Pre-Conference Workshop day: Wednesday 14th March
Machine Learning in Finance : A Practical View by Miquel Noguer Alonso: UBS & Columbia University
- Thursday 15th March: Main Conference Day One
- Friday 16th March: Main Conference Day Two
Speakers:
- O. Ediz Ozkaya: Executive Director, Machine Learning Strategist, Securities Division, Goldman Sachs
- Daniel Giamouridis: Global Head of Scientific Implementation, Bank of America Merrill Lynch
- Lawrence Edwards: Executive Director, Morgan Stanley
- Daniel Drummer: Vice President, Corporate & Investment Bank FinTech, J.P. Morgan
- Miquel Noguer Alonso: Executive Director, UBS & Adjunct Assistant Professor, Columbia University
- Abdel Lantere, Data Scientist, Quantitative Consultant, HSBC
- William McGhee: Global Head of Quantitative Analytics, NatWest Markets
- Paul Bilokon: Founder, CEO,Thalesians, Senior Quantitative Consultant, BNP Paribas & Visiting Lecturer, Imperial College
- Ignacio Ruiz: Founder & CEO, MoCaX Intelligence
- Claudi Ruiz Camps: Machine Learning, Deep Learning Specialist, ABN AMRO Clearing Bank N.V.
- Saeed Amen: Quant strategist & trader, Cuemacro
- Farhan Feroz: eFX Quantitative Trader, UBS
- Pawel Chilinski: Quantitative Trader, UBS
Topics:
- Predictive Power vs. Expressiveness of Machine Learning Models
- Machine Learning: History and Implications for Quantitative Finance
- Reliable Machine Learning
- Black-box Machine Learning: Improving Transparency
- Machine Learning Models
- Fast MVA Optimisation using Chebyshev Interpolants
- Machine Learning - Recent Trends and Applicability to Risk and Related Areas
- Machine Learning, High-Frequency Trading and Kdb+/q for Quants and Data Scientists
- Unsupervised Anomaly Detection in Finance
- Practical Aspects of Applying Deep Learning for Market Making
- Applications & Challenges of using Deep Learning & Bayesian Inference Methods for High Frequency Market Making
- Co-creating Machine Learning solutions within a global Corporate & Investment Bank
- Using Big Data to Trade FX (& Python for finance)
- Can AI help FRTB?”
- Time Series Data & FRTB - time to get it right
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