Monday, April 13, 2026

6:00 PM Seminar Begins

7:30 PM Reception

Hybrid Event

Fordham University

McNally Amphitheater

140 West 62nd Street

New York, NY 10023

Free Registration!

For Virtual Attendees: Please select virtual instead of member type upon registration.

Abstract:

In 1952, Harry Markowitz formulated portfolio selection as a trade-off between expected return and variance. This launched a massive research effort devoted to finding suitable inputs to mean-variance optimization. We show that PCA constructed Markowitz portfolios display highly counterintuitive properties as more securities are added. For example, the ratio of the true to the estimated portfolio risk grows without bound. We derive a correction formula that adjusts a PCA model in such a way that this ratio is stochastically bounded. These corrected Markowtitz portfolios also achieve zero variance asymptotically. We confirm these results via numerical simulations and test this theory further on a WRDS data set of U.S. Equity returns from 1975 to the present.

Bio:

Alex Shkolnik is an Assistant Professor at the Department of Statistics and Applied Probability at the University of California, Santa Barbara and a Research Fellow at the Consortium for Data Analytics in Risk at the University of California, Berkeley where he was a postdoctoral scholar. Alex received his PhD in computational mathematics and engineering from Stanford University. His research interests include Monte Carlo simulation, high-dimensional statistics and quantitative financial risk management.

Financial Engineer of the Year:

Bruno Dupire

And IAQF Innovation Award Recipient:

Antoine Savine

Award Dinner Information

Tuesday, May 19, 2026

The Yale Club

New York City

6:30pm Cocktails 7:30pm Dinner

Corporate sponsorships including tables of ten are available

Individual seats are available for $600

For more information please contact the

IAQF office at 646-736-0705 or info@iaqf.org

About the Winner: 

Bruno Dupire is head of Quantitative Research at Bloomberg L.P., which he joined in 2004. Prior to this assignment in New York, he has headed the Derivatives Research teams at Société Générale, Paribas Capital Markets and Nikko Financial Products where he was a Managing Director. He is best known for having pioneered the widely used Local Volatility model (simplest extension of the Black-Scholes-Merton model to fit all option prices) in 1993 and the Functional Itô Calculus (framework for path dependency) in 2009. After a Master's degree in Artificial Intelligence in 1982 and a PhD in Numerical Analysis in 1985 he has conducted in 1987-88 a study to apply Neural Nets to time series forecasting for Caisse des Dépôts et Consignations. 

At Bloomberg he has initiated the BQuant project, a quant platform that combines easy access to the data with the expressivity of Python. He runs the BBQ (Bloomberg Quant) seminar, the largest monthly quant seminar worldwide. He is a Fellow and Adjunct Professor at NYU and he is in the Risk magazine “Hall of Fame”. He is the recipient of the 2006 “Cutting edge research” award of Wilmott Magazine, of the Risk Magazine “Lifetime Achievement” award for 2008 and of the 2025 Financial Engineer of the Year Award of IAQF. 

About the Innovation Award Winner:

Antoine Savine is a Managing Director and the Global Head of Rates Quants at Barclays Investment Bank. In the previous years, he led Macro Analytics at Hudson River Trading. In the previous decades, he built the Fixed Income Quant group at BNP, and served as chief quantitative analyst at Danske Bank's Superfly Analytics and adjunct professor of mathematical finance at Copenhagen University. He wrote the book on adjoint differentiation (AAD) with Wiley (Modern Computational Finance, 2018), created differential machine learning with Brian Huge, and delivered multiple influential publications and conference talks. He holds a PhD in mathematical finance from Copenhagen University and a Masters (DEA) of mathematical finance from University of Paris, City.