Join us for the Brooklyn Quant Experience (BQE) Lecture Series today,  Thursday, March 31st at 6 pm ET on Zoom.

“When to Sell an Asset? – A Distribution Builder Approach”
(This is joint work with Peter Carr.)

Stephan Sturm
Associate Professor
Mathematical Sciences
Worcester Polytechnic Institute

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*Please note a meeting password is required for this event.
Meeting ID: 947 7419 9649
Password: BQESS331

Abstract
We revisit the question of the optimal time of an asset sale from the point of view of Sharpe’s “Distribution Builder” approach: Instead of assuming the investor’s risk preferences in form of a utility function, the investor provides themself a distribution that should be attained when selling the asset at a stopping time (specified a priori). This obviously begs the question of which distributions are attainable for an investor. We connect this problem to the Skorokhod embedding problem for one-dimensional diffusions and provide explicit representation for optimal stopping times as well as their expected values. In the case that the target distribution is specified from a parametrized family (e.g., log-normal distributions), we show that optimality involves a mean-variance trade-off similar to the efficient frontier in Markowitz’s approach to portfolio optimization. This is joint work with Peter Carr.

Bio
Stephan Sturm is an Associate Professor of Mathematical Sciences at Worcester Polytechnic Institute (WPI) in Massachusetts. After obtaining his Ph.D. in Mathematics from TU Berlin (Germany), he became a Postdoctoral Research Associate and Lecturer at ORFE before joining WPI as a faculty member. Sturm’s research covers mainly different areas of financial mathematics, but he is interested in stochastic modeling in general, such as applications to climate science. In finance, his work is devoted in particular to questions of value adjustments for derivative securities (XVAs), optimal portfolio selection, and systemic risk in financial markets.

Featuring Machine Learning experts from Cornell, Citi, and more…

You and your colleagues are invited to attend the Cornell Financial Data Science Webinars. Through online talks in Spring 2022, we are excited to collaborate with various guest speakers in highlighting machine learning applications in finance.

All webinars are from 5:00 pm to 6:00 pm ET.

This webinar is free and open to all guests. Registration is required (please RSVP here). You will receive the webinar link and dial-in info upon registration (the confirmation email will come from no-reply@zoom.us).

Abstract: 

This talk presents a mathematical analogy between financial trading strategies and biological species and shows how to apply standard concepts from ecology to financial markets. We analyze the interactions of stereotypical trading strategies in ecological terms, showing that they can be competitive, predator-prey, or mutualistic, depending on the wealth invested in each strategy. The deterministic dynamics suggest that the system should evolve toward an efficient state where all strategies make the same average returns. However, this happens slowly, and the evolution is so noisy that there are large fluctuations away from the efficient state, causing bursts of volatility and extended periods where prices deviate from fundamental values.

Speaker Bio:

Maarten P. Scholl is a PhD student at the Institute for New Economic Thinking (INET) at the Oxford Martin School and the Department of Computer Science. He works on classifying financial market activities using regulatory reporting data and uses Agent-Based Models (ABMs) to simulate financial market scenarios to uncover all possible interactions between market activities.

We hope to see you online!

**Please excuse any duplication of this announcement

If you are interested in our past seminars, you are welcome to subscribe to our YouTube Channel and watch our videos!

Past Events

February 15, 2022
Speaker: Kevin Webster
Title of Presentation: “How Price Impact Distorts Accounting P&L – Revisiting Caccioli, Bouchaud and Farmer’s Impact-Adjusted Valuation”

Upcoming Events

April 2022
Speaker: Andreea Minca (Cornell)
Title of Presentation: “Clustering Heterogeneous Financial Networks”

It is with indescribable sadness that we write to inform you that Professor Peter Carr passed away last week. Peter touched so many lives in the FRE Department, NYU Tandon community, and within the finance industry.

Our BQE Lecture Series was created by Peter when he joined the department in 2016. We will keep his legacy alive and continue sharing events and research by other practitioners in financial engineering.

We hope you can join us.

Join us for the Brooklyn Quant Experience (BQE) Lecture Series on Thursday, March 10th at 6 pm ET on Zoom.

“Optimal Execution with Quadratic Variation Inventories”

Laura Leal
Ph.D. Student
Operations Research and Financial Engineering Department
Princeton University

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*Please note a meeting password is required for this event.
Meeting ID: 922 7756 8804
Password: BQELL310

Abstract

We describe and implement statistical tests arguing for the presence of a Brownian component in the inventories and wealth processes of individual traders. Using intra-day data from the Toronto Stock Exchange, we provide empirical evidence of this claim. Both for regularly spaced time intervals, as well as for asynchronously observed data, the tests reveal with high significance the presence of a non-zero Brownian motion component. Furthermore, we extend the theoretical analysis of an existing optimal execution model to accommodate the presence of Ito inventory processes, and we compare empirically the optimal behavior of traders in such fitted models, to the actual behavior read off the data.

Bio
Laura Leal is a final-year Ph.D. student in the Operations Research and Financial Engineering department at Princeton University. Her research interests are centered in high-frequency finance, using machine learning, deep neural networks, optimization, statistical and econometric methods to study high-frequency trading data. The main topics she has worked on include optimal execution, market making, identification of institutional activity, and tail risk.