Global co-head of the quantitative strategies group
Bank of America Merrill Lynch
Leif B. G. Andersen is the Global Co-Head of The Quantitative Strategies Group at Bank of America Merrill Lynch, and is an adjunct professor at NYU’s Courant Institute of Mathematical Sciences and CMU’s Tepper School of Business. He holds MSc's in Electrical and Mechanical Engineering from the Technical University of Denmark, an MBA from University of California at Berkeley, and a PhD in Finance from Aarhus Business School. He was the co-recipient of Risk Magazine’s 2001 Quant of the Year Award, and has worked for more than 20 years as a quantitative researcher in the derivatives pricing area. He has authored influential research papers and books in all areas of quantitative finance, and is an Associate Editor of Journal of Computational Finance.
Alexandre Antonov received his PhD degree from the Landau Institute for Theoretical Physics in 1997. He worked for Numerix during 1998-2017, then in Standard Chartered bank in London as a director. Currently, AA is a chief analyst at Danske Bank in Copenhagen.
His activity is concentrated on modeling and numerical methods for interest rates, cross currency, credit and XVA, as well as Machine Learning and its applications. AA is an author for multiple publications in mathematical finance and a frequent speaker at financial conferences.
He has received a Quant of Year Award of Risk magazine in 2016.
Global head of equities analytics, automation and optimisation
Hans Buehler heads Analytics, Automation and Optimization in Equities and runs the Equities and Investor Services Data Analytics and Quantitative Research teams. His mandate is data-driven business transformation across derivatives, cash equity, electronic trading, prime, and securities services using both modern machine learning and classic analytical methods. Specific focus in the machine learning space is on AI-driven electronic execution and derivative risk management, and the use of modern machine learning techniques for engaging with our clients. His team is behind JP Morgan’s LOXM AI effort in electronic trading and the recently published “Deep Hedging” research on AI derivative management.
Hans is a Managing Director, having joined JP Morgan in Hong Kong in 2008. Before that, he worked for seven years at Deutsche Bank, also in Equities. He has a PhD from Technical University in Berlin in Financial Mathematics, and a MSc from Humboldt University in Stochastic Analysis.
Hans is based in London.
Chair of the finance and risk engineering department
NYU Tandon School of Engineering
Professor Peter Carr is the Chair of the Finance and Risk Engineering Department at NYU's Tandon School He has headed various quant groups in the financial industry for the last twenty years. He also presently serves as a trustee for the National Museum of Mathematics and WorldQuant University. Prior to joining the financial industry, Dr. Carr was a finance professor for 8 years at Cornell University, after obtaining his PhD from UCLA in 1989. He has over 85 publications in academic and industry-oriented journals and serves as an associate editor for 8 journals related to mathematical finance. He was selected as Quant of the Year by Risk Magazine in 2003 and Financial Engineer of the Year by IAQF/Sungard in 2010. From 2011 to 2014, Dr. Carr was included in Institutional Investor's Tech 50, an annual listing of the 50 most influential people in financial technology.
Editor, quantitative finance
Mauro Cesa is quantitative finance editor for Risk.net, based in London. He leads the team responsible for the publication of quantitative research across all brands of the division. The section of Risk.net he manages, Cutting Edge, publishes peer-reviewed papers on derivatives, asset and risk management, and commodities.
Mauro holds a degree in economics from the University of Trieste and a masters in quant finance from the University of Brescia.
Chief Risk Officer and Head of Quantitative Research
Andrew Y. Chin is the Chief Risk Officer and Head of Quantitative Research for AB. As the Chief Risk Officer, Chin oversees all aspects of risk management to ensure that the risks being taken are well understood and appropriately managed. In the Quantitative Research role, he is responsible for the firm’s data science strategy and for optimizing the quantitative research infrastructure, tools and resources across the firm’s investing platforms. He joined the firm in 1997 and held various quantitative research roles in New York and London. In 2004, Chin became a senior portfolio manager for Style Blend Equities. In 2005, he was named director of Quantitative Research for Value Equities. Prior to joining the firm, Chin was a project manager and business analyst in Global Investment Management at Bankers Trust from 1994 to 1997.
Chin teaches in the School of Operations Research and Information Engineering (Master of Financial Engineering Program) at Cornell University. He also leads teams of students on capstone projects utilizing quantitative and data science skills to address investment issues.
Chin earned a BA and an MBA from Cornell University.
Presidential professor of mathematics
Baruch College, CUNY
Jim Gatheral is Presidential Professor of Mathematics at Baruch College, CUNY teaching mostly courses in the Masters of Financial Engineering (MFE) program. Prior to joining the faculty of Baruch College, Jim was involved in all of the major derivative product areas as bookrunner, risk manager, and quantitative analyst in London, Tokyo and New York, in a career in the financial industry that spanned over 27 years. Jim has served as a Managing Editor of the International Journal of Theoretical and Applied Finance and as Associate Editor of the SIAM Journal on Financial Mathematics; he currently serves as Joint Editor-in-Chief of Quantitative Finance with Michael Dempster. His current research focus is on volatility modeling and modeling equity market microstructure for algorithmic trading. Jim is also a frequent speaker at both practitioner and academic conferences around the world. His best-selling book, The Volatility Surface: A Practitioner's Guide (Wiley 2006) is one of the standard references on the subject of volatility modeling. He received his Ph.D. in theoretical physics from Cambridge University.
Julien is a senior quantitative analyst in the Quantitative Research group at Bloomberg L.P., New York. He is also an adjunct professor in the Department of Mathematics at Columbia University and at the Courant Institute of Mathematical Sciences, NYU. Before joining Bloomberg, Julien worked in the Global Markets Quantitative Research team at Societe Generale in Paris for six years (2006-2012), and was an adjunct professor at Universite Paris 7 and Ecole des ponts. He co-authored the book Nonlinear Option Pricing (Chapman & Hall, CRC Financial Mathematics Series, 2014) with Pierre Henry-Labordere. His main research interests include nonlinear option pricing, volatility and correlation modeling, and numerical probabilistic methods. Julien holds a Ph.D. in Probability Theory and Statistics from Ecole des ponts. He graduated from Ecole Polytechnique (Paris), Universite Paris 6, and Ecole des ponts. A big football fan, Julien has also developed a strong interest in sports analytics, and has published several articles on the FIFA World Cup, the UEFA Champions League, and the UEFA Euro in top-tier newspapers such as The New York Times, Le Monde, and El Pais, including a new, fairer draw method for the FIFA World Cup.
Lecturer in financial mathematics
Dr Blanka Horvath is a Lecturer at the Department of Mathematics, King's College London. Blanka’s current research interests evolve around a new generation of option pricing models (Rough Stochastic Volatility models), and their asymptotic and numerical properties. Prior to her current appointment, she was at ETH Zurich, specialising in functional analytic and numerical properties of SABR-type stochastic models. Blanka holds a PhD in Mathematical Finance from ETH Zurich, a Diploma in Mathematics from the University of Bonn and an MSc in Economics from the University of Hong Kong.
Head of Asia-Pacific quantitative strategies and global product head for equities modelling
George Hong is a Managing Director at Credit Suisse, based in Hong Kong. He leads the APAC Quantitative & Risk Strategies team and is also the global product horizontal head for Equities modelling. He holds an B.A. in Mathematics and a Ph.D. in Mathematical Finance from Cambridge University.
Clinical professor & director of the mathematics in finance
Courant Institute of Mathematical Sciences, New York University
Petter Kolm is the Director of the Mathematics in Finance Master’s Program and Clinical Professor at the Courant Institute of Mathematical Sciences, New York University and Partner at CorePoint-Partners.com. Previously, Petter worked in the Quantitative Strategies Group at Goldman Sachs Asset Management. Petter has coauthored four books: Financial Modeling of the Equity Market: From CAPM to Cointegration (Wiley, 2006), Trends in Quantitative Finance (CFA Research Institute, 2006), Robust Portfolio Management and Optimization (Wiley, 2007), and Quantitative Equity Investing: Techniques and Strategies (Wiley, 2010). He holds a Ph.D. in Mathematics from Yale, an M.Phil. in Applied Mathematics from the Royal Institute of Technology, and an M.S. in Mathematics from ETH Zurich.
Petter is a member of the editorial boards of the International Journal of Portfolio Analysis and Management (IJPAM), Journal of Financial Data Science (JFDS), Journal of Investment Strategies (JoIS), and Journal of Portfolio Management (JPM). He is an Advisory Board Member of Alternative Data Group (AltDG), AISignals and Operations in Trading (Aisot), Betterment (one of the largest robo-advisors) and Volatility and Risk Institute at NYU Stern (VRI). Petter is also on the Board of Directors of the International Association for Quantitative Finance (IAQF) and Scientific Advisory Board Member of Artificial Intelligence Finance Institute (AIFI).
As a consultant and expert witness, Petter provides services in areas including alternative data, data science, econometrics, forecasting models, high-frequency trading, machine learning, portfolio optimization with transaction costs and taxes, quantitative and systematic trading, risk management, robo-advisory, smart beta strategies, tax-aware investing, and transaction costs.
Head of quantamental investments
Antonia joined Schroders in 2019 to lead their new initiative in quantamental investments, melding quantitative techniques with fundamental expertise and insight. Prior to Schroders, Antonia was Global Head of Quantitative Research for Barclays UK, designing its asset allocation policy, products and investment tools. She has two decades of experience in investment management, is a CFA charterholder and is on the management committee of the not-for-profit organization London Quant Group. Antonia holds a Masters in Physics from the University of Oxford where she was awarded an academic scholarship. Happy lending intuition, pragmatism and curiosity to the real, abstract and complex, Antonia enjoys cross-disciplinary ideas and making those ideas useful.
Global head of quantitative analytics
Fabio is global head of Quantitative Analytics at Bloomberg LP, New York. His team is responsible for the research on and implementation of cross-asset analytics for derivatives pricing, XVA valuations and credit and market risk. Fabio is also adjunct professor at NYU, and a former CME risk committee member. He has jointly authored the book 'Interest rate models: theory and practice' and published extensively in books and international journals, including 16 cutting-edge articles in Risk Magazine. Fabio holds a BSc in Applied Mathematics from the University of Padua, Italy, and a PhD in Mathematical Finance from the Erasmus University of Rotterdam, The Netherlands
Managing director, head of quantitative analytics and quantitative development
Vladimir Piterbarg is the global head of Quantitative Analytics at NatWest Markets since 2018. He held similar positions at Rokos Capital Management LLP, Barclays Capital/Barclays investment bank, and Bank of America. Vladimir Piterbarg has a PhD in Mathematics (Stochastic Calculus) from the University of Southern California. He serves as an associate editor of the Journal of Computational Finance and the Journal of Investment Strategies. Together with Leif Andersen, Vladimir Piterbarg wrote the authoritative, three-volume set of books “Interest Rate Modelling”. He published multiple papers in various areas of quantitative finance, and won Risk Magazine’s Quant of the Year award twice.
Professor of finance
Mathieu Rosenbaum obtained is Ph.D from University Paris-Estin 2007. After being Assistant Professor at École Polytechnique, he became Professor at University Pierre et Marie Curie (Paris 6) in 2011. He is now full-time professor at Ecole Polytechnique, where he is the at the head of the chair "Analytics and Models for Regulation". He is also in charge, with Nicole El Karoui, Gilles Pagès and Emmanuel Gobet, of the Master program “Probability and Finance”.
His research mainly focuses on statistical finance problems, such as market microstructure modeling or designing statistical procedures for high frequency data and on regulatory issues, especially in the context of high frequency trading. In particular, he is one of the organizers of the conference "Market Microstructure, Confronting Many Viewpoints", which takes place every two years in Paris.
Mathieu Rosenbaum has collaborations with various financial institutions, notably BNP-Paribas since 2004. He also has several editorial activities. He is one of the editors in chief of the journal "Market Microstructure and Liquidity", together with F. Abergel, J.P. Bouchaud, J. Hasbrouck and C.A. Lehalle. Furthermore, he is managing editor for "Quantitative Finance" and associate editor for "Electronic Journal of Statistics", "Journal of Applied Probability", "Mathematics and Financial Economics", "Statistical Inference for Stochastic Processes", "SIAM Journal in Financial Mathematics","Springer Briefs" and "Statistics and Risk Modeling".
He received the Europlace Award for Best Young Researcher in Finance in 2014 and the European Research Council Grant in 2015.
Head of quant analytics & digital transformation, APAC global markets
MD, head of cross asset quantitative research
Sandrine Ungari is currently Head of Cross-Asset Quantitative Research team and Deputy Head of the Global Quantitative Research team at Société Générale. The Quantitative Research team is active in risk premia strategies, derivatives and structured products, portfolio risk modelling, and provides research to investors worldwide. The group has been recognised as a market leader in quantitative research, and was ranked #1 in the Extel survey in the Quantitative Strategies category. Sandrine joined Société Générale in 2006. Prior to that, she worked as a quantitative analyst at HBOS Treasury and at Reech Sungard in London. She is a graduate of ENSTA (Paris) and hold a Master's in Quantitative Finance from Paris VI University. She is a guest lecturer at University Paris Diderot.