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