The 2nd Machine Learning & AI in Quantitative Finance Conference USA: New York City 14th - 16th November


Machine Learning & AI in Quantitative Finance Conference: New York City 14th – 16th November


Discount Structure:

  • 20% Past Delegate Discount Until until Friday October 5th 2018
  • When 2 colleagues attend the 3rd goes free!
  • Register to the Main Conference + Workshop and receive a $250 discount

Due to a complete sell out in March 2018 our highly popular USA Conference is back in New York City this November.

Pre-Conference Workshop day: Wednesday November 14th 2018

  • Machine Learning, AI, & FinTech in the Capital Markets by Sol Steinberg

Thursday November 15th 2018:

  • Main Conference Day One Stream

Friday November 16th 2018:

  • Main Conference Day Two Stream

Speakers & Topics:

Marcelo Labre: Executive Director, Morgan Stanley

  • Keynote Speech: Machine Learning and AI in Finance: Applications, Cases and Research

Richard V. Rothenberg: Global AI Corporation & Research Affiliate, Lawrence Berkeley National Laboratory

  • Keynote Speech "AI-driven ESG / SDG Strategies for Investment and Risk Management " 

Peter Carr: Professor and Dept. Chair of FRE Tandon, New York University

  • Using Machine Learning to Forecast Realized Volatility

Terry Benzschawel: Founder and CEO, Lambda Financial, LLC.

  • Machine Learning Models for Corporate Bond Default, Recovery in Default, and Relative Value

Cristian Homescu: Director, Portfolio Analytics Bank of America Merrill Lynch

  • Opportunities and Challenges of Machine Learning in Quantitative Investment and Wealth Management

Amit Srivastav: Executive Director, Quantitative Analytics Group (Model Risk), Morgan Stanley

  • “Risks and Regulatory Framework around using AI Models”

Arik Ben Dor: Managing Director and Head of Quantitative Equity Research, Barclays

  • Using Natural Language Processing (NLP) to Analyze Earning Call Transcript

Bernhard Hientzsch: Managing Director, Head of Model, Library, and Tools Development for Corporate Model Risk, Wells Fargo

  • Deep Learning and Computational Graph Techniques for Derivatives Pricing and Analytics

Joseph Simonian: Director of Quantitative Research, Portfolio Research & Consulting Group, Natixis Investment Managers

  • How Data Science is Impacting Multi-Asset Investing

Miquel Alonso: Adjunct Assistant Professor, COLUMBIA UNIVERSITY

  • Deep Learning in Finance – LSTN’s 

Igor Halperin: Research Professor of Financial Machine Learning, NYU Tandon School of Engineering

  • Model-free Option Pricing and Hedging by Reinforcement Learning

Gordon Ritter: Senior Portfolio Manager, GSA Capital

  • Trading Strategies Using a Mixture of Supervised and Reinforcement Learning

Shengquan Zhou: Quantitative Researcher, Bloomberg LP

  • Factor Investing Using Volatility Data & Machine Learning

Michael Beal: CEO, Data Capital Management

  • Delivering Alpha: Artificial Intelligence in Capital Markers Investing

Ksenia Shnyra: Senior Advisor, Deloitte

  • Applying Machine Learning to Evaluate Systemic Risk and Contribution of Individual SIFIs​​​​​​​