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

You and your colleagues are invited to attend the UBS & CFEM AI, Data & Analytics Speaker Series. UBS Investment Bank is proud to be partnering with Cornell Financial Engineering Manhattan to provide insights directly from practitioners and academics to the next generation of AI, Data & Analytics talent.

All webinars are from 5:30 pm to 6:30 pm ET.

This seminar is free and open to all. 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: 

Assets on blockchain trade 24×7 with very thin liquidity. This demands new fully automated processes, including Automated Market Making (AMM). We dive into the microstructure of the fully-automated systems, comparing the differences between traditional and modern microstructure implementations.

Speaker Bio:

Irene Aldridge is an internationally-recognized quantitative Finance and AI researcher, Adjunct Professor at Cornell University and Lecturer at Cambridge University (U.K.). In addition, Irene is President and Managing Director, Research, of AbleMarkets, an AI-for-Finance company, as well as President of AbleBlox, a blockchain startup. Prior to AbleMarkets and AbleBlox, she designed and ran high-frequency trading strategies in a $20-million cross-asset portfolio. Still previously, Aldridge was, in reverse order, a quant on a trading floor; in charge of risk quantification of commercial loans; Basel regulation team lead; technology equities researcher; lead systems architect on large integration projects, including web security and trading floor globalization. Aldridge started her career as a software engineer in financial services. Irene is a co-author of “Big Data Science in Finance” (with Marco Avellaneda, Wiley 2021),  “Real-Time Risk: What Investors Should Know About Fintech, High-Frequency Trading, Flash Crashes” (co-authored with Steve Krawciw, Wiley, 2017), and the author of “High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems” (2nd edition, translated into Chinese, Wiley 2013), among other work.

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

January 24^th, 2023
Speaker: Agostino Capponi (Columbia)
Title of Presentation: Do Private Transaction Pools Mitigate Frontrunning Risk?

February 28^th, 2023
Speaker: Ernest Chan (Predictnow.ai)
Title of Presentation: How to Use Machine Learning for Optimization

 Upcoming Events

April 25^th, 2023
Speaker:Harrison Waldon (UT Austin)
Title of Presentation: TBD