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08:00: Registration and Morning Welcome Coffee

Chair:

To be confirmed 


09.00 - 09.45: Keynote: Machine Learning Enhanced Trading

Presenter: Georgios Papaioannou: 
Trading Strategist, Bank of America Merrill Lynch


09.45 - 10.30: Machine Learning & AI in Quantitative Finance Panel: 

Moderator: 

  • Paul Bilokon: Founder, CEO,Thalesians, Senior Quantitative Consultant, BNP Paribas  

Panelists: 

  • Miquel Noguer Alonso: Adjunct Assistant Professor, Columbia University
  • Georgios Papaioannou: Trading Strategist, Bank of America Merrill Lynch
  • Abdel Lantere: Data Scientist, Quantitative Consultant, HSBC 
  • Alexei Kondratyev: Managing Director, Head of Prime Services Analytics, Standard Chartered Bank
  • Christoph Burgard: Head of Risk Analytics For Global Markets, Bank of America Merrill Lynch

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

10.30 – 11.00: Morning Break and Networking Opportunities


11.00 - 11.45: Tough Vol

  • Fractional Brownian motion and analogies with interest rate modeling
  • Fractional volatility: definition, motivation and empirical findings
  • Expansions and short maturity limits for skew, smile, delta and digitals
  • Connection with Hawkes processes and market micro structure models
  • Numerical implementation

Presenter: Jesper Andreasen: Global Head Of Quantitative Research, Saxo Bank  


11.45 - 12.30: An Extension of the Heston Model for P and Q Measure Modelling of FX Options 

Presenter: Riccardo Rebonato: Professor of Finance, EDHEC Business School


12.30 - 13.45: Lunch


13.45 - 14.30: ‘Local-Stochastic Volatility for Vanilla Modelling: A Tractable and Arbitrage Free Approach’ 

  • Mixing of Local and Stochastic Volatilities via Lamperti transform: replication formulae
  • Normal SABR: Jamshidian’s Trick and measure change for accurate option pricing proxies. Application to SABR Local Vol
  • Heston Local Vol

Presenter: Dominique Bang: Director, Head of Interest Rates Vanilla Modelling, London, Bank of America Merrill Lynch 


14.30 - 15.15: Pricing Swaptions Without Tears 

  • Equity-like local volatility model for interest rate underlyings
  • Approximate swap rate diffusion with “short rate” and “dividend”
  • Pricing European and Bermudan swaptions without intensive yield curve modeling using techniques borrowed from the equity space
  • Numerical examples 

Presenter: Juliusz JabÅ‚ecki: Divisional Head, Narodowy Bank Polski


15.15 – 15.45: Afternoon Break and Networking Opportunities


15.45 - 16.30: Smart Derivative Contracts (Detaching Transactions from Counterparty Credit Risk: Specification, Parametrisation, Valuation)   

Presenter: Christian Fries: Head of Model Development, DZ Bank


16.30 - 17.15: Composite Average Option Valuation with Smiles

  • The economic purpose of composite options
  • Turning a multiplication into a subtraction
  • Generic bilinear option valuation: lots of digitals!
  • Solid bivariate cumulative normals
  • Does it work?

Presenter: Peter Jaeckel: Deputy Head of Quantitative Research, VTB Capital

20.00: Gala Dinner

Plage Beau Rivage, Nice