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08:30: Registration and Morning Welcome Coffee

Chair:

To be confirmed


 09.00 - 09.45: Keynote: 'From Changes of Numeraire and Changes of Measure to Bitcoins and Blockchains' 

Presenter: Helyette Geman: Professor of Mathematical Finance, Birkbeck: Professor of Mathematical Finance - University of London & Johns Hopkins University


09.45 - 10.30: PANEL: Talent Attraction & Retention

Topics:

  • What are QR Financial Services currently doing and what should they be doing to attract more female talent?
  • What can recruitment companies do to help?
  • What strategies are financial companies using at present if any?
  • What are QR Financial Services currently doing and what should they be doing to retain female talent? 

Moderator:

  • Helyette Geman: Birkbeck - University of London & Johns Hopkins University (to be confirmed)

Panellist:

  • Roxana Simion: Risk Specialist, Prudential Regulation Authority, Bank of England 
  • Diana Ribeiro: Deputy Head of Rates Quantitative Research, CB Markets, Lloyds Banking Group
  • Nicole Sandler: FinTech and Regtech - EMEA Legal Regulatory Policy and Affairs, Barclays
  • Other panelists to be confirmed 

10.30 – 11.00: Morning Break and Networking Opportunities


11.00 - 11.45: Usage of Machine Learning in Finance 

  • What is Machine Learning
  • Current usage in Finance, e.g. algo trading, fraud, etc
  • Other possible applications in the future
  • How to implement these technics

Presenter: Sarah B Tremel: Global Head of Analytics, Global Valuation Group, HSBC Bank 


11.45 - 12.30: From Artificial Intelligence to Machine Learning, from Logic to Probability  

Applications of Artificial Intelligence (AI) and Machine Learning (ML) are rapidly gaining steam in quantitative finace. These terms are often used interchangeably. However, the pioneering work on AI by participants of the Dartmouth Summer Research Project --- Marvin Minsky, Nathaniel Rochester, and Claude Shannon --- was more symbolic than numerical, and often used the language of logic. Recent advances in ML --- especially Deep Learning --- are more numerical than symbolic, and often use the language of probability. In this talk we shall show how to connect these two worldviews.   

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


12.30 - 13.45: Lunch


13.45 - 14.30: "Black-box Machine Learning: Improving Transparency" 

"Many of the state of the art machine learning applications are based on black-box models which are difficult to interpret and explain. With more ML-based models being integrated into live decision-making systems, new challenges will be faced by various functions within banks as well as by the regulators. This talk disucsses the challenges faced and presents techniques to help provide more transparency and better understanding of the results of a given ML black-box model." 

Presenter: Abdel Lantere: Data Scientist, Quantitative Consultant, HSBC  


14.30 - 15.15: PANEL: Machine Learning, AI & Quantum Computing in Quantitative Finance 

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

Moderator:  

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

Panellists:  

  • Sarah B Tremel: Global Head of Analytics, Global Valuation Group, HSBC Bank
  • O. Ediz Ozkaya: Executive Director, Machine Learning Labs, Securities, Goldman Sachs (to be confirmed)
  • Abdel Lantere: Data Scientist, Quantitative Consultant, HSBC 
  • Other panelists to be confirmed 

15.15 – 15.45: Afternoon Break and Networking Opportunities


15.45 - 16.30: Deep Learning in Finance – LSTN’s 

  • Modern Data Analysis
  • Times Series Models Univariate
  • Linear Factor Models
  • Multivariate Time Series
  • Modern Financial Engineering
  • Long Short Term Memory Networks
    • Results
    • Conclusions 

Presenter: To be confirmed


16.30 - 17.15: Topic to be confirmed

Presenter: Katia Babbar: MD, Head of e-FX Algorithmic Trading, FX Product | CB Markets, Lloyds Banking Group


17.15 - 18.00: PANEL: Career Progression

Topics:

  • Do you think that being a woman is a significant factor in slowing down career progression in QR Financial Services?
    • If so, could this be avoided and how?
  • What mentoring programs are available for juniors if any? 
  • Is it still hard to make it to the top positions, if so why and what can do done to change the situation?
  • Discuss female role models in finance and significant achievements
  • Tips from coaches on career progression (eg having your voice heard)
  • Gender diversity issues (discuss numbers, policies, how to address it)
  • How important are the following:
    • Promotions/Career opportunities
    • Pay gap elimination
    • Agile/Flexible working

Moderator:

  • To be confirmed

Panelists:

  • Katia Babbar: MD, Head of e-FX Algorithmic Trading, FX Product | CB Markets, Lloyds Banking Group
  • Jessica James: Managing Director, Commerzbank AG
  • Christoph Burgard: Head of Risk Analytics For Global Markets, Bank of America Merrill Lynch
  • Other panelists to be confirmed