The seminar takes place in the Spring of 2026, Thursdays, 7:40 pm — 8:55 pm.
Location: Mathematics Building, Room 207
For directions, please see Directions to Campus and Directions to Mathematics Building (Morningside Campus Map).
Organizer: Jaehyuk Choi
Current/upcoming Schedule of Presentations
View the Schedule of Past Presentations.
Thursday, March 12, 2026
Title: Introduction to Quantitative Balance Sheet Strategy (QBSS) in Commercial Banks [Lecture Series: 2/4]
Speaker: Greg Borovykh
Abstract:
Thursday, March 19, 2026 – SPRING BREAK
Thursday, March 26, 2026
Title: Applications of Deep Learning Methods in Quantitative Trading
Speaker: Denis Lapitski, Head of Strategy Research, Trexquant
Abstract:
We describe the portfolio construction process at Trexquant, introduce Mixture of Experts models and demonstrate their behavior with a toy example using synthetic data. Then we describe in more detail the neural networks constructed for Mixture of Experts in our real world trading strategies, discuss what aspects of model set up and expert construction are specific to this application of Mixture of Experts. Then we briefly discuss other examples of deep learning models we use – alpha forecast models, CNN models, contrastive learning, transfer learning, and reinforcement learning models. Conclude with comments on challenges encountered in applications of deep learning to quantitative trading.
Thursday, APRIL 2, 2026
Title: Kelly Criterion and Regime Switching Universal Portfolios (Joint Work with Dmitrii Vlasiuk)
Speaker: Mikhail Smirnov
Abstract:
We discuss Kelly criterion in single and multivariate case and go to its applications to regime-switching universal portfolios that invest in the risky universe during bull regimes and hold cash during bear regimes, and compare them to regime-blind universal portfolios and their best constant rebalanced portfolio comparators in hindsight. We find that regime awareness delivers similar annualized returns but substantially lower volatility and drawdowns. The switching part extends the model of Shu and Mulvey.
Thursday, APRIL 9, 2026
Title: Introduction to Quantitative Balance Sheet Strategy (QBSS) in Commercial Banks [Lecture Series: 3/4]
Speaker: Greg Borovykh
Abstract:
Thursday, APRIL 16, 2026
Title: Introduction to Quantitative Balance Sheet Strategy (QBSS) in Commercial Banks [Lecture Series: 4/4]
Speaker: Greg Borovykh
Abstract:
Thursday, APRIL 23, 2026
Title: Joint arbitrage-free smoothing of American call and put options surfaces
Speaker: Zhenyu Cui, Professor at Stevens Institute of Technology
Zhenyu Cui is an Associate Professor at the School of Business at the Stevens Institute of Technology. His research interests lie in financial engineering and stochastic simulation. He has published in Mathematical Finance, Finance and Stochastics, SIAM Journal on Financial Mathematics, INFORMS Journal on Computing, and Econometric Theory. He is currently the principal investigator of NSF-funded project, “Fast Quantum Method for Financial Risk Measurement.”
Abstract:
We propose a novel and computationally efficient methodology for joint arbitrage-free smoothing of American call and put option surfaces in the non-dividend case. Specifically, we formulate a joint cubic spline smoothing framework and recast it as a quadratic programming problem. Leveraging the joint smoothing technique, we further develop two efficient calibration schemes for parametric models. Simulation experiments demonstrate that the proposed joint smoothing method attains remarkably improved accuracy and robustness compared with natural cubic spline interpolation and the smoothing solely based on calls, particularly in the presence of added artificial noise. Furthermore, joint calibration based on smoothed American options prices is not only more accurate but also about three times faster than the state of the art neural network-based schemes in literature.
Thursday, APRIL 30, 2026
Title:
Speaker: Ioannis Kyriakou, Professor of Actuarial Finance, Bayes Business School
Abstract:
PAST PRESENTATIONS
Thursday, January 22, 2026
Title: Introduction to Spring MAFN Courses (Credit Analytics, Generative AI, and others)
Speaker: Steven Zhu / David Li, Laura Leal, and Others.
Abstract:
Thursday, January 29, 2026
Title: A Mathematical Approach for Generative AI
Speaker: Konstantin Kuchenmeister, Goldman Sachs
Abstract:
Generative AI (“GenAI”) is reshaping the global economy and the future of work by revolutionizing problem-solving, optimizing complex systems, and enabling data-driven decision-making. In this session, Konstantin will provide an overview of GenAI, exploring both the mathematical foundations and common patterns for developing AI applications at a high level.
Thursday, February 5, 2026
Title: Trading Volatility in Commodity Markets
Speaker: Ilia Bouchouev Ph.D., Pentathlon Investments, LLC
Dr. Ilia Bouchouev is the former President of Koch Global Partners where he launched and managed global derivatives trading business for over 20 years and was recognized as one of the pioneers in energy options trading. He is currently a managing partner at Pentathlon Investments and an adjunct professor at New York University, where he teaches energy trading at The Courant Institute of Mathematical Sciences. He is also a senior research fellow with The Oxford Institute for Energy Studies.
Ilia Bouchouev published in top academic journals on energy markets and derivatives modelling. He is frequently quoted by Wall Street Journal, Financial Times, Bloomberg, many other news providers, and on social media.
He is the author of the book “Virtual Barrels,” and he recently launched a YouTube channel on quantitative commodities trading.
Abstract:
Thursday, February 12, 2026
Title: A Model Risk History of Financial Failures
Speaker: Shyam Madhavan, Managing Director, Head of Enterprise Risk, Mizuho Americas
Shyam Madhavan is a Managing Director and Head of Enterprise Risk at Mizuho Americas, where he is responsible for Market and Credit Risk Analytics, Model Risk Management, and a number of capital and strategy related efforts including Risk Appetite, Stress Testing, and New Product development. He received a BA from Columbia University and began his career in interest rate derivatives trading at Morgan Stanley and Bear Stearns before pursuing his MBA at The George Washington University where he worked in Congress on the Dodd-Frank bill. Shyam then moved into risk management as a Macro Market Risk Manager at Nomura, Mizuho Americas, and Citibank, before returning again to Mizuho.
Abstract:
Financial models are ubiquitous on Wall Street; within Risk Management these mathematical representations of reality are often used as tools to forecast potential losses arising from market, credit, and liquidity risks. In this seminar, we will explore failures of financial institutions related to each of these risk types, the role models played in each of them, and lessons learned that can help ensure a long, successful career.
Thursday, February 19, 2026
Title: Introduction to Quantitative Balance Sheet Strategy (QBSS) in Commercial Banks [Lecture Series: 1/4]
Speaker: Greg Borovykh
Abstract:
Thursday, February 26, 2026
Title: What Risk Managers Really Do: Decision-Making, Uncertainty, and Life Beyond the Models
Speaker: Florent Cohen, Fixed Income Chief Risk Officer at Jefferies Group LLC
Abstract:
This presentation introduces the real-world responsibilities of a Risk Officer. It explains that risk management is not just about numbers or models, but about building frameworks that support smart decision-making and institutional stability. You will learn how risk officers assess trades from multiple perspectives—market, credit, liquidity, operational, and regulatory—and why judgment and collaboration are as important as quantitative tools. I will also highlight the importance of strategic partnerships with business units, effective communication with stakeholders, and the need to go beyond traditional risk metrics. The goal is to show that successful risk management combines technical analysis with practical, holistic thinking.
Thursday, March 5, 2026
Title: Kelly Criterion for one and several investments and its calculation
Speaker: Mikhail Smirnov
Abstract:
Kelly criterion, which is an optimal fixed-fraction betting strategy in favorable games was introduced by J.L.Kelly of Bell Labs in 1956. It was further applied by E.Thorpe who solved Blackjack and stock warrant arbitrage to gambling and investment situations. In financial markets Kelly criterion is known as a Merton optimal growth portfolio strategy. E.Thorp using 1926-1984 data found SP500 index optimal Kelly leverage to be 117%. We extend Thorp and find that more recently 1996-2024 SP500 Kelly leverage was significantly higher at 240%, discuss fractional Kelly investing, calculate multivariable US stocks/bonds/corporate bonds Kelly ratios and propose methodologies for practically calculating them.