Mathematical Finance & Financial Data Science Seminar
The mathematical finance & financial data science seminar covers a broad range of topics in mathematical and quantitative finance, including:
- Data science and machine learning in finance
- Big data and econometric techniques
- Quantitative finance
- Market microstructure and trading costs
- Portfolio and risk management
- Pricing, hedging and risk models
- Regulation and regulatory models
- Trading strategies and back testing
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This seminar series is part of the Quantitative Finance & Financial Data Science Working Group's activities at NYU Courant, organized by Petter Kolm (email: petter DOT kolm AT nyu DOT edu).
Presenters include invited visitors and NYU Courant faculty. Seminar presentations often cover original research. All seminars are held online as per the schedule below.
Seminar Organizer(s): Prof. Petter Kolm
Past Events
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Tuesday, May 7, 20195:30PM, Warren Weaver Hall 1302
An Algorithmic Approach to Taxable Investing
Adam Grealish, Director of Investing, Betterment -
Tuesday, April 30, 20195:30PM, Warren Weaver Hall 1302
Reduced Order Representation of Implied Volatility Surfaces
Andrew Papanicolaou, NYU Tandon -
Friday, April 26, 20195:30PM, Warren Weaver Hall 109
Machine Learning for Trading
Gordon Ritter, Courant Institute of Mathematical Sciences -
Tuesday, April 23, 20195:30PM, Warren Weaver Hall 1302
Deep (Supervised or Otherwise) Learning
Dhruv Madeka, Senior Machine Learning Scientist, Amazon -
Tuesday, April 2, 20195:30PM, Warren Weaver Hall 1302
The Adaptive Curve Evolution Model for Interest Rates
Matthias Heymann, Goldman Sachs, Model Risk Management -
Tuesday, March 5, 20195:30PM, Warren Weaver Hall 1302
Repo Haircut and Pricing
Wujiang Lou, HSBC