationally acclaimed books on mathematical modeling and derivatives, including the best-selling Paul Wilmott On Quantitative Finance, published by John Wiley & Sons.
Miquel is a financial markets practitioner with more than 20 years of experience in asset management. He is currently Chief Development Officer for Global AI a Big Data Company that uses State-of-the-Art Statistical and Artificial Intelligence models to produce actionable insights, signals and alternative data for institutional clients, including Investors, Governments and Corporations. He worked for UBS AG (Switzerland) 10 years as Executive Director. He acted a member of European Investment Committee. He worked as a Chief Investment Office and CIO for Andbank from 2000 to 2006. He started his career at KPMG.
Tony is Senior Investment Manager - Quantitative PM, managing multi-factor equity portfolios for the asset manager of a UK pension fund in London. Prior to that Tony was Senior Research Consultant for Smart Beta and Risk allocation at EDHEC RISK Scientific Beta, advising asset owners how to construct and allocate to risk premia. Before joining EDHEC Tony worked eight years at UNIGESTION as a Senior Research Analyst. He was a member of the Research and Investment Committee for Minimum Variance Strategies and he was leading Factor Investing research group for institutional clients. He is the editor and co-author of the forthcoming book: Practical Applications of Machine learning and Big Data for Quantitative Investment (Winter 2018). He holds Bachelor and Master degrees in Econometry and Finance from the University of Savoy, France.
Yves is founder and Managing Partner of The Python Quants, a group focusing on the use of open source technologies for financial data science, artificial intelligence, algorithmic trading and computational finance. He is author of the books Python for Finance (O'Reilly, 2nd edition, 2018), Listed Volatility and Variance Derivatives (Wiley, 2017), Derivatives Analytics with Python (Wiley, 2015) and Python for Finance (O'Reilly, 2014). Yves lectures on computational finance at the CQF Program and on algorithmic trading at the EPAT Program. He is also the director of the first online training program leading to a University Certificate in Python for Algorithmic Trading. Yves has written the financial analytics library DX Analytics and organizes meetups, conferences and bootcamps about python for quantitative finance and has given keynote speeches at conferences in the US, Europe and Asia.
Karolos is a vice president in the Model Risk Management division of Citigroup overseeing model validations for various asset classes. Previously, he worked on the FX electronic trading desk of MUFG Bank as a quantitative researcher. There, he developed algorithms using statistical and machine learning techniques to extract meaningful patterns inside the big data produced in a high frequency trading environment. Karolos holds a PhD in Statistics from the London School of Economics and was a Fellow in Finance at the same school; he is also a published author and his research interests lie in the detection of change-points in big datasets and high dimensional risk management.
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