Friday 20th November: Regulations
Presenter to be confirmed
Head of Quantamental Investments, Schroders
Antonia Lim: Head of Quantamental Investments, Schroders
Antonia joined Schroders in 2019 to lead their new initiative in quantamental investments, melding quantitative techniques with fundamental expertise and insight. Prior to Schroders, Antonia was Global Head of Quantitative Research for Barclays UK, designing its asset allocation policy, products and investment tools. She has two decades of experience in investment management, is a CFA charterholder and is on the management committee of the not-for-profit organization London Quant Group. Antonia holds a Masters in Physics from the University of Oxford where she was awarded an academic scholarship. Happy lending intuition, pragmatism and curiosity to the real, abstract and complex, Antonia enjoys cross-disciplinary ideas and making those ideas useful.
We examine the impact of interest rates benchmark reform and upcoming Libor transition on options markets. We address various modelling challenges the transition brings. We specifically focus on the impact of the clearing houses’ discounting switch on swaptions, and the consequences of Libor transition on Libor-in-arrears swaps, caps, and range accruals as typical representatives of a very wide range of Libor derivatives.
MD, Head of Quantitative Analytics and Quantitative Development, NatWest Markets
Vladimir Piterbarg: MD, Head of Quantitative Analytics and Quantitative Development at NatWest Markets
- How the IBOR transition impacts other models
- Definition of model uncertainty
- ML techniques to deal with uncertainty propagation through the model inventory
Co-founder and CEO, Yields.io
Jos Gheerardyn: Co-founder and CEO of Yields.io
Jos is the co-founder and CEO of Yields.io. Prior to his current role he has been active in quantitative finance both as a manager and as an analyst. Over the past 15 years he has been working with leading international investment banks as well as with award winning start-up companies. He is the author of multiple patents applying quantitative risk management techniques on imbalance markets. Jos holds a PhD in superstring theory from the University of Leuven.
- Unique challenges of using ML in finance
- Dealing with scarce and non-stationary data
- Best practices to overcome these challenges
- How do we deal with model risk in ML?
- Is there a way to make ML more explainable?
- Should we trust ML models more than traditional stochastic models chosen because they have an analytical solution?
- Will the regulators allow ML models for capital or accounting P&L?
- How much value is ML adding?
- Classical machine learning (RBMs, SVMs, etc.) vs. classical statistics (linear regression, convex optimization)
- Deep learning vs. classical machine learning
- What are the most important machine learning techniques for the future?
- Where is the greatest potential for ML in systematic trading:
- What styles of systematic trading can benefit from ML
- How can ML be applied to systematic trading: sentiment analysis, time series analysis, alternative data use
- What applications can you list among ML successes in finance?
- Time series analysis, market generators
- Derivative valuation
- Capital and margin optimization
Executive Chairman, CompatibL
Alexander Sokol: Executive Chairman, CompatibL
Managing Director, Head of Data Analytics, Standard Chartered Bank
Alexei Kondratyev: Managing Director, Head of Data Analytics, Standard Chartered Bank
In his role as Managing Director and Head of Data Analytics at Standard Chartered Bank, Alexei is responsible for providing data analytics services to Financial Markets sales and trading.
He joined Standard Chartered Bank in 2010 from Barclays Capital where he managed a model development team within Credit Risk Analytics. Prior to joining Barclays Capital in 2004, he was a senior quantitative analyst at Dresdner Bank in Frankfurt.
Alexei holds MSc in Theoretical Nuclear Physics from the University of Kiev and PhD in Mathematical Physics from the Institute for Mathematics, National Academy of Sciences of Ukraine.