World Business StrategiesServing the Global Financial Community since 2000
08.00 - 09.00
Registration and Morning Welcome Coffee
09.00 - 10.00
Keynote: Portfolio Model Risk for Systematic / Quant Trading

Gordon Ritter:

Founder, CIO, Ritter Alpha, LP

10.00 - 10.45
Dynamic Replication and Hedging: A Reinforcement Learning Approach

Abstract:

We address the problem of how to optimally hedge an options book in a practical setting, where trading decisions are discrete and trading costs can be nonlinear and difficult to model. Based on reinforcement learning, a well-established machine learning technique, our model is shown to be flexible, accurate and very promising for real-world applications.

This is joint work with Gordon Ritter.

Petter Kolm:

Clinical Full Professor and Director, Courant Institute of Mathematical Sciences, NYU

10.45 - 11.15
Morning Break and Networking Opportunities
11.15 - 12.45
Advanced Natural Language Processing (NLP) Techniques

Terry Benzschawel:

Founder and Principal, Benzschawel Scientific, LLC

12.45 - 14.00
Lunch
14.00 - 14.45
Quantifying Model Uncertainty with Artificial Intelligence
  • Defining model risk and model uncertainty
  • Overview of relevant regulatory frameworks
  • Measuring uncertainty with ML
  • Model risk of AI

Victor Davis:

Python Developer, Yields.io

14.45 - 15.30
Latest Developments in Deep Learning in Finance

Miquel Noguer Alonso:

Co – Founder and Chief Science Officer, Artificial Intelligence Finance Institute – AIFI

15.30 - 16.00
Afternoon Break and Networking Opportunities
16.00 - 16.45
Machine Learning and Signals in High Frequency Trade Execution

We describe a framework for processing market data to produce short-term price forecasts for optimizing trade execution in futures and interest rate markets. The framework first computes a substantial number of simple features based on order book data. It then determines a number of signals from the features, using a variety of techniques including machine learning. Finally, a consensus layer uses a new clustering algorithm to decide which combination of signals to believe in which market conditions. The framework is in production use and is delivering substantial value.

Robert Almgren:

Co-Founder and Head of Research, Quantitative Brokers

16.45 - 17.45
Machine Learning & Ai in Quantitative Finance Panel

Topics:

  • What is the current state of utilisation of machine learning in finance?
  • What are the distinct features of machine learning problems in finance compared to other industries?
  • What are the best practices to overcome these difficulties?
  • What’s the evolution of a team using machine learning in terms of day to day operations?
    What is a typical front office ‘Quant’ skillset going to look like in three to five years time?
  • How do we deal with model risk in machine learning case?
  • How is machine learning expected to be regulated?
    What applications can you list among its successes?
    How much value is it adding over and above the “classical” techniques such as linear regression, convex optimisation, etc.?
  • Do you see high-performance computing (HPC) as a major enabler of machine learning?
    What advances in HPC have caused the most progress?
  • What do you see as the most important machine learning techniques for the future?
    What are the main pitfalls of using Machine Learning currently in trading strategies?
  • What new insights can Machine Learning offer into the analysis of financial time series?
    Discuss the potential of Deep Learning in algorithmic trading?
  • Do you think machine learning and HPC will transform finance 5-10 years from now?
    If so, how do you envisage this transformation?
  • Can you anticipate any pitfalls that we should watch out for.
  • Discuss quantum computing in quant finance:
    • Breakthroughs
    • Applications
    • Future uses

Panellists:

Terry Benzschawel:

Founder and Principal, Benzschawel Scientific, LLC

Knarig Arabshian:

Senior Knowledge Engineer in Technology Innovation, Federal Reserve Bank of New York

Gordon Ritter:

Founder, CIO, Ritter Alpha, LP

Victor Davis:

Python Developer, Yields.io

Miquel Noguer Alonso:

Co – Founder and Chief Science Officer, Artificial Intelligence Finance Institute – AIFI

  • Discount Structure
  • Special Offer
    When two colleagues attend the 3rd goes free!

  • 70% Academic Discount
    (FULL-TIME Students Only)

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