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, November 28, 20177:10PM, Warren Weaver Hall 109
Deep Learning
Dhruv Madeka, Amazon -
Tuesday, October 31, 20175:30PM, Warren Weaver Hall 1302
Alternative Data in Finance – Interworking of a Buy-Side R&D Team
Gene Ekster, Alternative Data Group -
Tuesday, October 24, 20175:30PM, Warren Weaver Hall 1302
Machine Learning Applied to Portfolio Construction
Gontran de Quillacq, Clinton Group -
Tuesday, October 3, 20175:30PM, Warren Weaver Hall 1302
Optimal Execution, Order-Placement Tactics, and Hamiltonian Dynamics
Jerome Benveniste (joint work with Gordon Ritter), NYU Courant, M.S. Mathematics in Finance