Events
Department of Mathematics and Statistics
Texas Tech University
 | Wednesday
Sep. 23
4 PM
Math 011
|
| Applied Mathematics and Machine Learning
TBA
Adam Umar
Department of Mathematics & Statistics, Texas Tech University
|
Abstract: TBA
When: 4:00 pm (Lubbock's local time is GMT -5)
Where: room Math 011 (Math Basement)
ZOOM details:
- Choice #1: use this link
Direct Link that embeds meeting and ID and passcode.
- Choice #2: join meeting using this link
Join Meeting, then you will have to input the ID and Passcode by hand:
* Meeting ID: 949 9288 2213
* Passcode: Applied
Outreach program for advanced middle and high school math studentsSince the seminal work of Gatheral, Jaisson, and Rosenbaum (2014), it has become widely accepted that volatility in derivatives markets exhibits rough behavior. Numerical methods for rough volatility models are often difficult to stabilize and scale to large volatility smile surfaces. In addition, calibration to volatility surfaces, rather than to historical data, remains a significant challenge, as does the reliable valuation of exotic derivatives. In this work, we clarify how machine learning tools can be used most effectively to address these problems.
Zoom link: texastech.zoom.us/j/3067000354
Meeting ID: 306 700 0354
Passcode: TTUMF