What we’re about
The Thalesians are a group of dedicated professionals with an interest in Artificial Intelligence (AI) / Machine Learning (ML), quantitative finance, economics, mathematics, physics and computer science, not necessarily in that order. We currently run events London, New York, Budapest, Frankfurt and Prague!
Please also visit our main Thalesians web page here too to learn more about us!
The Thalesians are a member of Level39 - Europe's largest technology accelerator for finance, retail, cyber-security and future cities technology companies.
We consult, train, and write software. Our offering can be found on http://ai.thalesians.com/
Our GitHub page contains our open source Python financial analysis library PyThalesians.
If you are a full-time student, between jobs, or for any other reason would struggle with our Meetup dues, please let us know and we'll mark you as exempt from them!
Upcoming events (1)
See all- Hybrid Event: Stephan Sturm - Signatures for Option Strategies140 W 62nd St, New York, NY
IAQF & Thalesians Seminar Series: Signatures for Data Pooling and Commodities Strategies - A Seminar by Stephan Sturm
6:00 PM Seminar Begins
7:30 PM ReceptionHybrid Event
Location: Room Change
Fordham University
Pope Auditorium 113 W 60th St #7
New York, NY 10023Free Registration!
For Virtual Attendees: Please email web@iaqf.org for the link.Abstract:
Signature methods have successfully been used as a tool for feature extraction in statistical learning methods, notably in mathematical finance. The specific reason for their success is often much less clear, besides a general hand-waving to path-dependence. This presentation highlights the potential of signatures for data pooling and options strategies in the commodities space. We further aim to explain the success of signatures in the foundational task: classifying commodity futures markets according to storability. We provide a regular perturbation of the signature of the futures term structure in terms of the convenience yield and identify the volatility of the convenience yield as major discriminant. This is joint work with Hari P. Krishnan.Bio:
Stephan Sturm is Associate Professor of Mathematical Sciences at Worcester Polytechnic Institute (WPI) in Massachusetts. After obtaining his PhD in Mathematics from TU Berlin (Germany), he became a Postdoctoral Research Associate and Lecturer at ORFE in Princeton 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 recent work has been focused in particular on portfolio selection and incentives, indifference pricing and the use of signature-based models.
